Vibration mechanism control method and device based on image recognition

Abstract

The invention discloses a vibration mechanism control method and device based on image recognition, particularly relates to the technical field of color sorter vibration, and can ensure the accuracy of color non-uniformity detection of a target product by obtaining an image of the target product and calculating a color non-uniformity index. The vibration state of the vibration mechanism is divided into a vibration-free state and a vibration-needing state according to the color non-uniformity index, when the vibration state of the vibration mechanism is a vibration-needing state, vibration state data of the vibration mechanism is obtained, and a state coefficient of the vibration mechanism is obtained according to the vibration state data; the state coefficient of the vibration mechanism is compared with the preset threshold value, and whether the current vibration parameter of the vibration mechanism needs to be changed or not is determined according to the comparison result, so that whether the vibration parameter of the vibration mechanism of the color sorter needs to be changed or not can be judged according to the actual condition, and the purity and the consistency of a final product are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of color sorter vibration, and in particular to a vibration mechanism control method and device based on image recognition. Background Art

[0002] The color sorter is an advanced sorting equipment that uses high-speed cameras and image processing algorithms to accurately identify the color of materials. Its working principle is to detect the color differences of the materials, analyze the color characteristics of each particle in real time, and determine whether the color of the material is uniform. When it detects that some materials are uneven in color, the color sorter will automatically start the vibration mechanism to further separate and sort the materials during the vibration process, thereby improving the accuracy and efficiency of sorting. In addition to the color recognition function, the color sorter can also quickly remove particles and impurities of different colors to ensure the purity and consistency of the final product. Due to its high efficiency and accuracy, color sorters are widely used in many industries such as grain, food, and minerals, significantly improving the quality and market competitiveness of products; at the same time, the intelligent operation interface and degree of automation of the color sorter also reduce labor costs for enterprises, optimize production processes, and become an indispensable and important equipment in modern industrial production;

[0003] However, the vibration mechanism of the traditional color sorter only vibrates the product according to the pre-set vibration parameters, without judging whether the vibration parameters of the vibration mechanism need to be changed according to the actual situation, resulting in problems with the purity and consistency of the final product. Summary of the invention

[0004] The purpose of the present invention is to solve the problem and to propose a vibration mechanism control method and device based on image recognition.

[0005] In a first aspect of the present invention, a vibration mechanism control method based on image recognition is first proposed, the method comprising:

[0006] Acquire an image of a target product, determine a color unevenness index of the target product according to the image, and classify a vibration state of the vibration mechanism into one in which vibration is not required and one in which vibration is required according to the color unevenness index;

[0007] When the vibration state of the vibration mechanism is that vibration is required, the vibration state data of the vibration mechanism is obtained, and the state coefficient of the vibration mechanism is obtained according to the vibration state data; the vibration state data includes a vibration non-uniformity coefficient, a vibration frequency abnormality coefficient and a heat dissipation unqualified coefficient;

[0008] The state coefficient of the vibration mechanism is compared with a preset threshold value, and it is determined whether the current vibration parameters of the vibration mechanism need to be changed according to the comparison result, and the vibration of the vibration mechanism is controlled according to the vibration parameters.

[0009] Optionally, determining a color unevenness index of a target product according to an image includes:

[0010] Decompose the image into multiple scales through wavelet transform, and for each scale, calculate the pixel mean and pixel variance of each color channel R, G, and B respectively;

[0011] The pixel variances of the three channels R, G, and B at each scale are added together to obtain the pixel variance sum of the scale, and the pixel variance sum of the scale is multiplied by the corresponding preset weight value to obtain the color unevenness index of the scale;

[0012] The color unevenness index corresponding to each layer of scale is added together to obtain the total color unevenness index sum, and then divided by the number of scale layers to obtain the color unevenness index of the target product.

[0013] Optionally, dividing the vibration state of the vibration mechanism into no vibration required and vibration required according to the color unevenness index includes:

[0014] The color unevenness index of the target product is compared with the preset color unevenness index threshold. If the color unevenness index is less than the preset color unevenness index threshold, the vibration state is classified as no vibration is required. If the color unevenness index is not less than the preset color unevenness index threshold, the vibration state is classified as vibration is required.

[0015] Optionally, the method for obtaining the vibration non-uniformity coefficient includes:

[0016] Continuously extracting a number of vibration signals of the vibration mechanism from the historical data, and calculating the average value of each vibration signal, and calculating the standard deviation of the corresponding vibration signal according to the average value of each vibration signal;

[0017] Divide the standard deviation of each vibration signal by the corresponding mean value to obtain the vibration non-uniformity coefficient of the corresponding vibration signal;

[0018] The final vibration non-uniformity coefficient of the vibration mechanism is obtained according to the vibration non-uniformity coefficient of each vibration signal. The calculation formula is: Where KL is the vibration non-uniformity coefficient of the vibration mechanism, i is the order number of the vibration signal, g is the total number of vibration signals, and U is i is the vibration non-uniformity coefficient corresponding to each vibration signal, R i The weight value corresponding to the vibration non-uniformity coefficient of each vibration signal, and R i Both are greater than 0.

[0019] Optionally, the method for obtaining the vibration frequency abnormality coefficient includes:

[0020] Continuously extracting vibration frequency data of the vibration mechanism from historical data, averaging multiple vibration frequencies to obtain a frequency mean, and calculating a frequency standard deviation based on the frequency mean;

[0021] Calculate the absolute difference between the frequency mean and the preset target frequency, and divide the absolute difference by the preset target frequency to obtain a relative deviation value;

[0022] The vibration frequency abnormality coefficient is obtained according to the relative deviation value, the frequency standard deviation and the preset target frequency. The calculation formula is: EF = HT + σf / GF, where EF is the vibration frequency abnormality coefficient, HT is the relative deviation value, σf is the frequency standard deviation, and GF is the preset target frequency;

[0023] Optionally, the method for obtaining the heat dissipation failure coefficient includes:

[0024] The temperature of the vibration mechanism is continuously extracted from the historical data to obtain a temperature sequence, and the difference between the latter data and the previous data in the adjacent data in the temperature sequence is calculated to obtain a temperature difference sequence;

[0025] The mean of the temperature difference sequence is calculated as the temperature difference mean, and the temperature difference mean is divided by the preset temperature difference mean threshold to obtain the heat dissipation failure coefficient.

[0026] Optionally, obtaining the state coefficient of the vibration mechanism according to the vibration state data includes:

[0027] Klh=f1×KL+f2×EF+f3×TG

[0028] Wherein, Klh is the state coefficient of the vibration mechanism, KL, EF, TG are respectively the vibration unevenness coefficient, the vibration frequency abnormality coefficient and the heat dissipation unqualified coefficient, f1, f2, f3 are respectively the preset proportional coefficients of the vibration unevenness coefficient, the vibration frequency abnormality coefficient and the heat dissipation unqualified coefficient, and f1, f2, f3 are all greater than 0;

[0029] Optionally, comparing the state coefficient of the vibration mechanism with a preset threshold, and determining whether it is necessary to change the current vibration parameter of the vibration mechanism according to the comparison result includes:

[0030] If the state coefficient of the vibration mechanism is less than the preset threshold, there is no need to change the current vibration parameters of the vibration mechanism, and an alarm is issued;

[0031] If the state coefficient of the vibration mechanism is not less than the preset threshold, the current vibration parameters of the vibration mechanism need to be changed.

[0032] In a second aspect of the present invention, a vibration mechanism control device based on image recognition is provided, comprising:

[0033] Vibration state classification module: obtains an image of the target product, determines the color unevenness index of the target product according to the image, and classifies the vibration state of the vibration mechanism into one that does not require vibration and one that requires vibration according to the color unevenness index;

[0034] Vibration state coefficient module: when the vibration state of the vibration mechanism is that vibration is required, the vibration state data of the vibration mechanism is obtained, and the state coefficient of the vibration mechanism is obtained according to the vibration state data; the vibration state data includes a vibration non-uniformity coefficient, a vibration frequency abnormality coefficient and a heat dissipation unqualified coefficient;

[0035] Parameter changing module: compares the state coefficient of the vibration mechanism with the preset threshold, and determines whether it is necessary to change the current vibration parameters of the vibration mechanism according to the comparison result, and controls the vibration of the vibration mechanism according to the vibration parameters.

[0036] Beneficial effects of the present invention:

[0037] 1. The present invention proposes a vibration mechanism control method and device based on image recognition. By acquiring an image of a target product and decomposing the image into multiple scales through wavelet transform to calculate the color unevenness index, the color change details at different scales can be effectively captured, thereby improving the accuracy of color unevenness detection of the target product;

[0038] 2. The present invention obtains the vibration state data of the vibration mechanism, obtains the state coefficient of the vibration mechanism according to the vibration state data, compares the state coefficient of the vibration mechanism with a preset threshold, and determines whether it is necessary to change the current vibration parameters of the vibration mechanism according to the comparison result. In this way, it is possible to judge whether it is necessary to change the vibration parameters of the vibration mechanism of the color sorter according to the actual situation to ensure the purity and consistency of the final product. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The present invention will be further described below in conjunction with the accompanying drawings.

[0040] Figure 1 A flowchart of a vibration mechanism control method based on image recognition provided by an embodiment of the present invention;

[0041] Figure 2 A framework diagram of a vibration mechanism control device based on image recognition provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0044] The embodiment of the present invention provides a vibration mechanism control method based on image recognition. Figure 1 , Figure 1 A flow chart of a vibration mechanism control method based on image recognition provided by an embodiment of the present invention. The method comprises the following steps:

[0045] Acquire an image of a target product, determine a color unevenness index of the target product according to the image, and classify a vibration state of the vibration mechanism into one in which vibration is not required and one in which vibration is required according to the color unevenness index;

[0046] When the vibration state of the vibration mechanism is that vibration is required, the vibration state data of the vibration mechanism is obtained, and the state coefficient of the vibration mechanism is obtained according to the vibration state data; the vibration state data includes a vibration non-uniformity coefficient, a vibration frequency abnormality coefficient and a heat dissipation unqualified coefficient;

[0047] The state coefficient of the vibration mechanism is compared with a preset threshold value, and it is determined whether the current vibration parameters of the vibration mechanism need to be changed according to the comparison result, and the vibration of the vibration mechanism is controlled according to the vibration parameters.

[0048] Based on a vibration mechanism control method based on image recognition provided by an embodiment of the present invention, through the above-mentioned method, it is possible to judge whether it is necessary to change the vibration parameters of the vibration mechanism of the color sorter according to the actual situation, so as to ensure the purity and consistency of the final product.

[0049] In one embodiment, determining the color unevenness index of the target product according to the image includes:

[0050] Decompose the image into multiple scales through wavelet transform, and for each scale, calculate the pixel mean and pixel variance of each color channel R, G, and B respectively;

[0051] The pixel variances of the three channels R, G, and B at each scale are added together to obtain the pixel variance sum of the scale, and the pixel variance sum of the scale is multiplied by the corresponding preset weight value to obtain the color unevenness index of the scale;

[0052] Add the color unevenness index corresponding to each layer of scale to get the total color unevenness index, and divide it by the number of scale layers to get the color unevenness index of the target product;

[0053] According to the color unevenness index, the vibration state of the vibration mechanism is divided into no vibration and need vibration, including:

[0054] The color unevenness index of the target product is compared with the preset color unevenness index threshold. If the color unevenness index is less than the preset color unevenness index threshold, the vibration state is classified as no vibration is required. If the color unevenness index is not less than the preset color unevenness index threshold, the vibration state is classified as vibration is required.

[0055] In one implementation, the image is decomposed into multiple scales through wavelet transform to calculate the color non-uniformity index, which can effectively capture the details of color changes at different scales, thereby improving the accuracy of color non-uniformity detection. This method can more comprehensively reflect the subtle and overall color distribution differences in the image, so that the color uniformity of the product can be accurately judged under different detection environments. By combining the results of different scales, the working state of the vibration mechanism can also be adjusted more accurately, thereby improving the overall efficiency of the color sorter and product quality.

[0056] It should be noted that the preset color unevenness index threshold is set by enterprise personnel based on actual conditions, and no specific limitation or elaboration is made.

[0057] In one embodiment, a method for obtaining a vibration non-uniformity coefficient includes:

[0058] Continuously extracting a number of vibration signals of the vibration mechanism from the historical data, and calculating the average value of each vibration signal, and calculating the standard deviation of the corresponding vibration signal according to the average value of each vibration signal;

[0059] Divide the standard deviation of each vibration signal by the corresponding mean value to obtain the vibration non-uniformity coefficient of the corresponding vibration signal;

[0060] The final vibration non-uniformity coefficient of the vibration mechanism is obtained according to the vibration non-uniformity coefficient of each vibration signal. The calculation formula is: Where KL is the vibration non-uniformity coefficient of the vibration mechanism, i is the order number of the vibration signal, g is the total number of vibration signals, and U is i is the vibration non-uniformity coefficient corresponding to each vibration signal, R i The weight value corresponding to the vibration non-uniformity coefficient of each vibration signal, and R i Both are greater than 0.

[0061] It should be noted that the vibration signal may be acceleration, velocity, displacement, amplitude, etc., which are specifically set and determined by professional personnel and are not limited or elaborated on.

[0062] It should be noted that the weight value corresponding to the vibration non-uniformity coefficient of each vibration signal is determined by professional staff according to the actual situation. For example, assuming that the vibration signal is acceleration, velocity, displacement, and amplitude, the corresponding weight values ​​can be 0.25, 0.25, 0.25, 0.25; it can also be other values, which are not limited or elaborated here.

[0063] It should be noted that the vibration unevenness coefficient refers to the degree of abnormal vibration of the vibration mechanism. The larger the vibration unevenness coefficient, the more it is necessary to change the vibration parameters pre-set by the vibration mechanism to vibrate the product. The reason is that a high vibration unevenness coefficient usually means that the intensity of the vibration fluctuates greatly, which may lead to unstable vibration effects, thereby affecting the processing quality or performance of the product. Therefore, in order to ensure that the product achieves the expected effect during the vibration treatment process, it is necessary to adjust the vibration parameters according to the size of the vibration unevenness coefficient to optimize the vibration process and improve product quality.

[0064] In one implementation, through the above method, the vibration non-uniformity coefficient of the vibration mechanism obtained is more accurate and can better represent the vibration condition of the vibration mechanism.

[0065] In one embodiment, a method for obtaining the vibration frequency abnormality coefficient includes:

[0066] Continuously extracting vibration frequency data of the vibration mechanism from historical data, averaging multiple vibration frequencies to obtain a frequency mean, and calculating a frequency standard deviation based on the frequency mean;

[0067] Calculate the absolute difference between the frequency mean and the preset target frequency, and divide the absolute difference by the preset target frequency to obtain a relative deviation value;

[0068] The vibration frequency abnormality coefficient is obtained according to the relative deviation value, the frequency standard deviation and the preset target frequency. The calculation formula is: EF = HT + σf / GF, where EF is the vibration frequency abnormality coefficient, HT is the relative deviation value, σf is the frequency standard deviation, and GF is the preset target frequency;

[0069] Methods for obtaining the heat dissipation failure coefficient include:

[0070] The temperature of the vibration mechanism is continuously extracted from the historical data to obtain a temperature sequence, and the difference between the latter data and the previous data in the adjacent data in the temperature sequence is calculated to obtain a temperature difference sequence;

[0071] The mean of the temperature difference sequence is calculated as the temperature difference mean, and the temperature difference mean is divided by the preset temperature difference mean threshold to obtain the heat dissipation failure coefficient.

[0072] It should be noted that the preset target frequency and the preset temperature difference mean threshold are determined by professional staff according to actual conditions and are not limited or elaborated on.

[0073] It should be noted that the vibration frequency abnormality coefficient refers to the degree of abnormal fluctuation of the vibration frequency of the vibration mechanism. The larger the vibration frequency abnormality coefficient, the more it is necessary to change the vibration parameters pre-set by the vibration mechanism to vibrate the product. The reason is that the larger the vibration frequency abnormality coefficient, the more significant the deviation of the vibration frequency from the preset target in actual operation. This deviation will increase the volatility of the vibration, making the vibration effect uneven. If the vibration frequency fluctuates frequently or deviates from the normal range, it may cause instability in the product processing process, such as inconsistent material screening effects or uneven surface treatment. This situation will not only reduce production efficiency, but may also affect the overall quality and consistency of the product. Therefore, timely adjustment of the vibration frequency and related parameters to ensure the stability and accuracy of the vibration mechanism is a key measure to improve product quality and maintain the stability of the production process.

[0074] It should be noted that the heat dissipation failure coefficient refers to the degree of heat dissipation failure of the vibration mechanism. The larger the heat dissipation failure coefficient, the more it is necessary to change the pre-set vibration parameters of the vibration mechanism to vibrate the product. The reason is that if the heat dissipation failure coefficient is larger, it means that the vibration mechanism has more serious problems in heat dissipation, which usually means that the heat generated by the equipment during operation cannot be effectively dissipated, resulting in temperature increase. If the vibration parameters are not adjusted or optimized in time, the equipment may experience performance degradation, increased component wear, or even failure due to overheating. Therefore, by detecting and adjusting the heat dissipation failure coefficient, it can ensure that the vibration mechanism operates within a reasonable temperature range, thereby improving the reliability and service life of the equipment.

[0075] In one implementation, the vibration frequency abnormality coefficient and heat dissipation unqualified coefficient of the vibration mechanism obtained by the above method are more accurate and can better represent the vibration frequency abnormality and heat dissipation abnormality of the vibration mechanism.

[0076] In one embodiment, obtaining the state coefficient of the vibration mechanism according to the vibration state data includes:

[0077] Klh=f1×KL+f2×EF+f3×TG

[0078] Wherein, Klh is the state coefficient of the vibration mechanism, KL, EF, TG are respectively the vibration unevenness coefficient, the vibration frequency abnormality coefficient and the heat dissipation unqualified coefficient, f1, f2, f3 are respectively the preset proportional coefficients of the vibration unevenness coefficient, the vibration frequency abnormality coefficient and the heat dissipation unqualified coefficient, and f1, f2, f3 are all greater than 0;

[0079] Comparing the state coefficient of the vibration mechanism with the preset threshold, and determining whether it is necessary to change the current vibration parameters of the vibration mechanism according to the comparison result includes:

[0080] If the state coefficient of the vibration mechanism is less than the preset threshold, there is no need to change the current vibration parameters of the vibration mechanism, and an alarm is issued;

[0081] If the state coefficient of the vibration mechanism is not less than the preset threshold, the current vibration parameters of the vibration mechanism need to be changed.

[0082] It should be noted that the preset threshold is determined by professional staff based on actual conditions and is not limited or elaborated on.

[0083] It should be noted that when the state coefficient of the vibration mechanism is less than the preset threshold value, it means that the vibration mechanism of the color sorter will not have a significant impact on the purity and consistency of the product according to the preset vibration parameters, so there is no need to change the vibration mechanism according to the preset vibration parameters; when the state coefficient of the vibration mechanism is not less than the preset threshold value, it means that the vibration mechanism of the color sorter will have a significant impact on the purity and consistency of the product according to the preset vibration parameters, so it is necessary to change the vibration mechanism according to the preset vibration parameters.

[0084] It should be noted that when the vibration mechanism needs to be changed according to the pre-set vibration parameters, professional staff can reset them according to the actual situation, such as increasing or decreasing the vibration frequency according to the vibration frequency abnormality coefficient, adding heat sinks or improving heat dissipation materials according to the heat dissipation failure coefficient, and optimizing the heat dissipation channel design; at the same time, recalibrate the vibration, frequency and temperature sensors of the equipment to ensure accurate readings; finally, check and replace worn mechanical parts to ensure the stability and performance of the vibration mechanism. Through these specific adjustment measures, the working efficiency of the vibration mechanism can be improved, ensuring that the equipment operates in the best condition, thereby improving the purity and consistency of the product.

[0085] Based on the same inventive concept, the embodiment of the present invention also provides a vibration mechanism control device based on image recognition. Figure 2 , Figure 2 A structural schematic diagram of a vibration mechanism control device based on image recognition provided by an embodiment of the present invention includes:

[0086] Vibration state classification module: obtains an image of the target product, determines the color unevenness index of the target product according to the image, and classifies the vibration state of the vibration mechanism into one that does not require vibration and one that requires vibration according to the color unevenness index;

[0087] Vibration state coefficient module: when the vibration state of the vibration mechanism is that vibration is required, the vibration state data of the vibration mechanism is obtained, and the state coefficient of the vibration mechanism is obtained according to the vibration state data; the vibration state data includes the vibration unevenness coefficient, the vibration frequency abnormality coefficient and the heat dissipation unqualified coefficient;

[0088] Parameter changing module: compares the state coefficient of the vibration mechanism with the preset threshold, and determines whether it is necessary to change the current vibration parameters of the vibration mechanism according to the comparison result, and controls the vibration of the vibration mechanism according to the vibration parameters.

[0089] According to a vibration mechanism control device based on image recognition provided by an embodiment of the present invention, through the above method, it is possible to judge whether it is necessary to change the vibration parameters of the vibration mechanism of the color sorter according to actual conditions, so as to ensure the purity and consistency of the final product.

[0090] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A vibration mechanism control method based on image recognition, characterized in that: The following steps are involved: Acquire an image of a target product, determine a color unevenness index of the target product according to the image, and classify a vibration state of the vibration mechanism into one in which vibration is not required and one in which vibration is required according to the color unevenness index; When the vibration state of the vibration mechanism is that vibration is required, the vibration state data of the vibration mechanism is obtained, and the state coefficient of the vibration mechanism is obtained according to the vibration state data; the vibration state data includes a vibration non-uniformity coefficient, a vibration frequency abnormality coefficient and a heat dissipation unqualified coefficient; The state coefficient of the vibration mechanism is compared with a preset threshold value, and it is determined whether the current vibration parameters of the vibration mechanism need to be changed according to the comparison result, and the vibration of the vibration mechanism is controlled according to the vibration parameters.

2. The vibration mechanism control method based on image recognition according to claim 1, characterized in that: Determining the color unevenness index of the target product based on the image includes: Decompose the image into multiple scales through wavelet transform, and for each scale, calculate the pixel mean and pixel variance of each color channel R, G, and B respectively; The pixel variances of the three channels R, G, and B at each scale are added together to obtain the pixel variance sum of the scale, and the pixel variance sum of the scale is multiplied by the corresponding preset weight value to obtain the color unevenness index of the scale; The color unevenness index corresponding to each layer of scale is added together to obtain the total color unevenness index sum, and then divided by the number of scale layers to obtain the color unevenness index of the target product.

3. The vibration mechanism control method based on image recognition according to claim 1, characterized in that: According to the color unevenness index, the vibration state of the vibration mechanism is divided into no vibration and need vibration, including: The color unevenness index of the target product is compared with the preset color unevenness index threshold. If the color unevenness index is less than the preset color unevenness index threshold, the vibration state is classified as no vibration is required. If the color unevenness index is not less than the preset color unevenness index threshold, the vibration state is classified as vibration is required.

4. The vibration mechanism control method based on image recognition according to claim 1, characterized in that: The method for obtaining the vibration non-uniformity coefficient includes: Continuously extracting a number of vibration signals of the vibration mechanism from the historical data, and calculating the average value of each vibration signal, and calculating the standard deviation of the corresponding vibration signal according to the average value of each vibration signal; Divide the standard deviation of each vibration signal by the corresponding mean value to obtain the vibration non-uniformity coefficient of the corresponding vibration signal; The final vibration non-uniformity coefficient of the vibration mechanism is obtained according to the vibration non-uniformity coefficient of each vibration signal. The calculation formula is: Where KL is the vibration non-uniformity coefficient of the vibration mechanism, i is the order number of the vibration signal, g is the total number of vibration signals, and U is i is the vibration non-uniformity coefficient corresponding to each vibration signal, R i The weight value corresponding to the vibration non-uniformity coefficient of each vibration signal, and R i Both are greater than 0.

5. The vibration mechanism control method based on image recognition according to claim 1, characterized in that: The method for obtaining the vibration frequency abnormality coefficient includes: Continuously extracting vibration frequency data of the vibration mechanism from historical data, averaging multiple vibration frequencies to obtain a frequency mean, and calculating a frequency standard deviation based on the frequency mean; Calculate the absolute difference between the frequency mean and the preset target frequency, and divide the absolute difference by the preset target frequency to obtain a relative deviation value; The vibration frequency anomaly coefficient is obtained according to the relative deviation value, the frequency standard deviation and the preset target frequency. The calculation formula is: EF=HT+σf / GF, where EF is the vibration frequency anomaly coefficient, HT is the relative deviation value, σf is the frequency standard deviation, and GF is the preset target frequency.

6. The vibration mechanism control method based on image recognition according to claim 1, characterized in that: The method for obtaining the heat dissipation failure coefficient includes: The temperature of the vibration mechanism is continuously extracted from the historical data to obtain a temperature sequence, and the difference between the latter data and the previous data in the adjacent data in the temperature sequence is calculated to obtain a temperature difference sequence; The mean of the temperature difference sequence is calculated as the temperature difference mean, and the temperature difference mean is divided by the preset temperature difference mean threshold to obtain the heat dissipation failure coefficient.

7. The vibration mechanism control method based on image recognition according to claim 1, characterized in that: The state coefficients of the vibration mechanism obtained according to the vibration state data include: Klh=f1×KL+f2×EF+f3×TG Wherein, Klh is the state coefficient of the vibration mechanism, KL, EF, and TG are the vibration unevenness coefficient, the vibration frequency abnormality coefficient, and the heat dissipation unqualified coefficient, respectively, and f1, f2, and f3 are the preset proportional coefficients of the vibration unevenness coefficient, the vibration frequency abnormality coefficient, and the heat dissipation unqualified coefficient, respectively, and f1, f2, and f3 are all greater than 0.

8. The vibration mechanism control method based on image recognition according to claim 1, characterized in that: Comparing the state coefficient of the vibration mechanism with the preset threshold, and determining whether it is necessary to change the current vibration parameters of the vibration mechanism according to the comparison result includes: If the state coefficient of the vibration mechanism is less than the preset threshold, there is no need to change the current vibration parameters of the vibration mechanism, and an alarm is issued; If the state coefficient of the vibration mechanism is not less than the preset threshold, the current vibration parameters of the vibration mechanism need to be changed.

9. A vibration mechanism control device based on image recognition, characterized in that: The device comprises: Vibration state classification module: obtains an image of the target product, determines the color unevenness index of the target product according to the image, and classifies the vibration state of the vibration mechanism into one that does not require vibration and one that requires vibration according to the color unevenness index; Vibration state coefficient module: when the vibration state of the vibration mechanism is that vibration is required, the vibration state data of the vibration mechanism is obtained, and the state coefficient of the vibration mechanism is obtained according to the vibration state data; the vibration state data includes a vibration non-uniformity coefficient, a vibration frequency abnormality coefficient and a heat dissipation unqualified coefficient; Parameter changing module: compares the state coefficient of the vibration mechanism with the preset threshold, and determines whether it is necessary to change the current vibration parameters of the vibration mechanism according to the comparison result, and controls the vibration of the vibration mechanism according to the vibration parameters.

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