WO2019222964A1 - Procédé permettant de déterminer un équipement de détection, dispositif de détection et support d'informations lisible - Google Patents

Procédé permettant de déterminer un équipement de détection, dispositif de détection et support d'informations lisible Download PDF

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Publication number
WO2019222964A1
WO2019222964A1 PCT/CN2018/088250 CN2018088250W WO2019222964A1 WO 2019222964 A1 WO2019222964 A1 WO 2019222964A1 CN 2018088250 W CN2018088250 W CN 2018088250W WO 2019222964 A1 WO2019222964 A1 WO 2019222964A1
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Prior art keywords
detected substance
detection device
substance
determining
detected
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Ceased
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PCT/CN2018/088250
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English (en)
Chinese (zh)
Inventor
骆磊
牟涛涛
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Cloudminds Shenzhen Holdings Co Ltd
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Cloudminds Shenzhen Holdings Co Ltd
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Priority to PCT/CN2018/088250 priority Critical patent/WO2019222964A1/fr
Priority to CN201880001107.4A priority patent/CN108780048B/zh
Publication of WO2019222964A1 publication Critical patent/WO2019222964A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/71—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light thermally excited
    • G01N21/718—Laser microanalysis, i.e. with formation of sample plasma
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/65—Raman scattering

Definitions

  • the present application relates to the field of detection, and in particular, to a method, a detection device, and a readable storage medium for determining a detection device.
  • the inventor has discovered in the process of studying the prior art that the current two-in-one products are simply a combination of the two, that is, two types of detection equipment are put in one structure.
  • the two detection devices are completely independent, with their own detection light paths and different laser focus positions, and there is not much difference between holding a Raman detection device and a Libs detection device. If the user does not know which kind of detection equipment should be used for the detection of a substance, two kinds of detection equipment should be used to detect the substance separately, resulting in a lower detection efficiency of the user.
  • a technical problem to be solved in some embodiments of the present application is how to determine which kind of detection equipment is used to detect a substance to be detected.
  • An embodiment of the present application provides a method for determining a detection device, including: obtaining particle composition information of a detected substance; wherein the particle composition information is used to indicate that the detected substance is composed of atoms, the detected substance is composed of molecules, and Determining any one of the attributes of particles constituting the detected substance; and determining a detection device for detecting the detected substance based on the particle composition information of the detected substance.
  • An embodiment of the present application further provides a detection device, including an acquisition module and a determination module; the acquisition module is used to acquire particle composition information of a detected substance; wherein the particle composition information is used to indicate that the detected substance is composed of atoms, The detection substance is composed of molecules and the attributes of the particles constituting the detection substance cannot be determined; the determination module is used to determine a detection device for detecting the detection substance based on the particle composition information of the detection substance.
  • An embodiment of the present application further provides a detection device, including at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are at least A processor executes to enable at least one processor to execute the method for determining a detection device mentioned in the foregoing embodiment.
  • An embodiment of the present application further provides a computer-readable storage medium storing a computer program.
  • the computer program is executed by a processor, the method for determining a detection device mentioned in the foregoing embodiment is implemented.
  • the embodiments of the present application allow the detection device to determine the detection for detecting the detected substance by acquiring the particle composition information of the detected substance when the user is not sure which detection equipment is used to detect the detected substance.
  • the device improves the detection efficiency of the user and the intelligence of the detection device.
  • FIG. 1 is a flowchart of a method for determining a detection device according to a first embodiment of the present application
  • FIG. 2 is a flowchart of a method for determining a detection device according to a second embodiment of the present application
  • FIG. 3 is a schematic structural diagram of a detection device according to a third embodiment of the present application.
  • FIG. 4 is a schematic structural diagram of a detection device according to a fourth embodiment of the present application.
  • FIG. 5 is a schematic structural diagram of a detection device using an independent laser light path structure according to a fourth embodiment of the present application.
  • FIG. 6 is a schematic structural diagram of a detection device using a common laser light path structure according to a fourth embodiment of the present application.
  • FIG. 7 is a schematic structural diagram of a detection device according to a fifth embodiment of the present application.
  • the detection devices in the embodiments of the present application are all combined detection devices, and at least two types of detection devices are provided.
  • a combination of a Raman detection device and a Libs detection device is taken as an example.
  • a method of determining the detection device by other combined detection devices refer to the embodiments of the present application.
  • the first embodiment of the present application relates to a method for determining a detection device, which is applied to a detection device.
  • a method for determining a detection device includes:
  • Step 101 Obtain particle composition information of the detected substance.
  • the particle composition information is used to indicate any one of an atomic substance to be detected, a molecular substance to be detected, and an attribute whose particles constitute the substance to be detected cannot be determined.
  • the detection device determines whether a specified instruction specifying a detection device is received. If a specified instruction is received, the specified detection equipment is directly called to detect the detected substance. For example, if the user knows the properties of the particles constituting the detected substance and manually selects the Libs detection device, the Libs detection device is directly activated. If the designated instruction is not received, the method for determining the detection device is executed to determine the detection device for detecting the detected substance.
  • Step 102 Determine a detection device for detecting the detected substance according to the particle composition information of the detected substance.
  • the detection device determines that the particle composition information indicates that the detected substance is composed of atoms, it determines that the detection device for detecting the detected substance is a first detection device, such as a Libs detection device.
  • the first detection device is configured to obtain a first spectrum of the detected substance, and the first spectrum is used to characterize an atomic composition of the detected substance.
  • the detection device determines that the particle composition information indicates that the detected substance is composed of molecules, it determines that the detection device for detecting the detected substance is a second detection device, such as a Raman detection device.
  • the second detection device is used to obtain a second spectrum of the detected substance, and the second spectrum is used to characterize the molecular composition of the detected substance. If it is determined that the particle composition information indicates that the attributes constituting the detected substance cannot be determined, the detection equipment used to detect the detected substance is determined to be the first detection equipment and the second detection equipment.
  • the particle composition information is determined according to the probability that the detected substance is composed of atoms.
  • the particle composition information indicates that the detected substance is composed of atoms.
  • the particle composition information indicates that the detected substance is composed of molecules.
  • the preset value can be 50% or 60%.
  • the particle composition information is determined according to the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules.
  • the detection device when a user is not sure which detection device is used to detect a detected substance, the detection device can determine the The detection equipment for detecting the detected substance improves the detection efficiency of the user and the intelligence of the detection device.
  • the second embodiment of the present application relates to a method for determining a detection device.
  • This embodiment is a further refinement of the first embodiment, and specifically describes step 101 and other related steps.
  • this embodiment includes steps 201 to 207.
  • step 203 is substantially the same as step 102 in the first embodiment, which will not be described in detail here. The following mainly describes the differences:
  • Step 201 Obtain test data of the detected substance.
  • the user places the sample at a specified location and clicks to start the test.
  • the detection device receives a detection instruction, it obtains test data of the detected substance.
  • the test data of the detected substance includes an image of the detected substance.
  • Step 202 Input the test data of the detected substance into a classification model trained in advance, and determine the particle composition information of the detected substance according to the output of the classification model.
  • the classification model is used to define the correspondence between the test data of the detected substance and the particle composition information of the detected substance.
  • atomic substances only include very few substances such as metals, diamonds, graphite, and rare gases
  • the above substances are used as atomic substances, and substances other than the above substances are used as molecular substances.
  • An image of atomic matter is stored in a training module for training a classification model, and features in the image of atomic matter are extracted through a Convolutional Neural Network (CNN).
  • CNN Convolutional Neural Network
  • the process of training the classification model may be performed in a detection device, or may be performed in another device that communicates with the detection device.
  • the training data is transmitted to the cloud, and the classification model is trained by the cloud.
  • a detection device for detecting a substance to be detected is determined.
  • detection devices for detecting molecular substances in the detection device include Raman detection equipment and infrared detection equipment, and the classification model can be trained according to which substances the Raman detection equipment and the infrared detection equipment are suitable for detecting, respectively.
  • the detection device is also provided with a microwave detection device. Since Raman detection equipment and Libs detection equipment cannot detect the detected substance in the metal bottle, the test data of the detected substance also includes information on the container containing the detected substance.
  • the classification model determines that the detection device for detecting the detection substance is a microwave detection device when it is determined that the detection substance is placed in the metal bottle according to the container information containing the detection substance.
  • the classification model determines that the test substance is not placed in the metal bottle based on the information of the container containing the test substance, it determines the attributes of the particles constituting the test substance based on the test substance's test data and other data. Further, the classification model determines that the detection device used to detect the detected substance is a Libs detection device or a Raman detection device according to the attributes of the particles constituting the detected substance.
  • test data of the detected substance may also include data obtained by detecting the detected substance such as an odor sensor, an infrared sensor, and the like.
  • the output of the classification model may be the particle composition information of the detected substance; it may also be the probability that the detected substance is composed of atoms, and the probability that the detected substance is composed of molecules.
  • the output of the classification model is the particle composition information of the detected substance.
  • the classification model determines the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules based on the test data of the detected substance.
  • the output of the classification model is determined based on the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules.
  • the method of determining the output of the classification model based on the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules is determined below.
  • Method 1 The classification model determines whether the probability that the detected substance is composed of atoms is greater than the probability that the detected substance is composed of molecules. If so, the output of the classification model is determined to be that the detected substance is composed of atoms; otherwise, the output of the classification model is determined to be detected. Matter is made up of molecules.
  • Method 2 The classification model determines whether the difference between the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules is greater than a threshold. For example, the threshold is 10%. If the determination is greater than the threshold, the classification model further determines the attributes of the particles constituting the detected substance according to the method described in Mode 1. Otherwise, it is determined that the output of the classification model cannot determine the attributes of the particles constituting the detected substance.
  • a threshold is 10%. If the determination is greater than the threshold, the classification model further determines the attributes of the particles constituting the detected substance according to the method described in Mode 1. Otherwise, it is determined that the output of the classification model cannot determine the attributes of the particles constituting the detected substance.
  • the output of the classification model is the probability that the detected substance is composed of atoms, and the probability that the detected substance is composed of molecules.
  • the detection device determines particle composition information of the detected substance based on the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules.
  • the detection device determines the particle composition information of the detected substance based on the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules, and the classification model is based on the probability that the detected substance is composed of atoms. , And the probability that the detected substance is composed of molecules, the method of determining the output of the classification model is roughly the same, and is not repeated here.
  • Step 204 Calling a detection device for detecting the detected substance to detect the detected substance.
  • Step 205 Determine whether the spectrum detected by the detection device for detecting the detected substance meets a preset requirement.
  • the preset requirement may be that the signal-to-noise ratio of the spectrum is in a preset range, and / or there are peaks in the waveform of the spectrum. If the detection device determines that the spectrum meets the preset requirements, step 206 is performed, and if it is determined that the spectrum does not meet the preset requirements, the detection device performs step 207.
  • Step 206 Determine the detection result of the detected substance according to the spectrum. End the process of determining the detection equipment.
  • the detection device calls a matching algorithm, matches the spectrum of the detected substance with the spectrum of a known sample stored in advance, determines the detection result according to the matching result, and presents the detection result to the user.
  • the detection device may use the test data of the detected substance and the particle composition information of the detected substance as training data of the classification model to train the classification model; wherein the classification model is used to define Correspondence between the test data of the test substance and the particle composition information of the test substance.
  • the data of all detection devices can be used as training data in the cloud, which improves the training speed.
  • the increase in training data makes the training results more accurate.
  • Step 207 Calling a detection device other than the detection device for detecting the detected substance to detect the detected substance.
  • the classification model may be incorrectly classified, or the test data of the detected substance is incorrect, resulting in a detection device.
  • Misidentification issues occur, such as misidentifying atomic matter as molecular matter, or the substance being detected as molecular matter without a Raman signal. In this case, another detection device is called to detect the detected substance.
  • the detection device used to detect the detected substance is a user-specified detection device, a detection abnormality is prompted, and another detection device may be used for detection.
  • the detection device when a user is not sure which detection device is used to detect a detected substance, the detection device can determine the The detection equipment for detecting the detected substance improves the detection efficiency of the user and the intelligence of the detection device.
  • the data of all detection devices when training a classification model in the cloud, the data of all detection devices can be used as training data in the cloud, which improves the training speed. The increase in training data makes the training results more accurate.
  • a third embodiment of the present application relates to a detection device.
  • the detection device includes an obtaining module 301 and a determining module 302.
  • the obtaining module 301 is configured to obtain particle composition information of a detected substance.
  • the particle composition information is used to indicate any one of an atomic substance to be detected, a molecular substance to be detected, and an attribute whose particles constitute the substance to be detected cannot be determined.
  • the determining module 302 is configured to determine a detection device for detecting the detected substance according to the particle composition information of the detected substance.
  • this embodiment is a system embodiment corresponding to the first embodiment, and this embodiment can be implemented in cooperation with the first embodiment.
  • the related technical details mentioned in the first embodiment are still valid in this embodiment. To reduce repetition, details are not described here. Accordingly, the related technical details mentioned in this embodiment can also be applied in the first embodiment.
  • the fourth embodiment of the present application relates to a detection device.
  • This embodiment is a refinement of the third embodiment, and specifically describes the function of the acquisition module and other modules of the detection device.
  • the detection device includes: an obtaining module 401, a determining module 402, and a calling module 403.
  • the obtaining module 401 is specifically configured to obtain test data of a detected substance, input the test data of the detected substance into a classification model trained in advance, and determine particle composition information of the detected substance according to an output of the classification model.
  • the calling module 403 is used to call the detection device for detecting the detected substance to detect the detected substance; determine whether the spectrum detected by the detection device for detecting the detected substance meets the preset requirements, and if so, determine the detection result of the detected substance according to the spectrum ; Otherwise, call a detection device other than the detection device for detecting the detected substance to detect the detected substance.
  • the detection device uses the first detection device 404 and the second detection device 405 as examples to describe the structure of the detection device. In practical applications, the number of detection devices can be set as required.
  • the first detection device 404 and the second detection device 405 may be set so that the focal points do not coincide, and the two may be set as a common focus.
  • the first detection device 404 and the second detection device 405 may be two independent laser light paths, or they may share the last part of the laser light path. Among them, a detection device using an independent laser light path structure is shown in FIG. 5, and a detection device using a common laser light path structure is shown in FIG. 6.
  • this embodiment is a system embodiment corresponding to the second embodiment, and this embodiment can be implemented in cooperation with the second embodiment.
  • the related technical details mentioned in the second embodiment are still valid in this embodiment. To reduce repetition, details are not described here. Accordingly, the related technical details mentioned in this embodiment can also be applied in the second embodiment.
  • a fifth embodiment of the present application relates to a detection device, as shown in FIG. 7, including at least one processor 501; and a memory 502 communicatively connected to the at least one processor 501.
  • the memory 502 stores instructions that can be executed by the at least one processor 501, and the instructions are executed by the at least one processor 501, so that the at least one processor 501 can execute the method for determining a detection device.
  • the processor 501 is a central processing unit (Central Processing Unit, CPU) as an example
  • the memory 502 is a readable and writable memory (Random Access Memory (RAM) as an example.
  • the processor 501 and the memory 502 may be connected through a bus or in other manners. In FIG. 7, the connection through the bus is taken as an example.
  • the memory 502 is a non-volatile computer-readable storage medium and can be used to store non-volatile software programs, non-volatile computer executable programs, and modules.
  • the classification model in the embodiment of the present application can be stored in the memory. 502.
  • the processor 501 executes various functional applications and data processing of the device by running non-volatile software programs, instructions, and modules stored in the memory 502, that is, the above method for determining a detection device is implemented.
  • the memory 502 may include a storage program area and a storage data area, where the storage program area may store an operating system and an application program required for at least one function; the storage data area may store a list of options and the like.
  • the memory 502 may include a high-speed random access memory, and may further include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage device.
  • the memory 502 may optionally include a memory remotely set relative to the processor, and these remote memories may be connected to an external device through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
  • One or more modules are stored in the memory, and when executed by one or more processors, execute the method for determining a detection device in any of the foregoing method embodiments.
  • the above product can execute the method provided in the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method.
  • the above product can execute the method provided in the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method.
  • a sixth embodiment of the present application relates to a computer-readable storage medium storing a computer program.
  • the computer program is executed by a processor, the method for determining a detection device described in any of the above method embodiments is implemented.
  • the program is stored in a storage medium and includes several instructions to make a device ( It may be a single-chip microcomputer, a chip, or the like) or a processor that executes all or part of the steps of the method described in each embodiment of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disks or optical disks and other media that can store program code .

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Abstract

L'invention porte sur un procédé permettant de déterminer un équipement de détection, un dispositif de détection et un support d'informations lisible. Le procédé permettant de déterminer un équipement de détection comprend les étapes consistant : à acquérir des informations de composition de particules d'une matière détectée (101), lesdites informations servant à indiquer que la matière détectée est composée d'atomes, que la matière détectée est composée de molécules, ou qu'il n'est pas possible de déterminer les propriétés des particules dont la matière détectée est composée ; et à déterminer un équipement de détection utilisé pour détecter la matière détectée en fonction des informations de composition de particules de la matière détectée.
PCT/CN2018/088250 2018-05-24 2018-05-24 Procédé permettant de déterminer un équipement de détection, dispositif de détection et support d'informations lisible Ceased WO2019222964A1 (fr)

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PCT/CN2018/088250 WO2019222964A1 (fr) 2018-05-24 2018-05-24 Procédé permettant de déterminer un équipement de détection, dispositif de détection et support d'informations lisible
CN201880001107.4A CN108780048B (zh) 2018-05-24 2018-05-24 一种确定检测设备的方法、检测装置及可读存储介质

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