Visual algorithm and industrial control creation method, computer equipment and medium

Abstract

The invention relates to the technical field of industrial automation control. The invention relates to a visual algorithm and industrial control creation method, computer equipment and a medium, and the method comprises the steps: obtaining industrial equipment operation information, obtaining industrial equipment control information according to the industrial equipment operation information, and generating visual algorithm execution information according to the industrial equipment control information, the visual algorithm execution information is used for carrying out image processing and monitoring on the operation process of the industrial equipment, industrial equipment state feedback information is generated according to the visual algorithm execution instruction, and the industrial equipment state feedback information is used for feeding back and optimizing an industrial equipment control strategy in real time. The industrial equipment has the effect of improving the automation degree and the operation efficiency of the industrial equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial automation control, and in particular to a method for creating a visual algorithm and industrial control, a computer device and a medium. Background Art

[0002] With the continuous development of industrial automation, the requirements for the control and monitoring of industrial equipment are becoming higher and higher. At present, although some industrial control systems can realize the automatic control of equipment, there is still a lack of real-time monitoring and feedback mechanism of equipment status during equipment operation, and it is impossible to detect and handle abnormal situations in the equipment operation process in time. Summary of the invention

[0003] In order to improve the automation level and operational efficiency of industrial equipment, the present application provides a method for creating a visual algorithm and industrial control, a computer device and a medium.

[0004] The above-mentioned invention objective of the present application is achieved through the following technical solutions: A method for creating a visual algorithm and industrial control, the method comprising: Obtaining information about industrial equipment operations; Obtaining industrial equipment control information according to the industrial equipment operation information; Generate visual algorithm execution information according to the industrial equipment control information, wherein the visual algorithm execution information is used to perform image processing and monitoring on the operation process of the industrial equipment; Instructions are executed according to the visual algorithm to generate industrial equipment status feedback information, and the industrial equipment status feedback information is used for real-time feedback and optimization of industrial equipment control strategies.

[0005] By adopting the above technical solution, industrial equipment operation information is obtained, and industrial equipment control information is generated based on this information, which can reflect the operating status and operating conditions of the equipment in real time. This ability to obtain and process real-time information enables the system to quickly respond to changes in the status of the equipment and provide accurate control instructions, thereby ensuring that the equipment always operates under optimal conditions in different working modes. This not only improves the operating efficiency of the equipment, but also reduces energy consumption and resource waste caused by improper operation or delayed response. By further generating visual algorithm execution information and applying it to the operation process of industrial equipment, real-time monitoring and image processing of equipment operation can be achieved. This visual monitoring technology can not only capture subtle changes in the equipment during operation, but also identify potential operational anomalies or hidden faults through image features. The generation and application of visual algorithm execution information greatly improves the transparency and controllability of equipment operation, so that any abnormal situation can be discovered and handled in time, thereby reducing equipment downtime and maintenance costs. The industrial equipment status feedback information generated by the visual algorithm execution instruction can compare the image processing results with the preset operating standards to evaluate the operating status of the equipment in real time. Through this feedback mechanism, the system can automatically identify deviations in equipment operation and adjust the control strategy in real time according to the evaluation results.

[0006] In a preferred example, the present application may be further configured as follows: obtaining industrial equipment control information according to the industrial equipment operation information includes: Acquire current operating parameter information and operating status information of the industrial equipment from the industrial equipment operating information, analyze the current operating parameter information and the operating status information of the industrial equipment, and identify the working mode and operating condition of the industrial equipment; Based on the working mode and the operating conditions, the industrial equipment control information is generated by a preset control algorithm.

[0007] By adopting the above technical solution, the current operating parameter information and operating status information of industrial equipment are obtained, and the working mode and operating conditions of industrial equipment can be identified in real time. The industrial equipment control information generated by the preset control algorithm can dynamically adjust the operating parameters of the equipment according to different working modes and operating conditions, so that the equipment can operate in the best state in various environments, thereby improving the automation and operating efficiency of industrial equipment.

[0008] In a preferred example, the present application may be further configured as follows: the industrial equipment control information is generated by a preset control algorithm based on the working mode and the operating condition, and further includes: Obtain historical operating information of industrial equipment; Based on the historical operation information of the industrial equipment, combined with the working mode and the operating conditions, and in accordance with the preset control algorithm, the operating parameters with the highest adaptability under the current operating conditions of the industrial equipment are calculated; The industrial equipment control information is generated according to the operating parameter with the highest adaptability.

[0009] By adopting the above technical solution, in the process of generating industrial equipment control information, the historical operation information of the equipment and the current working mode and operating conditions are combined. Through this combination, not only can the most suitable operating parameters be calculated, but also the control information of the equipment can be further optimized, making the operation of the equipment more accurate and intelligent, thereby significantly improving the equipment's adaptability and operating efficiency.

[0010] In a preferred example, the present application may be further configured as follows: generating visual algorithm execution information according to the industrial equipment control information, wherein the visual algorithm execution information is used to perform image processing and monitoring on the operation process of the industrial equipment, including: Acquiring operating parameters and target task information from the industrial equipment control information; Selecting a visual processing algorithm model according to the operating parameters and the target task information; Based on the visual processing algorithm model, the visual algorithm execution information is generated, and the visual algorithm execution information is used to perform the image processing and the monitoring on the operation process of the industrial equipment.

[0011] By adopting the above technical solution, the visual algorithm execution information generated according to the industrial equipment control information can perform real-time image processing and monitoring of the equipment operation process. In this way, key visual information can be captured and processed in real time when the equipment is running, ensuring the accuracy and safety of equipment operation, thereby improving the automated monitoring capability and operating efficiency of industrial equipment.

[0012] In a preferred example, the present application may be further configured as follows: selecting a visual processing algorithm model according to the operating parameters and the target task information includes: Analyzing the operation parameters and the target task information to determine image processing requirements; According to the image processing requirements, the visual processing algorithm model is selected.

[0013] By adopting the above technical solution, when selecting a visual processing algorithm model, the image processing requirements required for the operation of the device can be accurately determined by analyzing the operating parameters and target task information. The most suitable visual processing algorithm model is selected according to these requirements, so that the device can apply the optimal algorithm for processing under different tasks, thereby improving the image processing effect and overall operation efficiency of the device.

[0014] In a preferred example, the present application may be further configured as follows: generating industrial equipment operation feedback information according to the visual algorithm execution information, wherein the industrial equipment operation feedback information is used for real-time feedback and optimization of industrial equipment control strategies, including: Obtaining industrial equipment image features according to the visual algorithm execution information, and evaluating the state of the industrial equipment according to the industrial equipment image features to obtain industrial equipment evaluation results; The industrial equipment evaluation result is compared with a preset operation standard to generate industrial equipment status feedback information, and the industrial equipment control strategy is adjusted based on the industrial equipment status feedback information.

[0015] By adopting the above technical solution, the operation feedback information of industrial equipment is generated according to the visual algorithm execution information, and the status of the equipment can be evaluated in real time. By comparing with the preset operation standards, the generated feedback information can instantly reflect the operation status of the equipment and optimize the equipment control strategy. This closed-loop feedback mechanism improves the adaptive ability and operation accuracy of the equipment, thereby significantly improving the automation level and overall operation efficiency of industrial equipment.

[0016] In a preferred example, the present application may be further configured as follows: comparing the industrial equipment evaluation result with a preset operation standard to generate industrial equipment status feedback information, and adjusting the industrial equipment control strategy based on the industrial equipment status feedback information, further comprising: Identifying industrial equipment operation deviation information based on the industrial equipment status feedback information; According to the industrial equipment operation deviation information, a control parameter with the highest matching degree with the industrial equipment operation deviation information is selected, and according to the control parameter with the highest matching degree, the industrial equipment control strategy is adjusted.

[0017] By adopting the above technical solution, in the process of generating industrial equipment status feedback information, the equipment operation deviation information is identified and adjusted according to the control parameters with the highest matching degree, which can ensure that the equipment can quickly return to the optimal state when deviation occurs. This real-time adjustment and optimization capability enables the equipment to adapt to different operating conditions, significantly improving the equipment's operational stability and automation control level.

[0018] The second object of the invention is achieved by the following technical solutions: An industrial control and feedback device based on a visual algorithm, characterized in that the industrial control and feedback device based on a visual algorithm comprises: An information acquisition module, used to obtain industrial equipment operation information; An instruction generation module, used to obtain industrial equipment control instruction information according to the industrial equipment operation information; A visual algorithm execution module, used to generate visual algorithm execution information according to the industrial equipment control information, wherein the visual algorithm execution information is used to perform image processing and monitoring on the operation process of the industrial equipment; The control strategy module is used to execute instructions according to the visual algorithm to generate industrial equipment status feedback information, and the industrial equipment status feedback information is used for real-time feedback and optimization of industrial equipment control strategy.

[0019] By adopting the above technical solution, industrial equipment operation information is obtained, and industrial equipment control information is generated based on this information, which can reflect the operating status and operating conditions of the equipment in real time. This ability to obtain and process real-time information enables the system to quickly respond to changes in the status of the equipment and provide accurate control instructions, thereby ensuring that the equipment always operates under optimal conditions in different working modes. This not only improves the operating efficiency of the equipment, but also reduces energy consumption and resource waste caused by improper operation or delayed response. By further generating visual algorithm execution information and applying it to the operation process of industrial equipment, real-time monitoring and image processing of equipment operation can be achieved. This visual monitoring technology can not only capture subtle changes in the equipment during operation, but also identify potential operational anomalies or hidden faults through image features. The generation and application of visual algorithm execution information greatly improves the transparency and controllability of equipment operation, so that any abnormal situation can be discovered and handled in time, thereby reducing equipment downtime and maintenance costs. The industrial equipment status feedback information generated by the visual algorithm execution instruction can compare the image processing results with the preset operating standards to evaluate the operating status of the equipment in real time. Through this feedback mechanism, the system can automatically identify deviations in equipment operation and adjust the control strategy in real time according to the evaluation results.

[0020] The third objective of the present application is achieved through the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for creating the above-mentioned visual algorithm and industrial control when executing the computer program.

[0021] The fourth objective of the present application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned visual algorithm and industrial control creation method.

[0022] In summary, the present application includes at least one of the following beneficial technical effects: 1. Obtaining industrial equipment operation information and generating industrial equipment control information based on this information can reflect the operating status and operating conditions of the equipment in real time. This real-time information acquisition and processing capability enables the system to quickly respond to changes in the status of the equipment and provide accurate control instructions, thereby ensuring that the equipment always operates under optimal conditions in different working modes. This not only improves the operating efficiency of the equipment, but also reduces energy consumption and resource waste caused by improper operation or delayed response. By further generating visual algorithm execution information and applying it to the operation process of industrial equipment, real-time monitoring and image processing of equipment operation can be achieved. This visual monitoring technology can not only capture subtle changes in the equipment during operation, but also identify potential operational anomalies or hidden faults through image features. The generation and application of visual algorithm execution information greatly improves the transparency and controllability of equipment operation, so that any abnormal situation can be discovered and handled in a timely manner, thereby reducing equipment downtime and maintenance costs. The industrial equipment status feedback information generated according to the visual algorithm execution instructions can compare the image processing results with the preset operating standards to evaluate the operating status of the equipment in real time. Through this feedback mechanism, the system can automatically identify deviations in equipment operation and adjust the control strategy in real time according to the evaluation results; 2. When selecting a visual processing algorithm model, by analyzing the operating parameters and target task information, the image processing requirements required for the operation of the device can be accurately determined. According to these requirements, the most appropriate visual processing algorithm model is selected so that the device can apply the optimal algorithm for processing under different tasks, thereby improving the image processing effect and overall operating efficiency of the device; 3. In the process of generating industrial equipment status feedback information, the equipment operation deviation information is identified and adjusted according to the control parameters with the highest matching degree, which can ensure that the equipment can quickly return to the optimal state when deviation occurs. This real-time adjustment and optimization capability enables the equipment to adapt to different operating conditions, significantly improving the equipment's operational stability and automation control level. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of a method for creating a visual algorithm and industrial control in an embodiment of the present application; Figure 2 It is a flowchart for implementing step S20 of the method for creating a visual algorithm and industrial control in one embodiment of the present application; Figure 3 It is a flowchart for implementing step S202 of the method for creating a visual algorithm and industrial control in one embodiment of the present application; Figure 4 It is a flowchart for implementing step S30 of the method for creating a visual algorithm and industrial control in one embodiment of the present application; Figure 5It is an implementation flow chart of step S302 of the method for creating a visual algorithm and industrial control in one embodiment of the present application; Figure 6 It is an implementation flow chart of step S40 of the method for creating a visual algorithm and industrial control in one embodiment of the present application; Figure 7 It is an implementation flow chart of step S402 of the method for creating a visual algorithm and industrial control in one embodiment of the present application; Figure 8 It is a principle block diagram of an industrial control and feedback device based on a visual algorithm in one embodiment of the present application; Fig. 9 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The present application is further described in detail below in conjunction with the accompanying drawings.

[0025] In one embodiment, if Figure 1 As shown, the present application discloses a method for creating a visual algorithm and industrial control, which specifically includes the following steps: S10: Obtaining industrial equipment operation information.

[0026] In this embodiment, industrial equipment operation information refers to operation information related to industrial equipment collected in real time through sensors and data acquisition devices on the industrial equipment. The industrial equipment operation information includes but is not limited to parameters such as the operating status, operating temperature, pressure, flow, vibration, and rotation speed of the industrial equipment.

[0027] Specifically, comprehensive real-time monitoring of various operating parameters of the equipment is achieved by placing a variety of sensors and data acquisition devices at key locations of industrial equipment. These sensors may include temperature sensors, pressure sensors, flow meters, accelerometers, tachometers, etc., which are responsible for collecting physical quantities such as temperature, pressure, flow, vibration, and speed of the equipment. The working status information of the equipment is determined by comprehensive analysis of these physical quantities, for example, by detecting changes in speed and vibration to determine the running stability of the equipment. At the same time, the control command information input by the operator through the human-computer interaction interface, such as start-stop commands, speed adjustment commands, etc., is also recorded in real time and used as part of the industrial equipment operation information.

[0028] S20: Obtaining industrial equipment control information according to the industrial equipment operation information.

[0029] In this embodiment, the industrial equipment control information refers to the control instructions for adjusting the operating status of the industrial equipment generated by analyzing and processing the acquired operation information.

[0030] Specifically, the collected industrial equipment operation information is preprocessed to improve the accuracy and reliability of the data. The preprocessing steps include filtering to eliminate noise, data deduplication to remove redundant information, and processing missing data through interpolation and other methods. The preprocessed operation information is then input into the preset control algorithm, which performs a comprehensive analysis based on the real-time operating parameters of the equipment, historical operating data and current task requirements. For example, by analyzing the current temperature and pressure and comparing them with historical data, the optimal operating conditions of the equipment under different working conditions are predicted, or the operating safety under the current load is judged based on the flow and vibration data. The industrial equipment control information finally generated includes specific control instructions, such as equipment start and stop instructions, speed regulation, load adjustment, temperature control, etc. S30: Generate visual algorithm execution information based on the industrial equipment control information, and the visual algorithm execution information is used to perform image processing and monitoring on the operation process of the industrial equipment.

[0031] In this embodiment, the visual algorithm execution information refers to converting the device control information into operation information for guiding image processing.

[0032] Specifically, the key operating links and equipment parts that need to be monitored are determined based on the industrial equipment control information. For example, if the control information shows that the equipment has entered a high-load mode, the system will give priority to parts related to equipment vibration and wear, and select appropriate visual algorithms for processing. Then, the system adjusts the execution details of the image processing algorithm according to the specific parameters in the control information (such as the speed and temperature of the equipment), such as adjusting the exposure time of the camera, the frequency and resolution of image acquisition, etc., to adapt to the current operating status of the equipment. The visual algorithm execution information also includes specific image processing tasks, such as defect detection, shape recognition, motion trajectory analysis, etc., which are performed by the industrial camera and visual processing unit on the equipment. Finally, the generated visual algorithm execution information will be issued to the image processing module of the equipment to guide it to perform real-time monitoring during the operation of the equipment and generate corresponding image analysis results.

[0033] S40: Execute instructions according to the visual algorithm to generate industrial equipment status feedback information, and the industrial equipment status feedback information is used for real-time feedback and optimization of industrial equipment control strategies.

[0034] In this embodiment, image features such as shape, motion trajectory, etc. are extracted from the output of the visual algorithm and compared with the preset operating standards. If an abnormality is found, feedback information is generated, which includes a specific description of the deviation and the possible type of fault. The feedback information is transmitted to the control system in real time and triggers immediate adjustment of the equipment control strategy to ensure stable and efficient operation of the equipment.

[0035] Specifically, the real-time collected image data is analyzed by visual algorithms to extract key image features that reflect the status of the equipment. For example, when performing defect detection, the extracted image features may include the shape, length, and distribution area of ​​surface cracks; in motion trajectory analysis, the extracted features may include the motion path of equipment components, speed change curves, etc. The extracted image features will be compared with the preset operating standards to determine whether the equipment is operating normally. If a deviation is found between the image features and the standard, the system will generate corresponding feedback information. The feedback information describes in detail the nature of the deviation, such as the specific location and size of the cracks on the surface of the equipment, or the degree of deviation of the equipment's motion trajectory, and the types of failures that may result, such as excessive wear and loose parts. The generated feedback information will be transmitted to the central control system in real time through the communication network, triggering immediate adjustments to the equipment control strategy to correct the deviation or prevent potential failures, thereby ensuring the stability and operating efficiency of the equipment.

[0036] In one embodiment, if Figure 2 As shown, in step S20, the industrial equipment control information is obtained according to the industrial equipment operation information, including: S201: Acquire current operating parameter information and operating status information of the industrial equipment from the industrial equipment operating information, analyze the current operating parameter information and operating status information of the industrial equipment, and identify the working mode and operating conditions of the industrial equipment.

[0037] Specifically, the current operating parameter information extracted from the industrial equipment operation information may include real-time data such as temperature, pressure, speed, flow, vibration frequency, etc. After obtaining these operating parameter information, the system will also synchronously obtain operating status information, such as the startup status of the equipment, the current operating mode, the operating cycle, the load condition, etc. By performing data analysis and pattern recognition on the operating parameter information and the operating status information, the system can identify the current working mode of the industrial equipment, such as the normal operating mode, the peak load mode, the maintenance mode, etc., and identify the specific operating conditions of the equipment in these modes, such as the operation of the equipment in a high temperature and high pressure environment, or the performance under low load conditions. These identification results provide basic input data for subsequent control algorithms to ensure that the operating status of the equipment is accurately evaluated.

[0038] Furthermore, the system refers to an integrated platform for monitoring, analyzing, controlling and providing feedback on the operating status of industrial equipment.

[0039] S202: Generate industrial equipment control information through a preset control algorithm based on the working mode and operating conditions.

[0040] In this embodiment, the preset control algorithm refers to a defined mathematical model or a set of logical rules, which is used to generate corresponding control decisions according to the operating parameters and status information of the industrial equipment.

[0041] Specifically, the identified working mode and operating conditions will be used as input data and input into the preset control algorithm for calculation. The control algorithm may include proportional-integral-differential (PID) control algorithm, fuzzy control algorithm or intelligent control algorithm based on machine learning. Taking PID control as an example, the algorithm will calculate a set of control parameters, including the proportional part, integral part and differential part of the control quantity, based on the deviation between the input actual operating parameters and the set value. These control parameters are used to accurately adjust the operating state of industrial equipment, such as maintaining the set operating speed by adjusting the speed of the motor, or controlling the power output of the heating device by changing the temperature set value. In fuzzy control, the algorithm will infer appropriate control actions based on the input conditions through fuzzy rules, such as adjusting the valve opening to control the flow rate. The generated control information is sent to the actuator of the equipment in the form of a control signal, instructing the equipment to make corresponding operational adjustments, thereby ensuring that the equipment operates stably under the current working mode and operating conditions.

[0042] In one embodiment, if Figure 3 As shown, in step S202, based on the working mode and the operating conditions, the industrial equipment control information is generated by a preset control algorithm, which also includes: S2021: Obtain historical operation information of industrial equipment.

[0043] In this embodiment, the historical operation information of the industrial equipment refers to all relevant data and operation records generated and recorded during the past operation of the industrial equipment.

[0044] Specifically, historical operation information includes the operating parameter data of the equipment in different working modes, the equipment status change records, the execution of operation instructions, and the input records of the operator. For example, the historical data may record the temperature and pressure change curves of the equipment under high load conditions, the time points of equipment start and stop, the specific content of equipment maintenance and maintenance, and the adjustment instructions entered by the operator at a specific moment. These data are usually stored in a central database for centralized management. Through data mining technology, the system can extract valuable information from these historical records to provide support for the evaluation of the current operating status and future operation decisions.

[0045] Furthermore, the central database refers to a core for centrally storing and managing data related to industrial equipment.

[0046] S2022: Based on the historical operation information of the industrial equipment, combined with the working mode and operating conditions, and in accordance with a preset control algorithm, calculate the operating parameters with the highest adaptability under the operating conditions of the current industrial equipment; Specifically, the system first extracts historical data similar to the current working mode and operating conditions from the historical operation information. These historical data usually include the operating parameters of the equipment under the same or similar working conditions, the response of the equipment to the control instructions, and the corresponding operating results. The system will use these historical data as a reference, combined with the current real-time operating parameters and operating status information, and input them into the preset control algorithm. The control algorithm will perform parameter optimization calculations based on these input conditions to find a set of operating parameters with the highest adaptability under the current operating conditions. These operating parameters include but are not limited to the optimal operating speed of the equipment, the appropriate temperature setting value, the reasonable pressure adjustment range, and the appropriate load distribution. The selection of these parameters is not only based on the current operating conditions, but also fully considers the experience of success and failure in historical operations to improve the reliability and adaptability of the control strategy. The calculated operating parameters will be used as the final control instructions to guide the actual operation of the equipment.

[0047] S2023: Generate industrial equipment control information based on the operating parameters with the highest adaptability.

[0048] Specifically, based on the calculated operating parameters with the highest degree of adaptability, the system generates specific control information. The control information includes detailed instructions for equipment operation, such as setting the specific speed of the motor, adjusting the target temperature of the temperature control system, changing the opening of the valve to control the flow, or adjusting the load distribution to balance the workload of the equipment. The control information is transmitted to the control unit of the equipment through the industrial communication network to guide the equipment to perform the corresponding operation adjustments. The control instruction information is usually encoded in the form of digital signals to ensure the integrity and accuracy of the data during the transmission process. At the same time, the system will continuously track and feedback the execution of the instructions based on the real-time monitoring data to ensure that the equipment can operate according to the instructions, and fine-tune or regenerate the instructions when necessary to adapt to dynamically changing operating conditions. This closed-loop control mechanism ensures the operating efficiency and safety of industrial equipment.

[0049] In one embodiment, if Figure 4 As shown, in step S30, visual algorithm execution information is generated according to the industrial equipment control information, and the visual algorithm execution information is used to perform image processing and monitoring on the operation process of the industrial equipment, including: S301: Acquire operation parameters and target task information from industrial equipment control information.

[0050] In this embodiment, the operation parameters and target task information refer to specific operation settings and expected task goals of industrial equipment extracted from industrial equipment control information.

[0051] Specifically, the operating parameters include specific control variables such as the equipment's operating speed, operating temperature, pressure, valve opening, etc. The control variables directly affect the equipment's operating status. The target task information indicates the specific operation tasks that the equipment needs to complete, such as a certain stage of operation in the production line, material processing tasks, quality inspection tasks, etc.

[0052] S302: Select a visual processing algorithm model according to the operating parameters and target task information.

[0053] In this embodiment, the visual processing algorithm model refers to determining the image processing algorithm that best suits the current task based on the extracted operating parameters and task objectives.

[0054] Specifically, based on the acquired operating parameters, the working environment and operating requirements of the current equipment are classified, such as low temperature and high pressure environment, fast motion environment, etc. Then, based on the target task information, the image processing priority of the task is determined, such as the need to focus on edge detection, motion trajectory tracking, or surface defect recognition. Next, the system combines the operating parameters with the task information, queries the preset visual processing algorithm model library, and selects the algorithm model with the highest matching degree with the current task according to multiple indicators such as algorithm performance, processing efficiency, and adaptability.

[0055] S303: Generate visual algorithm execution information based on the visual processing algorithm model, and the visual algorithm execution information is used to perform image processing and monitoring on the operation process of the industrial equipment.

[0056] Specifically, according to the selected visual processing algorithm model, the algorithm parameter configuration is initialized, including but not limited to image resolution, filtering parameters, feature extraction methods, etc. Then, the operating parameters and target task information are input into the algorithm model, and the algorithm model is started to perform image processing operations. Next, the algorithm model processes the image data from the sensor or camera in real time according to the operation process of the industrial equipment, extracts key image features, and generates specific visual algorithm execution information through feature comparison and pattern recognition. The visual algorithm execution information includes image processing results, identified key point information, and comparison results with standard operating parameters.

[0057] In one embodiment, if Figure 5 As shown, in step S302, a visual processing algorithm model is selected according to the operation parameters and target task information, including: S3021: Analyze operation parameters and target task information to determine image processing requirements.

[0058] In this embodiment, the image processing requirement refers to analyzing the demand for image processing according to the operation parameters and task objectives.

[0059] Specifically, we first statistically analyze the acquired operating parameters to determine the real-time, precision, and reliability requirements of industrial equipment for image processing under current operating conditions; then, based on the target task information, we identify key image processing tasks during equipment operation, such as motion trajectory tracking, surface quality inspection, or operation process monitoring. By combining operating parameters and task objectives, we determine the specific requirements that image processing needs to meet, including processing speed, resolution, feature extraction accuracy, etc.

[0060] S3022: Select a visual processing algorithm model based on image processing requirements.

[0061] Specifically, according to the image processing requirements determined above, all algorithm models that meet the basic requirements are called out from the visual processing algorithm model library; then, by comparing the performance indicators of these algorithm models, such as processing speed, applicable scenarios, algorithm complexity, etc., the candidate models that can meet all image processing requirements are screened out, and then, the actual performance of the candidate models under the current industrial equipment operating conditions is further evaluated, including processing effect, operating stability and resource occupancy, and finally the visual processing algorithm model that best suits the current task is determined.

[0062] In one embodiment, if Figure 6 As shown, in step S40, the industrial equipment operation feedback information is generated according to the visual algorithm execution information, and the industrial equipment operation feedback information is used for real-time feedback and optimization of the industrial equipment control strategy, including: S401: Obtain industrial equipment image features according to visual algorithm execution information, evaluate the status of the industrial equipment according to the industrial equipment image features, and obtain industrial equipment evaluation results.

[0063] In this embodiment, the industrial equipment image features refer to the key image feature data generated during the operation of the industrial equipment through the information extraction of the visual algorithm execution. These image features may include texture changes on the surface of the equipment, deviations in the motion trajectory, wear of equipment components, abnormal temperature distribution, etc. By analyzing these image features, the operating status of the industrial equipment can be further evaluated to determine whether the equipment has potential failures or improper operation. The industrial equipment evaluation result refers to the evaluation conclusion on the operating status of the industrial equipment obtained by analyzing the image features, combining the historical data of the equipment operation and the current operating parameters. The evaluation results may include whether the equipment is in normal working condition, whether there are signs of abnormal operation, whether the equipment performance meets the expected standards, etc.

[0064] Specifically, the image data of industrial equipment is processed through visual algorithms to extract key image features, such as scratches, wear and tear on the equipment surface, and component offsets. These image features are then compared with the standard image features of the equipment in normal working conditions to identify possible abnormal features. Next, the extracted image features are input into the equipment status assessment model, which comprehensively analyzes the overall operating status of the equipment based on historical data and current operating parameters to generate detailed equipment assessment results.

[0065] S402: Compare the industrial equipment evaluation result with the preset operation standard, generate industrial equipment status feedback information, and adjust the industrial equipment control strategy based on the industrial equipment status feedback information.

[0066] In this embodiment, the preset operating standard refers to the baseline value of the equipment operating performance and status that is preset according to the industrial equipment design specifications, operating manuals and industry standards. These standards may include the normal operating parameter range of the equipment, the allowable wear limit, the upper limit of temperature and pressure, etc., which are used to evaluate whether the equipment is in normal operating state. Industrial equipment status feedback information refers to the feedback data generated after comparing the equipment evaluation results with the preset operating standards, reflecting the difference between the current operating status of the equipment and the standards. The feedback information may include the current operating deviation of the equipment, the parameters that need to be adjusted, and potential fault warnings.

[0067] Specifically, the operating parameters and status information contained in the equipment evaluation results are compared item by item with the preset operating standards to identify the parts that do not meet the standards. Then, based on the comparison results, detailed industrial equipment status feedback information is generated, including the equipment's operating deviation, description of abnormal conditions, and recommended control adjustment measures. The generated feedback information is then used to optimize the equipment's control strategy, such as adjusting operating parameters, changing the execution mode of the control algorithm, or adding additional maintenance procedures to ensure that the equipment can meet the preset standards in subsequent operation.

[0068] In one embodiment, if Figure 7 As shown, in step S402, the industrial equipment evaluation result is compared with the preset operation standard to generate industrial equipment status feedback information, and the industrial equipment control strategy is adjusted based on the industrial equipment status feedback information, which also includes: S4021: Identify industrial equipment operation deviation information based on industrial equipment status feedback information.

[0069] In this embodiment, the industrial equipment operation deviation information refers to the deviation information in the equipment operation process identified by analyzing the industrial equipment status feedback information. Such deviation information may include the difference between the actual operating parameters and the preset standards, such as excessive temperature, insufficient pressure, abnormal equipment vibration, etc., reflecting the degree of deviation between the current operating state of the equipment and the expected state.

[0070] Specifically, the data in the feedback information is analyzed, and each parameter is compared with the preset standard to calculate the deviation value of each parameter. Then, based on these deviation values, the degree of deviation of the equipment operation is judged, and the deviation of which parameters may affect the overall operation of the equipment is identified.

[0071] S4022: According to the industrial equipment operation deviation information, select the control parameter with the highest matching degree with the industrial equipment operation deviation information, and adjust the industrial equipment control strategy according to the control parameter with the highest matching degree.

[0072] Specifically, according to the nature and severity of the deviation information of the operation of industrial equipment, the control parameters with the highest matching degree with the deviation information are screened out from a predefined set of control parameters. These control parameters may include temperature adjustment values, pressure setting values, equipment operation speed, etc. Then, by comparing the adjustment effect of each control parameter, the parameter combination that best suits the current deviation condition is selected. Then, according to the selected control parameter combination, the control strategy of the equipment is adjusted in real time, such as modifying the execution logic of the control algorithm, adding or reducing certain operation steps, or changing the operation mode of the equipment, so as to eliminate the operation deviation and restore the normal operation state of the equipment.

[0073] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0074] In one embodiment, an industrial control and feedback device based on a visual algorithm is provided, and the industrial control and feedback device based on a visual algorithm corresponds one-to-one to the creation method of the visual algorithm and industrial control in the above embodiment. Figure 8 As shown, the industrial control and feedback device based on visual algorithm includes an information acquisition module, an instruction generation module, a visual algorithm execution module and a control strategy module. The detailed description of each functional module is as follows: An information acquisition module, used to obtain industrial equipment operation information; An instruction generation module, used to obtain industrial equipment control instruction information according to industrial equipment operation information; A visual algorithm execution module is used to generate visual algorithm execution information according to industrial equipment control information, and the visual algorithm execution information is used to perform image processing and monitoring on the operation process of the industrial equipment; The control strategy module is used to execute instructions according to the visual algorithm and generate industrial equipment status feedback information. The industrial equipment status feedback information is used for real-time feedback and optimization of industrial equipment control strategies.

[0075] Optionally, the instruction generation module includes: An analysis submodule is used to obtain current operating parameter information and operating status information of the industrial equipment from the industrial equipment operation information, analyze the current operating parameter information and operating status information of the industrial equipment, and identify the working mode and operating conditions of the industrial equipment; The information generation submodule is used to generate industrial equipment control information through a preset control algorithm based on the working mode and operating conditions.

[0076] Optionally, the information generation submodule includes: A historical information unit, used to obtain historical operation information of industrial equipment; An operating parameter unit is used to calculate the operating parameters with the highest adaptability under the operating conditions of the current industrial equipment based on the historical operating information of the industrial equipment, combined with the working mode and operating conditions, according to the preset control algorithm; The device control unit is used to generate industrial device control information according to the operating parameters with the highest adaptability.

[0077] Optionally, the visual algorithm execution module includes: The operating parameter and target task submodule is used to obtain the operating parameter and target task information from the industrial equipment control information; The model selection submodule is used to select the visual processing algorithm model according to the operation parameters and target task information; The execution submodule is used to generate visual algorithm execution information based on the visual processing algorithm model. The visual algorithm execution information is used to perform image processing and monitoring on the operation process of industrial equipment.

[0078] Optionally, the model selection submodule includes: An image processing unit, used to analyze operating parameters and target mission information and determine image processing requirements; The model confirmation unit is used to select a visual processing algorithm model according to image processing requirements.

[0079] Optionally, the control strategy module includes: The industrial equipment evaluation result submodule is used to obtain the image features of the industrial equipment according to the visual algorithm execution information, and to evaluate the status of the industrial equipment according to the image features of the industrial equipment to obtain the industrial equipment evaluation results; The control strategy submodule is used to compare the industrial equipment evaluation results with the preset operating standards, generate industrial equipment status feedback information, and adjust the industrial equipment control strategy based on the industrial equipment status feedback information.

[0080] Optionally, the control strategy submodule includes: An operation deviation unit, used to identify operation deviation information of industrial equipment according to feedback information of industrial equipment status; The control strategy adjustment unit is used to select the control parameter with the highest matching degree with the industrial equipment operation deviation information according to the industrial equipment operation deviation information, and adjust the industrial equipment control strategy according to the control parameter with the highest matching degree.

[0081] For the specific definition of the industrial control and feedback device based on visual algorithms, please refer to the definition of the creation method of visual algorithms and industrial control in the above text, which will not be repeated here. Each module in the above-mentioned industrial control and feedback device based on visual algorithms can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0082] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig. 9 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used for a central database. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for creating a visual algorithm and industrial control is implemented.

[0083] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: Obtaining industrial equipment operating information; According to the industrial equipment operation information, the industrial equipment control information is obtained; Generate visual algorithm execution information based on industrial equipment control information, and use the visual algorithm execution information to process and monitor the operation process of the industrial equipment; According to the instructions executed by the visual algorithm, industrial equipment status feedback information is generated, and the industrial equipment status feedback information is used for real-time feedback and optimization of industrial equipment control strategies.

[0084] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Obtaining information about industrial equipment operations; According to the industrial equipment operation information, the industrial equipment control information is obtained; Generate visual algorithm execution information based on industrial equipment control information, and use the visual algorithm execution information to process and monitor the operation process of the industrial equipment; According to the instructions executed by the visual algorithm, industrial equipment status feedback information is generated, and the industrial equipment status feedback information is used for real-time feedback and optimization of industrial equipment control strategies.

[0085] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0086] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0087] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person 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 do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for creating visual algorithms and industrial control, It is characterized in that The method for creating the visual algorithm and industrial control includes: Obtaining industrial equipment operating information; Obtaining industrial equipment control information according to the industrial equipment operation information; Generate visual algorithm execution information according to the industrial equipment control information, wherein the visual algorithm execution information is used to perform image processing and monitoring on the operation process of the industrial equipment; Instructions are executed according to the visual algorithm to generate industrial equipment status feedback information, and the industrial equipment status feedback information is used for real-time feedback and optimization of industrial equipment control strategies.

2. The method for creating a visual algorithm and industrial control according to claim 1, It is characterized in that The step of obtaining industrial equipment control information according to the industrial equipment operation information includes: Acquire current operating parameter information and operating status information of the industrial equipment from the industrial equipment operating information, analyze the current operating parameter information and the operating status information of the industrial equipment, and identify the working mode and operating condition of the industrial equipment; Based on the working mode and the operating conditions, the industrial equipment control information is generated by a preset control algorithm.

3. The method for creating a visual algorithm and industrial control according to claim 2, It is characterized in that The generating the industrial equipment control information by a preset control algorithm based on the working mode and the operating condition also includes: Obtain historical operating information of industrial equipment; Based on the historical operation information of the industrial equipment, combined with the working mode and the operating conditions, and in accordance with the preset control algorithm, the operating parameters with the highest adaptability under the current operating conditions of the industrial equipment are calculated; The industrial equipment control information is generated according to the operating parameter with the highest adaptability.

4. The method for creating a visual algorithm and industrial control according to claim 1, It is characterized in that The generating of visual algorithm execution information according to the industrial equipment control information, wherein the visual algorithm execution information is used for image processing and monitoring of the operation process of the industrial equipment, includes: Acquiring operating parameters and target task information from the industrial equipment control information; Selecting a visual processing algorithm model according to the operating parameters and the target task information; Based on the visual processing algorithm model, the visual algorithm execution information is generated, and the visual algorithm execution information is used to perform the image processing and the monitoring on the operation process of the industrial equipment.

5. The method for creating a visual algorithm and industrial control according to claim 4, It is characterized in that The step of selecting a visual processing algorithm model according to the operating parameters and the target task information includes: Analyzing the operation parameters and the target task information to determine image processing requirements; According to the image processing requirements, the visual processing algorithm model is selected.

6. The method for creating a visual algorithm and industrial control according to claim 1, It is characterized in that The step of generating industrial equipment operation feedback information according to the visual algorithm execution information, wherein the industrial equipment operation feedback information is used for real-time feedback and optimization of industrial equipment control strategies, includes: Obtaining industrial equipment image features according to the visual algorithm execution information, and evaluating the state of the industrial equipment according to the industrial equipment image features to obtain industrial equipment evaluation results; The industrial equipment evaluation result is compared with a preset operation standard to generate industrial equipment status feedback information, and the industrial equipment control strategy is adjusted based on the industrial equipment status feedback information.

7. The method for creating a visual algorithm and industrial control according to claim 6, It is characterized in that The step of comparing the industrial equipment evaluation result with a preset operation standard to generate industrial equipment status feedback information, and adjusting the industrial equipment control strategy based on the industrial equipment status feedback information, further includes: Identifying industrial equipment operation deviation information based on the industrial equipment status feedback information; According to the industrial equipment operation deviation information, a control parameter with the highest matching degree with the industrial equipment operation deviation information is selected, and according to the control parameter with the highest matching degree, the industrial equipment control strategy is adjusted.

8. An industrial control and feedback device based on visual algorithm, It is characterized in that The industrial control and feedback device based on visual algorithm includes: An information acquisition module, used to obtain industrial equipment operation information; An instruction generation module, used to obtain industrial equipment control instruction information according to the industrial equipment operation information; A visual algorithm execution module, used to generate visual algorithm execution information according to the industrial equipment control information, wherein the visual algorithm execution information is used to perform image processing and monitoring on the operation process of the industrial equipment; The control strategy module is used to execute instructions according to the visual algorithm to generate industrial equipment status feedback information, and the industrial equipment status feedback information is used for real-time feedback and optimization of industrial equipment control strategy.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the steps of the method for creating a visual algorithm and industrial control according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program. It is characterized in that When the computer program is executed by a processor, the steps of the method for creating a visual algorithm and industrial control according to any one of claims 1 to 7 are implemented.

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