CN110095083B - Hot casting measuring method and device based on compressed sensing algorithm - Google Patents

Abstract

The invention discloses a hot casting measuring method and a device based on a compressed sensing algorithm, which comprises the following steps: step 1, acquiring a complete optical signal of a part to be measured of the thermal casting to be measured, and converting the acquired optical signal into an electrical signal; step 2, converting the electric signals into an electric signal matrix, and simplifying the electric signal matrix into an equation; step 3, solving the electric signal equation through a compressed sensing algorithm to obtain a vector C; step 4, restoring the obtained vector C into a two-dimensional grid matrix according to a row-first principle, and obtaining image information of a part to be detected of the detected thermal casting; step 5, acquiring the size information of the part to be measured of the measured thermal casting according to the image information of the part to be measured of the measured thermal casting; according to the invention, the hot casting below the shielded high-temperature-resistant asbestos mesh is measured for multiple times, and the complete measurement information of the hot casting is obtained by combining a compressive sensing algorithm, so that the form of the measured hot casting can be accurately obtained.

Description

A method and device for measuring hot castings based on compressive sensing algorithm

technical field

The invention relates to the technical field of hot casting measurement, in particular to a hot casting measurement method and device based on a compressive sensing algorithm.

Background technique

When the metal casting is first cast, the temperature is very high, which can reach 800 degrees. At this time, it is difficult to measure its size, and manual measurement is used, the working environment is poor, and workers cannot work for a long time. Using contact sensor measurement, due to high temperature, the sensor measurement will be inaccurate, and the life of the sensor will be shortened. Using the method of image capture, the high temperature of the tested casting causes the temperature of the nearby air to rise, resulting in the change of the refractive index of the air to the light, resulting in the distortion of the captured image, and the correct image cannot be obtained.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a method and device for measuring a hot casting based on a compressed sensing algorithm, so as to solve the problem of inability to obtain a correct image in the prior art.

To achieve the above object, the present invention adopts the following technical solutions to realize:

A method for measuring a hot casting based on a compressive sensing algorithm, comprising the following steps:

Step 1, acquire the complete optical signal of the part to be tested of the thermal casting to be tested, and convert the acquired optical signal into an electrical signal; Step 2, convert the electrical signal into an electrical signal matrix, and the electrical signal matrix expresses The formula is:

Simplify the above-mentioned electrical signal matrix into the equation: Y=KC; wherein, Y _i (i=1,...m) represents the light intensity detected by the detector at different positions of the corresponding grid baffle; k _ij i=1...n , j=1...n whose value is 1 or 0, indicating whether the light can pass at the jth position on the ith grid baffle position, 1 means passing, 0 means not passing; c _j means in the image jth position light intensity at each position;

Step 3, solve the electrical signal equation by compressive sensing algorithm, and obtain the vector C; Step 4, restore the obtained vector C into a two-dimensional grid matrix according to the principle of row priority, and obtain the measured heat casting part to be tested. Image information; Step 5: Acquire size information of the to-be-measured part of the measured thermal casting according to the image information of the to-be-measured part of the measured thermal casting.

A thermal casting measurement device based on compressive sensing algorithm, comprising: a photoelectric processing module, a conversion module, a calculation module, an image restoration module and an image processing module; signal, and convert the acquired optical signal into an electrical signal; the conversion module is used to convert the electrical signal into an electrical signal matrix, and the electrical signal matrix is simplified into an electrical signal equation; the calculation module is used to pass the compressed sensing algorithm Solve the electric signal equation to obtain the vector C; the image recovery module is used to restore the obtained vector C into a two-dimensional grid matrix according to the principle of row priority, and obtain the image of the to-be-measured part of the tested thermal casting; the image processing module It is used to obtain the size information of the to-be-measured part of the measured thermal casting according to the image information of the to-be-measured part of the measured thermal casting.

Further, the photoelectric processing module is a photoelectric sensor.

Further, the device also includes: a placing table and an asbestos net; the heat-to-be-measured casting is placed on the placing table, both sides of the placing table are provided with support motors, and the asbestos net is rotatably connected to the said placing table on both sides. Between the supporting motors, the photoelectric sensor is fixed above the asbestos mesh.

The advantages of the present invention are: the present invention provides a method and device for measuring the shape of a hot casting based on a compressive sensing algorithm, which can effectively solve the problem of inaccurate measurement of the hot casting due to excessive surface temperature. Block the hot casting under the high temperature resistant asbestos mesh, and combine the compression sensing algorithm to obtain the complete measurement information of the hot casting, which can accurately obtain the shape of the measured hot casting.

Description of drawings

Fig. 1 is the overall structure schematic diagram of embodiment 1 and embodiment 2 in the specific embodiment of the present invention;

Fig. 2 is the overall structure schematic diagram of the asbestos net in the specific embodiment of the present invention;

Fig. 3 is the schematic diagram of the hot casting target image in the specific embodiment of the present invention;

4 is a top view of the overall structure of Example 2 in the specific embodiment of the present invention;

5 is a schematic diagram of the overall structure of Embodiment 3 and Embodiment 4 in the specific embodiment of the present invention;

6 is a schematic diagram of a photoelectric sensor receiving signals in Embodiment 3 and Embodiment 4 of the specific embodiment of the present invention;

Fig. 7 is the schematic diagram of the asbestos net in embodiment 4 and embodiment 6 in the specific embodiment of the present invention;

8 is a schematic diagram of the overall structure of Embodiment 5 and Embodiment 6 in the specific embodiment of the present invention;

9 is a schematic diagram of a signal received by a photoelectric sensor in Embodiment 5 and Embodiment 6 of the specific embodiment of the present invention;

FIG. 10 is an angular schematic diagram of a signal collected by a photoelectric sensor in Example 5 and Example 6 in the specific implementation of the present invention.

Among them: 1. Photoelectric sensor; 2. Asbestos mesh; 3. Hot casting; 4. Placing table; 5. Support motor; 6. Baffle plate; 7. Upper transmission device; 8. Lower transmission device;

Detailed ways

In order to make the technical means, creative features, achievement goals and effects realized by the present invention easy to understand, the present invention will be further described below with reference to the specific embodiments.

Example 1

As shown in Figures 1-3, this embodiment includes a photoelectric sensor 1, a placing table 4 and a grid baffle, which is made of asbestos mesh or other high temperature resistant materials. The high temperature resistance refers to the temperature resistance above 800 degrees. The structure of the asbestos net 2 is a square grid structure, the size of each grid is d, and 50% of the grids are fixed with light-shielding baffles, and the distribution of the light-shielding baffles is distributed according to a random vector generated by the computer, which is generated by the computer. and storage. The light emitted by the measured heat casting 3 cannot pass through the light-shielding baffle, but can only pass through the grid without the light-shielding baffle on the asbestos mesh 2 . In order to ensure the measurement accuracy of the device, the size of the square grid should be smaller than the measurement accuracy requirement. At the same time, the distance between the hot casting 3 and the asbestos mesh 2 should also be smaller than the measurement accuracy requirement.

The hot casting 3 is placed on the placing table 4, the supporting motors 5 are fixed on both sides of the placing table 4, the asbestos net 2 is connected between the supporting motors 5 on both sides of the placing table 4, and the supporting motor 5 rotates to drive the asbestos net 2 on the two sides. The two support motors 5 move bidirectionally. The photoelectric sensor 1 is fixed on the top of the asbestos mesh 2. The photoelectric sensor 1 can receive the light source information from the hot casting 3 through the grid on the asbestos mesh 2 without light-shielding baffles. It can convert the received light source signal into an electrical signal.

During the detection process, turbulence or atmospheric disturbance caused by high temperature mainly affects the spatial distribution of the light field, but has little effect on the total intensity of the entire light field. Therefore, the turbulent flow between the asbestos mesh 2 and the photoelectric sensor 1 does not affect the single-pixel imaging results. Thereby, the anti-disturbance imaging of the hot casting 3 is realized, and then the corresponding casting shape is obtained through image processing.

In this embodiment, the measurement method includes the following steps:

Step 1. The photoelectric sensor 1 receives the light source signal from the hot casting 3, and converts the received light source signal into an electrical signal; the electrical signal expression is:

Among them, α is the photoelectric conversion coefficient, _ki is the random vector coefficient, the value is 0 or 1, and _ci is the luminous brightness of a small point on the hot casting.

Step 2. Control the rotation of the support motors 5 on both sides to move the asbestos mesh 2 to the right. Every time the asbestos mesh 2 moves one column of grids, the photoelectric sensor 1 acquires the light signal from the hot casting 3 once until the measured thermal casting 3 is obtained. Complete optical signal information, control the support motor 5 to stop rotating, so that the asbestos mesh 2 stops moving. Step 3: Convert the obtained complete optical signal of the hot casting 3 into complete electrical signal information of the hot casting.

Step 4. Convert the complete electrical signal information into an electrical signal matrix, and the electrical signal matrix expression is:

Simplify the above-mentioned electrical signal matrix into the equation: Y=KC; wherein, Y _i (i=1,...m) represents the light intensity detected by the detector at different positions of the corresponding grid baffle; k _ij i=1...n , j=1...n whose value is 1 or 0, indicating whether the light can pass at the jth position on the ith grid baffle position, 1 means passing, 0 means not passing; c _j means in the image jth position light intensity at a location.

Step 5: Solve the electrical signal equation through a compressive sensing algorithm to obtain a vector C.

Take the OMP algorithm in the compressed sensing algorithm as an example:

Step 1: Initialize r ⁰ =Y, C ⁰ =0, Γ ⁰ =φ

Step 2: n=1,

Step 2.1:

Step 2.2:

Step 2.3: Γ ⁿ = Γ ^{n -1} ∪in

Step 2.4: C ⁿ = Γ ⁿ Y

Step 2.5: rn = Y ^- KC ⁿ

Step 2.6: Repeat 2.1-2.5 until ||r ⁿ -r ^n-1 ||<ε, where ε is the set precision requirement. At this point C ⁿ is the solution of the equation. (the meaning of each letter in the supplementary formula)

表示这些内积的值。iⁿ表示取内积值最大情况下，对应的K中的列向量。Γⁿ＝Γ^n-1∪iⁿ表示将iⁿ这个向量放入集合中。C ⁿ represents the predicted value of the vector C in the equation Y=KC. r ⁿ Residuals after substituting the predicted values into the equation. Γ ⁿ represents a set of vectors, which starts with the empty set φ. <r ^n-1 ,K> represents the inner product of the residual r ^n-1 and the column vector of the matrix K,

represent the values of these inner products. i ⁿ represents the column vector in the corresponding K when the inner product value is the largest. Γ ⁿ = Γ ^{n -1} ∪in means to put the vector i ⁿ into the set.

Step 6. Restore the obtained vector C into a two-dimensional grid matrix according to the principle of row priority, and rearrange it according to its position on the asbestos mesh 2, so that the image of the hot casting 3 can be restored. Specifically, according to the different positions of c _i on the asbestos mesh, the brightness (value of c _i ) on different grids is recorded in the corresponding positions, and a two-dimensional brightness distribution can be obtained, which is a picture.

Step 7: Obtain size information of the hot casting 3 according to the image information of the hot casting 3 . Specifically, the size of the hot casting can be calculated according to the number of grids occupied by the hot casting 3 on the asbestos mesh 2 . In FIG. 3, a reconstructed target image of the hot casting 3 is shown, and its width is 6 pixels, so the actual width is D=6d.

The images taken remotely by this method can avoid the occurrence of measurement errors due to the interference of temperature.

Example 2

As shown in FIG. 1, FIG. 2 and FIG. 4, this embodiment includes a photoelectric sensor 1, a placing table 4, a baffle 6 and a mesh baffle, and the baffle 6 and the mesh baffle are made of asbestos mesh or other high temperature resistant materials completed. The high temperature resistance refers to the temperature resistance above 800 degrees. The baffle 6 is fixed on the placing table 4 , and the left end of the hot casting 3 is fixed on the placing table 4 . The hot casting 3 is placed on the placing table 4, the supporting motors 5 are fixed on both sides of the placing table 4, the asbestos net 2 is connected between the supporting motors 5 on both sides of the placing table 4, and the supporting motor 5 rotates to drive the asbestos net 2 on the two sides. The two support motors 5 move bidirectionally. The photoelectric sensor 1 is fixed on the top of the asbestos mesh 2. The photoelectric sensor 1 can receive the light source information from the hot casting 3 through the grid on the asbestos mesh 2 without light-shielding baffles. It can convert the received light source signal into an electrical signal.

The structure of the asbestos mesh 2 is a square grid structure, and the size of each grid is d. The non-fixed end of the hot casting 3, that is, the right end of the hot casting 3, is fixed with shading baffles in 50% of the grids on the asbestos mesh 2. The distribution of the shading baffles is distributed according to a random vector generated by the computer, which is generated and stored by the computer. The light emitted by the heat casting 3 to be tested cannot pass through the light shielding baffle, but can only pass through the grid without the light shielding baffle on the asbestos mesh 2 . In order to ensure the measurement accuracy of the device, the size of the square grid should be smaller than the measurement accuracy requirement. At the same time, the distance between the hot casting 3 and the asbestos mesh 2 should also be smaller than the measurement accuracy requirement.

During the detection process, turbulence or atmospheric disturbance caused by high temperature mainly affects the spatial distribution of the light field, but has little effect on the total intensity of the entire light field. Therefore, the turbulent flow between the asbestos mesh 2 and the photoelectric sensor 1 does not affect the single-pixel imaging results. Thereby, the anti-disturbance imaging of the hot casting 3 is realized, and then the corresponding casting shape is obtained through image processing.

In this embodiment, the measurement method includes the following steps:

Step 1. The photoelectric sensor 1 receives the light source signal from the right end of the hot casting 3, and converts the received light source signal into an electrical signal; the electrical signal expression is:

Among them, α is the photoelectric conversion coefficient, _ki is the random vector coefficient, the value is 0 or 1, and _ci is the luminous brightness of a small point on the hot casting.

Step 2. Control the rotation of the support motors 5 on both sides to move the asbestos mesh 2 to the right. Every time the asbestos mesh 2 moves one column of grids, the photoelectric sensor 1 acquires the light signal from the hot casting 3 once until the measured thermal casting 3 is obtained. The complete optical signal information of the right end part controls the support motor 5 to stop rotating, so that the asbestos mesh 2 stops moving. Step 3: Convert the acquired complete optical signal at the right end of the hot casting 3 into complete electrical signal information of the hot casting.

Step 4. Convert the complete electrical signal information into an electrical signal matrix, and the electrical signal matrix expression is:

Simplify the above-mentioned electrical signal matrix into the equation: Y=KC; wherein, Y _i (i=1,...m) represents the light intensity detected by the detector at different positions of the corresponding grid baffle; k _ij i=1...n , j=1...n whose value is 1 or 0, indicating whether the light can pass at the jth position on the ith grid baffle position, 1 means passing, 0 means not passing; c _j means in the image jth position light intensity at a location.

Step 5: Solve the electrical signal equation through a compressive sensing algorithm to obtain a vector C.

Take the OMP algorithm in the compressed sensing algorithm as an example:

Step 1: Initialize r ⁰ =Y, C ⁰ =0, Γ ⁰ =φ

Step 2: n=1,

Step 2.1: g ⁿ =<r ^n-1 ,K>

Step 2.2:

Step 2.3: Γ ⁿ = Γ ^{n -1} ∪in

Step 2.4: C ⁿ = Γ ⁿ Y

Step 2.5: rn = Y ^- KC ⁿ

Step 2.6: Repeat 2.1-2.5 until ||r ⁿ -r ^n-1 ||<ε, where ε is the set precision requirement. At this point C ⁿ is the solution of the equation.

表示这些内积的值。iⁿ表示取内积值最大情况下，对应的K中的列向量。Γⁿ＝Γ^n-1∪iⁿ表示将iⁿ这个向量放入集合中。C ⁿ represents the predicted value of the vector C in the equation Y=KC. r ⁿ Residuals after substituting the predicted values into the equation. Γ ⁿ represents a set of vectors, which starts with the empty set φ. <r ^n-1 ,K> represents the inner product of the residual r ^n-1 and the column vector of the matrix K,

represent the values of these inner products. i ⁿ represents the column vector in the corresponding K when the inner product value is the largest. Γ ⁿ = Γ ^{n -1} ∪in means to put the vector i ⁿ into the set.

Step 6. Restore the obtained vector C into a two-dimensional grid matrix according to the principle of row priority, and rearrange it according to its position on the asbestos mesh 2, so that the image of the hot casting 3 can be restored. Specifically, according to the different positions of c _i on the asbestos mesh, the brightness (value of c _i ) on different grids is recorded in the corresponding positions, and a two-dimensional brightness distribution can be obtained, which is a picture.

Step 7: Obtain the height information of the hot casting 3 according to the image information of the right end of the hot casting 3 . Specifically, according to the distance between the grid position occupied by the rightmost end of the hot casting 3 on the asbestos mesh 2 and the grid position occupied by the baffle 6, the height of the hot casting can be calculated.

The images taken remotely by this method can avoid the occurrence of measurement errors due to the interference of temperature. For large hot castings, only the image of the partial position is measured, which improves the measurement accuracy and measurement speed.

Example 3

As shown in Fig. 2, Fig. 3, Fig. 5 and Fig. 6, this embodiment includes a photoelectric sensor 1, a lower transmission device 8, an upper transmission device 7 and a grid baffle, the grid baffle is asbestos mesh or other high temperature resistant material. The high temperature resistance refers to the temperature resistance above 800 degrees. The structure of the asbestos net 2 is a square grid structure, the size of each grid is d, and 50% of the grids are fixed with light-shielding baffles, and the distribution of the light-shielding baffles is distributed according to a random vector generated by the computer, which is generated by the computer. and storage. The light emitted by the measured heat casting 3 cannot pass through the light-shielding baffle, but can only pass through the grid without the light-shielding baffle on the asbestos mesh 2 . In order to ensure the measurement accuracy of the device, the size of the square grid should be smaller than the measurement accuracy requirement. At the same time, the distance between the hot casting 3 and the asbestos mesh 2 should also be smaller than the measurement accuracy requirement.

The hot casting 3 is fixed on the lower transmission device 8 , the lower transmission device 8 and the upper transmission device 7 are both transmission belts, and the asbestos mesh 2 is fixedly connected between the upper transmission device 7 and the lower transmission device 8 . The square tube 9 is fixed on the upper transmission device 7 , and the photoelectric sensor 1 is fixed inside the square tube 9 , and the light received by the photoelectric sensor 1 only comes from the hot casting 3 by the shielding of the tube. The photoelectric sensor 1 can receive the light source information from the hot casting 3 through the grid without light-shielding baffles on the asbestos mesh 2, and the photoelectric sensor 1 can convert the received light source signal into an electrical signal.

During the detection process, turbulence or atmospheric disturbance caused by high temperature mainly affects the spatial distribution of the light field, but has little effect on the total intensity of the entire light field. Therefore, the turbulent flow between the asbestos mesh 2 and the photoelectric sensor 1 does not affect the single-pixel imaging results. Thereby, the anti-disturbance imaging of the hot casting 3 is realized, and then the corresponding casting shape is obtained through image processing.

In this embodiment, the measurement method includes the following steps:

Step 1. The photoelectric sensor 1 receives the light source signal from the hot casting 3, and converts the received light source signal into an electrical signal; the electrical signal expression is:

Among them, α is the photoelectric conversion coefficient, _ki is the random vector coefficient, the value is 0 or 1, and _ci is the luminous brightness of a small point on the hot casting.

Step 2. The upper transmission device 7 and the lower transmission device 8 move to the right at the same speed, that is, the upper transmission device 7 and the lower transmission device 8 remain relatively static. Since the hot casting 3 is fixed on the lower transmission device, the asbestos mesh 2 is relative to the hot casting. 3 is moving. Each time the asbestos mesh 2 moves one column of grids, the photoelectric sensor 1 acquires the optical signal from the thermal casting 3 once, until the complete optical signal information of the thermal casting 3 to be measured is acquired, and the upper transmission device 7 and the lower transmission device 8 stop moving. Step 3: Convert the obtained complete optical signal of the hot casting 3 into complete electrical signal information of the hot casting.

Step 4. Convert the complete electrical signal information into an electrical signal matrix, and the electrical signal matrix expression is:

Simplify the above-mentioned electrical signal matrix into the equation: Y=KC; wherein, Y _i (i=1,...m) represents the light intensity detected by the detector at different positions of the corresponding grid baffle; k _ij i=1...n , j=1...n whose value is 1 or 0, indicating whether the light can pass at the jth position on the ith grid baffle position, 1 means passing, 0 means not passing; c _j means in the image jth position light intensity at a location.

Step 5: Solve the electrical signal equation through a compressive sensing algorithm to obtain a vector C.

Take the OMP algorithm in the compressed sensing algorithm as an example:

Step 1: Initialize r ⁰ =Y, C ⁰ =0, Γ ⁰ =φ

Step 2: n=1,

Step 2.1: g ⁿ =<r ^n-1 ,K>

Step 2.2:

Step 2.3: Γ ⁿ = Γ ^{n -1} ∪in

Step 2.4: C ⁿ = Γ ⁿ Y

Step 2.5: rn = Y ^- KC ⁿ

Step 2.6: Repeat 2.1-2.5 until ||r ⁿ -r ^n-1 ||<ε, where ε is the set precision requirement. At this point C ⁿ is the solution of the equation.

表示这些内积的值。iⁿ表示取内积值最大情况下，对应的K中的列向量。Γⁿ＝Γ^n-1∪iⁿ表示将iⁿ这个向量放入集合中。C ⁿ represents the predicted value of the vector C in the equation Y=KC. r ⁿ Residuals after substituting the predicted values into the equation. Γ ⁿ represents a set of vectors, which starts with the empty set φ. <r ^n-1 ,K> represents the inner product of the residual r ^n-1 and the column vector of the matrix K,

represent the values of these inner products. i ⁿ represents the column vector in the corresponding K when the inner product value is the largest. Γ ⁿ = Γ ^{n -1} ∪in means to put the vector i ⁿ into the set.

Step 6. Restore the obtained vector C into a two-dimensional grid matrix according to the principle of row priority, and rearrange it according to its position on the asbestos mesh 2, so that the image of the hot casting 3 can be restored. Specifically, according to the different positions of c _i on the asbestos mesh, the brightness (value of c _i ) on different grids is recorded in the corresponding positions, and a two-dimensional brightness distribution can be obtained, which is a picture.

Step 7: Obtain size information of the hot casting 3 according to the image information of the hot casting 3 . Specifically, the size of the hot casting can be calculated according to the number of grids occupied by the hot casting 3 on the asbestos mesh 2 . In FIG. 3, a reconstructed target image of the hot casting 3 is shown, and its width is 6 pixels, so the actual width is D=6d.

The images taken remotely by this method can avoid the occurrence of measurement errors due to the interference of temperature. Using the existing transmission device to measure the hot casting can fully save time and improve production efficiency.

Example 4

As shown in Figures 3 and 5-7, this embodiment includes a photoelectric sensor 1, a lower transmission device 8, an upper transmission device 7 and a grid baffle, which is made of asbestos mesh or other high temperature resistant materials . The high temperature resistance refers to the temperature resistance above 800 degrees. The structure of the asbestos mesh 2 is covered with a square grid structure, and the size of each mesh is d. The asbestos mesh 2 in this embodiment is shown in Figure 7, and the meshes in the middle of the asbestos mesh 2 are all blocked by light-shielding baffles. , 50% of the grids on both sides are fixed with light-shielding baffles, and the distribution of the light-shielding baffles is distributed according to a random vector generated by the computer, which is generated and stored by the computer. The middle and both sides of the asbestos mesh 2 are determined according to the approximate shape of the hot casting 3 . The light emitted by the measured heat casting 3 cannot pass through the light-shielding baffle, but can only pass through the grid without the light-shielding baffle on the asbestos mesh 2 . In order to ensure the measurement accuracy of the device, the size of the square grid should be smaller than the measurement accuracy requirement. At the same time, the distance between the hot casting 3 and the asbestos mesh 2 should also be smaller than the measurement accuracy requirement.

The hot casting 3 is fixed on the lower transmission device 8 , the lower transmission device 8 and the upper transmission device 7 are both transmission belts, and the asbestos mesh 2 is fixedly connected between the upper transmission device 7 and the lower transmission device 8 . The square tube 9 is fixed on the upper transmission device 7 , and the photoelectric sensor 1 is fixed inside the square tube 9 , so that the light received by the photoelectric sensor 1 only comes from the hot casting 3 . The photoelectric sensor 1 can receive the light source information from the hot casting 3 through the grid without light-shielding baffles on the asbestos mesh 2, and the photoelectric sensor 1 can convert the received light source signal into an electrical signal.

During the detection process, turbulence or atmospheric disturbance caused by high temperature mainly affects the spatial distribution of the light field, but has little effect on the total intensity of the entire light field. Therefore, the turbulent flow between the asbestos mesh 2 and the photoelectric sensor 1 does not affect the single-pixel imaging results. Thereby, the anti-disturbance imaging of the hot casting 3 is realized, and then the corresponding casting shape is obtained through image processing.

In this embodiment, the measurement method includes the following steps:

Step 1. The photoelectric sensor 1 receives the light source signal from the right end of the hot casting 3, and converts the received light source signal into an electrical signal; the electrical signal expression is:

Among them, α is the photoelectric conversion coefficient, _ki is the random vector coefficient, the value is 0 or 1, and _ci is the luminous brightness of a small point on the hot casting.

Step 2. The upper transmission device 7 and the lower transmission device 8 move to the right at the same speed, that is, the upper transmission device 7 and the lower transmission device 8 remain relatively static. Since the hot casting 3 is fixed on the lower transmission device, the asbestos mesh 2 is relative to the hot casting. 3 is moving. Every time the asbestos mesh 2 moves one column of grids, the photoelectric sensor 1 acquires the optical signal from the hot casting 3 once, until the complete optical signal information of the two ends of the tested thermal casting 3 is obtained, and the upper transmission device 7 and the lower transmission device 8 stop moving. . Step 3: Convert the acquired complete optical signals at both ends of the hot casting 3 into complete electrical signal information of the hot casting.

Step 4. Convert the complete electrical signal information into an electrical signal matrix, and the electrical signal matrix expression is:

Simplify the above-mentioned electrical signal matrix into the equation: Y=KC; wherein, Y _i (i=1,...m) represents the light intensity detected by the detector at different positions of the corresponding grid baffle; k _ij i=1...n , j=1...n whose value is 1 or 0, indicating whether the light can pass at the jth position on the ith grid baffle position, 1 means passing, 0 means not passing; c _j means in the image jth position light intensity at a location.

Step 5: Solve the electrical signal equation through a compressive sensing algorithm to obtain a vector C.

Take the OMP algorithm in the compressed sensing algorithm as an example:

Step 1: Initialize r ⁰ =Y, C ⁰ =0, Γ ⁰ =φ

Step 2: n=1,

Step 2.1: g ⁿ =<r ^n-1 ,K>

Step 2.2:

Step 2.3: Γ ⁿ = Γ ^{n -1} ∪in

Step 2.4: C ⁿ = Γ ⁿ Y

Step 2.5: rn = Y ^- KC ⁿ

Step 2.6: Repeat 2.1-2.5 until ||r ⁿ -r ^n-1 ||<ε, where ε is the set precision requirement. At this point C ⁿ is the solution of the equation.

表示这些内积的值。iⁿ表示取内积值最大情况下，对应的K中的列向量。Γⁿ＝Γ^n-1∪iⁿ表示将iⁿ这个向量放入集合中。C ⁿ represents the predicted value of the vector C in the equation Y=KC. r ⁿ Residuals after substituting the predicted values into the equation. Γ ⁿ represents a set of vectors, which starts with the empty set φ. <r ^n-1 ,K> represents the inner product of the residual r ^n-1 and the column vector of the matrix K,

represent the values of these inner products. i ⁿ represents the column vector in the corresponding K when the inner product value is the largest. Γ ⁿ = Γ ^{n -1} ∪in means to put the vector i ⁿ into the set.

Step 6. Restore the obtained vector C into a two-dimensional grid matrix according to the principle of row priority, and rearrange it according to its position on the asbestos mesh 2, so that the image of the hot casting 3 can be restored. Specifically, according to the different positions of c _i on the asbestos mesh, the brightness (value of c _i ) on different grids is recorded in the corresponding positions, and a two-dimensional brightness distribution can be obtained, which is a picture.

Step 7: Acquire height information of the hot casting 3 according to the image information of both ends of the hot casting 3 . Specifically, the height of the hot casting can be calculated according to the sum of the grid positions occupied by the hot casting 3 at the extreme ends of the asbestos net 2 and the grid position occupied by the light shielding baffle in the middle of the asbestos net 2 .

The images taken remotely by this method can avoid the occurrence of measurement errors due to the interference of temperature. For large hot castings, only the image of the partial position needs to be measured, which improves the measurement accuracy and efficiency.

Example 5

As shown in Figures 2 and 8-10, this embodiment includes a photoelectric sensor 1, a lower transmission device 8, a square cylinder 9 and a grid baffle, which is made of asbestos mesh or other high temperature resistant materials. The high temperature resistance refers to the temperature resistance above 800 degrees. The structure of the asbestos net 2 is a square grid structure, the size of each grid is d, and 50% of the grids are fixed with light-shielding baffles, and the distribution of the light-shielding baffles is distributed according to a random vector generated by the computer, which is generated by the computer. and storage. The light emitted by the measured heat casting 3 cannot pass through the light-shielding baffle, but can only pass through the grid without the light-shielding baffle on the asbestos mesh 2 . In order to ensure the measurement accuracy of the device, the size of the square grid should be smaller than the measurement accuracy requirement. At the same time, the distance between the hot casting 3 and the asbestos mesh 2 should also be smaller than the measurement accuracy requirement.

The hot casting 3 is fixed on the lower conveying device 8 , which is a conveying belt, and the asbestos mesh 2 is fixedly connected above the lower conveying device 8 . The square tube 9 is fixed on the middle part of the square on the asbestos mesh 2 , and the photoelectric sensor 1 is fixed inside the square tube 9 , so that the photoelectric sensor 1 receives light from the entire asbestos mesh 2 . Adding a square tube 9 prevents the photoelectric sensor 1 from receiving direct light from other light sources and reduces measurement noise. The photoelectric sensor 1 can receive the light source information from the hot casting 3 through the grid without light-shielding baffles on the asbestos mesh 2, and the photoelectric sensor 1 can convert the received light source signal into an electrical signal.

During the detection process, turbulence or atmospheric disturbance caused by high temperature mainly affects the spatial distribution of the light field, but has little effect on the total intensity of the entire light field. Therefore, the turbulent flow between the asbestos mesh 2 and the photoelectric sensor 1 does not affect the single-pixel imaging results. Thereby, the anti-disturbance imaging of the hot casting 3 is realized, and then the corresponding casting shape is obtained through image processing.

In the measurement process, it should be ensured that a basic range is determined according to the size of the hot casting 3, and the size of n is determined. n is the number of pixels in the final image, the larger the n, the higher the resolution and the more accurate the measurement result, but the measurement time will increase. With the movement of the hot casting 3, the photoelectric sensor 1 collects a signal every time a column of grids is moved. Due to the difference in relative position for each acquisition, the pixel size will be inconsistent. Therefore, relative calibration is required: the brightness I = I ₀ /cos(α) collected each time, where I ₀ is the brightness when the hot casting 3 is directly below, and α is the connection between the center of the hot casting 3 and the photoelectric sensor 1 and the photoelectric sensor 1 angle in the vertical direction.

In this embodiment, the measurement method includes the following steps:

Step 1. The photoelectric sensor 1 receives the light source signal from the hot casting 3, and converts the received light source signal into an electrical signal; the electrical signal expression is:

Among them, α is the photoelectric conversion coefficient, _ki is the random vector coefficient, the value is 0 or 1, and _ci is the luminous brightness of a small point on the hot casting.

Step 2. The lower transmission device 8 moves to the right to drive the hot casting 3 to move to the right. Taking the hot casting 3 as a reference point, the asbestos mesh 2 moves to the left. Every time the asbestos mesh 2 moves a column of grids, the photoelectric sensor 1 obtains a hot casting. 3, until the complete optical signal information of the tested thermal casting 3 is obtained, the lower transmission device 8 stops moving. Step 3: Convert the obtained complete optical signal of the hot casting 3 into complete electrical signal information of the hot casting 3 .

Step 4. Convert the complete electrical signal information into an electrical signal matrix, and the electrical signal matrix expression is:

Simplify the above-mentioned electrical signal matrix into the equation: Y=KC; wherein, Y _i (i=1,...m) represents the light intensity detected by the detector at different positions of the corresponding grid baffle; k _ij i=1...n , j=1...n whose value is 1 or 0, indicating whether the light can pass at the jth position on the ith grid baffle position, 1 means passing, 0 means not passing; c _j means in the image jth position light intensity at a location.

Step 5: Solve the electrical signal equation through a compressive sensing algorithm to obtain a vector C.

Take the OMP algorithm in the compressed sensing algorithm as an example:

Step 1: Initialize r ⁰ =Y, C ⁰ =0, Γ ⁰ =φ

Step 2: n=1,

Step 2.1: g ⁿ =<r ^n-1 ,K>

Step 2.2:

Step 2.3: Γ ⁿ = Γ ^{n -1} ∪in

Step 2.4: C ⁿ = Γ ⁿ Y

Step 2.5: rn = Y ^- KC ⁿ

Step 2.6: Repeat 2.1-2.5 until ||r ⁿ -r ^n-1 ||<ε, where ε is the set precision requirement. At this point C ⁿ is the solution of the equation.

表示这些内积的值。iⁿ表示取内积值最大情况下，对应的K中的列向量。Γⁿ＝Γ^n-1∪iⁿ表示将iⁿ这个向量放入集合中。C ⁿ represents the predicted value of the vector C in the equation Y=KC. r ⁿ Residuals after substituting the predicted values into the equation. Γ ⁿ represents a set of vectors, which starts with the empty set φ. <r ^n-1 ,K> represents the inner product of the residual r ^n-1 and the column vector of the matrix K,

represent the values of these inner products. i ⁿ represents the column vector in the corresponding K when the inner product value is the largest. Γ ⁿ = Γ ^{n -1} ∪in means to put the vector i ⁿ into the set.

Step 6. Restore the obtained vector C into a two-dimensional grid matrix according to the principle of row priority, and rearrange it according to its position on the asbestos mesh 2, so that the image of the hot casting 3 can be restored. Specifically, according to the different positions of c _i on the asbestos mesh, the brightness (value of c _i ) on different grids is recorded at the corresponding position, and a two-dimensional brightness distribution can be obtained, which is a picture.

Step 7: Obtain size information of the hot casting 3 according to the image information of the hot casting 3 . Specifically, the size of the hot casting can be calculated according to the number of grids occupied by the hot casting 3 on the asbestos mesh 2 . In FIG. 3, a reconstructed target image of the hot casting 3 is shown, and its width is 6 pixels, so the actual width is D=6d.

In this embodiment, only one photoelectric sensor 1 can be used to effectively measure the shape of the casting, which saves costs.

Example 6

As shown in Figures 7-10, this embodiment includes a photoelectric sensor 1, a lower transmission device 8, a square cylinder 9 and a grid baffle, which is made of asbestos mesh or other high temperature resistant materials. The high temperature resistance refers to the temperature resistance above 800 degrees. The structure of the asbestos mesh 2 is covered with a square grid structure, and the size of each mesh is d. The asbestos mesh 2 in this embodiment is shown in Figure 7, and the meshes in the middle of the asbestos mesh 2 are all blocked by light-shielding baffles. , 50% of the grids on both sides are fixed with shading baffles, and the distribution of the shading baffles is distributed according to a random vector generated by the computer, which is generated and stored by the computer. The middle and both sides of the asbestos mesh 2 are determined according to the approximate shape of the hot casting 3 . The light emitted by the measured heat casting 3 cannot pass through the light-shielding baffle, but can only pass through the grid without the light-shielding baffle on the asbestos mesh 2 . In order to ensure the measurement accuracy of the device, the size of the square grid should be smaller than the measurement accuracy requirement. At the same time, the distance between the hot casting 3 and the asbestos mesh 2 should also be smaller than the measurement accuracy requirement.

The hot casting 3 is fixed on the lower conveying device 8 , which is a conveying belt, and the asbestos mesh 2 is fixedly connected above the lower conveying device 8 . The square tube 9 is fixed on the middle part of the square on the asbestos mesh 2 , and the photoelectric sensor 1 is fixed inside the square tube 9 , so that the photoelectric sensor 1 receives light from the entire asbestos mesh 2 . The photoelectric sensor 1 can receive the light source information from the hot casting 3 through the grid without light-shielding baffles on the asbestos mesh 2, and the photoelectric sensor 1 can convert the received light source signal into an electrical signal.

During the detection process, turbulence or atmospheric disturbance caused by high temperature mainly affects the spatial distribution of the light field, but has little effect on the total intensity of the entire light field. Therefore, the turbulent flow between the asbestos mesh 2 and the photoelectric sensor 1 does not affect the single-pixel imaging results. Thereby, the anti-disturbance imaging of the hot casting 3 is realized, and then the corresponding casting shape is obtained through image processing.

In this embodiment, the measurement method includes the following steps:

Step 1. The photoelectric sensor 1 receives the light source signal from the right end of the hot casting 3, and converts the received light source signal into an electrical signal; the electrical signal expression is:

Among them, α is the photoelectric conversion coefficient, _ki is the random vector coefficient, the value is 0 or 1, and _ci is the luminous brightness of a small point on the hot casting.

Step 2. Step 2. The lower transmission device 8 moves to the right to drive the hot casting 3 to move to the right. Taking the hot casting 3 as a reference point, the asbestos mesh 2 moves to the left. Each time the asbestos mesh 2 moves one column of grids, the photoelectric sensor 1 acquires the optical signal from the hot casting 3 once, until the complete optical signal information of the two ends of the tested thermal casting 3 is obtained, and the lower transmission device 8 stops moving. Step 3: Convert the acquired complete optical signals at both ends of the hot casting 3 into complete electrical signal information of the hot casting.

Step 4. Convert the complete electrical signal information into an electrical signal matrix, and the electrical signal matrix expression is:

Simplify the above-mentioned electrical signal matrix into the equation: Y=KC; wherein, Y _i (i=1,...m) represents the light intensity detected by the detector at different positions of the corresponding grid baffle; k _ij i=1...n , j=1...n whose value is 1 or 0, indicating whether the light can pass at the jth position on the ith grid baffle position, 1 means passing, 0 means not passing; c _j means in the image jth position light intensity at a location.

Step 5: Solve the electrical signal equation through a compressive sensing algorithm to obtain a vector C.

Take the OMP algorithm in the compressed sensing algorithm as an example:

Step 1: Initialize r ⁰ =Y, C ⁰ =0, Γ ⁰ =φ

Step 2: n=1,

Step 2.1: g ⁿ =<r ^n-1 ,K>

Step 2.2:

Step 2.3: Γ ⁿ = Γ ^{n -1} ∪in

Step 2.4: C ⁿ = Γ ⁿ Y

Step 2.5: rn = Y ^- KC ⁿ

Step 2.6: Repeat 2.1-2.5 until ||r ⁿ -r ^n-1 ||<ε, where ε is the set precision requirement. At this point C ⁿ is the solution of the equation.

表示这些内积的值。iⁿ表示取内积值最大情况下，对应的K中的列向量。Γⁿ＝Γ^n-1∪iⁿ表示将iⁿ这个向量放入集合中。C ⁿ represents the predicted value of the vector C in the equation Y=KC. r ⁿ Residuals after substituting the predicted values into the equation. Γ ⁿ represents a set of vectors, which starts with the empty set φ. <r ^n-1 ,K> represents the inner product of the residual r ^n-1 and the column vector of the matrix K,

represent the values of these inner products. i ⁿ represents the column vector in the corresponding K when the inner product value is the largest. Γ ⁿ = Γ ^{n -1} ∪in means to put the vector i ⁿ into the set.

Step 6. Restore the obtained vector C into a two-dimensional grid matrix according to the principle of row priority, and rearrange it according to its position on the asbestos mesh 2, so that the image of the hot casting 3 can be restored. Specifically, according to the different positions of c _i on the asbestos mesh, the brightness (value of c _i ) on different grids is recorded at the corresponding position, and a two-dimensional brightness distribution can be obtained, which is a picture.

Step 7: Acquire height information of the hot casting 3 according to the image information of both ends of the hot casting 3 . Specifically, the height of the hot casting can be calculated according to the sum of the grid positions occupied by the hot casting 3 at the extreme ends of the asbestos net 2 and the grid position occupied by the light shielding baffle in the middle of the asbestos net 2 .

In this embodiment, only one photoelectric sensor 1 can be used to effectively measure the shape of the casting, which saves costs.

Combining the above six embodiments, the present invention provides a method for measuring a hot casting based on a compressive sensing algorithm, comprising the following steps:

Step 1, acquire the complete optical signal of the part to be tested of the thermal casting to be tested, and convert the acquired optical signal into an electrical signal; Step 2, convert the electrical signal into an electrical signal matrix, and the electrical signal matrix expression is:

Simplify the above-mentioned electrical signal matrix into the equation: Y=KC; wherein, Y _i (i=1,...m) represents the light intensity detected by the detector at different positions of the corresponding grid baffle; k _ij i=1...n , j=1...n whose value is 1 or 0, indicating whether the light can pass at the jth position on the ith grid baffle position, 1 means passing, 0 means not passing; c _j means in the image jth position light intensity at a location.

Step 3, solve the electrical signal equation through the compressed sensing algorithm, and obtain the vector C; Step 4, restore the obtained vector C into a two-dimensional grid matrix according to the principle of row priority, and obtain the image of the to-be-measured part of the tested thermal casting 3 information; Step 5, obtain the size information of the to-be-measured part of the measured thermal casting 3 according to the image information of the to-be-measured part of the measured thermal casting 3 .

A thermal casting measurement device based on compressive sensing algorithm, comprising: a photoelectric processing module, a conversion module, a calculation module, an image recovery module and an image processing module; the photoelectric processing module is used to obtain the complete optical signal of the to-be-measured part of the measured thermal casting 3 , and convert the acquired optical signal into an electrical signal; the conversion module is used to convert the electrical signal into an electrical signal matrix, and the electrical signal matrix is simplified into an electrical signal equation; the calculation module is used to solve the electrical signal equation through the compressed sensing algorithm, Obtain the vector C; the image restoration module is used to restore the obtained vector C into a two-dimensional grid matrix according to the principle of row priority, and obtain the image of the part to be tested of the tested thermal casting 3; the image processing module is used to The image information of the part to be measured obtains the size information of the part to be measured of the thermal casting 3 to be measured.

The invention provides a method and device for measuring the shape of a hot casting based on a compressive sensing algorithm, which can effectively solve the problem of inaccurate measurement of the hot casting due to excessive surface temperature. The hot casting below, combined with the compressive sensing algorithm to obtain the complete measurement information of the hot casting, can accurately obtain the shape of the measured hot casting.

It is known from the technical common sense that the present invention can be realized by other embodiments without departing from its spirit or essential characteristics. Accordingly, the above-disclosed embodiments are, in all respects, illustrative and not exclusive. All changes within the scope of the present invention or within the scope equivalent to the present invention are encompassed by the present invention.

Claims (10)

1. A hot casting measuring method based on a compressed sensing algorithm is characterized by comprising the following steps:

acquiring a complete optical signal of a part to be measured of the thermal casting to be measured, and converting the acquired optical signal into an electrical signal;

converting the electrical signals into an electrical signal matrix, wherein the electrical signal matrix expression is as follows:

simplifying the electrical signal matrix into an equation: y ═ α KC; wherein, alpha is a photoelectric conversion coefficient, Y_i(i-1, … m) represents the intensity of light detected by the detector at the ith moment of the grid barrier; k is a radical of_ij(i-1 … m, j-1 … n) indicates whether the light can pass through the j-th position on the grid baffle at the ith moment, 1 represents passing, and 0 represents not passing; c. C_jRepresenting the light intensity of the measured heat casting at the j position on the grid baffle; wherein the structure of the grid baffle is a structure of being fully distributed with square grids,the size of each grid is d, shading baffles are fixed in 50% of the grids, and the shading baffles are distributed according to random vectors generated by a computer;

solving the electric signal equation through a compressed sensing algorithm to obtain a vector C;

restoring the obtained vector C into a two-dimensional grid matrix according to a row-first principle to obtain image information of the part to be measured of the measured thermal casting;

and acquiring the size information of the part to be measured of the measured thermal casting according to the image information of the part to be measured of the measured thermal casting.

2. The method for measuring the hot casting based on the compressed sensing algorithm according to claim 1, wherein the step of acquiring the complete optical signal of the part to be measured of the hot casting to be measured comprises the following steps:

receiving an optical signal sent by a measured thermal casting below a grid baffle, and converting the optical signal into an electrical signal;

and moving the grid baffle, wherein the grid baffle acquires the optical signal emitted by the measured thermal casting once when moving one row of grids until acquiring the complete optical signal of the measured thermal casting, and the grid baffle stops moving.

3. The method for measuring the hot casting based on the compressed sensing algorithm according to claim 1, wherein the step of acquiring the complete optical signal of the part to be measured of the hot casting to be measured comprises the following steps:

fixing one end of the measured thermal casting on a mounting plate;

receiving an optical signal sent by a non-fixed end of a measured thermal casting below a grid baffle, and converting the optical signal into an electrical signal;

and moving the grid baffle, wherein the grid baffle acquires the optical signal emitted by the measured thermal casting once when moving one row of grids until acquiring the optical signal with the whole non-fixed end of the measured thermal casting, and the grid baffle stops moving.

4. The method for measuring the hot casting based on the compressed sensing algorithm according to claim 1, wherein the step of acquiring the complete optical signal of the part to be measured of the hot casting to be measured comprises the following steps:

receiving an optical signal sent by a measured thermal casting below a grid baffle, and converting the optical signal into an electrical signal;

and moving the measured thermal casting, wherein the optical signal emitted by the measured thermal casting is acquired once the measured thermal casting moves through a row of grids until the complete optical signal of the measured thermal casting is acquired, and the measured thermal casting is stopped moving.

5. A hot cast measurement device based on a compressive sensing algorithm, comprising:

the photoelectric processing module: the optical signal acquisition module is used for acquiring a complete optical signal of a part to be measured of the thermal casting to be measured and converting the acquired optical signal into an electrical signal;

a conversion module: the system is used for converting the electric signals into an electric signal matrix and simplifying the electric signal matrix into an electric signal equation;

the electric signal matrix expression is as follows:

simplifying the electrical signal matrix into an equation: y ═ α KC; wherein, alpha is a photoelectric conversion coefficient, Y_i(i-1, … m) represents the intensity of light detected by the detector at the ith moment of the grid barrier; k is a radical of_ij(i-1 … m, j-1 … n) indicates whether the light can pass through the j-th position on the grid baffle at the ith moment, 1 represents passing, and 0 represents not passing; c. C_jRepresenting the light intensity of the measured heat casting at the j position on the grid baffle; the grid baffles are of a structure that square grid structures are fully distributed, the size of each grid is d, shading baffles are fixed in 50% of the grids, and the shading baffles are distributed according to random vectors generated by a computer;

a calculation module: the system is used for solving the electric signal equation through a compressed sensing algorithm to obtain a vector C; wherein the vector C represents the light intensity of the measured thermal cast at different locations;

an image restoration module: the system is used for recovering the obtained vector C into a two-dimensional grid matrix according to a row-first principle and obtaining an image of the part to be measured of the measured thermal casting;

an image processing module: the size information of the part to be measured of the measured thermal casting is obtained according to the image information of the part to be measured of the measured thermal casting.

6. The apparatus according to claim 5, wherein the photoelectric processing module is a photoelectric sensor.

7. The apparatus for measuring hot castings based on compressed sensing algorithm according to claim 6, further comprising: placing a table and an asbestos gauge; the measured heat casting is placed on the placing table, supporting motors are arranged on two sides of the placing table, the asbestos gauze is rotatably connected between the supporting motors on the two sides, and the photoelectric sensor is fixed above the asbestos gauze.

8. The apparatus for measuring hot castings based on compressed sensing algorithm according to claim 6, further comprising: place platform, asbestos gauge and mounting panel, the mounting panel is fixed place the bench, the one end of being surveyed hot castings is fixed on the mounting panel, the both sides of placing the platform all are equipped with the support motor, the asbestos gauge rotates to be connected in both sides between the support motor, photoelectric sensor fixes asbestos gauge top.

9. The apparatus for measuring hot castings based on compressed sensing algorithm according to claim 6, further comprising: the device comprises an asbestos net, a lower transmission device and an upper transmission device which are relatively static, a measured heat casting is fixed on the lower transmission device, the asbestos net is fixed above the lower transmission device, and the photoelectric sensor is fixed on the upper transmission device.

10. The apparatus for measuring hot castings based on compressed sensing algorithm according to claim 6, further comprising: still include asbestos gauge and lower transmission device, it fixes to be surveyed hot foundry goods on the transmission device down, the asbestos gauge is fixed transmission device's top down, photoelectric sensor fixes asbestos gauge top.

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