CN106123789A - The identification device of a kind of wooden boards burr and recognition methods - Google Patents

Abstract

The invention discloses an identification device for burrs of wooden boards, which comprises a transmission table, a laser emitter, a bracket, and an area array industrial camera. A laser emitter and an area array industrial camera are arranged on the support, and the light source emitted by the laser emitter to the surface of the measured wooden board on the transfer table is received by the area array industrial camera after being reflected by the measured wooden board, and the area array industrial camera Simultaneously communicate with a computer. The invention also discloses its identification method. The method of the present invention does not need manual operation when detecting the burrs of wooden boards, and realizes automation, and the wooden boards to be tested are in the process of continuous conveyance during measurement, which improves work efficiency, and at the same time, the identification device used is simple in structure and easy to install ,low cost.

Description

A device and method for identifying rough edges of wooden boards

technical field

The invention relates to an identification device and an identification method, in particular to an identification device and an identification method for the burrs of wooden boards, belonging to the field of wood processing and manufacturing.

Background technique

In recent years, my country's timber industry has developed rapidly, but the scope of forest resource exploitation is gradually decreasing. Forest resources are facing a serious shortage problem, and the contradiction between supply and demand of timber is becoming increasingly acute. This puts forward higher and higher demands on maximizing the value of timber resources Require. In the case of lack of wood resources, improving the utilization of wood is an urgent problem in the field of wood processing and automation. In the processing and production of many wood products, logs are sawed into boards with a certain thickness. The cross-section of the log can be approximately regarded as a circle, and the log can be approximated as a cylinder, and the general sawing process is parallel to the axis of the cylinder. The section of the long board after sawing is not a regular rectangle, but a trapezoid with irregular curved sides on both sides. Figure 1 is a schematic diagram of the structure of the rough-edged board, as shown in Figure 1: this kind of board is called a raw-edged board, and the irregular trapezoidal edge is called a raw-edged board, which is located on both sides of the board. Figure 2 is a schematic structural view of the unedged plate in the sawing state, as shown in Figure 2: Generally, in the subsequent section, the burrs of the unedged plate are often removed to make the cross-section of the plate into a regular rectangle, so as to facilitate subsequent processing and utilization. Since the cross-section of the wood itself is similar to a circle, it is impossible to completely remove this kind of rough board. There are also wider boards that can be optimized to obtain the maximum profit or save raw materials after determining the rough edges. However, as the natural forest with a larger diameter is prohibited from logging , Small-diameter plantations are widely used. There will be more such burr boards, and the ratio of the burrs to the board area is larger. Reasonable and rapid removal of burrs can improve wood utilization and production efficiency.

At present, the identification of the raw edges of the raw wood boards is mainly done manually. The method is to place the raw boards on the conveyor belt of the machine tool to be sawed, and there are several rows of movable lasers directly above the conveyor belt. The laser can emit a laser beam, and the operator uses a joystick to operate the laser to move, select a suitable position, and the laser can make a laser line on the raw material to be sawed. If the operator thinks that the laser line just falls on all the raw edges Inside, note down the current position of the laser line at this time. After marking the positions of the laser lines on both sides, you can enter the saw machine for sawing. Generally, when the rough edge is determined, the rough board is still on the conveyor belt. After confirmation, the board starts to move again and enters the saw machine for sawing. One of the disadvantages of this method is that the inner edge of the rough edge is identified by the naked eye, and the labor intensity of the worker is high during work, which is easy to visual fatigue; secondly, the rough edge board is required to be stationary when judging the inner edge of the rough edge, which reduces the work efficiency; Once again, this method will have control systems such as special guide rails and servo motors when in use, and the cost is relatively high and difficult to promote.

Contents of the invention

In order to overcome the problems in the prior art, the purpose of the present invention is to provide a recognition device and method for the burrs of wooden boards with high degree of automation and high measurement accuracy.

In order to solve the problems of the technologies described above, the technical solution adopted in the present invention is:

A device for identifying rough edges of wooden boards, including a conveyor table, a laser transmitter, a bracket, and an area array industrial camera. Transmitter and area array industrial camera, and the light source emitted by the laser transmitter to the surface of the measured wooden board on the transfer table is received by the area array industrial camera after being reflected by the measured wooden board, and the area array industrial camera is connected with a computer at the same time connected.

A method for identifying rough edges of wooden boards, comprising the following steps:

S1: The laser transmitter emits a laser light source to the tested wooden board passing on the conveyor table, and the fan-shaped laser light source on the surface of the tested wooden board is reflected and received by the area array industrial camera;

S2: The area array industrial camera converts the obtained laser light source information reflected by the measured wooden board into the thickness profile image information of the tested wooden board;

S3: The data acquisition card in the computer collects the thickness profile image information of the measured wooden board from the area array industrial camera, and obtains the thickness information of the measured wooden board after calculation by the computer's data processing software;

S4: According to the thickness information of the measured wooden board, determine the boundary point between the normal board surface and the rough edge of the wooden board, detect a boundary point every certain length, and use the innermost boundary point among the boundary points measured on the same side as the sawing Point, remove the burrs along the sawing road parallel to the centerline of the normal board surface.

Further, in step S1, the laser light source emitted by the laser transmitter to the wooden product under test is a fan-shaped laser light source, and the light bars formed on the surface of the wood product under test are in-line light bars.

In step S2, each time the laser emitter emits a laser light source, the converted thickness profile image information of the measured wooden board is the thickness value pixel and width value pixel of the measured section of the wooden board.

And in step S2, the method of converting the laser light source information into the thickness profile image information of the measured wooden board is: the optical signal is received by the area array industrial camera and converted into a charge signal, and then converted into digital image signal.

And in S3 step, the calculation formula of the data processing software of described computer is: x=k y (1)

In the formula (1), x is the detected thickness value of the measured wooden board; y is the offset of the measured wooden board surface and the reference bottom surface in the area array industrial camera, and y is shown as the thickness of the wooden board in the thickness profile image; k is the spatial resolution, and the k is the linear relationship coefficient between the offset y between the surface of the measured wooden board and the reference bottom surface in the area array industrial camera and the detected thickness value x of the wooden board.

The numerical formula of described k is: k=1/(β sin θ), in the numerical formula of k, β is the optical element of objective lens in the area array industrial camera and the transverse magnification of imaging system, described transverse enlargement The magnification is: after the light source emitted by the laser transmitter is received by the area array industrial camera, the ratio of the thickness of the measured wooden board to the image height after being imaged by the area array industrial camera optical elements and the imaging system; θ is the axis and surface of the laser transmitter The angle between the optical axis of the objective lens in the array industrial camera, β and θ can be measured, and when the imaging system is fixed, the lens position of the area array industrial camera is fixed and the inclination angle is determined, the height of the laser transmitter from the transmission table is determined, and the axis of the laser transmitter The angle θ with the optical axis of the objective lens in the area array industrial camera is fixed, and the lateral magnification β of the optical element of the objective lens and the imaging system in the area array industrial camera is fixed, so k is also a fixed value.

And in step S3, it also includes the step of using standard gauge blocks for calibration, and the calibration method is: put standard gauge blocks of different thicknesses under the laser transmitter for calibration, gauge blocks of different thicknesses, and sample in the thickness direction The pixel values are different, and the linear regression is performed on the corresponding pixel values to obtain a regression function said For measuring pixel values, is the actual thickness value, the correlation coefficient R=0.999, and the measured pixel value is linearly related to the thickness value of the standard gauge block.

The beneficial effects of the present invention are:

1) The method of the present invention does not need manual operation when detecting wooden board burrs, and realizes automation;

2) The present invention realizes continuous measurement, and the measured wooden board is in the process of continuous delivery during measurement, which improves work efficiency;

3) The identification device used in the present invention has simple structure, convenient installation and low cost.

Description of drawings

Fig. 1 is the structural representation of rough-edged plate;

Fig. 2 is the structural schematic diagram of the burr sheet material of sawing state;

Fig. 3 is a schematic structural diagram of the identification device of the present invention;

Fig. 4 is a schematic diagram of the basic principle of wooden board burr detection;

Fig. 5 is the calibration work curve figure of wood plank thickness detection method;

Figure 6 is a laser detection diagram when there is no plate;

Fig. 7 is a laser detection diagram of a regular board without burrs;

Fig. 8 is a laser inspection diagram of a rough plate.

The meanings of the main reference signs in the figure are:

1. Transmission platform 2. Laser transmitter 3. Support 4. Wooden board to be tested 5. Area array industrial camera.

detailed description

The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

Fig. 3 is a schematic structural diagram of the identification device of the present invention.

As shown in Figure 3: the identification device for the rough edges of wooden boards, including a transmission platform 1, a laser transmitter 2, a bracket 3, and an area array industrial camera 5, and the bracket 3 is bridge-type erected on the transmission platform 1, along the transmission direction of the transmission platform 1 A laser emitter 2 and an area array industrial camera 5 are arranged on the bracket above the transfer table 1 in sequence, and the light source emitted by the laser emitter 2 to the surface of the wooden board 4 to be tested on the transfer table 1 is reflected by the wooden board 4 to be tested. The area array industrial camera 5 receives, and the area array industrial camera 5 communicates with a computer at the same time.

Fig. 4 is a schematic diagram of the basic principle of wood panel burr detection.

As shown in Figure 4: the measured wooden board 4 is transported to the detection position by the conveyor belt on the transmission platform 1, and the laser emitter 2 above the tested wooden board 4 is used as an indicating light source for detection, The plate 4 emits a laser light source, the laser light source is a fan-shaped laser light source, and the light strip formed on the surface of the measured wooden plate 4 is a straight light strip, which can measure multiple points on a section of the measured wooden plate 4 at the same time. The laser light source on the surface of the measured wooden board 4 is reflected and received by the area array industrial camera 5, and the area array industrial camera 5 converts the obtained reflected light source information of the measured wooden board 4 into the thickness profile image information of the measured wooden board 4, Through the function of measuring multiple points at the same time, the measurement of each point represents a measurement, and each measurement will form a pixel in the image, and each measurement can obtain the thickness value of the location of a pixel. A pixel is formed on the width of the image, the width value in the image is the number of measurements, the unit of the thickness value and the width value is a pixel, specifically: the optical signal is received by the area array industrial camera and converted into a charge signal, and then externally sampled Amplification and analog-to-digital conversion circuits are converted into digital image signals, and the thickness value and width value of a certain section of the rough-edged board (measured wooden board 4) in the image are input into the computer by the data acquisition card, and then calculated by the data processing software using formula (I) Get the thickness and width of a certain section of the unedged board.

The computing formula of the data processing software of above-mentioned computer is: x=k y (1)

In the formula (I), x is the detected thickness value of the measured wooden board; y is the offset of the measured wooden board 4 surface and the reference bottom surface in the area array industrial camera 5, and y is shown as the measured wooden board in the thickness profile image The thickness k of 4 is the spatial resolution, and the k is the linear relationship coefficient between the offset y between the surface of the measured wooden board 4 and the reference bottom surface in the area array industrial camera 5 and the detected thickness value x of the measured wooden board 4 .

The numerical formula of described k is: k=1/(β sin θ), in the numerical formula of k, β is the optical element of objective lens in the area array industrial camera 5 and the transverse magnification of imaging system, described transverse The magnification is: after the light source emitted by the laser transmitter 2 is received by the area array industrial camera 5, the ratio of the thickness of the measured wooden board 4 to the image height after being imaged by the area array industrial camera 5 optical elements and the imaging system; θ is the laser emission The angle between the axis of the device 2 and the optical axis of the objective lens in the area array industrial camera 5, β and θ can be measured, and when the imaging system is fixed, the lens position of the area array industrial camera 5 is fixed and the inclination angle is determined, and the distance between the laser transmitter 2 and the transmission The height of the table 1 is determined, the angle θ between the axis of the laser transmitter 2 and the optical axis of the objective lens in the area array industrial camera 5 is fixed, and the optical elements of the objective lens in the area array industrial camera 5 and the lateral magnification β of the imaging system are fixed, then k Also a fixed value, k is scaled. Real-time display of the calculated thickness and width of the wood product, determine the boundary point between the normal surface and the rough edge of the measured wooden plate 4 according to the thickness information of the measured wooden plate 4, and detect a boundary point every certain length , the rough-edged board is driven by the conveyor belt to move at a constant speed, and continuous detection is carried out to obtain the size information of the overall thickness and width of the raw-edged board. The innermost boundary point among the boundary points measured on the same side is used as the sawing point, and the edge parallel to the normal board The sawing path of the surface center line removes the burrs, and the above information is input into the processing device on the production line, so that the automatic removal of the burrs of the burrs can be realized.

Fig. 5 is a calibration work curve diagram of the wooden board thickness detection method.

As shown in Figure 5: before using the identification device described in the present invention, it is necessary to use a standard gauge block for calibration. The specific steps are: place the standard gauge block with a thickness of 0.5mm from 2mm to 25mm under the laser emitter. For calibration, gauge blocks of different heights have different sampling pixel values in the height direction, and the corresponding relationship between the thickness value of the standard gauge block and the height in the image is shown in Table 1:

Table 1: Correspondence table between the thickness value of the standard gauge block and the height in the image

It can be seen from Table 1 that linear regression is performed between the thickness value of the standard gauge block and the pixel value corresponding to the height in the image, and the linear regression function is obtained said For measuring pixel values, It is the actual height value, the correlation coefficient R=0.999, and the spatial resolution in the thickness direction is 0.24mm/pixel after calibration of the standard gauge block, and the ratio in the width direction is 0.12mm/pixel.

During use, if the device parameters are not changed, there is no need to calibrate again, and the detection can be carried out after the calibration is completed.

The specific detection method is

Example 1:

The horizontal movement speed of the transmission table 1 is 500mm/s, and the laser transmitter 2 emits a fan-shaped light source to scan the wooden board under test on the transmission table 1. The wavelength of the laser emitted light is 660nm, and the fan angle of the light is 90°; the surface of the wooden board 4 under test The reflected light is received by the area array industrial camera 5, the pixel size of the image is 1920×1200, the area array industrial camera 5 shoots 100 images per second, and the focal length of the lens is 50mm.

Figure 6 is a laser detection diagram when there is no plate.

As shown in Figure 6: there is only one reference bottom line in the laser detection diagram.

Figure 7 is a laser inspection diagram of a regular board without burrs.

As shown in Figure 7: the surface image of the burr-free sheet is a straight line.

Take a rough-edged plate with a thickness of 30mm, and place it on the beginning of the conveyor table 1. The rough-edged plate to be tested is transported forward at a constant speed by the conveyor belt on the conveyor table 1. When it reaches the detection position, the laser emitter 2 above the detection position emits a fan-shaped laser light source. Form an in-line light bar on the surface of the rough-edged plate and reflect it, and the reflected light is received by the area array industrial camera 5; Thickness profile image information, the data acquisition card in the computer collects the thickness profile image information of the measured rough edge plate of the area array industrial camera 5, and through the data processing software of the computer according to the height direction spatial resolution and the width direction space of the area array industrial camera After the resolution is calculated, the thickness information and width information of the rough-edged sheet to be tested are obtained, and finally the boundary points between the normal board surface and the rough-edged sheet are determined according to the thickness information and width information distribution of the tested rough-cut sheet, and a boundary is detected every certain length Point, take the innermost boundary point among the boundary points measured on the same side as the sawing point, and remove the burrs along the sawing road parallel to the centerline of the normal board surface.

Table 2 is a statistical table of the measurement data of the rough-edged sheet with a thickness of 30mm

Fig. 8 is a laser inspection diagram of a rough plate.

As shown in Figure 8: due to the change in the thickness of the edges on both sides of the uncut board, trapezoidal bevel changes appear at the edges on both sides of the image, and the points of the folding lines on both sides are the boundary points between the uncut board and the normal board.

It can be seen from Table 2 and Figure 8 that when sawing, the left side should be sawed from 21.24mm, and the right side should be sawed from 219.96mm, which can remove the burr and ensure the maximum size of the material.

Compared with the traditional manual detection method, the laser detection used in the present invention has the advantages of high efficiency, high precision, and high automation level. information, which reduces the amount of calculation data and realizes online detection; compared with the existing laser detection technology, the single-point measurement is improved to multi-point measurement, and the detection speed is improved. At the same time, the triangular ranging method is used for measurement, and the measurement accuracy is improved. The industrial online detection is realized, and the work efficiency is improved.

The present invention has been described according to the above-mentioned embodiments. It should be understood that the above-mentioned embodiments do not limit the present invention in any form, and all technical solutions obtained by adopting equivalent replacement or equivalent transformation methods fall within the protection scope of the present invention.

Claims (8)

1. A recognition device for the burrs of wooden boards is characterized in that it includes a transmission table, a laser transmitter, a support, and an area array industrial camera. A laser emitter and an area array industrial camera are arranged on the bracket above, and the light source emitted by the laser emitter to the surface of the measured wooden board on the transfer table is received by the area array industrial camera after being reflected by the measured wooden board, and the area array The industrial camera is connected with a computer at the same time. 2. A method for identifying wooden board burrs, comprising the following steps: S1: The laser transmitter emits a laser light source to the tested wooden board passing on the conveyor table, and the fan-shaped laser light source on the surface of the tested wooden board is reflected and received by the area array industrial camera; S2: The area array industrial camera converts the obtained laser light source information reflected by the measured wooden board into the thickness profile image information of the tested wooden board; S3: The data acquisition card in the computer collects the thickness profile image information of the measured wooden board from the area array industrial camera, and obtains the thickness information of the measured wooden board after calculation by the computer's data processing software; S4: According to the thickness information of the measured wooden board, determine the boundary point between the normal board surface and the rough edge of the wooden board, detect a boundary point every certain length, and use the innermost boundary point among the boundary points measured on the same side as the sawing Point, remove the burrs along the sawing road parallel to the centerline of the normal board surface. 3. the identification method of a kind of wooden plank rough edge according to claim 2, it is characterized in that, in S1 step, the laser light source that laser emitter emits to measured wooden product is fan-shaped laser light source, and measured wooden product surface The formed light bar is a straight line light bar. 4. the identification method of a kind of wooden plank rough edge according to claim 2, it is characterized in that, in S2 step, laser emitter emits a laser light source every time, the thickness profile image information of the measured wooden plank after conversion is wood The thickness value pixel and width value pixel of the measured section of the plate. 5. The recognition method of a kind of wood panel burrs according to claim 2, characterized in that, in the S2 step, the method for converting the laser light source information into the thickness profile image information of the measured wood panel is: the optical signal is scanned by the area array The industrial camera receives and converts the charge signal, and then converts it into a digital image signal through an external sampling amplification and analog-to-digital conversion circuit. 6. the identification method of a kind of wooden plank burrs according to claim 2, is characterized in that, in S3 step, the computing formula of the data processing software of described computer is: x=k y (1) In the formula (I), x is the detected thickness value of the measured wooden board; y is the offset between the measured wooden board surface and the reference bottom surface in the area array industrial camera, and y is shown as the thickness of the wooden board in the thickness profile image, k is the spatial resolution, and the k is the linear relationship coefficient between the offset y between the surface of the measured wooden board and the reference bottom surface in the area array industrial camera and the detected thickness value x of the wooden board. 7. the identification method of a kind of wooden plank rough edge according to claim 6, is characterized in that, the numerical formula of described k is: k=1/(β sin θ), in the numerical formula of k, β is The horizontal magnification of the optical elements of the objective lens and the imaging system in the area array industrial camera, the horizontal magnification is: after the laser emitter emits light source and is received by the area array industrial camera, the thickness of the wooden board to be measured is measured by the area array industrial camera optics. The ratio of the image height of the component and the imaging system after imaging; θ is the angle between the axis of the laser emitter and the optical axis of the objective lens in the area array industrial camera, both β and θ can be measured, and when the imaging system is fixed, the area array industrial camera The position of the lens is fixed and the inclination angle is determined. The height of the laser transmitter from the transmission table is determined. The angle θ between the axis of the laser transmitter and the optical axis of the objective lens in the area array industrial camera is fixed. The optical elements of the objective lens and the imaging system in the area array industrial camera If the horizontal magnification β is fixed, then k is also a fixed value. 8. The identification method of a kind of wooden board burrs according to claim 2, characterized in that, in step S3, also includes the step of using a standard gauge block for calibration, and the calibration method is: different thicknesses The standard gauge block is placed under the laser transmitter for calibration. For gauge blocks of different thicknesses, the sampling pixel values in the thickness direction are different, and linear regression is performed on the corresponding pixel values to obtain a regression function said For measuring pixel values, is the actual thickness value, the correlation coefficient R=0.999, and the measured pixel value is linearly related to the thickness value of the standard gauge block.