Operational effect analysis, data processing methods, devices, equipment and storage media

Abstract

The embodiments of the present application provide a commissioning effect analysis and data processing method, apparatus, device, and storage medium. In the data processing method, when the equipment is automatically commissioned, the operating data of the equipment under automatic commissioning is detected to obtain the actual values ​​of the operating parameters after the commissioning operation. Based on the recommended values ​​and actual values ​​of the operating parameters corresponding to the commissioning operation, the commissioning effect of the operating parameters can be automatically analyzed, realizing intelligent analysis of the commissioning effect, greater flexibility, and greatly improving the reliability of the analysis results.

Description

Technical Field

[0001] The present application relates to the field of intelligent control technology, and in particular to an operation effect analysis, data processing method, device, equipment and storage medium. Background Art

[0002] Currently, process manufacturing companies (such as cement and chemical companies) have achieved automated production processes. During automated operations, intelligent algorithms predict the required operating parameters for production equipment and send corresponding instructions to the Advanced Process Control (APC), which then controls the production equipment through the Distributed Control System (DCS).

[0003] During automatic commissioning, management personnel can manually intervene based on production needs or the operating status of production equipment. To analyze the prediction effectiveness of the intelligent algorithm, it is necessary to collect statistics on manual interventions during the automatic commissioning process. Existing technologies typically rely on manual statistics, which is less reliable. Therefore, a solution is needed. Summary of the Invention

[0004] Multiple aspects of the present application provide an operation effect analysis, data processing method, device, equipment and storage medium for automatically analyzing the effect of automatic operation under algorithm control, improving the flexibility of analysis operations and the reliability of analysis results.

[0005] An embodiment of the present application provides a method for analyzing the commissioning effect of industrial equipment, including: obtaining a commissioning value used for automatic commissioning of industrial equipment; the commissioning value includes a recommended value for each of at least one commissioning operation; the industrial equipment belongs to the field of process manufacturing; detecting the operating data of the industrial equipment under the automatic commissioning, and obtaining the actual value corresponding to each of the at least one commissioning operation from the operating data; analyzing the commissioning effect of the automatic commissioning based on the recommended value of each of the at least one commissioning operation and the actual value corresponding to each of the at least one commissioning operation.

[0006] An embodiment of the present application provides a data processing method, including: obtaining a commissioning value for automatic commissioning of equipment; the commissioning value includes a recommended value for each of at least one commissioning operation; detecting the operating data of the equipment under the automatic commissioning, and obtaining the actual value corresponding to each of the at least one commissioning operation from the operating data; analyzing the commissioning effect of the automatic commissioning based on the recommended value for each of the at least one commissioning operation and the actual value corresponding to each of the at least one commissioning operation.

[0007] An embodiment of the present application also provides a data processing device, including: a data acquisition module, used to: obtain the commissioning value adopted for automatic commissioning of equipment; the commissioning value includes the recommended value of each at least one commissioning operation; and detect the operating data of the equipment under the automatic commissioning, and obtain the actual value corresponding to each of the at least one commissioning operations from the operating data; an analysis module, used to: analyze the commissioning effect of the automatic commissioning based on the recommended value of each of the at least one commissioning operations and the actual value corresponding to each of the at least one commissioning operations.

[0008] An embodiment of the present application also provides a data processing device, including: a memory, a processor, and a communication component; the memory is used to store one or more computer instructions; the processor is used to execute the one or more computer instructions to: execute the industrial equipment commissioning effect analysis method or data processing method provided in an embodiment of the present application.

[0009] An embodiment of the present application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it can implement the industrial equipment commissioning effect analysis method or data processing method provided in the embodiment of the present application.

[0010] In the data processing method provided in the embodiment of the present application, when the equipment is automatically put into operation, the operating data of the equipment under automatic operation is detected, and the actual values ​​of the operating parameters after the commissioning operation can be obtained; based on the recommended values ​​and actual values ​​of the operating parameters corresponding to the commissioning operation, the commissioning effect of the operating parameters can be automatically analyzed, thereby realizing intelligent analysis of the commissioning effect, being more flexible, and greatly improving the reliability of the analysis results. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0012] Figure 1 A flowchart of a data processing method provided for an exemplary embodiment of the present application;

[0013] Figure 2a A schematic diagram showing the operation effect provided by an exemplary embodiment of the present application;

[0014] Figure 2b A schematic diagram of generating merged data provided by an exemplary embodiment of the present application;

[0015] Figure 3 A flow chart of a method for analyzing the operation effect of industrial equipment provided by an exemplary embodiment of the present application;

[0016] Figure 4 This is a schematic diagram showing changes in the actual value of a first operating parameter in an application scenario embodiment of the present application;

[0017] Figure 5 A flowchart of a data processing device provided by an exemplary embodiment of the present application;

[0018] Figure 6 A schematic structural diagram of a data processing device provided as an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0019] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0020] In the prior art, manual statistics and analysis of data generated during the commissioning process are relied upon. When manually counting commissioning data, it is difficult to perform accurate statistics in scenarios with high commissioning frequencies; when manually analyzing commissioning data, subjective ideas are easily introduced, making it difficult to obtain accurate analysis results; in addition, the above-mentioned statistics and analysis operations consume too much manpower costs and are not easy to promote flexibly. In order to solve the above-mentioned technical problems, a solution is provided in some embodiments of the present application, which will be exemplified below with reference to the accompanying drawings.

[0021] Figure 1 A flow chart of a data processing system provided by an exemplary embodiment of the present application is shown as follows: Figure 1 As shown, the method includes:

[0022] Step 101: Acquire commissioning values ​​for automatic commissioning of equipment; the commissioning values ​​include recommended values ​​for at least one commissioning operation of a first operating parameter.

[0023] Step 102: Detect operating data of the equipment under the automatic operation, and obtain an actual value of the first operating parameter under the at least one operation from the operating data.

[0024] Step 103: Analyze the operation effect of the first operating parameter according to the recommended values ​​of the first operating parameter in the at least one operation and the actual value of the first operating parameter in the at least one operation.

[0025] Among them, equipment refers to the general term for labor materials and material materials that can be used by individuals or enterprises for a long time in production and basically maintain their original physical form and function during repeated use.

[0026] The implementation of equipment varies across different production scenarios, as exemplified below. For example, in the cement manufacturing industry, typical equipment may include: cement rotary kilns, cyclone preheaters, coolers, and other equipment. For example, in the steel production industry, typical equipment may include: blast furnaces, hot blast furnaces, converters, electric furnaces, refining furnaces, continuous casting machines, and other equipment. For example, in the chip manufacturing industry, typical equipment may include: photolithography machines, dicing machines, die bonders, wire bonders, and other equipment. For example, in the food processing industry, typical equipment may include: quick freezing equipment, sorting equipment, cleaning equipment, sterilization equipment, food canning machines, automatic capping machines, paper labeling machines, case packing machines, empty package inspection machines, and so on. As another example, in the chemical industry, typical production equipment may include: fans, compressors, pumps, separation equipment, electrolyzers, reactors, filters, crushers, centrifuges, rotary kilns, mixers, dryers, and other equipment.

[0027] Commissioning refers to the process of configuring the operating parameters of a device to set values, ensuring that it meets the required operating conditions, and then putting it into operation. Automatic commissioning involves using a specific algorithm to automatically calculate appropriate values ​​for the device's operating parameters. Based on the calculated values, control instructions are directly or indirectly issued to the device to automatically control the device to operate in the specified mode.

[0028] For example, in a typical automated commissioning scenario, real-time data related to equipment, such as operational data, environmental data, and production demand data, can be acquired. Based on the pre-defined automated commissioning algorithm and this data, the required values ​​for the equipment's operating parameters at a future time are predicted. The calculated values ​​are then sent to the APC system, which controls equipment operation based on these values.

[0029] The operating parameters of a device include any one or more operating parameters that the device's operation depends on, such as temperature, humidity, pressure, speed, power, etc. The term "first operating parameter" refers to any one of these operating parameters, and the term "first" is used here for ease of description only.

[0030] The values ​​of the operating parameters sent to the device for automatic commissioning can be referred to as commissioning values. During the automatic commissioning process, one or more commissioning operations can be performed. Different commissioning operations can recommend different parameter values ​​for the same operating parameter, which is not limited in this embodiment.

[0031] For example, automatic commissioning includes three commissioning operations corresponding to temperature parameters. The first commissioning operation recommends a first temperature value for the temperature parameter, the second commissioning operation recommends a second temperature value for the temperature parameter, and the third commissioning operation recommends a third pressure value for the temperature parameter.

[0032] Typically, after the equipment is automatically commissioned, it will operate according to the recommended operating parameter values. In some scenarios, if the equipment's operating results are unsatisfactory or do not meet the user's production requirements after automatic commissioning, the user can perform manual intervention. Manual intervention refers to manually modifying the equipment's operating parameter values. In this case, the equipment will continue to operate according to the manually modified parameter values.

[0033] To analyze the effectiveness of automatic commissioning, the actual values ​​of the equipment's operating parameters for each commissioning operation can be obtained during the process. These actual values ​​are obtained by sampling the equipment's actual operating status. For each commissioning operation, the corresponding operational effect can be analyzed based on the recommended and actual values. Based on the operational effect of each operational parameter operation, the overall operational effect of the operating parameters can be analyzed.

[0034] When analyzing the operational effects, we can analyze the manual intervention during automatic operation, the reasons for manual intervention, the operating parameters of manual intervention, etc. The operational effects obtained from the analysis can be used to quantify the effectiveness of the automatic operation algorithm and further optimize the automatic operation algorithm.

[0035] In this embodiment, when the equipment is automatically put into operation, the operating data of the equipment under automatic operation is detected, and the actual values ​​of the operating parameters after the commissioning operation can be obtained; based on the recommended values ​​and actual values ​​of the operating parameters corresponding to the commissioning operation, the commissioning effect of the operating parameters can be automatically analyzed, thereby realizing intelligent analysis of the commissioning effect, being more flexible, and greatly improving the reliability of the analysis results.

[0036] In the above and following embodiments of the present application, after analyzing and obtaining the operational effect corresponding to the first operating parameter, the operational effect can be further visualized. For example, a page can be displayed, and at least one operational operation for the first operating parameter can be visually displayed on the page. In response to selecting a target operational operation from the at least one operational operation, detailed operational data corresponding to the target operational operation is displayed.

[0037] Visualization refers to the use of computer graphics and image processing techniques to convert data into graphics or images for display on a screen. For example, analysis results can be displayed through data charts, which may include: column charts (histograms), line charts, pie charts, bar charts, radar charts, funnel charts, data maps, waterfall charts, etc. Figure 2a This figure shows a typical implementation method of using a line chart to display the commissioning effect. Figure 2a As shown, multiple commissioning operations are highlighted on the line chart.

[0038] The target operation can be any operation selected by the user. Optionally, when displaying the operation effect corresponding to the target operation, a floating window can be displayed on the page, and the operation details data corresponding to the target operation can be displayed in the floating window, such as Figure 2a Alternatively, a details page may be displayed, and the commissioning details data corresponding to the target commissioning operation may be displayed on the details page without further illustration.

[0039] Optionally, the execution entity of the above-mentioned and following embodiments of the present application can be implemented as a cloud computing platform. In some scenarios, users can access the cloud computing platform through a browser, and the cloud computing platform can display the operation effect of automatic commissioning through the web page provided by the browser. In other scenarios, the cloud computing platform can send the operation effect to the user's terminal device, such as a mobile phone, tablet computer, computer device, etc. on the user side. The terminal device can display the operation effect through a page provided by an application or plug-in running thereon, which is not limited in this embodiment.

[0040] In some optional embodiments, an optional implementation method for detecting the operating data of the equipment under automatic operation can be implemented by automatically sampling the operating data of the equipment during the automatic operation process. The sampling operation can be implemented based on various sampling devices, such as sensors, and this embodiment does not limit this.

[0041] Optionally, during the automatic commissioning process, the parameter value of the first operating parameter of the device may be sampled at a set sampling frequency; wherein the sampling frequency is greater than the commissioning frequency of the at least one commissioning operation. This ensures that the actual operating data of the device after each commissioning operation is sampled.

[0042] Alternatively, the parameter value of the first operating parameter may be sampled within a set time range after each commissioning operation of the first operating parameter. For example, the parameter value of the first operating parameter may be sampled 3 seconds or 5 seconds after each commissioning operation. The set time range may be determined based on the time interval between two adjacent commissioning operations, and this embodiment does not impose any limitation thereto.

[0043] Based on the above implementation, even when the frequency of automatic commissioning is high, the actual operation data of the equipment can be obtained in a timely manner, automatic analysis of the commissioning effect can be achieved, and the analysis difficulties caused by high-frequency commissioning can be overcome.

[0044] After sampling the parameter value of the first operating parameter, multiple sampling points may be obtained. In some optional embodiments, the multiple sampling points obtained by sampling and the recording nodes corresponding to at least one commissioning operation of the first operating parameter may be optionally merged according to a time correspondence to obtain merged data.

[0045] The recording node corresponding to each commissioning operation is used to record the commissioning time corresponding to the commissioning operation, the identifier of the equipment being commissioned, the identifier of the operating parameter being commissioned, the recommended value of the operating parameter, etc. For example, the recording node corresponding to a commissioning operation may be: at time T, the first coal value of the first boiler is set to N.

[0046] The merging may include: mixing the sampling points and the recording nodes, and rearranging the mixed points in chronological order. That is, the merged data includes the recording nodes and the sampling points arranged in chronological order.

[0047] Next, for any of the at least one commissioning operation, a sampling point sorted after the record node corresponding to the commissioning operation can be determined from the merged data and set as a target sampling point. Then, based on the operating data corresponding to the target sampling point, an actual value corresponding to the commissioning operation can be determined.

[0048] Optionally, the setting order can be the first, the second, or the third, which can be determined according to the sampling interval and the control response time of the equipment, and is not limited in this embodiment. Among them, the control response time of the equipment refers to the time interval for the equipment to operate according to the recommended value after the equipment is put into operation. For example, when the control response time of the equipment is short, after the commissioning operation is performed, the equipment can quickly receive the recommended value and operate according to the recommended value. At this time, if the sampling time is greater than the control response time of the equipment, the operating data corresponding to the first sampling point after the recording node can be used as the actual value corresponding to the commissioning operation.

[0049] A typical merge operation can be as follows Figure 2b As shown, Figure 2b In the example, circles represent recording nodes for the commissioning operation of the first operating parameter, and dots represent sampling points for the actual value of the first operating parameter. By merging multiple recording boundary nodes and sampling points based on the commissioning time corresponding to the commissioning operation and the sampling time corresponding to the sampling point, the temporal relationship between the recording nodes and sampling points can be obtained.

[0050] For example, for recording node A, the first sampling point B after recording node A can be determined from the merged data. Then, the parameter value corresponding to sampling point B is obtained as the actual value of the commissioning operation corresponding to recording node A. Alternatively, the second sampling point C after recording node A can be determined from the merged data. Then, the parameter value corresponding to sampling point C is obtained as the actual value of the commissioning operation corresponding to recording node A.

[0051] Optionally, in some scenarios, the execution entity of the embodiments of the present application is implemented as an electronic device with data sampling and computing functions. In this scenario, the electronic device includes at least two modules: a sampling module, a storage module, and a computing module. The sampling module can sample the parameter values ​​of the operating parameters during the operation of the device and write the sampled data to the storage module. The computing module can obtain the sampled data from the storage module and obtain the actual value of the operating parameter corresponding to each commissioning operation from the sampled data.

[0052] Optionally, in other scenarios, when the execution subject of the embodiment of the present application is a cloud computing platform, the device for sampling the parameter values ​​of the operating parameters of the device can be implemented as a third-party data sampling device (such as a variety of data sensors). The third-party sampling device uploads the sampled parameter values ​​to the cloud computing platform and saves them in a designated database on the cloud computing platform for subsequent analysis. Among them, the designated database can be implemented as a TSDB (Time Series Database), a streaming data processing platform (such as Datahub), or a message queue (such as Kafka), and this embodiment includes but is not limited to this.

[0053] Optionally, the cloud computing platform and the sampling device of the third party can establish a communication connection, and the specific communication connection method can depend on the actual application scenario. In some exemplary embodiments, the server and the sampling device can communicate with each other using a wired communication method or a wireless communication method. Among them, the wireless communication method includes short-range communication methods such as Bluetooth, ZigBee, infrared, WiFi (WIreless-Fidelity, wireless fidelity technology), as well as long-range wireless communication methods such as LORA, and can also include wireless communication methods based on mobile networks. Among them, when connected through a mobile network communication, the network standard of the mobile network can be any one of 2G (GSM), 2.5G (GPRS), 3G (WCDMA, TD-SCDMA, CDMA2000, UTMS), 4G (LTE), 4G+ (LTE+), 5G, WiMax, etc.

[0054] In some optional embodiments, the operation of analyzing the operation effect may include, but is not limited to: analyzing whether manual intervention is included in the automatic operation, analyzing the number of manual interventions, analyzing the reasons for the manual interventions, determining the operating parameters of the manual interventions, etc. The following will provide exemplary explanations of each of these.

[0055] Optionally, a manually intervened commissioning operation can be determined from at least one commissioning operation based on the recommended value corresponding to each commissioning operation of the first operating parameter and the actual value of the first operating parameter during the at least one commissioning operation. According to the definition of manual intervention, after manual intervention in a commissioning operation, the equipment may not operate according to the recommended commissioning value. Based on this, the presence of manual intervention can be analyzed by analyzing the difference between the recommended value corresponding to each commissioning operation and the actual value of the equipment.

[0056] In some scenarios, for any commissioning operation, if the recommended value and the actual value corresponding to the commissioning operation are different, it can be determined that the commissioning operation has been manually intervened.

[0057] In other scenarios, taking into account the accuracy of the sampling equipment, for any commissioning operation, the difference between the recommended value and the actual value of the commissioning operation can be calculated; if the difference is greater than the statistical threshold of the first operating parameter, the commissioning operation is determined to be a commissioning operation with manual intervention. The statistical threshold of the first operating parameter can be an empirical value, and the user can set different statistical thresholds for different operating parameters. For example, based on experience, the statistical threshold corresponding to the temperature parameter can be set to 0.5, and the statistical threshold corresponding to the pressure parameter can be set to 1. This is not limited in this embodiment.

[0058] Optionally, in some scenarios, the statistical threshold corresponding to each operating parameter can be calculated based on historical commissioning records. Taking the first operating parameter as an example, the historical recommended value and historical actual value of the first operating parameter without human intervention can be obtained from the historical commissioning records. Then, based on the historical recommended value and historical actual value, the parameter value fluctuation range of the first operating parameter without human intervention is calculated. The statistical threshold of the first operating parameter is determined based on the fluctuation range of the operating data.

[0059] The operating parameters may include temperature parameters, humidity parameters, pressure parameters, speed parameters, power parameters, etc. In some scenarios, when a sensor is used to detect the operating parameters of a device, the operating parameters may be referred to as sensor points or sensor measurement points.

[0060] For example, if the operating parameter is temperature, historically recommended temperature values ​​and actual operating temperature values ​​can be obtained without human intervention. Based on the difference between the historically recommended and actual operating temperature values, the temperature fluctuation range can be calculated. This temperature fluctuation range is then used as the statistical threshold for the commissioning operation. This is illustrated below using a specific example.

[0061] For example, if a device's temperature parameter is being commissioned, and the difference between the historically recommended temperature value and the actual operating temperature value is 0.05°C without human intervention, 0.05°C can be used as the statistical threshold for the temperature parameter. In other words, if the difference between the recommended and actual values ​​of a temperature parameter for a particular commissioning operation is greater than 0.05°C, it can be considered that the commissioning operation encountered human intervention.

[0062] It's worth noting that in some scenarios, when calculating statistical thresholds based on historical commissioning records, the granularity of these records can be further refined to obtain individual historical commissioning records for each type of equipment. Based on these records, the corresponding statistical thresholds for each type of equipment are calculated. This approach fully considers the responsiveness of different types of equipment to automatic commissioning, improving the accuracy of statistical results.

[0063] Based on the above, optionally, when obtaining the statistical threshold corresponding to the first operating parameter, the type of equipment to which the first operating parameter belongs (i.e., the type of equipment being put into operation) can be obtained. Next, from the historical operation records, a target historical operation record that matches the type of equipment is obtained, and from the target historical operation record, the historical recommended value and historical actual value of the first operating parameter without manual intervention are obtained. Next, based on the historical recommended value and historical actual value, the parameter value floating range of the first operating parameter is calculated, and based on the parameter value floating range, the statistical threshold of the first operating parameter is determined.

[0064] For example, for a blast furnace, if the difference between the historically recommended blast furnace temperature and the actual operating temperature without human intervention is 0.01°C, 0.01°C can be used as the statistical threshold for the blast furnace temperature parameter. For another example, for a sintering furnace, if the difference between the historically recommended sintering furnace temperature and the actual operating temperature without human intervention is 0.03°C, 0.03°C can be used as the statistical threshold for the sintering furnace temperature parameter.

[0065] Based on this, when the commissioning operation is the recommended temperature value for the blast furnace, the difference between the recommended temperature value for the commissioning operation and the actual temperature value of the blast furnace can be obtained. If the absolute value of this difference is greater than 0.01°C, it can be considered that the commissioning operation has encountered human intervention. When the commissioning operation is the recommended temperature value for the sintering furnace, the difference between the recommended temperature value for the commissioning operation and the actual temperature value of the sintering furnace can be obtained. If the absolute value of this difference is greater than 0.03°C, it can be considered that the commissioning operation has encountered human intervention.

[0066] It should be noted that in some scenarios, when analyzing the operational effects of operating parameters, the operational switch values ​​corresponding to the operating parameters can be further obtained. The operational switch value is used to characterize whether one side of the equipment is in an automatic operational state. The operational switch value can be collected by a set acquisition device. Usually, the operational switch value of an operating parameter can be 1 or 0. If the operational switch value is 1, it indicates that the automatic operational function of the operating parameter has been turned on on the equipment side; if the operational switch is 0, it indicates that the automatic operational function of the operating parameter has been turned off on the equipment side. The operation of turning on or off the automatic operation can be performed by the user on the equipment side.

[0067] Continuing with the first operating parameter as an example, when analyzing any commissioning operation corresponding to the first operating parameter, the commissioning switch value of the first operating parameter when executing this commissioning operation can be obtained in advance. Then, based on the commissioning switch value, it is judged whether the equipment has turned on the automatic commissioning function of the first operating parameter when executing this commissioning operation. If the equipment turns on the automatic commissioning function of the first operating parameter, it is possible to continue to judge whether this commissioning operation has been manually intervened based on the recommended value and actual value of this commissioning operation. If the equipment does not turn on the automatic commissioning function of the first operating parameter, this commissioning operation has no statistical significance, and subsequent analysis operations can be discontinued to save computing power.

[0068] Based on the above embodiment, optionally, after analyzing whether at least one commissioning operation of the first operating parameter encountered manual intervention, the number of manual interventions and the manual intervention ratio can be calculated based on the number of commissioning operations with manual intervention. For example, if 3 of 15 commissioning operations of the first operating parameter encountered manual intervention, the manual intervention ratio is 20%.

[0069] Based on the above embodiment, optionally, after determining that a certain commissioning operation has been manually intervened, the reason for the manual intervention corresponding to the commissioning operation can be further analyzed based on the range of the difference between the recommended value and the actual value corresponding to the commissioning operation. Optionally, the range can be a positive range or a negative range. For example, for commissioning operation R, if the difference between its recommended pressure value and the actual pressure value is a positive value, then the corresponding reason for manual intervention can be determined to be: pressure is too high; conversely, if the difference between its recommended pressure value and the actual pressure value is a negative value, then the corresponding reason for manual intervention can be determined to be: pressure is too low.

[0070] It should be understood that environmental conditions may affect the operation of the equipment during operation. For example, when the ambient temperature is high, recommending the D1 temperature for the sintering furnace can meet the sintering requirements without manual intervention. However, when the ambient temperature is low, if the D1 temperature is still recommended for the sintering furnace, it may not meet the sintering requirements and manual intervention may be required.

[0071] Based on this, in order to optimize the algorithm for automatic commissioning, optionally, for commissioning operations with manual intervention, environmental data of the equipment at the time of manual intervention can be further collected to optimize the recommended algorithm for operating parameters based on the environmental data.

[0072] Optionally, the environmental data may include environmental data within the physical space where the equipment is located, such as temperature, humidity, pressure, wind force, etc. within the factory. The environmental data can be acquired by a variety of sensors deployed in the physical space where the equipment is located. Optionally, the environmental data may also include operating data of other equipment related to the equipment. For example, for a certain equipment, its environmental data may include operating data of its upstream equipment and operating data of its downstream equipment, which is not limited in this embodiment. Based on the above, the recommendation algorithm for automatic commissioning can be continuously optimized so that automatic commissioning can better meet production needs.

[0073] Figure 3 A flow chart of a method for analyzing the operation effect of industrial equipment provided by an exemplary embodiment of the present application is shown as follows: Figure 3 As shown, the method includes:

[0074] Step 301: Acquire commissioning values ​​for automatic commissioning of industrial equipment; the commissioning values ​​include recommended values ​​for at least one commissioning operation of a first operating parameter; the industrial equipment belongs to the field of process manufacturing.

[0075] Step 302: Detect operating data of the industrial equipment under the automatic operation, and obtain an actual value of the first operating parameter under the at least one operation from the operating data.

[0076] Step 303: Analyze the operation effect of the first operating parameter according to the recommended values ​​of the first operating parameter in the at least one operation and the actual value of the first operating parameter in the at least one operation.

[0077] Process manufacturing refers to the manufacturing process in which the object being processed continuously passes through a series of processing devices, causing chemical or physical changes in the raw materials to ultimately produce the final product. In process manufacturing, materials are highly variable, and numerous variables constrain the process flow. Therefore, the automated operation of industrial equipment in this field often requires a high frequency of operation.

[0078] Detecting the operating data of industrial equipment during automatic operation can be achieved by sampling the values ​​of the operating parameters of the industrial equipment during automatic operation. The sampling frequency can be flexibly adjusted based on the operation frequency to ensure that the actual values ​​corresponding to each operation are collected. Typically, the sampling frequency can be set to be greater than the operation frequency.

[0079] In process manufacturing scenarios, a higher sampling frequency can be set. Consequently, even with a high frequency of operation, the actual values ​​of the operating parameters during each operation can be accurately obtained. Based on the recommended values ​​and actual values ​​of the operating parameters during operation, the effects of automatic operation can be analyzed more accurately, overcoming the difficulties in analyzing the effects of operation caused by the frequency of operation (especially high frequency) and improving the flexibility of the analysis.

[0080] It should be noted that the execution entity of each step of the method provided in the above embodiment can be the same device, or the method can be executed by different devices. For example, the execution entity of steps 101 to 103 can be device A; for another example, the execution entity of steps 101 and 102 can be device A, and the execution entity of step 103 can be device B; and so on.

[0081] In addition, some of the processes described in the above embodiments and the accompanying drawings include multiple operations that appear in a specific order, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to different types.

[0082] It should be noted that the methods provided in the embodiments of the present application can be used to count the automatic operation effects of various operation objects. For example, in the cement industry, it can be used to count the automatic operation effects of cement rotary kilns, cyclone preheaters, coolers and other equipment. For example, in the steel production industry, it can be used to count the automatic operation effects of blast furnaces, hot blast furnaces, converters, electric furnaces, refining furnaces, continuous casting machines and other equipment. For another example, in the chemical industry, it can be used to count the automatic operation effects of fans, compressors, pumps, separation equipment, electrolyzers, reactors, filters, crushers, centrifuges, rotary kilns, mixers, dryers and other equipment. The following will be combined with Figure 4 , further illustrating the data processing method provided in the embodiments of the present application.

[0083] Assume that at time T1, the cloud computing platform automatically commissioned the recommendation algorithm based on the recommended value, adjusting the "first coal set value" of the cement rotary kiln from 10 to 11. At time T1+1, the APC system received the adjustment instruction and adjusted the "first coal set value" in the APC from 10 to 11. Assume that at time T2, the cloud computing platform's recommendation algorithm recommended adjusting the "first coal set value" from 11 to 12. At time T2+1, the APC system received the adjustment instruction and adjusted the "first coal set value" in the APC from 10 to 11.

[0084] Next, the actual operation data of the cement rotary kiln fed back by the DCS system is obtained, and the top coal value of the cement rotary kiln in the actual operation data is sampled. After obtaining the sampled data, the top coal value of the cement rotary kiln at time T1+1 and the top coal value of the cement rotary kiln at time T2+1 are obtained from the sampled data. Figure 4 As shown in the figure, if the top coal value of the cement rotary kiln is 11 at time T1+1, it can be assumed that the APC accepted the value of 11. If it remains unchanged when the next commissioning operation occurs, it can be recorded that there was no manual intervention in this commissioning. If the top coal value of the cement rotary kiln is 13 at time T2+1, which is not the expected 12, it can be recorded that there was manual intervention in this commissioning.

[0085] In addition to the data processing method described in the aforementioned embodiment, the embodiment of the present application also provides a data processing device.

[0086] Figure 5 FIG. 1 is a structural diagram of a data processing device provided by an exemplary embodiment of the present application. Figure 5 As shown, the device includes:

[0087] The data acquisition module 501 is used to: obtain the commissioning value adopted for automatic commissioning of the equipment; the commissioning value includes the recommended value of each of the at least one commissioning operation of the first operating parameter; and detect the operating data of the equipment under the automatic commissioning, and obtain the actual value of the first operating parameter under the at least one commissioning operation from the operating data; the analysis module 502 is used to: analyze the commissioning effect of the first operating parameter based on the recommended value of each of the at least one commissioning operation of the first operating parameter and the actual value of the first operating parameter under the at least one commissioning operation.

[0088] Further optionally, a result output module 503 is also included, which is specifically used to: visually display the at least one commissioning operation on the page; in response to the selection operation of the target commissioning operation in the at least one commissioning operation, display the commissioning detail data corresponding to the target commissioning operation.

[0089] Further optionally, when detecting the operating data of the equipment under the automatic commissioning, the data acquisition module 501 is specifically used to: sample the parameter value of the first operating parameter according to the set sampling frequency during the automatic commissioning; the sampling frequency is greater than the commissioning frequency of the at least one commissioning operation; or, sample the parameter value of the first operating parameter within a set time range after each execution of the commissioning operation of the first operating parameter.

[0090] Further optionally, when the data acquisition module 501 obtains the actual value of the first operating parameter under the at least one commissioning operation from the operating data, it is specifically used to: obtain multiple sampling points obtained by sampling the parameter value of the first operating parameter; merge the multiple sampling points and the record nodes corresponding to the at least one commissioning operation according to the time correspondence to obtain merged data; for any commissioning operation in the at least one commissioning operation, determine from the merged data the record node corresponding to the commissioning operation and set the sorted sampling points as the target sampling points; determine the actual value corresponding to the commissioning operation according to the parameter value corresponding to the target sampling point.

[0091] Further optionally, when analyzing the operation effect of the first operating parameter based on the recommended values ​​of the at least one operation of the first operating parameter and the actual values ​​of the at least one operation of the first operating parameter, the analysis module 502 is specifically used to: determine the operation operation with manual intervention from the at least one operation operation based on the recommended values ​​of the at least one operation of the first operating parameter and the actual values ​​of the at least one operation of the first operating parameter; and analyze the number of manual interventions in the at least one operation operation based on the operation operation with manual intervention.

[0092] Further optionally, when the analysis module 502 determines the manually intervened operation from the at least one commissioning operation based on the recommended value of the at least one commissioning operation of the first operating parameter and the actual value of the first operating parameter under the at least one commissioning operation, it is specifically used to: calculate the difference between the recommended value and the actual value of the commissioning operation for any commissioning operation in the at least one commissioning operation; if the difference is greater than the statistical threshold of the first operating parameter, determine that the commissioning operation is a manually intervened commissioning operation.

[0093] Further optionally, it also includes: a threshold maintenance module 504, which is specifically used to: obtain the historical recommended value and historical actual value of the first operating parameter when there is no human intervention from the historical commissioning records; calculate the parameter value floating range of the first operating parameter when there is no human intervention based on the historical recommended value and historical actual value; determine the statistical threshold of the first operating parameter based on the parameter value floating range.

[0094] Further optionally, when the threshold maintenance module 504 obtains the historical recommended value and the historical actual value of the first operating parameter without manual intervention from the historical commissioning records, it is specifically used to: obtain the target historical commissioning records that match the type of the equipment from the historical commissioning records; and obtain the historical recommended value and the historical actual value of the first operating parameter without manual intervention from the target historical commissioning records.

[0095] Further optionally, the analysis module 502 is further configured to: if the commissioning operation is a commissioning operation requiring manual intervention, analyze the cause of the manual intervention corresponding to the commissioning operation according to the numerical range to which the difference between the recommended value and the actual value of the commissioning operation belongs.

[0096] Further optionally, the analysis module 502 is further configured to: for the commissioning operation with manual intervention, collect environmental data of the equipment at the time of manual intervention, so as to optimize the recommendation algorithm for the first operating parameter according to the environmental data.

[0097] In this embodiment, when the equipment is automatically put into operation, the operating data of the equipment under automatic operation is detected, and the actual values ​​of the operating parameters after the commissioning operation can be obtained; based on the recommended values ​​and actual values ​​of the operating parameters corresponding to the commissioning operation, the commissioning effect of the operating parameters can be automatically analyzed, thereby realizing intelligent analysis of the commissioning effect, being more flexible, and greatly improving the reliability of the analysis results.

[0098] In some scenarios, Figure 5 The device shown can also be used to perform a method for analyzing the operational effects of industrial equipment. The data acquisition module 501 is configured to: obtain operational values ​​for automatic operational operation of industrial equipment; the operational values ​​include recommended values ​​for at least one operational operation of a first operating parameter; the industrial equipment belongs to the field of process manufacturing; detect operational data of the industrial equipment under the automatic operational operation, and obtain, from the operational data, the actual value of the first operating parameter under the at least one operational operation; and the analysis module 502 is configured to: analyze the operational effects of the automatic operation based on the recommended values ​​for the at least one operational operation and the actual values ​​corresponding to the at least one operational operation.

[0099] Figure 6 is a structural diagram of a data processing device provided by an exemplary embodiment of the present application, such as Figure 6 As shown, the data processing device includes: a memory 601 , a processor 602 and a display component 603 .

[0100] Memory 601 is used to store computer programs and can be configured to store various other data to support operations on the data processing device. Examples of such data include instructions for any application or method operating on the data processing device, contact data, phone book data, messages, images, videos, etc.

[0101] Among them, the memory 601 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0102] The processor 602 is coupled to the memory 601 and is used to execute the computer program in the memory 601, so as to: obtain the commissioning value adopted for automatic commissioning of the equipment; the commissioning value includes the recommended value of at least one commissioning operation of the first operating parameter; and detect the operating data of the equipment under the automatic commissioning, and obtain the actual value of the first operating parameter under the at least one commissioning operation from the operating data; analyze the commissioning effect of the first operating parameter according to the recommended value of the at least one commissioning operation of the first operating parameter and the actual value of the first operating parameter under the at least one commissioning operation.

[0103] Further optionally, the data processing device further includes: a display component 603. The processor 602 is further configured to: visually display the at least one commissioning operation on a page via the display component 603; and in response to selecting a target commissioning operation from the at least one commissioning operation, display commissioning detail data corresponding to the target commissioning operation.

[0104] Further optionally, when detecting the operating data of the equipment under the automatic commissioning, the processor 602 is specifically used to: sample the parameter value of the first operating parameter according to a set sampling frequency during the automatic commissioning process; the sampling frequency is greater than the commissioning frequency of the at least one commissioning operation; or, sample the parameter value of the first operating parameter within a set time range after each execution of the commissioning operation of the first operating parameter.

[0105] Further optionally, when the processor 602 obtains the actual value of the first operating parameter under the at least one commissioning operation from the operating data, it is specifically used to: obtain multiple sampling points obtained by sampling the parameter value of the first operating parameter; merge the multiple sampling points and the record nodes corresponding to the at least one commissioning operation according to the time correspondence to obtain merged data; for any commissioning operation in the at least one commissioning operation, determine from the merged data the record node corresponding to the commissioning operation and then set the sorted sampling points as the target sampling points; determine the actual value corresponding to the commissioning operation according to the parameter value corresponding to the target sampling point.

[0106] Further optionally, when the processor 602 analyzes the operation effect of the first operating parameter based on the recommended values ​​of the at least one operation of the first operating parameter and the actual values ​​of the at least one operation of the first operating parameter, it is specifically used to: determine the operation operation with manual intervention from the at least one operation operation based on the recommended values ​​of the at least one operation of the first operating parameter and the actual values ​​of the at least one operation of the first operating parameter; and analyze the number of manual interventions in the at least one operation operation based on the operation operation with manual intervention.

[0107] Further optionally, when the processor 602 determines the commissioning operation subject to manual intervention from the at least one commissioning operation based on the recommended value of the at least one commissioning operation of the first operating parameter and the actual value of the first operating parameter under the at least one commissioning operation, it is specifically used to: calculate the difference between the recommended value and the actual value of the commissioning operation for any commissioning operation in the at least one commissioning operation; if the difference is greater than the statistical threshold of the first operating parameter, determine that the commissioning operation is a commissioning operation subject to manual intervention.

[0108] Further optionally, the processor 602 is also used to: obtain the historical recommended value and the historical actual value of the first operating parameter when there is no human intervention from the historical commissioning records; calculate the parameter value floating range of the first operating parameter when there is no human intervention based on the historical recommended value and the historical actual value; and determine the statistical threshold of the first operating parameter based on the parameter value floating range.

[0109] Further optionally, when the processor 602 obtains the historical recommended value and the historical actual value of the first operating parameter without manual intervention from the historical commissioning records, it is specifically used to: obtain the target historical commissioning records that match the type of the equipment from the historical commissioning records; and obtain the historical recommended value and the historical actual value of the first operating parameter without manual intervention from the target historical commissioning records.

[0110] Further optionally, the processor 602 is further configured to: if the commissioning operation is a commissioning operation requiring manual intervention, analyze the cause of the manual intervention corresponding to the commissioning operation according to the numerical range to which the difference between the recommended value and the actual value of the commissioning operation belongs.

[0111] Further optionally, the processor 602 is further configured to: for the commissioning operation with manual intervention, collect environmental data of the equipment at the time of manual intervention, so as to optimize the recommendation algorithm of the first operating parameter according to the environmental data.

[0112] Further, if Figure 6 As shown, the data processing device further includes: a communication component 604, a power supply component 605 and other components. Figure 6 Only some components are shown schematically, which does not mean that the data processing device only includes Figure 6 Components shown.

[0113] Among them, the communication component 604 is configured to facilitate wired or wireless communication between the device where the communication component is located and other devices. The device where the communication component is located can access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G or 5G, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component can be implemented based on near field communication (NFC) technology, radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0114] The power supply assembly 605 provides power to various components of the device in which the power supply assembly is located. The power supply assembly may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device in which the power supply assembly is located.

[0115] In this embodiment, when the equipment is automatically put into operation, the operating data of the equipment under automatic operation is detected, and the actual values ​​of the operating parameters after the commissioning operation can be obtained; based on the recommended values ​​and actual values ​​of the operating parameters corresponding to the commissioning operation, the commissioning effect of the operating parameters can be automatically analyzed, thereby realizing intelligent analysis of the commissioning effect, being more flexible, and greatly improving the reliability of the analysis results.

[0116] In some scenarios, Figure 6The device shown can also be used to execute a method for analyzing the commissioning effect of industrial equipment. Specifically, the processor 602 is used to: obtain the commissioning value used for automatic commissioning of industrial equipment; the commissioning value includes the recommended value of at least one commissioning operation of the first operating parameter; the industrial equipment belongs to the field of process manufacturing; detect the operating data of the industrial equipment under the automatic commissioning, and obtain the actual value of the first operating parameter under the at least one commissioning operation from the operating data; analyze the commissioning effect of the automatic commissioning according to the recommended value of each of the at least one commissioning operation and the actual value corresponding to each of the at least one commissioning operation.

[0117] Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when executed, can implement the steps that can be executed by a data processing device in the above method embodiment.

[0118] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0119] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0120] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0121] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0122] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0123] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0124] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0125] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0126] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for analyzing the operation effect of industrial equipment, characterized in that: include: Obtaining commissioning values ​​for automatically commissioning industrial equipment; the commissioning values ​​include recommended values ​​for at least one commissioning operation of a first operating parameter; the industrial equipment belongs to the field of process manufacturing; the recommended values ​​for each commissioning operation are obtained by using a set recommendation algorithm to predict parameter values ​​required for the industrial equipment at a future time based on data related to the industrial equipment obtained in real time; detecting operating data of the industrial equipment under the automatic commissioning, and obtaining an actual value of the first operating parameter under the at least one commissioning operation from the operating data; Analyzing the operation effect of the first operating parameter according to the recommended value of the at least one operation operation of the first operating parameter and the actual value of the first operating parameter under the at least one operation operation; wherein analyzing the operation effect of the first operating parameter includes: analyzing whether the automatic operation process of the first operating parameter includes manual intervention; It also includes: if the automatic commissioning process of the first operating parameter includes manual intervention, for the commissioning operation with manual intervention, collecting environmental data of the equipment at the time of manual intervention, so as to optimize the recommendation algorithm of the first operating parameter according to the environmental data.

2. A data processing method, characterized in that: include: Obtaining commissioning values ​​for automatically commissioning the equipment; the commissioning values ​​include recommended values ​​for at least one commissioning operation of the first operating parameter; The recommended values ​​for any commissioning operation are obtained by using a set recommendation algorithm to predict the parameter values ​​required for the equipment at a future time based on the data related to the equipment obtained in real time; detecting operating data of the device under the automatic commissioning, and obtaining an actual value of the first operating parameter under the at least one commissioning operation from the operating data; Analyzing the operation effect of the first operating parameter according to the recommended value of the at least one operation operation of the first operating parameter and the actual value of the first operating parameter under the at least one operation operation; wherein analyzing the operation effect of the first operating parameter includes: analyzing whether the automatic operation process of the first operating parameter includes manual intervention; It also includes: if the automatic commissioning process of the first operating parameter includes manual intervention, for the commissioning operation with manual intervention, collecting environmental data of the equipment at the time of manual intervention, so as to optimize the recommendation algorithm of the first operating parameter according to the environmental data.

3. The method according to claim 2, characterized in that Also includes: Visually displaying the at least one commissioning operation on the page; In response to a selection operation of a target commissioning operation in the at least one commissioning operation, commissioning detail data corresponding to the target commissioning operation is displayed.

4. The method according to claim 2, characterized in that Detecting the operating data of the equipment under the automatic operation includes: During the automatic operation, the parameter value of the first operating parameter is sampled according to a set sampling frequency; the sampling frequency is greater than the operation frequency of the at least one operation operation; or The parameter value of the first operating parameter is sampled within a set time range after each execution of the commissioning operation of the first operating parameter.

5. The method according to claim 4, characterized in that Obtaining an actual value of the first operating parameter under the at least one commissioning operation from the operating data includes: Acquire a plurality of sampling points obtained by sampling the parameter value of the first operating parameter; Merging the plurality of sampling points and the recording nodes corresponding to the at least one commissioning operation according to a time correspondence to obtain merged data; For any one of the at least one commissioning operations, determining from the merged data a sampling point that is sorted after a record node corresponding to the commissioning operation and setting the sampling point as a target sampling point; According to the parameter value corresponding to the target sampling point, the actual value corresponding to the commissioning operation is determined.

6. The method according to claim 2, characterized in that Analyzing the operation effect of the first operating parameter according to the recommended value of the first operating parameter in the at least one operation and the actual value of the first operating parameter in the at least one operation, including: determining a manually-intervention operation from the at least one operation according to the recommended value of the first operating parameter for each of the at least one operation and the actual value of the first operating parameter during the at least one operation; According to the commissioning operation with manual intervention, the number of manual interventions in the at least one commissioning operation is analyzed.

7. The method according to claim 6, characterized in that Determining a manually intervened operation from the at least one operation according to the recommended value of the first operating parameter for each of the at least one operation operations and the actual value of the first operating parameter during the at least one operation operation includes: For any commissioning operation in the at least one commissioning operation, calculating a difference between a recommended value and an actual value of the commissioning operation; If the difference is greater than the statistical threshold of the first operating parameter, it is determined that the commissioning operation is a commissioning operation with manual intervention.

8. The method according to claim 7, characterized in that Also includes: Obtaining, from historical commissioning records, historical recommended values ​​and historical actual values ​​of the first operating parameter without manual intervention; Calculating a parameter value floating range of the first operating parameter without manual intervention based on the historical recommended value and the historical actual value; A statistical threshold of the first operating parameter is determined according to the parameter value floating range.

9. The method according to claim 8, characterized in that Obtaining historical recommended values ​​and historical actual values ​​of the first operating parameter without manual intervention from historical commissioning records includes: Acquire a target historical operation record matching the type of the device from the historical operation records; From the target historical operation records, historical recommended values ​​and historical actual values ​​of the first operating parameter without human intervention are obtained.

10. The method according to claim 7, characterized in that Also includes: If the commissioning operation is a commissioning operation requiring manual intervention, the manual intervention reason corresponding to the commissioning operation is analyzed according to the numerical range to which the difference between the recommended value and the actual value of the commissioning operation belongs.

11. A data processing device, characterized in that: include: A data acquisition module is used to: obtain an operation value used for automatically commissioning the equipment; the operation value includes a recommended value for at least one commissioning operation of the first operating parameter; detecting operating data of the equipment under the automatic commissioning, and obtaining, from the operating data, an actual value of the first operating parameter under the at least one commissioning operation; the recommended value for any commissioning operation is obtained by using a set recommendation algorithm to predict the parameter value required by the industrial equipment at a future time based on real-time data related to the equipment; an analysis module, configured to analyze, based on the recommended values ​​of the at least one commissioning operation of the first operating parameter and the actual value of the first operating parameter during the at least one commissioning operation, an operation effect of the first operating parameter; wherein analyzing the operation effect of the first operating parameter includes analyzing whether the automatic commissioning process of the first operating parameter includes manual intervention; The analysis module is also used to: if the automatic commissioning process of the first operating parameter includes manual intervention, collect environmental data of the equipment at the time of manual intervention for the commissioning operation with manual intervention, so as to optimize the recommendation algorithm of the first operating parameter based on the environmental data.

12. A data processing device, characterized in that: include: memory, processors, and communication components; The memory is used to store one or more computer instructions; The processor is configured to execute the one or more computer instructions to perform the steps of the method according to any one of claims 1 to 10.

13. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 can be implemented.

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