Food production process monitoring method based on visual inspection

Abstract

The invention relates to the technical field of food production, in particular to a food production process monitoring method based on visual inspection, which comprises the following steps: arranging vibration equipment on the outer wall of a baking station of baking equipment, arranging a camera module in the baking station of the baking equipment, and continuously operating the baking equipment based on set operation logic, in the continuous operation process of the baking equipment, the vibration equipment and the camera module are in linkage operation; the baking target image data is acquired based on the camera module, the baking target image data is acquired in real time, and the baking target image data is used as baking progress monitoring judgment support, so that the baking dynamic change of the baking target in the baking equipment can be monitored in real time, and therefore, the baking speed of the baking target is improved. Intelligent control over baking of the baking target to the optimal state is achieved, it is ensured that after baking of the baking target is completed, a semi-finished product with better baking quality is obtained, and therefore the quality of a final product is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of food production, and in particular to a food production process monitoring method based on visual detection. Background Art

[0002] Food safety is of vital importance. It is related to everyone's physical health and life safety. In order to ensure food safety, relevant departments have introduced comprehensive food production safety management regulations to prevent unqualified food from entering the market.

[0003] The invention patent with application number 202410432080.1 discloses a food production management system, including a raw material procurement unit, a production planning unit, a production control unit, a quality inspection unit, a warehousing unit, a sales and distribution unit and a coordination unit, wherein the raw material procurement unit, the production planning unit, the production control unit, the quality inspection unit, the warehousing unit and the sales and distribution unit are all connected to the coordination unit through wireless signal data; and the raw material procurement unit, the production planning unit, the production control unit, the quality inspection unit, the warehousing unit and the sales and distribution unit are respectively a top-down management process, and the coordination unit is used to coordinate and control each unit of the raw material procurement unit, the production planning unit, the production control unit, the quality inspection unit, the warehousing unit and the sales and distribution unit.

[0004] The application aims to solve the problem that "a food production management system in the prior art is not ideal in the implementation of centralized control and data sharing of each production unit during actual use, which affects management efficiency and response speed. In terms of sales management, a complete sales network and distribution channels have not been established, which is not convenient for rapid response to market demand. At the same time, the cross-departmental information communication mechanism and collaboration process do not work, resulting in poor overall collaboration efficiency and problem-solving capabilities."

[0005] In the food industry, during the coffee production process, the roasting of coffee beans directly affects the subsequent grinding process of the coffee beans. However, the roasting state of the coffee beans is difficult to control during the roasting process; therefore, a food production process monitoring method based on visual inspection is proposed. Summary of the invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides a food production process monitoring method based on visual detection, which solves the technical problems raised in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] Food production process monitoring methods based on visual inspection include:

[0009] A vibration device is deployed on the outer wall of the baking station of the baking equipment, and a camera module is deployed inside the baking station of the baking equipment. The baking equipment runs continuously based on the set operation logic. During the continuous operation of the baking equipment, the vibration device and the camera module run in conjunction.

[0010] Collecting baking target image data based on the camera module, storing the collected baking target image data in the camera module, monitoring the number of baking target image data stored in the camera module in real time, and performing an evaluation operation of baking target baking progress when the number of baking target image data is not less than three groups;

[0011] Obtain the baking progress evaluation result of the baking target in real time, and when the baking progress of the baking target is not less than 85%, continuously execute the determination of whether the baking target has been completed;

[0012] When the determination result is yes, the baking target of the baking station in the baking equipment is transferred to the cooling station. When the determination result is no, the baking equipment is controlled to continue to operate until the determination result is yes.

[0013] Furthermore, at least two groups of vibration devices are arranged on the outer wall of the baking device, and the vibration devices are distributed on the outer wall of the baking device in an equidistant and surrounding shape;

[0014] The operation logic used by the baking equipment is customized by the equipment management end user, and the setting logic is subject to: baking cycle, baking temperature change curve, baking mixing cycle, and the vibration device and camera module are operated once after each baking mixing cycle.

[0015] Among them, the vibration equipment is deployed in the middle of the outer wall of the baking equipment. The vibration equipment is provided with an operation cycle. The operation cycle of the vibration equipment is after the baking and stirring cycle. Two adjacent baking cycles are separated by a group of baking and stirring cycles and a vibration equipment operation cycle. The camera module runs once before the start of each baking cycle to collect baking target image data.

[0016] Furthermore, after the baking target image data is acquired and before being stored in the camera module, the baking target image data is optimized and then stored.

[0017] The optimization processing logic of the baking target image data is expressed as:

[0018]

[0019] Where: P′ is the pixel value of the optimized image; P is the pixel value of the original image; α and β are contrast adjustment parameters; C is the actual contrast value; C0 is the expected contrast value; a, η, ξ are constants; γ, ω, is the color periodic change parameter; D is the color related variable; δ and λ are the saturation adjustment parameters; S is the actual saturation value; S0 is the expected saturation value;

[0020] Among them, the constant in the above formula is greater than zero, and the value of the color-related variable D obeys: R, G, and B are the three color channel values ​​of the image. Based on the above formula, each pixel in the baking target image data is used as the processing target, the output of the optimized image pixel value is completed, and then the original baking target image data is optimized based on the optimized image pixel value.

[0021] Furthermore, before performing the baking progress evaluation operation, the baking target image data synchronously performs contour extraction on each baking target image data based on the Canny edge detection algorithm to obtain a contour image of the baking target image data, and further extracts a complete contour image from the contour image of the baking target image data;

[0022] The contour image of the baking target image data includes contour images of several baking targets. When extracting the complete contour image from the contour image of the baking target image data, each contour in the contour image is identified as a closed contour. All non-closed contours in the contour image are discarded based on the identification result, and the remaining one is the complete contour image.

[0023] Furthermore, the evaluation operation of the baking progress of the baking target is:

[0024]

[0025] Where: Q is the baking target baking progress; h(max) last 、h(max) first h(min) is the size of the area encompassed by the largest contour in the group of contour images with the latest acquisition time stamp, and the size of the area encompassed by the largest contour in the group of contour images with the earliest acquisition time stamp; last 、h(min) first is the size of the area encompassed by the smallest contour in the group of contour images with the latest acquisition time stamp, and the size of the area encompassed by the smallest contour in the group of contour images with the earliest acquisition time stamp; χ is the influencing factor;

[0026] Among them, the influence factor χ∈(0,1], the value of the influence factor χ follows, the higher the size symmetry of the baking target, the larger the value of the influence factor, and vice versa, the smaller the value of the influence factor, the size symmetry of the baking target is determined based on the size and shape of the baking target.

[0027] Furthermore, the cycle of the baking target baking progress evaluation operation is based on the user definition of the baking equipment management. When the baking progress of the baking target is not less than 85%, the determination cycle of whether the baking target is completed is continuously executed, which is 0.0001% to 0.1% of the baking target baking progress evaluation operation cycle;

[0028] The continuous determination period of whether the baking target has been baked is always no longer than one second.

[0029] Furthermore, the decision logic of whether the baking target has completed baking is expressed as:

[0030]

[0031] Where: k is the baking target baking progress; n is the total number of pixels in the image; τ(last) i The color value of the i-th pixel in the last collected baking target image data; τ(first) i is the color value of the i-th pixel in the earliest collected baking target image data; q is the adjustment factor; θ is the normalization factor;

[0032] The adjustment factor q takes the value of 1 or -1. When the numerator is greater than the denominator, the adjustment factor q takes the value of -1. When the numerator is smaller than the denominator, the adjustment factor q takes the value of 1. Express If the above formula is true, it means that the baking target has been completed, otherwise it means that the baking target has not been completed.

[0033] Furthermore, the normalization factor θ>1, and is defined by the user of the baking equipment management end, and the normalization factor θ controls The value of is in the range of 0 to 1, and the normalization factor θ is set in several groups, and the several groups of normalization factors are bound to the baking target volume and moisture content baked by the specified baking equipment, and each normalization factor is selected and applied based on the initial volume and moisture content of the baking target baked by the baking equipment;

[0034] Among them, the initial volume and moisture content of the baking target are prior data, which are manually detected and obtained by the user of the baking equipment management end.

[0035] Furthermore, when the baking equipment continues to operate based on the determination result, the baking stirring cycle control of the baking station of the baking equipment is shortened, and the baking target baking progress evaluation operation cycle of the baking equipment is shortened;

[0036] Among them, the shortening amount of the baking stirring cycle of the baking station of the baking equipment and the baking target baking progress evaluation operation cycle is proportional to the number of times the baking is judged as no in the judgment result of whether the baking is completed.

[0037] Furthermore, when the baking target in the baking station of the baking equipment is transferred to the cooling station, a baking station operation message is synchronously generated, the baking station operation message is transmitted to the control target of the baking equipment, and the baking station operation message is displayed on the control panel of the baking station for the user of the baking equipment management end to read;

[0038] The content of the baking station operation message includes: the operation time, the number of consecutive determinations of whether the baking station has completed baking of the baking target, and the baking target image data collected by the camera module for the last time before the baking target in the baking station is transferred to the cooling station.

[0039] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects:

[0040] The present invention provides a food production process monitoring method based on visual inspection. During the execution of the method, baking target image data is collected in real time, and the baking target image data is used as a baking progress monitoring and judgment support, so that the baking dynamic changes of the baking target in the baking equipment can be monitored in real time, thereby realizing intelligent control of baking the baking target to an optimal state, ensuring that after the baking target is baked, a semi-finished product with better baking quality is obtained, thereby improving the quality of the final product. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 Schematic diagram of the food production process monitoring method based on visual inspection. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0044] The present invention will be further described below in conjunction with the embodiments.

[0045] Embodiment 1:

[0046] The food production process monitoring method based on visual detection in this embodiment is as follows: Figure 1 As shown, including:

[0047] A vibration device is deployed on the outer wall of the baking station of the baking equipment, and a camera module is deployed inside the baking station of the baking equipment. The baking equipment runs continuously based on the set operation logic. During the continuous operation of the baking equipment, the vibration device and the camera module run in conjunction.

[0048] Collecting baking target image data based on the camera module, storing the collected baking target image data in the camera module, monitoring the number of baking target image data stored in the camera module in real time, and performing an evaluation operation of baking target baking progress when the number of baking target image data is not less than three groups;

[0049] Obtain the baking progress evaluation result of the baking target in real time, and when the baking progress of the baking target is not less than 85%, continuously execute the determination of whether the baking target has been completed;

[0050] When the determination result is yes, the baking target of the baking station in the baking equipment is transferred to the cooling station, and when the determination result is no, the baking equipment is controlled to continue to operate until the determination result is;

[0051] There are no less than two groups of vibration devices deployed on the outer wall of the baking equipment, and the vibration devices are distributed on the outer wall of the baking equipment in an equidistant and surrounding manner;

[0052] The operation logic used by the baking equipment is customized by the user of the equipment management end. The setting logic is subject to: baking cycle, baking temperature change curve, baking mixing cycle, and the vibration equipment and camera module are operated once after each baking mixing cycle.

[0053] Among them, the vibration device is deployed in the middle of the outer wall of the baking device. The vibration device is set with an operation cycle. The operation cycle of the vibration device is after the baking and stirring cycle. There is a baking and stirring cycle and a vibration device operation cycle between two adjacent baking cycles. The camera module runs once before each baking cycle to collect baking target image data;

[0054] The decision logic of whether the baking target has completed baking is expressed as:

[0055]

[0056] Where: k is the baking target baking progress; n is the total number of pixels in the image; τ(last) i The color value of the i-th pixel in the last collected baking target image data; τ(first) iis the color value of the i-th pixel in the earliest collected baking target image data; q is the adjustment factor; θ is the normalization factor;

[0057] The adjustment factor q takes the value of 1 or -1. When the numerator is greater than the denominator, the adjustment factor q takes the value of -1. When the numerator is smaller than the denominator, the adjustment factor q takes the value of 1. Express If the above formula is true, it means that the baking target has been completed, otherwise it means that the baking target has not been completed;

[0058] Normalization factor θ>1, and is defined by the user of the baking equipment management end. Normalization factor θ controls The value of is in the range of 0 to 1, and the normalization factor θ is set in several groups, and the several groups of normalization factors are bound to the baking target volume and moisture content of the specified baking equipment. Each normalization factor is selected and applied based on the initial volume and moisture content of the baking target of the baking equipment;

[0059] Among them, the initial volume and moisture content of the baking target are prior data, which are manually detected and obtained by the user of the baking equipment management end.

[0060] In this embodiment, by executing the above method, image recognition and analysis technology is used to monitor the roasting progress of coffee beans, ensuring that the roasted coffee beans can more stably achieve the expected roasting effect, thereby improving the quality of the products obtained from the subsequent processing of the roasted coffee beans.

[0061] Embodiment 2:

[0062] In terms of specific implementation, based on Example 1, this example refers to Figure 1 The food production process monitoring method based on visual detection in Example 1 is further described in detail:

[0063] After the acquisition of the baking target image data is completed, before the baking target image data is stored in the camera module, the baking target image data is optimized and then stored;

[0064] The optimization processing logic of baking target image data is expressed as:

[0065]

[0066] Where: P′ is the pixel value of the optimized image; P is the pixel value of the original image; α and β are contrast adjustment parameters; C is the actual contrast value; C0 is the expected contrast value; a, η, ξ are constants; γ, ω, is the color periodic change parameter; D is the color related variable; δ and λ are the saturation adjustment parameters; S is the actual saturation value; S0 is the expected saturation value;

[0067] Among them, the constant in the above formula is greater than zero, and the value of the color-related variable D obeys: R, G, and B are the three color channel values ​​of the image. Based on the above formula, each pixel in the baking target image data is used as the processing target, the output of the optimized image pixel value is completed, and then the original baking target image data is optimized based on the optimized image pixel value.

[0068] Through the above formula, the baking target image data is further optimized to provide more accurate data support for the further operation of the method in Example 1, thereby ensuring that the output result of the method in Example 1 is more accurate.

[0069] like Figure 1 As shown, before performing the baking progress evaluation operation on the baking target image data, contour extraction is synchronously performed on each baking target image data based on the Canny edge detection algorithm to obtain a contour image of the baking target image data, and further a complete contour image is extracted from the contour image of the baking target image data;

[0070] The contour image of the baking target image data includes contour images of several baking targets. When extracting the complete contour image from the contour image of the baking target image data, each contour in the contour image is identified as a closed contour. All non-closed contours in the contour image are discarded based on the identification result, and the remaining one is the complete contour image.

[0071] The evaluation operation of baking target baking progress is:

[0072]

[0073] Where: Q is the baking target baking progress; h(max) last 、h(max) first h(min) is the size of the area encompassed by the largest contour in the group of contour images with the latest acquisition time stamp, and the size of the area encompassed by the largest contour in the group of contour images with the earliest acquisition time stamp; last 、h(min) first is the size of the area encompassed by the smallest contour in the group of contour images with the latest acquisition time stamp, and the size of the area encompassed by the smallest contour in the group of contour images with the earliest acquisition time stamp; χ is the influencing factor;

[0074] Among them, the influence factor χ∈(0,1], the value of the influence factor χ follows, the higher the size symmetry of the baking target, the larger the value of the influence factor, and vice versa, the smaller the value of the influence factor, the size symmetry of the baking target is determined based on the size and shape of the baking target.

[0075] The above settings provide further step execution data support for the method in Example 1, and further provide a specified evaluation logic for the baking progress evaluation of the baking target.

[0076] Embodiment 3:

[0077] In terms of specific implementation, based on Example 1, this example refers to Figure 1 The food production process monitoring method based on visual detection in Example 1 is further described in detail:

[0078] The baking target baking progress evaluation operation cycle is based on the user definition of the baking equipment management. When the baking target baking progress is not less than 85%, the baking target baking progress evaluation operation cycle is continuously executed, which is 0.0001% to 0.1% of the baking target baking progress evaluation operation cycle;

[0079] Among them, the continuous determination period of whether the baking target has completed baking is always no more than one second;

[0080] When the baking equipment continues to operate based on the determination result, the baking stirring cycle control of the baking station of the baking equipment is shortened, and the baking target baking progress evaluation operation cycle of the baking equipment is shortened;

[0081] The shortening amount of the baking stirring cycle of the baking station of the baking equipment and the baking target baking progress evaluation operation cycle is proportional to the number of times the baking is judged as no in the judgment result of whether the baking is completed;

[0082] When the baking target in the baking station of the baking equipment is transferred to the cooling station, a baking station operation message is generated synchronously, and the baking station operation message is transmitted to the control target of the baking equipment, and the baking station operation message is displayed on the control panel of the baking station for the user of the baking equipment management end to read;

[0083] The content of the baking station operation message includes: the operation time, the number of consecutive determinations of whether the baking station has completed baking of the baking target, and the baking target image data collected by the camera module for the last time before the baking target in the baking station is transferred to the cooling station.

[0084] In this embodiment, through the above settings, further step execution data support is provided for the method in Embodiment 1.

[0085] In summary, during the execution of the method in the above embodiment, by real-time acquisition of baking target image data, the baking target image data is used as a support for baking progress monitoring and judgment, so that the dynamic changes of the baking target in the baking equipment can be monitored in real time, thereby realizing intelligent control of the baking target to the optimal state, ensuring that after the baking target is baked, a semi-finished product with better baking quality is obtained, thereby improving the quality of the final product.

[0086] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A food production process monitoring method based on visual inspection, characterized in that: include: A vibration device is deployed on the outer wall of the baking station of the baking equipment, and a camera module is deployed inside the baking station of the baking equipment. The baking equipment runs continuously based on the set operation logic. During the continuous operation of the baking equipment, the vibration device and the camera module run in conjunction. Collecting baking target image data based on the camera module, storing the collected baking target image data in the camera module, monitoring the number of baking target image data stored in the camera module in real time, and performing an evaluation operation of baking target baking progress when the number of baking target image data is not less than three groups; Obtain the baking progress evaluation result of the baking target in real time, and when the baking progress of the baking target is not less than 85%, continuously execute the determination of whether the baking target has been completed; When the determination result is yes, the baking target of the baking station in the baking equipment is transferred to the cooling station. When the determination result is no, the baking equipment is controlled to continue to operate until the determination result is yes.

2. The food production process monitoring method based on visual detection according to claim 1 is characterized in that: There are at least two groups of vibration devices deployed on the outer wall of the baking equipment, and the vibration devices are distributed on the outer wall of the baking equipment in an equidistant and surrounding shape; The operation logic used by the baking equipment is customized by the equipment management end user, and the setting logic is subject to: baking cycle, baking temperature change curve, baking mixing cycle, and the vibration device and camera module are operated once after each baking mixing cycle. Among them, the vibration equipment is deployed in the middle of the outer wall of the baking equipment. The vibration equipment is provided with an operation cycle. The operation cycle of the vibration equipment is after the baking and stirring cycle. Two adjacent baking cycles are separated by a group of baking and stirring cycles and a vibration equipment operation cycle. The camera module runs once before the start of each baking cycle to collect baking target image data.

3. The food production process monitoring method based on visual detection according to claim 1 is characterized in that: After the baking target image data is collected, before being stored in the camera module, the baking target image data is optimized and then stored. The optimization processing logic of the baking target image data is expressed as: Where: P′ is the pixel value of the optimized image; P is the pixel value of the original image; α and β are contrast adjustment parameters; C is the actual contrast value; C0 is the expected contrast value; a, η, ξ are constants; γ, ω, is the color periodic change parameter; D is the color related variable; δ and λ are saturation adjustment parameters; S is the actual saturation value; S0 is the expected saturation value; Among them, the constant in the above formula is greater than zero, and the value of the color-related variable D obeys: R, G, and B are the three color channel values ​​of the image. Based on the above formula, each pixel in the baking target image data is used as the processing target, the output of the optimized image pixel value is completed, and then the original baking target image data is optimized based on the optimized image pixel value.

4. The food production process monitoring method based on visual detection according to claim 1 is characterized in that: Before performing the baking progress evaluation operation, the baking target image data synchronously performs contour extraction on each baking target image data based on the Canny edge detection algorithm to obtain a contour image of the baking target image data, and further extracts a complete contour image from the contour image of the baking target image data; The contour image of the baking target image data includes contour images of several baking targets. When extracting the complete contour image from the contour image of the baking target image data, each contour in the contour image is identified as a closed contour. All non-closed contours in the contour image are discarded based on the identification result, and the remaining one is the complete contour image.

5. The method for monitoring food production process based on visual detection according to claim 4, characterized in that: The evaluation operation of the baking progress of the baking target is: Where: Q is the baking target baking progress; h(max) last 、h(max) first h(min) is the size of the area encompassed by the largest contour in the group of contour images with the latest acquisition time stamp, and the size of the area encompassed by the largest contour in the group of contour images with the earliest acquisition time stamp; last 、h(min) first is the size of the area encompassed by the smallest contour in the group of contour images with the latest acquisition time stamp, and the size of the area encompassed by the smallest contour in the group of contour images with the earliest acquisition time stamp; χ is the influencing factor; Among them, the influence factor χ∈(0,1], the value of the influence factor χ follows, the higher the size symmetry of the baking target, the larger the value of the influence factor, and vice versa, the smaller the value of the influence factor, the size symmetry of the baking target is determined based on the size and shape of the baking target.

6. The method for monitoring food production process based on visual detection according to claim 1, characterized in that: The baking target baking progress evaluation operation cycle is based on the user definition of the baking equipment management. When the baking target baking progress is not less than 85%, the baking target baking progress evaluation operation cycle is continuously executed, which is 0.0001% to 0.1% of the baking target baking progress evaluation operation cycle. The continuous determination period of whether the baking target has been baked is always no longer than one second.

7. The method for monitoring food production process based on visual detection according to claim 1, characterized in that: The decision logic of whether the baking target has completed baking is expressed as: Where: k is the baking target baking progress; n is the total number of pixels in the image; τ(last) i The color value of the i-th pixel in the last collected baking target image data; τ(first) i is the color value of the i-th pixel in the earliest collected baking target image data; q is the adjustment factor; θ is the normalization factor; The adjustment factor q takes the value of 1 or -1. When the numerator is greater than the denominator, the adjustment factor q takes the value of -1. When the numerator is smaller than the denominator, the adjustment factor q takes the value of 1. Express If the above formula is true, it means that the baking target has been completed, otherwise it means that the baking target has not been completed.

8. The method for monitoring food production process based on visual detection according to claim 7, characterized in that: The normalization factor θ>1, and is defined by the user of the baking equipment management end, and the normalization factor θ controls The value of is in the range of 0 to 1, and the normalization factor θ is set in several groups, and the several groups of normalization factors are bound to the baking target volume and moisture content baked by the specified baking equipment, and each normalization factor is selected and applied based on the initial volume and moisture content of the baking target baked by the baking equipment; Among them, the initial volume and moisture content of the baking target are prior data, which are manually detected and obtained by the user of the baking equipment management end.

9. The food production process monitoring method based on visual detection according to claim 2 or 6, characterized in that: When the baking equipment continues to operate based on the determination result, the baking stirring cycle control of the baking station of the baking equipment is shortened, and the baking target baking progress evaluation operation cycle of the baking equipment is shortened; Among them, the shortening amount of the baking stirring cycle of the baking station of the baking equipment and the baking target baking progress evaluation operation cycle is proportional to the number of times the baking is judged as no in the judgment result of whether the baking is completed.

10. The food production process monitoring method based on visual detection according to claim 1, characterized in that: When a baking target in a baking station of the baking equipment is transferred to a cooling station, a baking station operation message is synchronously generated, the baking station operation message is transmitted to a control target of the baking equipment, and the baking station operation message is displayed on a control panel of the baking station for a user of a baking equipment management end to read; The content of the baking station operation message includes: the operation time, the number of consecutive determinations of whether the baking station has completed baking of the baking target, and the baking target image data collected by the camera module for the last time before the baking target in the baking station is transferred to the cooling station.

Images