TWM605632U - Calibration system to improve the detection accuracy of environment sensing device - Google Patents

Abstract

This creation is about a calibration system that improves the detection accuracy of environmental sensing devices. The empty product monitoring station is equipped with standard equipment for testing environmental quality to provide a standard monitoring information at the monitoring site; the environmental sense to be calibrated The detection device is set next to the empty product monitoring station, and based on the geographic information and empty product detection information of the environmental sensing device, it integrates and generates an empty product positioning data corresponding to the geographic location of the empty product monitoring station; and cloud server The device is connected to the empty product monitoring station and the environmental sensing device to obtain the empty product location data and a standard monitoring information corresponding to the monitoring location of the empty product monitoring station; the cloud server will accumulate The empty product positioning data in a collection time is compared with the standard monitoring information to perform detection accuracy correction, and the corrected empty product positioning data is obtained, and the result is based on the previous calibration at every specific time within a calibration time The positioning data of this empty product will perform the next detection accuracy.

Description

Correction system for improving detection accuracy of environment sensing device

This creation is related to the detection technology field of an air pollution source concentration sensor, in particular to the collection/calibration of the detection data of an environmental sensing device and a method to improve detection accuracy.

Total suspended particulates (TSP), suspended particulates (PM10) and fine suspended particulates (PM2.5) are statutory air pollutants in China. In addition to fixed pipeline emission sources and mobile traffic sources, their main sources include exposure to the ground or streets Among them, the air pollution caused by dust exposed on the ground or on the street is mainly through the resuspension effect of wind or traffic, and the particle size of wind-prone particles is about 200μm or less, which is equivalent to total suspended particles. The ones that have a greater impact on human health are suspended particles (particle size less than 10μm) and fine suspended particles (particle size less than 2.5μm).

The environmental sensing device is a simple commercially available air pollution source concentration sensor, which is transmitted through a communication module to provide real-time PM2.5 monitoring data, temperature and relative humidity information. With increasing attention to air quality, the number of low-cost and miniaturized air pollution source concentration sensors such as environmental sensing devices continues to increase. However, due to their small size, the use of sensing principles is simple, making the sensing The data will have errors with the equipment used in the standard method. This kind of error is more likely to occur when measuring PM2.5. The simple sensor introduces particles in the air into the sensing area based on the principle of optical scattering. Without particle size screening, the number of particles of different sizes is measured optically (the principle of light scattering), and then converted to PM2.5 mass concentration. When light hits the surface of particles, there will be reflection, scattering and other effects. These benefits will be affected by the particle size, shape and surface roughness. At the same time, it is also related to the wavelength of light. When the particles contain water-absorbing components (such as sulfates, nitrates, etc.), the shape and size of the particles will change due to the absorption of moisture in the air, which will affect the measurement results.

When measuring PM2.5 with a simple sensor, in order to reduce the volume of the sensor, various possible interference factors are not included in the design, including particle size, temperature and humidity interference, etc., so the measured value is prone to errors. In addition, the particle size measured by the simple sensor using optical principles is called "optical particle size", which is also different from the "pneumatic particle size" associated with general measurement or breathing processes. As for the simple sensor that uses the principle of air diffusion or the motor to extract air samples, it is different from the standard measuring station using a precision flow controller for control. These are all important factors that affect the measurement results. When using a simple sensor to measure data, you should pay attention to possible differences in the measured values. Since most of the simple sensors on the market that are similar to environmental sensing devices have not undergone complete performance verification and evaluation, if people directly adopt their monitoring values without understanding their application restrictions, it will cause unnecessary panic.

Therefore, how to improve the above problems and improve the detection accuracy of the sensor, the applicant, in view of the deficiencies in the conventional technology, after careful experimentation and research, and a spirit of perseverance, finally conceived this creation. Solve the shortcomings of learning skills.

In view of this, this creation provides a calibration system that improves the detection accuracy of environmental sensing devices. The environmental sensing devices deployed at multiple empty product monitoring stations cooperate with positioning to generate corresponding empty product positioning data, and provide a cloud server for certain Collect data time and analyze calculation processing to generate calibration parameter commands, which can instantly calibrate empty product positioning data and standard monitoring information to ensure the accuracy of sensing.

In order to achieve the purpose of cost creation, this creation provides a calibration system to improve the detection accuracy of environmental sensing devices, which includes: an empty product monitoring station, which is used to provide a standard monitoring information of the monitoring site; the environmental sensing to be calibrated Device, which is set in the empty product monitoring station, and based on the geographic information and empty product detection information of the environmental sensor An empty product positioning data at the geographic location of the station; and a cloud server, which is connected to the empty product monitoring station and the environmental sensing device to obtain the empty product positioning data and the corresponding monitoring of the empty product monitoring station A standard monitoring information of the place; wherein the cloud server compares the empty product positioning data within a collection time with the standard monitoring information for detection accuracy calibration, obtains the corrected empty product positioning data, and performs a calibration Perform the next detection accuracy based on the empty product positioning data obtained after the previous calibration every specific time within the time.

According to an embodiment of the present creation, the cloud server uses multiple linear regression to establish a calibration model for temperature, humidity, wind speed, and air pollution source concentration.

According to an embodiment of the invention, the cloud server is provided with the calibration module, the calibration module calibrates the empty product detection information based on the calibration model, and transmits the calibrated empty product detection information to the environmental sense测装置。 Measuring device.

According to an embodiment of the present invention, the environment sensing device includes: a detection module for detecting the environment and generating the empty product detection information; a communication module for communicating with the cloud server , Used to transmit data; a positioning module, which is electrically connected to the communication module, used to confirm geographic location data and generate the geographic information; and a calibration module, which is electrically connected to the communication module To receive the calibration parameter and calibrate the empty product detection information based on the calibration model.

According to an embodiment of the present creation, the method for generating a calibration model for temperature and humidity includes: obtaining the temperature and humidity reference value obtained by the empty product monitoring station for the environment where it is located, and the measurement by the environmental sensing device at the same location Temperature and humidity detection value obtained; establish a calibration regression model between the temperature and humidity reference value and the temperature and humidity detection value: temperature and humidity reference value (y) = α × temperature and humidity detection value (x) + β; where α and β are Calibration parameters; the calibration parameters α and β are obtained after linear fitting based on the calibration regression model; the data of the calibration parameters α and β are written into the temperature/humidity sensor to establish the calibration model as follows: temperature and humidity correction value = α × temperature and humidity detection value + β.

According to an embodiment of the present creation, the method for generating a calibration model for the concentration of air pollution sources includes: obtaining the air pollution source concentration reference value, the temperature and humidity reference value, and the reference value of the air pollution source obtained by the air quality monitoring station for the environment monitoring. The air pollution source concentration detection value measured by the environmental sensing device; according to the multiple linear regression formula, a calibration regression model between the temperature and humidity reference value, the air pollution source concentration detection value and the air pollution source concentration reference value is established: air quality reference value = β ₀ + β ₁ × air pollution source concentration detection value + β ₂ × temperature reference value measured by the empty product monitoring station + β ₃ × relative humidity reference value measured by the empty product monitoring station; where β ₀ , β ₁ , Β ₂ , β ₃ are calibration parameters; the calibration parameters β ₀ , β ₁ , β ₂ , β _{3 are} obtained after linear fitting based on the calibration regression model; the data of these calibration parameters are written into the environmental sensing A correction model is established in the device: air pollution source concentration correction value = β ₀ + β ₁ × air pollution source concentration detection value + β ₂ × temperature correction value + β ₃ × relative humidity correction value.

According to an embodiment of the present creation, the method for generating a correction model for wind speed includes: obtaining the wind speed reference value obtained by the empty product monitoring station for the environment where it is located, and the wind speed measured by the environmental sensing device at the same location Detection value: According to the linear regression formula, establish a calibration regression model between the wind speed reference value and the wind speed detection value: wind speed reference value (y) = γ × wind speed detection value (x) + δ; among them, γ and δ are correction parameters; The calibration parameters γ and δ are obtained after linear fitting based on the calibrated regression model; the data of the calibration parameters are written into the environmental sensing device to establish a calibration model: wind speed correction value=γ×wind speed detection value+δ.

According to an embodiment of the present creation, the calculation method of the correction model for the concentration of air pollution sources includes: obtaining the air pollution source concentration reference value, temperature and humidity reference value, wind speed reference value, and The detection value of the air pollution source concentration measured by the environmental sensing device at the same location; according to the multiple linear regression formula, establish the calibration between the temperature and humidity reference value, the wind speed reference value, the air pollution source concentration detection value and the air pollution source concentration reference value Regression model: Air pollution source concentration reference value = β ₀ + β ₁ × air pollution source concentration detection value + β ₂ × wind speed reference value measured by the empty product monitoring station + β ₃ × temperature reference value measured by the empty product monitoring station +β ₄ × the relative humidity reference value measured by the empty product monitoring station; among them, β ₀ , β ₁ , β ₂ , β ₃ , and β ₄ are correction parameters; these are obtained after linear fitting based on the calibration regression model Correction parameters β ₀ , β ₁ , β ₂ , β ₃ , β ₄ ; write the data of these correction parameters into the environmental sensing device to establish a correction model: air pollution source concentration correction value = β ₀ + β ₁ × air Pollution source concentration detection value + β ₂ × wind speed correction value + β ₃ × temperature correction value + β ₄ × relative humidity correction value.

According to an embodiment of the present invention, in the calculation method of the correction model for the concentration of air pollution sources, the method further includes dividing the concentration of air pollution sources into a plurality of sections from low to high, and respectively calculating the correction model in each section .

According to an embodiment of the invention, the air pollution source concentration sensor includes a light emitter and a light sensor, and a photoelectric conversion circuit. The light emitter optically emits a predetermined light on the same gas, and The sample gas may contain a plurality of suspended particles or fine suspended particles, so that when the predetermined light passes through the fine suspended particles of the sample gas, a scattering, a refraction angle or a reflection angle of the predetermined light is caused; the light sensor is a scattering Type detection or a photodiode or photoelectric crystal based on the non-scattering detection method. The light sensor is arranged at a predetermined light receiving angle of the light emitter to measure the scattering, refraction or reflection of the predetermined light to obtain a Light measurement value; the photoelectric conversion circuit is used to convert the light measurement value into a measured value of suspended particles or a measured value of fine suspended particles.

10: Environmental sensing device

11: Detection module

12: Communication module

13: positioning module

14: Calibration module

110: light emitter

120: light sensor

130: photoelectric conversion circuit

150: Air pollution source concentration sensor

160: temperature/humidity sensor

20: Cloud server

90: Empty product monitoring station

S10~S60: process steps

S10’~S60’: Process steps

Figure 1 is a schematic diagram showing the flow in an embodiment of the authoring.

FIG. 2 is a schematic diagram showing the system operation architecture in an embodiment of the present creation.

Fig. 3 is a schematic diagram showing the flow in another embodiment of the authoring.

FIG. 4 is a schematic diagram showing the system operation architecture in another embodiment of the authoring.

In order to have a clearer understanding of the technical features, purpose and effects of this creation, the specific implementation of this creation will now be described in detail with reference to the drawings. The detailed description and technical content of this creation are described below with the drawings. However, the attached drawings are only for reference and explanation, and are not used to limit the creation; and the aforementioned and other technical content, features and characteristics of this creation The effect will be clearly presented in the following detailed description of each embodiment with reference to the drawings. The directional terms mentioned in the following embodiments, for example: "up", "down", "left", "right", "Front", "Back", etc., are just for reference to the directions of the attached icons. Therefore, the directional terms used are used to illustrate, but not to limit the creation. Furthermore, in the following embodiments, the same or similar elements will use the same or similar element numbers.

First of all, this creation is mainly a calibration method to improve the detection accuracy of environmental sensing devices; please refer to Figures 1 and 2 at the same time. Figure 1 is a schematic flow diagram of the creation calibration method, and Figure 2 is the system operation of the creation calibration method. Schematic diagram of the architecture.

The calibration system of this creation includes an empty product monitoring station 90, which is equipped with a standard instrument for testing environmental quality to provide a standard monitoring information at the monitoring site; the environmental sensing device 10 to be calibrated is installed at Next to the empty product monitoring station 90, and based on the geographic information and empty product detection information of the environmental sensing device, an empty product positioning data corresponding to the geographic location of the empty product monitoring station 90 is integrated and generated; and a cloud server, which is connected with The empty product monitoring station and the environmental sensing device are in communication connection to obtain the empty product positioning data and a standard monitoring information corresponding to the monitoring location of the empty product monitoring station 90.

The correction method of this creation mainly includes the following steps S10~S60:

Step S10: The environmental sensing device 10 to be calibrated is installed at any one or more empty product monitoring stations 90 of the national environmental protection agency or the environmental protection agency, wherein the environmental sensing device 10 has a display for displaying detection data outside Screen and sample gas sampling port to collect gas.

In this embodiment, the environment sensing device 10 includes a detection module 11, a communication module 12 for transmitting data, a positioning module 13 for confirming geographic location data, and a detection accuracy calibration module. A calibration module 14; wherein the detection module 11 has an air pollution source concentration sensor 150 capable of detecting a variety of pollutant gases or suspended particles, and a temperature/humidity sensor 160 that detects ambient temperature and humidity; an air pollution source concentration sensor 150 can sample air pollution sources containing at least one nitrogen oxide concentration (NOx), sulfur oxide concentration (SOx), carbon monoxide concentration (CO), carbon dioxide concentration (CO ₂ ), ozone concentration (O ₃ ), and a mixture of volatile organic substances Any one or a combination of gas concentration, particulate matter (PM10), and particulate matter concentration (PM2.5) mentioned above. To further illustrate, the sensors for collecting various parameters such as gas concentration, PM2.5/PM10 concentration, air temperature and relative humidity are integrated on a motherboard to form a complete environmental sensing device 10. The connection methods of these sensors and these modules can be plug-in (non-soldering) methods to facilitate maintenance, replacement and on-site installation.

Step S20: Use the sensors in the environmental sensing device 10 to detect the external temperature, humidity and air pollution sources, and record the geographic information of the environmental sensing device 10 through the positioning module 13 and correspond to the information obtained from the sensors The detection information is integrated to generate an empty product positioning data corresponding to the geographic location of the empty product monitoring station 90. Detailed information about the detection of the sensors in the environment sensing device 10 will be described later.

In this embodiment, the detection data is presented in the form of data of analog values measured by the detection module 11 of temperature and humidity, and external air pollution sources, and is generated after the built-in conversion relational calculation of the detection module 11 Corresponding detection information, but not limited to this. The conversion relation basically includes a first reference value, a second reference value, a first conversion coefficient, and a second conversion coefficient. When the measured analog value is below the first reference value, the corresponding detection information is equal to the analog value divided by the first reference value and then multiplied by the first conversion coefficient. When the measured analog value is greater than the first reference value and below the second reference value, the corresponding detection information is equal to the analog value divided by the difference between the second reference value and the first reference value and then multiplied by the second conversion coefficient .

Step S30: Send the empty product location data to a cloud server 20 via the communication module 12, and the cloud server 20 obtains the standard monitoring of the empty product monitoring station 90 corresponding to the location of the environmental sensing device 10 via the network connection News.

As mentioned above, the empty product location data records the empty product detection information (including the temperature and humidity detection value and the air pollution source concentration detection value) and geographic information of the location corresponding to the empty product monitoring station 90 of the environmental sensing device 10, and the empty product monitoring The station 90 will also transmit the standard monitoring information (including temperature and humidity reference values and air quality reference values) of the corresponding monitoring location to the cloud server 20 to facilitate subsequent data analysis and comparison calculations by the cloud server 20. In this embodiment, the cloud server 20 collects the empty product positioning data and the standard monitoring information for a collection time; the collection time is 3 to 30 days, but it is not limited to this, and can also be accumulated for a longer time according to demand. : One month or one quarter to accumulate and increase the data for big data analysis. In addition, the monitoring frequency during the collection time is generally collected every one hour.

Step S40: Through the cloud server 20, the empty product positioning data and the standard monitoring information of the empty product monitoring station 90 are analyzed and calculated to generate a calibration model, and the detection accuracy is corrected based on the calibration model to obtain the corrected empty product positioning data.

Continuing from the above, the empty product positioning data is analyzed and compared with the standard monitoring information of the corresponding location to generate a calibration model. In other words, after the cloud server 20 continues to collect data and accumulates the collection time, it combines the empty product positioning data with the standard monitoring information of the empty product monitoring station 90 at the corresponding location to generate correction data through big data analysis and calculation. In this embodiment, the cloud server 20 first distinguishes the standard measuring stations in a certain district of a certain city into various areas, and then collects the standard monitoring information and empty product positioning data in each area through the big data Analyze and adjust the calculation method to calculate the correction model.

Step S50: Repeat step S30 and step S40 every specific time within a calibration time, and perform the next detection accuracy calibration based on the empty product positioning data obtained after the previous calibration.

In this embodiment, the calibration time may be between 1 day and 7 days, but it is not limited to this, and the calibration time may be extended or shortened in accordance with the collection time or according to the actual situation. In addition, during the calibration time, the cloud server 20 will continue to analyze the standard monitoring information and the empty product positioning data obtained after the previous calibration, and update the calibration model every hour or day and send it to the calibration module 14. Perform the next detection accuracy calibration to achieve dynamic calibration.

Step S60: Move the environmental sensing device after the detection accuracy calibration is completed from the empty product monitoring station to the place where the environmental detection is required to be installed and activated.

Next, the method of generating the correction model in the above step S40 will be described below.

First, explain the method of generating the calibration model of the temperature/humidity sensor 160, which is mainly to calibrate the temperature and humidity through linear regression to analyze and explore the relationship between the single independent variable (x) and the strain term (y). Relation, by establishing the regression model to predict the strain term (y), as follows: y=αx+β.....

The calibration method is as follows: (1) Obtain the temperature and humidity detection value of the temperature and humidity sensor 160 (independent variable (x)) and the temperature and humidity reference value measured by the empty product monitoring station 90 (strain item (y)) (2) According to the linear regression formula, establish a calibration regression model between the temperature and humidity reference value and the temperature and humidity detection value as follows: temperature and humidity reference value (y) = α × temperature and humidity detection value (x) + β; (3) After linear fitting is performed, a fitting straight line is obtained to obtain the values of the correction parameters α and β; (4) The values of the correction parameters α and β are written into the environmental sensing device 10, so that the environmental sensing device 10 corrects the values The parameters α and β are substituted into the correction model as follows to obtain the temperature and humidity correction value: temperature and humidity correction value = α × temperature and humidity detection value + β.

In addition, the method of generating the calibration model of the air pollution source concentration sensor 150 for the pollution concentration in the sampled air is mainly through multiple regression analysis to correct the air quality measured by the air quality monitoring station 90 The reference value is used as the strain item (y), the air pollution source concentration detection value of the environmental sensing device 10 (measured value of total particulates, including measured value of suspended particulates and measured value of fine suspended particulates), and meteorological factors (detected value of temperature and humidity) As the relationship between the independent variable (x), through the establishment of the regression model, the strain term (y) can be predicted as follows: y=β ₀ +β ₁ x ₁ +β ₂ x ₂ +...+β _i x _i i=1,2,3,...,i

The calibration method is as follows: (1) The air quality reference value detected at the empty product monitoring station 90 is used as the contingency item (y), and the temperature and humidity reference value measured by the empty product monitoring station 90 and The air pollution source concentration detection value measured by the environmental sensing device 10 is used as the independent variable (x); (2) According to the multiple linear regression formula, a calibration regression model between multiple environmental test data and the reference value is established as follows: Air quality reference value = β ₀ + β ₁ × air pollution source concentration detection value + β ₂ × temperature reference value measured by empty product monitoring station 90 + β ₃ × relative humidity reference value measured by empty product monitoring station 90.

(3) After linear fitting is performed, a fitting straight line is obtained to obtain the values of the correction parameters β ₀ , β ₁ , β ₂ , and β ₃ ; (4) Write the values of the correction parameters β ₀ , β ₁ , β ₂ and β ₃ Into the environmental sensing device 10, the environmental sensing device 10 substitutes the correction parameters β ₀ , β ₁ , β ₂ , and β ₃ into the correction parameter model as follows to obtain the air pollution source concentration correction value: air pollution source concentration correction value = β ₀ + β ₁ × air pollution source concentration detection value + β ₂ × temperature correction value + β ₃ × relative humidity correction value.

In addition, based on the above-mentioned calibration method, this author proposes another embodiment. The difference from the above-mentioned embodiment is mainly that the environment sensing device 10 further includes an anemometer (not shown), the anemometer and the calibration module 14 Electrical connection, similar parts to the above embodiment will not be repeated here Narrated. The following is a description of the differences, please refer to Figure 3. In this embodiment, the calibration method includes steps S10'~S60': Step S10': install the environmental sensing device 10 to be calibrated in the environmental protection bureau of the country Or any one or more empty product monitoring stations 90 of the Environmental Protection Agency, wherein the environmental sensing device 10 has a display screen for displaying detection data and a sample gas sampling port for collecting gas.

Step S20': Use the sensors in the environmental sensing device 10 to detect the external temperature, humidity, wind speed, and air pollution sources, and record the geographic information of the environmental sensing device 10 through the positioning module 13 and correspond to the sensing The detection information obtained by the detector can be integrated to generate an empty product positioning data corresponding to the geographic location of the empty product monitoring station 90. The empty product location data records empty product detection information (including temperature and humidity detection value, wind speed detection value, and air pollution source concentration detection value) and geographic information of the location of the environmental sensing device 10 corresponding to the empty product monitoring station 90.

Step S30': The empty product location data is transmitted to a cloud server 20 via the communication module 12, and the cloud server 20 obtains the standard of the empty product monitoring station 90 corresponding to the position of the environmental sensing device 10 via the network connection Monitoring information (including temperature and humidity reference values, wind speed reference values, and air quality reference values).

Step S40': Through the cloud server 20, the empty product positioning data and the standard monitoring information of the empty product monitoring station 90 are analyzed and calculated to generate a calibration model and sent to the calibration module 14, and the detection accuracy is calibrated based on the calibration model to obtain the corrected model The location data of the empty product.

Step S50': Repeat step 30' and step 40' every specific time within a calibration time, and perform the next detection accuracy calibration based on the empty product positioning data obtained after the previous calibration.

Step S60': Move the environmental sensing device 10 after the detection accuracy calibration is completed from the empty product monitoring station to the place where the environmental detection is required for installation and use.

Next, the method of generating the calibration model in step S40' in this embodiment will be described below. The method of temperature and humidity calibration is the same as that described above, which will not be repeated here. The method of calibrating the wind speed value will describe the following steps: (1) The obtained environment The wind speed detection value measured by the sensing device 10 (independent variable (x)) and the wind speed reference value measured by the empty product monitoring station 90 (strain term (y)); (2) According to the linear regression formula, establish the temperature The calibration regression model between the humidity reference value and the temperature and humidity detection value is as follows: wind speed reference value (y)=γ×wind speed detection value (x) + δ; (3) After linear fitting, the fitting straight line is obtained to obtain the correction parameters The values of γ and δ; (4) Write the values of the correction parameters γ and δ into the environmental sensing device 10, so that the environmental sensing device 10 substitutes the correction parameters γ and δ into the correction parameter model as follows to obtain wind speed Correction value: Wind speed correction value = γ × wind speed detection value + δ, in order to obtain the wind speed correction value.

In addition, the calibration parameter generation method of the air pollution source concentration sensor 150 for the pollution concentration in the sampled air is mainly through multiple regression analysis to correct the air quality measured by the air quality monitoring station 90 The reference value is used as the strain item (y), the air pollution source concentration detection value of the environmental sensing device 10 (measured value of total particulates, including measured value of suspended particulates and measured value of fine suspended particulates), and meteorological factors (detected value of temperature and humidity, Wind speed detection value) is used as the relationship between the independent variable (x), and the strain term (y) can be predicted by the establishment of the regression model, as follows: y=β ₀ +β ₁ x ₁ +β ₂ x ₂ +. ..+β _i x _i ，i=1,2,3,....,i

The calibration method is as follows: (1) The air quality reference value detected at the empty product monitoring station 90 is used as the contingency item (y), and the temperature and humidity reference value measured by the empty product monitoring station 90, The wind speed reference value and the air pollution source concentration detection value measured by the environmental sensing device 10 are used as the independent variable (x); (2) According to the multiple linear regression formula, establish the relationship between the multiple environmental detection data and the reference value The calibration regression model is as follows: air quality reference value = β ₀ + β ₁ × air pollution source concentration detection value + β ₂ × wind speed reference value measured by the air product monitoring station 90 + β ₃ × air product monitoring station 90 Temperature reference value + β ₄ × relative humidity reference value measured by the empty product monitoring station 90.

(3) After performing linear fitting, a fitting straight line is obtained to obtain the values of the correction parameters β ₀ , β ₁ , β ₂ , β ₃ , and β ₄ ; (4) The correction parameters β ₀ , β ₁ , β ₂ , β ₃ The value of β ₄ is written into the environmental sensing device 10, so that the environmental sensing device 10 substitutes the correction parameters β ₀ , β ₁ , β ₂ , β ₃ , and β ₄ into the correction parameter model as follows to obtain the air pollution source Concentration correction value: air pollution source concentration correction value = β ₀ + β ₁ × air pollution source concentration detection value + β ₂ × wind speed correction value + β ₃ × temperature correction value + β ₄ × relative humidity correction value.

Please refer to Table 1 below, which is the difference between the PM2.5 concentration before/after calibration and the empty monitoring station after the environmental sensing devices (sensor1, sensor2..., sensor8) are calibrated with the calibration method of this creation And relevance. These environmental sensing devices are all installed at the Miaoli station. The monitoring period is from February 1, 2020 to March 14, 2020. A calibration model is established based on accumulated 14-day hourly empty product positioning data and hourly standard monitoring information , And make corrections every 1 hour. The results show that the difference percentage of each environmental sensing device before calibration is higher than 20%. Among them, the difference between the hourly value and daily average value of Sensor3 and the empty-product monitoring station is as high as 51.7 and 51.2% respectively, and then the calibration method of this creation is used for calibration After that, the percentage difference of each environmental sensing device was significantly reduced and was less than 10%, and the R ² value also increased significantly, and the daily average R ² value was all higher than 0.90.

Furthermore, in another embodiment of the present invention, the air pollution source concentration sensor 150 includes a light emitter 110, a light sensor 120, and a photoelectric conversion circuit 130. The light emitter 110 can be selected as an infrared module, a laser light module, a light emitting diode module or other light emitting modules. The light emitter 110 optically emits a predetermined light to the sample gas, and the sample gas may contain a plurality of fine suspended particles (PM 2.5, PM 10), so that when the predetermined light passes through the fine suspended particles of the sample gas, the predetermined light Produce a scattering, a refraction angle or a reflection angle.

In view of the above, the light sensor 120 can choose either a scattering detection or a non-scattering detection method; for example, the light sensor 120 can be a photodiode or a photoelectric crystal. Light sensor 120 is arranged at a predetermined light receiving angle of the light emitter 110, and the light sensor 120 measures the scattering, refraction or reflection of the predetermined light to obtain a light measurement value. To further illustrate, the composition of the light emitter 110 and the light sensor 120 is an optical detector, but the preliminary detection value is usually inaccurate, so further correction is required. The photoelectric conversion circuit can choose a physical circuit, a virtual circuit, an editable logic chip, an editable computer program, or a component with similar functions. The photoelectric conversion circuit 130 is used for converting the light measurement value into a suspended particle measurement value/fine suspended particle measurement value.

According to the technical idea of this creation, the calibration module 14 includes a component selected from a physical circuit, a virtual circuit, an editable logic chip, an editable computer program, or a similar function. In the foregoing embodiment, the calibration module 14 is provided in the environment sensing device 10, but not limited to this; as shown in FIG. 4, the calibration module 14 can also be provided in the cloud server 20, The calibrated empty product detection information is transmitted to the environmental sensing device 10 via the communication module 12.

The environmental sensing device 10 of this creation meets the following accuracy indicators within the working temperature and working humidity range: (1) Working principle: optical method (light scattering principle) to measure the number of particles with different particle sizes; (2) Measuring range: 1- 500μg/m ³ ; (3) Output resolution: 0.01μg/m ³ ; (4) Measurement accuracy: median of instrument error <30%; (5) Working temperature: 0-40℃; (6) Working humidity: 0-85% RH without condensation; (7) Power supply: 5.0V; (8) Output mode: UART output.

About the temperature and humidity sensor adopts a digital integrated temperature and humidity sensor, which has the characteristics of high measurement accuracy, fast response time, and high stability.

Humidity measurement: (1) Relative humidity measurement range: 0-100%RH; (2) Output resolution: 0.03% RH; (3) Measurement accuracy: <±5%RH; (4) Operating temperature range: -40- 110℃; (5) Response time: 5s; (6) Power supply: 3.0-5.0V; (7) Anti-condensation.

Temperature measurement: (1) Temperature measurement range: -40~100℃; (2) Output resolution: 0.016℃; (3) Measurement accuracy: <±0.5℃; (4) Operating temperature range: -40~110℃; (5) Response time: 1s; (6) Power supply: 3.0-5.0V; (7) Anti-condensation.

In addition, according to the technical idea of this creation, the concentration of air pollution sources can also be divided into a plurality of sections from low to high, and the correction model of the concentration of air pollution sources in each section can be converted to improve the accuracy of regression fitting. degree.

For example, the concentration may be in PM2.5 5μg / m ³ is set to the dividing point, the first section is PM2.5 concentration between 1 ~ 5μg / m ^3, PM2.5 concentration of the second section Is greater than 5μg/m ³ , and then the air pollution source concentration detection values falling within the numerical range of the first section and the second section, and the air quality reference value and related meteorological factors are linearly fitted to obtain the The air pollution source concentration correction model corresponding to the section, and the air pollution source concentration correction model corresponding to the second section.

In addition, the sensors and electronic components in the environmental sensing device 10 described in this creation should choose products with low drift coefficients to eliminate the problem of accuracy drift caused by long-term work or the influence of temperature and humidity from the source, according to changes in environmental temperature and humidity. , The collected data is automatically corrected and compensated through the above-mentioned correction parameters to ensure the accuracy of the detected data.

1Km；串列傳輸速率為9600；通訊協定為MODBUS-RTU。 In this embodiment, the communication module 12 may have at least one communication interface of WIFI, Ethernet, RS485, 4G and bluetooth 5.0: (1) The WIFI interface should support the network communication protocol IEEE802.11 B/ G/N and IEEE802.1X; support most WIFI encryption methods and algorithms WEP/WAP-PSK/WAP2-PSK/WAPI; support encryption type WEP64/WEP128/TKIP/AES; support communication protocol MODBUS-TCP; fault detection It shall have the function of automatic monitoring of WIFI connection, and the instrument shall be able to automatically restart and restore the connection if the WIFI connection is interrupted. (2) The Ethernet interface is a 10/100M self-adjusting RJ45 port; it supports the communication protocol MODBUS-TCP. (3) The working mode of the RS485 interface is half-duplex; the transmission medium is twisted pair; the transmission distance

1Km; serial transmission rate is 9600; communication protocol is MODBUS-RTU.

To sum up, this creation of the calibration method to improve the detection accuracy of environmental sensing devices uses environmental sensing devices deployed at multiple empty product monitoring stations to cooperate with positioning to generate corresponding empty product positioning data, and provide a cloud server for certain collection Data time and analysis calculation processing to generate calibration parameter commands, which can calibrate the empty product positioning data and standard monitoring information to ensure its accuracy and fairness, and continuously update the calibration model for dynamic calibration during the calibration process, so it can indeed achieve the cost The purpose of creation.

The embodiments of this creation are described above with reference to the accompanying drawings, but the creation is not limited to the above-mentioned specific implementations. The above-mentioned specific implementations are only illustrative and not restrictive. Those of ordinary skill in the art are Under the enlightenment of this creation, many forms can be made without departing from the purpose of this creation and the scope of protection of the scope of patent application, and these are all within the protection of this creation.

10: Environmental sensing device

11: Detection module

12: Communication module

13: positioning module

14: Calibration module

110: light emitter

120: light sensor

130: photoelectric conversion circuit

150: Air pollution source concentration sensor

160: temperature/humidity sensor

20: Cloud server

90: Empty product monitoring station

Claims (13)

A calibration system for improving the detection accuracy of environmental sensing devices, which includes: an empty product monitoring station, which is set up to provide a standard monitoring information of the monitoring place; the environmental sensing device to be calibrated, which is set up in the air In the product monitoring station, and based on the geographic information of the environmental sensing device and the empty product detection information, an empty product location data corresponding to the geographic location of the empty product monitoring station is integrated and generated; and the cloud server is connected to the empty product monitoring The station and the environmental sensing device are in communication connection to obtain the empty product location data and a standard monitoring information corresponding to the monitoring location of the empty product monitoring station; wherein the cloud server will accumulate the empty product location within a collection time The data is compared with the standard monitoring information for detection accuracy correction, the corrected empty product positioning data is obtained, and the next time is performed based on the empty product positioning data obtained after the previous calibration every specific time within a calibration period The detection accuracy of the empty product; and the empty product detection information is at least one of temperature and humidity detection values, wind speed detection values, and air pollution source concentration detection values. The calibration system for improving the detection accuracy of the environmental sensing device described in claim 1, wherein the cloud server uses multiple linear regression to establish a calibration model for temperature, humidity, wind speed, and air pollution source concentration. The calibration system for improving the detection accuracy of environmental sensing devices as described in claim 2, wherein the cloud server is provided with a calibration module, the calibration module calibrates the empty product detection information based on the calibration model, and the calibrated The empty product detection information is sent to the environment sensing device. The calibration system for improving the detection accuracy of an environmental sensing device as described in claim 2, wherein the environmental sensing device includes: a detection module for detecting the environment and generating the empty product detection information; A communication module, which is connected to the detection module and the cloud server, to transmit the empty product detection information; a positioning module, which is electrically connected to the communication module, to confirm the geographic location And generate the geographic information; and a calibration module, which is electrically connected with the communication module, for receiving the calibration model and calibrating the empty product detection information based on the calibration model. The calibration system for improving the detection accuracy of the environmental sensing device as described in claim 4, wherein the detection module includes an air pollution source concentration sensor, and the air pollution source concentration sensor includes a light emitter and a light sensor And a photoelectric conversion circuit. The calibration system for improving the detection accuracy of the environmental sensing device described in claim 5, wherein the light emitter optically emits a predetermined light to the sample gas, and the sample gas may contain a plurality of suspended particles or fine suspended particles, So that when the predetermined light passes through the fine suspended particles of the sample gas, it causes the predetermined light to produce a scattering, a refraction angle or a reflection angle; the light sensor is a scattering detection or a photodiode based on a non-scattering detection method Body or photoelectric crystal, the light sensor is configured to measure the scattering, refraction or reflection of the predetermined light with respect to the predetermined light receiving angle of the light emitter to obtain a light measurement value; and the photoelectric conversion circuit is used for The light measurement value is converted into a suspended particle measurement value or a fine suspended particle measurement value. The calibration system for improving the detection accuracy of the environmental sensing device described in claim 5, wherein the communication module has at least one communication interface of WIFI, Ethernet, RS485, 4G and Bluetooth 5.0. The calibration system for improving the detection accuracy of environmental sensing devices as described in claim 3 or 4, wherein the method for generating the calibration model for temperature and humidity includes: obtaining the temperature and humidity reference value obtained by the empty product monitoring station for the environment in which it is located , And the temperature and humidity detection value measured by the environmental sensing device at the same location; Establish a calibration regression model between temperature and humidity reference value and temperature and humidity detection value: temperature and humidity reference value (y)=α×temperature and humidity detection value (x) + β; among them, α and β are calibration parameters; regression based on this calibration After the model is linearly fitted, the correction parameters α and β are obtained; the data of the correction parameters α and β are written into the temperature/humidity sensor to establish the correction model as follows: temperature and humidity correction value = α × temperature and humidity detection value + β. The calibration system for improving the detection accuracy of environmental sensing devices as described in claim 8, wherein the method for generating a calibration model for the concentration of air pollution sources includes: obtaining the air pollution source concentration reference value obtained by the empty monitoring station for the environment where it is located, The reference value of temperature and humidity, and the detection value of air pollution source concentration measured by the environmental sensing device at the same location; according to the multiple linear regression formula, establish the temperature and humidity reference value, the detection value of air pollution source concentration and the reference value of air pollution source concentration Calibration regression model: air quality reference value = β ₀ + β ₁ × air pollution source concentration detection value + β ₂ × temperature reference value measured by the empty product monitoring station + β ₃ × relative humidity measured by the empty product monitoring station Reference value; among them, β ₀ , β ₁ , β ₂ , β ₃ are calibration parameters; after linear fitting is performed on the calibrated regression model, the calibration parameters β ₀ , β ₁ , β ₂ , β _{3 are obtained} ; The data of the calibration parameters are written into the environmental sensing device to establish a calibration model: air pollution source concentration correction value = β ₀ + β ₁ × air pollution source concentration detection value + β ₂ × temperature correction value + β ₃ × relative humidity correction value. As described in claim 9 of the calibration system for improving the detection accuracy of environmental sensing devices, the cloud server further divides the concentration of air pollution sources into a plurality of sections from low to high, and converts them into sections in each section. Correction model. The calibration system for improving the detection accuracy of the environmental sensing device as described in claim 8, wherein the method for generating the calibration model for wind speed includes: obtaining the wind speed reference value obtained by the empty product monitoring station for the environment where it is located, and in the same location The wind speed detection value measured by the environmental sensing device; According to the linear regression formula, establish a calibration regression model between the wind speed reference value and the wind speed detection value: wind speed reference value (y) = γ × wind speed detection value (x) + δ; among them, γ and δ are the correction parameters; based on the calibration The regression model is linearly fitted to obtain these correction parameters γ and δ; the data of the correction parameters are written into the environmental sensing device to establish a correction model: wind speed correction value = γ×wind speed detection value + δ. The calibration system for improving the detection accuracy of environmental sensing devices as described in claim 11, wherein the method for generating a calibration model for the concentration of air pollution sources includes: obtaining the air pollution source concentration reference value obtained by the air pollution monitoring station for the environment where it is located, The reference value of temperature and humidity, the reference value of wind speed, and the detection value of air pollution source concentration measured by the environmental sensing device at the same location; according to the multiple linear regression formula, the reference value of temperature and humidity, the reference value of wind speed, and the detection value of air pollution source concentration are established Calibration regression model between air pollution source concentration reference value and air pollution source concentration reference value = β ₀ + β ₁ × air pollution source concentration detection value + β ₂ × wind speed reference value measured by the air quality monitoring station + β ₃ × air The temperature reference value measured by the product monitoring station + β ₄ × the relative humidity reference value measured by the empty product monitoring station; among them, β ₀ , β ₁ , β ₂ , β ₃ , and β ₄ are the calibration parameters; based on the calibration The regression model is linearly fitted to obtain the calibration parameters β ₀ , β ₁ , β ₂ , β ₃ , β ₄ ; the data of these calibration parameters are written into the environmental sensing device to establish a calibration model: air pollution source concentration Correction value = β ₀ + β ₁ × air pollution source concentration detection value + β ₂ × wind speed correction value + β ₃ × temperature correction value + β ₄ × relative humidity correction value. For the calibration system for improving the detection accuracy of environmental sensing devices as described in claim 12, the cloud server further divides the concentration of air pollution sources into a plurality of sections from low to high, and converts them into sections in each section. Correction model.

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