An airport flight area water surface floating photovoltaic power generation system test method and platform

Abstract

The application provides a kind of airport flight area water surface floating photovoltaic power generation system test method and platform, it is related to airport flight area water surface floating photovoltaic power generation system test technical field, obtains system information, divides preset function area information and its preset running kind information;Corresponding kind test and corresponding area test are carried out, and test determination result is obtained;Actual operation monitoring is carried out, and each preset function area and each preset running kind thereof are analyzed, and kind running determination result and area running determination result are obtained;Difference analysis is carried out on the kind and area of the same preset function area and the same preset running kind thereof respectively, and difference analysis result of kind and operation is obtained, and then corresponding early warning is carried out, the application divides preset function area and preset running kind, realizes the fine monitoring and analysis of system performance, discovers potential problem in time, improves the stability and reliability of system, reduces failure rate and maintenance cost.

Description

TECHNICAL FIELD

[0001] The application provides an airport flight area water floating photovoltaic power generation system test method and platform, and relates to the technical field of power generation system testing, in particular to the technical field of airport flight area water floating photovoltaic power generation system testing. BACKGROUND

[0002] As an important hub of air traffic, the airport flight area has extremely high requirements for safety performance and operational stability. The performance monitoring, fault early warning, and optimization management of the water floating photovoltaic power generation system in actual operation have become a technical problem that needs to be solved urgently.

[0003] Traditionally, the performance monitoring of photovoltaic power generation systems mainly relies on regular inspection and manual recording. This method is not only time-consuming and labor-intensive, but also difficult to discover potential problems in a timely and accurate manner. In addition, for the special application scenario of the airport flight area, the water floating photovoltaic power generation system faces complex and variable natural environments and strict aviation safety standards. Its performance monitoring and early warning mechanism needs to be more intelligent and refined. Existing photovoltaic power generation system performance monitoring technologies mostly stay at the monitoring level of single devices or components, lacking comprehensive evaluation of the overall performance of the system and the performance of the region. At the same time, these technologies often focus on diagnosis and handling after the occurrence of faults, ignoring early warning and prevention before the occurrence of faults, resulting in high cost of fault discovery and repair, and possibly causing adverse effects on the normal operation of the airport flight area. SUMMARY

[0004] The application provides an airport flight area water floating photovoltaic power generation system test method and platform to solve the above problems:

[0005] The application provides an airport flight area water floating photovoltaic power generation system test method and platform, the method comprising:

[0006] S1, obtaining the water floating photovoltaic power generation system information of the airport flight area, dividing the preset functional area information and the preset running type information thereof, and extracting the regional type information;

[0007] S2, performing corresponding type testing and corresponding regional testing on each preset running type of each preset functional area to obtain type testing determination results and regional testing determination results;

[0008] S3, monitoring the actual running of each preset functional area and each preset running type thereof, performing running analysis on each preset functional area and each preset running type thereof according to the monitoring data of the actual running to obtain type running determination results and regional running determination results;

[0009] S4, difference analysis of the same preset function area and its same preset running type and area respectively, obtaining difference analysis results of the type and running, and then corresponding early warning.

[0010] Further, the S1 comprises:

[0011] Obtaining water surface floating photovoltaic power generation system information of the airport flight area, classifying the water surface floating photovoltaic power generation system information according to preset function area types, obtaining system area information of multiple preset function areas;

[0012] Classifying the system area information according to preset running types, obtaining running type information of multiple preset running types;

[0013] Preprocessing the system area information and the running type information, obtaining preprocessed system area information and running type information;

[0014] Packing and extracting each running type information of each system area information, obtaining area type information.

[0015] Further, the S2 comprises:

[0016] Setting the corresponding type test parameters of the preset running type for each preset function area and each preset running type;

[0017] Obtaining type test result data corresponding to the corresponding type test parameters;

[0018] Calculating the type test coefficient of the corresponding preset running type according to the type test result data;

[0019] Comparing the type test coefficient with a preset type test threshold, obtaining a type test analysis result;

[0020] According to the type test analysis result, the corresponding preset running type is tested and analyzed, and a type test determination result is obtained;

[0021] According to each type test coefficient of each preset function area and each preset running type, calculating a region test coefficient of each region;

[0022] Comparing the region test coefficient with a preset region test threshold, obtaining a region test analysis result;

[0023] According to the region test analysis result, the corresponding preset function area is tested and analyzed, and a region test determination result is obtained.

[0024] Further, the S3 comprises:

[0025] monitoring actual operation of the corresponding type for each preset operation type of each preset function area;

[0026] acquiring type operation data of the actual operation;

[0027] calculating a type operation coefficient of the corresponding preset operation type according to the type operation data;

[0028] comparing the type operation coefficient with a preset type operation threshold to obtain a type operation analysis result;

[0029] performing operation analysis and determination on the corresponding preset operation type according to the type operation analysis result to obtain a type operation determination result;

[0030] calculating a region operation coefficient of each region according to each type operation coefficient of each preset operation type of each preset function area;

[0031] comparing the region operation coefficient with a preset region operation threshold to obtain a region operation analysis result;

[0032] performing operation analysis and determination on the corresponding preset function area according to the region operation analysis result to obtain a region operation determination result.

[0033] Further, the S4 comprises:

[0034] calculating a type test operation difference value by difference calculation of the type operation coefficient and the type test coefficient of the same preset operation type of the same preset function area;

[0035] comparing the type test operation difference value with a preset type difference threshold to obtain a type difference comparison result;

[0036] performing deviation determination on the type test operation according to the type difference comparison result to obtain a type deviation determination result;

[0037] calculating a region test operation difference value by difference calculation of the region operation coefficient and the region test coefficient of the same preset function area;

[0038] comparing the region test operation difference value with a preset region difference threshold to obtain a region difference comparison result;

[0039] performing test abnormality early warning on the corresponding type and the corresponding region according to the type difference comparison result and the region difference comparison result.

[0040] Further, the test platform comprises:

[0041] The monitoring and dividing module is configured to acquire water surface floating photovoltaic power generation system information of an airport flight area, divide preset function area information and preset operation type information thereof, and extract area type information.

[0042] The test analysis module is configured to perform corresponding type test and corresponding area test on each preset operation type of each preset function area, and obtain type test determination result and area test determination result.

[0043] The operation analysis module is configured to monitor actual operation of each preset function area and each preset operation type thereof, perform operation analysis on each preset function area and each preset operation type thereof according to monitoring data of the actual operation, and obtain type operation determination result and area operation determination result.

[0044] The deviation early warning module is configured to perform difference analysis on type and area of the same preset function area and the same preset operation type thereof, obtain difference analysis result of the type and the area, and then perform corresponding early warning.

[0045] Further, the monitoring and dividing module comprises:

[0046] The area dividing module is configured to acquire water surface floating photovoltaic power generation system information of an airport flight area, classify the water surface floating photovoltaic power generation system information according to preset function area type, and acquire system area information of multiple preset function areas.

[0047] The type dividing module is configured to classify the system area information according to preset operation type, and obtain operation type information of multiple preset operation types.

[0048] The preprocessing module is configured to pre-process the system area information and the operation type information, and obtain pre-processed system area information and operation type information.

[0049] The packaging module is configured to package and extract each operation type information of each system area information, and obtain area type information.

[0050] Further, the test analysis module comprises:

[0051] The type test module is configured to set corresponding type test parameters of the preset operation type for each preset operation type of each preset function area.

[0052] The type test result data corresponding to the corresponding type test parameters is acquired.

[0053] The type test calculation module is configured to calculate type test coefficients of the corresponding preset operation type according to the type test result data.

[0054] The category test coefficient is compared with a preset category test threshold to obtain a category test analysis result;

[0055] A category determination module is configured to determine the corresponding preset operation category according to the category test analysis result to obtain a category test determination result.

[0056] A region test calculation module is configured to calculate a region test coefficient of each region according to each category test coefficient of each preset operation category of each preset functional region.

[0057] The region test coefficient is compared with a preset region test threshold to obtain a region test analysis result.

[0058] A region determination module is configured to determine the corresponding preset functional region according to the region test analysis result to obtain a region test determination result.

[0059] Further, the operation analysis module comprises:

[0060] A category operation monitoring module is configured to monitor the actual operation of each preset operation category of each preset functional region.

[0061] Category operation data of the actual operation are obtained.

[0062] A category operation calculation module is configured to calculate a category operation coefficient of the corresponding preset operation category according to the category operation data.

[0063] The category operation coefficient is compared with a preset category operation threshold to obtain a category operation analysis result.

[0064] A category operation determination module is configured to determine the corresponding preset operation category according to the category operation analysis result to obtain a category operation determination result.

[0065] A region operation calculation module is configured to calculate a region operation coefficient of each region according to each category operation coefficient of each preset operation category of each preset functional region.

[0066] The region operation coefficient is compared with a preset region operation threshold to obtain a region operation analysis result.

[0067] A region operation determination module is configured to determine the corresponding preset functional region according to the region operation analysis result to obtain a region operation determination result.

[0068] Further, the deviation early warning module comprises:

[0069] The difference calculation module is configured to calculate the difference between the category operation coefficient and the category test coefficient of the same preset operation category in the same preset function area, and obtain a category test operation difference value.

[0070] The deviation determination module is configured to compare the category test operation difference value with a preset category difference threshold value, and obtain a category difference comparison result.

[0071] The deviation determination module is configured to compare the category test operation difference value with a preset category difference threshold value, and obtain a category difference comparison result.

[0072] The difference calculation module is configured to calculate the difference between the category operation coefficient and the category test coefficient of the same preset operation category in the same preset function area, and obtain a category test operation difference value.

[0073] The abnormality early warning module is configured to compare the region test operation difference value with a preset region difference threshold value, and obtain a region difference comparison result.

[0074] The abnormality early warning module is configured to compare the region test operation difference value with a preset region difference threshold value, and obtain a region difference comparison result.

[0075] The present application has the following advantages: through the fine division of function areas and operation categories, as well as targeted testing and monitoring, the bottlenecks and problems in the system can be found and solved in a timely manner, thereby improving the operation efficiency of the entire photovoltaic power generation system. Through testing and monitoring of different regions of the system, potential faults and safety hazards in the system can be found and repaired in a timely manner, enhancing the stability and safety of the system. According to the test and monitoring results, resources (such as maintenance personnel, spare parts, etc.) can be more reasonably allocated, maintenance plans and scheduling strategies can be optimized, and operation and maintenance costs can be reduced. Through difference analysis and early warning mechanism, early detection and early warning of system abnormalities can be realized, providing timely and accurate information support for decision-makers, and improving emergency response speed and disposal capacity. BRIEF DESCRIPTION OF DRAWINGS

[0076] Figure 1 It is a kind of airport flight area water surface floating photovoltaic power generation system test method schematic diagram;

[0077] Figure 2 It is a kind of airport flight area water surface floating photovoltaic power generation system test system schematic diagram. DETAILED DESCRIPTION

[0078] The preferred embodiments of the present application will be described below with reference to the accompanying drawings, and it should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and not to limit the present application.

[0079] In one embodiment of the present application, the present application proposes a kind of airport flight area water surface floating photovoltaic power generation system test method and platform, the method comprises:

[0080] S1, obtaining water surface floating photovoltaic power generation system information of an airport flight area, dividing preset function area information and its preset operation type information, and extracting area type information;

[0081] S2, performing corresponding type testing and corresponding area testing on each preset operation type of each preset function area, to obtain type testing determination results and area testing determination results;

[0082] S3, monitoring actual operation of each preset function area and each preset operation type thereof, performing operation analysis on each preset function area and each preset operation type thereof according to monitoring data of actual operation, to obtain type operation determination results and area operation determination results;

[0083] S4, performing difference analysis on the type and area of the same preset function area and the same preset operation type, obtaining difference analysis results of the type and operation, and then performing corresponding early warning.

[0084] The working principle of the above technical solution is as follows: detailed information of the water surface floating photovoltaic power generation system in the airport flight area is obtained through data collection means (such as sensors, database queries, etc.), including its layout, capacity, configuration, etc. According to the layout and functional requirements of the system, the water surface floating photovoltaic power generation system is divided into multiple preset function areas, such as power generation area, floating support area, etc. For each preset function area, according to its operation characteristics and requirements, it is further divided into different preset operation types, such as power generation mode, storage power mode, power conversion mode, etc. From the above division, the information of each function area and its corresponding operation type is extracted. Corresponding type testing and corresponding area testing are performed on each preset operation type of each preset function area. This includes performance testing (such as power generation efficiency, stability), safety testing (such as short circuit protection, overload protection), etc., to obtain type testing determination results and area testing determination results. In actual operation, each preset function area and each preset operation type thereof are monitored in real time, and operation data (such as power generation capacity, failure rate, maintenance records, etc.) are collected. According to these data, operation analysis is performed on each preset function area and each preset operation type thereof, to obtain type operation determination results and area operation determination results. Difference analysis is performed on the type and area of the same preset function area and the same preset operation type. This includes comparing the performance difference, failure rate difference, etc. of different areas or types under the same conditions, to obtain difference analysis results of the type and operation. According to the difference analysis results, if the performance or operation status of a certain preset function area or preset operation type deviates significantly from the normal range, the early warning mechanism is triggered, prompting relevant personnel to take timely measures for intervention or adjustment.

[0085] The technical effects of the above technical solutions are: through the division of fine functional areas and operation categories, as well as targeted testing and monitoring, bottlenecks and problems in the system can be found and solved in a timely manner, thereby improving the operation efficiency of the entire photovoltaic power generation system. Through regular testing and monitoring, potential faults and safety hazards in the system can be found and repaired in a timely manner, thereby enhancing the stability and safety of the system. According to the testing and monitoring results, resources (such as maintenance personnel, spare parts, etc.) can be more reasonably allocated, maintenance plans and scheduling strategies can be optimized, and operation and maintenance costs can be reduced. Through difference analysis and early warning mechanisms, early detection and early warning of system abnormal conditions can be achieved, timely and accurate information support can be provided for decision-makers, and emergency response speed and disposal capacity can be improved.

[0086] In one embodiment of the present application, the S1 comprises:

[0087] Obtain water surface floating photovoltaic power generation system information of an airport flight area, classify the water surface floating photovoltaic power generation system information according to a preset functional area category, and obtain system area information of a plurality of preset functional areas;

[0088] Classify the system area information according to a preset operation category, and obtain operation category information of a plurality of preset operation categories;

[0089] Preprocess the system area information and the operation category information, and obtain preprocessed system area information and operation category information;

[0090] Pack and extract each operation category information of each system area information, and obtain area category information.

[0091] The working principle of the above technical solution is that the detailed information of the water surface floating photovoltaic power generation system in the airport flight area is comprehensively obtained through data collection means (such as sensor network, remote monitoring system, etc.), including geographic location, installed capacity, equipment state, power generation efficiency, etc. According to the functional layout and design requirements of the system, the water surface floating photovoltaic power generation system is divided into multiple preset functional areas, such as high-efficiency power generation area, maintenance convenient area, safety isolation area, etc. Information extraction is performed on each functional area to form system area information. Further according to the operation mode and demand of the system, the system area information of each preset functional area is classified according to the preset operation type, such as daytime high-efficiency power generation mode, night low-power consumption mode, emergency standby mode, etc. In this way, the different operation type information under each functional area is extracted separately to form operation type information. Preprocessing system area information and operation type information: preprocessing the extracted system area information and operation type information, including data cleaning (removing redundant and error data), data formatting (unifying data format), data normalization (converting data to unified dimension), etc. Packaged extraction of each operation type information of each system area information: integrating the preprocessed system area information and operation type information, packaging and extracting according to each operation type under each system area to form area type information. These information contains the detailed state and data of each functional area under different operation types.

[0092] The technical effect of the above technical solution is that by classifying and preprocessing the information of the water surface floating photovoltaic power generation system in the airport flight area, the utilization rate and accuracy of the information are improved. By dividing the preset functional areas and operation types, the fine management and optimization of the system are realized. This helps the system administrator better understand the running state and performance of the system and timely discover and solve potential problems. The preprocessed system area information and operation type information are more standardized and unified. This helps to discover the rules and trends of system operation. By packaging and extracting the area type information, comprehensive and detailed data support is provided for decision makers. This helps decision makers better understand the actual situation of the system, quickly make decisions, and improve decision efficiency and accuracy.

[0093] In one embodiment of the present application, the S2 comprises:

[0094] A corresponding type test parameter of the preset operation type is set for each preset operation type of each preset functional area;

[0095] Obtain the type test result data corresponding to the corresponding type test parameter;

[0096] Calculate the type test coefficient of the corresponding preset operation type according to the type test result data;

[0097] The calculation formula of the type test coefficient is:

[0098]

[0099] wherein ZC is a category test coefficient, q is a preset number of functional areas, b is a preset number of category test indexes, B sia is actual data of the i th area of the category for the a th test index, B yia is preset data of the i th area of the category for the a th test index, Z q is a preset weight of the category; the test indexes include each category of test purposes.

[0100] The category test coefficient is compared with a preset category test threshold to obtain a category test analysis result.

[0101] According to the category test analysis result, a test analysis determination is made on the corresponding preset running category to obtain a category test determination result.

[0102] When the category test coefficient is greater than the preset category test threshold, it is determined that the category test is qualified, otherwise it is not qualified.

[0103] According to each category test coefficient of each preset running category of each preset functional area, a region test coefficient of each area is calculated.

[0104] The calculation formula of the region test coefficient is:

[0105]

[0106] wherein QC is a region test coefficient, e is a preset total number of running categories in the region, ZC so is a category test coefficient of the o th preset running category in the region, ZC yo is a category test preset coefficient of the o th preset running category in the region, U q is a preset weight of the region.

[0107] The region test coefficient is compared with a preset region test threshold to obtain a region test analysis result.

[0108] According to the region test analysis result, a test analysis determination is made on the corresponding preset functional area to obtain a region test determination result.

[0109] When the region test coefficient is greater than the preset region test threshold, it is determined that the region test is qualified, otherwise it is not qualified.

[0110] The working principle of the above technical solution is: for each preset running category of each preset functional area, according to the design requirements, performance standards and test requirements of the system, set the corresponding category test parameters. These parameters include test conditions (such as light intensity, temperature, humidity, etc.), test time, test method, test index, etc. Under the set test conditions, the corresponding test method is executed to obtain the category test result data under the corresponding category test parameters. These data include power generation, efficiency, stability index, failure rate, etc. According to the obtained category test result data, the category test coefficient of the corresponding preset running category is calculated. This coefficient reflects the performance of the running category under the current test conditions. Compare the calculated category test coefficient with the preset category test threshold to analyze whether the running category meets the expected performance standard. According to the comparison result, obtain the category test analysis result, and make test analysis judgment on the corresponding preset running category, and obtain the category test judgment result (such as qualified, unqualified, need further optimization, etc.). For each preset functional area, according to the category test coefficients of all preset running categories in the area, calculate the area test coefficient of the area. This coefficient reflects the overall performance of the area. Compare the calculated area test coefficient with the preset area test threshold to analyze whether the area meets the expected performance standard. According to the comparison result, obtain the area test analysis result, and make test analysis judgment on the corresponding preset functional area, and obtain the area test judgment result (such as overall performance is good, there is a performance bottleneck, need to pay attention to, etc.).

[0111] The technical effect of the above technical solution is: by setting corresponding test parameters for each preset running category of each preset functional area, the fine testing and evaluation of system performance is realized. Through the calculation formula of the category test coefficient The comparison ratio of all index actual data and preset data of all categories under a certain weight can be calculated, which reflects the test coefficient of the calculation category. The larger the coefficient, the better the test performance of the calculation category. Through the calculation formula of the area test coefficient The ratio of the actual test coefficient of all categories under the area weight in the preset function area to the preset data can be calculated, which reflects the test coefficient of the area. The greater the coefficient, the better the test performance of the area. This helps to find the performance difference under different areas and operation categories. By calculating the category test coefficient and the area test coefficient, and comparing them with the preset test threshold, an objective evaluation of the system performance is realized. This helps to avoid subjective speculation and bias, and improves the accuracy and reliability of the evaluation results. According to the category test analysis results and the area test analysis results, the advantages and disadvantages of the system performance can be determined. This helps to improve the overall performance of the system, reduce the operation cost, and improve the economic benefit. Through the standardized test process and parameter setting, the efficiency and consistency of the test are improved. This helps to reduce the test time and cost, while ensuring the accuracy and comparability of the test results.

[0112] In one embodiment of the present application, the S3 comprises:

[0113] Monitoring the actual operation of the corresponding category for each preset operation category of each preset function area;

[0114] Obtaining the category operation data of the actual operation;

[0115] Calculating the category operation coefficient of the corresponding preset operation category according to the category operation data;

[0116] The calculation formula of the category operation coefficient is:

[0117]

[0118] Wherein, ZY is the category operation coefficient, q is the number of preset function areas, n is the number of category operation indexes, X sil is the actual data of the i-th area of the l-th operation index of the category, X yil is the preset data of the i-th area of the l-th operation index of the category, Z q is the preset weight of the category; the operation index includes each category of operation purpose.

[0119] Comparing the category operation coefficient with the preset category operation threshold to obtain the category operation analysis result;

[0120] According to the category operation analysis result, the operation analysis and judgment of the corresponding preset operation category are carried out to obtain the category operation judgment result;

[0121] When the category test operation is greater than the preset category operation threshold, it is judged that the category operation is qualified, otherwise it is not qualified.

[0122] a region operation coefficient of each region is calculated according to a kind operation coefficient of each preset operation kind of each preset function region;

[0123] The calculation formula of the region operation coefficient is:

[0124]

[0125] wherein QY is the region operation coefficient, e is the total number of preset operation kinds in the calculation region, ZYso is the kind operation coefficient of the oth preset operation kind in the calculation region, ZY yo is the kind operation preset coefficient of the oth preset operation kind in the calculation region, U q is the preset weight of the calculation region;

[0126] The region operation coefficient is compared with a preset region operation threshold value, and a region operation analysis result is obtained;

[0127] According to the region operation analysis result, operation analysis and judgment are performed on the corresponding preset function region, and a region operation judgment result is obtained;

[0128] When the region operation coefficient is greater than the preset region operation threshold value, it is determined that the region operation is qualified, otherwise it is not qualified.

[0129] The working principle of the above technical solution is as follows: the actual operation of each preset operation kind of each preset function region is continuously monitored. This usually involves installing sensors, using remote monitoring systems or data acquisition systems to collect data about system performance, status and environmental conditions in real time or periodically. From the actual operation data obtained from the monitoring process, data directly related to each preset operation kind is extracted, including power generation, efficiency, failure rate, response time and other key performance indicators. According to the collected kind operation data, the kind operation coefficient of the corresponding preset operation kind is calculated. This coefficient reflects the performance of the operation kind in actual operation. The calculated kind operation coefficient is compared with the preset kind operation threshold value to evaluate whether the operation kind meets the established performance standards and requirements. According to the comparison result, the kind operation analysis result is obtained, and the operation analysis and judgment of the corresponding preset operation kind are performed, and the kind operation judgment result is obtained. For each preset function region, the region operation coefficient of the region is calculated according to the kind operation coefficients of all preset operation kinds in the region. This coefficient reflects the overall actual operation performance of the region. The calculated region operation coefficient is compared with the preset region operation threshold value to evaluate whether the region meets the established performance standards and requirements. According to the comparison result, the region operation analysis result is obtained, and the operation analysis and judgment of the corresponding preset function region are performed, and the region operation judgment result is obtained.

[0130] The technical effects of the above technical solutions are: through continuous actual operation monitoring, the performance state of the system can be grasped in real time, potential problems can be found and solved in time, and the stability and reliability of the system are improved. Using the type operation coefficient and the area operation coefficient as evaluation indexes, the performance of the system and each operation type can be objectively and accurately reflected, and subjective speculation and bias are avoided. The comparison ratio of all index actual data of the calculation type in all areas under a certain weight to preset data can be calculated, which reflects the operation coefficient of the calculation type. The larger the coefficient is, the better the operation performance of the calculation type is.

[0131] According to the type operation analysis result and the area operation analysis result, the advantages and disadvantages of the system performance can be determined, and the overall performance and efficiency of the system can be improved. Through continuous monitoring and analysis of the system performance, potential fault points can be predicted, measures can be taken in time for prevention, and the possibility and influence of failure can be reduced. The automated and intelligent monitoring system can reduce manual intervention, improve management efficiency, and ensure the accuracy and consistency of data.

[0132] In an embodiment of the present application, the S4 comprises:

[0133] The type operation coefficient and the type test coefficient of the same preset operation type of the same preset functional area are calculated by difference, and a type test operation difference is obtained.

[0134] The type test operation difference is compared with a preset type difference threshold value, and a type difference comparison result is obtained.

[0135] According to the type difference comparison result, a type deviation determination result is obtained.

[0136] The area operation coefficient and the area test coefficient of the same preset functional area are calculated by difference, and an area test operation difference is obtained.

[0137] The area test operation difference is compared with a preset area difference threshold value, and an area difference comparison result is obtained.

[0138] According to the type difference comparison result and the area difference comparison result, a corresponding type and a corresponding area are tested for abnormal early warning.

[0139] The working principle of the above technical solution is as follows: for the same preset running category in the same preset functional area, the category running coefficient in actual running is calculated with the category test coefficient obtained under the test condition. The difference reflects the deviation degree of actual running performance and test performance, which is recorded as the category test running difference. The calculated category test running difference is compared with the preset category difference threshold. If the difference exceeds the threshold, it means that there is a large deviation between the actual running performance and the test performance, and further investigation or adjustment may be needed. According to the comparison result, the category test running deviation is determined, and the category deviation determination result is obtained. For the same preset functional area, the area running coefficient is calculated with the area test coefficient obtained under the test condition, and the area test running difference is obtained. This difference reflects the deviation degree of the performance of the entire area in actual running and the test performance. The calculated area test running difference is compared with the preset area difference threshold. If the difference exceeds the threshold, it means that the actual running performance of the area deviates significantly from the test performance, which may mean that there is an abnormality or potential problem in the area. Combined with the category difference comparison result and the area difference comparison result, the corresponding category and area are comprehensively determined. If a category or area is determined to have a deviation or abnormality, a test abnormality warning is triggered to prompt the management personnel to further investigate, analyze or take necessary maintenance measures.

[0140] The technical effect of the above technical solution is that by calculating the category test running difference and the area test running difference, the deviation degree of actual running performance and test performance can be more accurately evaluated, thereby improving the accuracy and precision of performance monitoring. The category deviation determination and area abnormality warning mechanism can timely discover potential problems in actual running, provide timely decision support for management personnel, and avoid further deterioration of problems or more serious consequences. By timely discovering and solving performance deviation or abnormality problems, the overall performance of the system can be optimized, the stability and reliability of the system can be improved, and the failure rate and maintenance cost can be reduced. The automated and intelligent monitoring, analysis and warning system can reduce manual intervention, improve management efficiency, and ensure the accuracy and consistency of data. By continuously monitoring and analyzing performance data, deficiencies in the system can be continuously discovered and improved, the continuous improvement and optimization of the system can be promoted, and the overall operation efficiency and economic benefits can be improved.

[0141] In an embodiment of the present application, the test platform comprises:

[0142] The monitoring division module is configured to obtain water surface floating photovoltaic power generation system information of the airport flight area, divide preset functional area information and preset running category information thereof, and extract area category information.

[0143] a test analysis module configured to perform corresponding type tests and corresponding area tests on each preset operation type of each preset functional area, to obtain type test determination results and area test determination results;

[0144] an operation analysis module configured to monitor actual operation of each preset functional area and each preset operation type thereof, to perform operation analysis on each preset functional area and each preset operation type thereof according to the monitoring data of the actual operation, to obtain type operation determination results and area operation determination results;

[0145] a deviation early warning module configured to perform difference analysis on the type and area of the same preset functional area and the same preset operation type thereof, to obtain difference analysis results of the type and operation, and to further perform corresponding early warning.

[0146] The working principle of the above technical solution is as follows: detailed information of the water surface floating photovoltaic power generation system in the airport flight area is obtained through data collection means (such as sensors, database queries, etc.), including its layout, capacity, configuration, etc. According to the layout and functional requirements of the system, the water surface floating photovoltaic power generation system is divided into multiple preset functional areas, such as power generation areas, floating support areas, etc. For each preset functional area, according to its operation characteristics and requirements, it is further divided into different preset operation types, such as power generation mode, storage power mode, power conversion mode, etc. From the above division, the information of each functional area and its corresponding operation type is extracted. Corresponding type tests and corresponding area tests are performed on each preset operation type of each preset functional area. This includes performance tests (such as power generation efficiency, stability), safety tests (such as short circuit protection, overload protection), etc., to obtain type test determination results and area test determination results. In actual operation, each preset functional area and each preset operation type thereof are monitored in real time, and operation data (such as power generation capacity, failure rate, maintenance records, etc.) are collected. According to these data, operation analysis is performed on each preset functional area and each preset operation type thereof, to obtain type operation determination results and area operation determination results. Difference analysis is performed on the type and area of the same preset functional area and the same preset operation type thereof. This includes comparing the performance difference, failure rate difference, etc. of different areas or types under the same conditions, to obtain difference analysis results of the type and operation. According to the difference analysis results, if the performance or operation status of a certain preset functional area or preset operation type deviates significantly from the normal range, the early warning mechanism is triggered, prompting relevant personnel to take timely measures for intervention or adjustment.

[0147] The technical effects of the above technical solutions are: through the division of fine functional areas and operation categories, as well as targeted testing and monitoring, bottlenecks and problems in the system can be found and solved in a timely manner, thereby improving the operation efficiency of the entire photovoltaic power generation system. Through regular testing and monitoring, potential faults and safety hazards in the system can be found and repaired in a timely manner, thereby enhancing the stability and safety of the system. According to the testing and monitoring results, resources (such as maintenance personnel, spare parts, etc.) can be more reasonably allocated, maintenance plans and scheduling strategies can be optimized, and operation and maintenance costs can be reduced. Through difference analysis and early warning mechanisms, early detection and early warning of system abnormalities can be achieved, timely and accurate information support can be provided for decision-makers, and emergency response speed and disposal capacity can be improved.

[0148] In an embodiment of the present application, the monitoring division module comprises:

[0149] The area division module is configured to obtain water surface floating photovoltaic power generation system information of an airport flight area, classify the water surface floating photovoltaic power generation system information according to a preset functional area category, and obtain system area information of a plurality of preset functional areas.

[0150] The category division module is configured to classify the system area information according to a preset operation category, and obtain operation category information of a plurality of preset operation categories.

[0151] The preprocessing module is configured to preprocess the system area information and the operation category information, and obtain preprocessed system area information and operation category information.

[0152] The packaging module is configured to package and extract each operation category information of each system area information, and obtain area category information.

[0153] The working principle of the above technical solution is: through data collection means (such as sensor network, remote monitoring system, etc.), the detailed information of the water surface floating photovoltaic power generation system in the airport flight area is comprehensively obtained, including geographic location, installed capacity, equipment state, power generation efficiency, etc. According to the functional layout and design requirements of the system, the water surface floating photovoltaic power generation system is divided into multiple preset functional areas, such as high-efficiency power generation area, maintenance convenient area, safety isolation area, etc. Information extraction is carried out for each functional area to form system area information. Further according to the operation mode and demand of the system, the system area information of each preset functional area is classified according to the preset operation type, such as daytime high-efficiency power generation mode, night low-power consumption mode, emergency standby mode, etc. In this way, the different operation type information under each functional area is extracted separately to form operation type information. Preprocessing system area information and operation type information: preprocessing the extracted system area information and operation type information, including data cleaning (removing redundant and error data), data formatting (unifying data format), data normalization (converting data to unified dimension), etc. Packaged extraction of each operation type information of each system area information: integrating the preprocessed system area information and operation type information, packaging and extracting according to each operation type under each system area to form area type information. These information contains the detailed state and data of each functional area under different operation types.

[0154] The technical effect of the above technical solution is: through the classification and preprocessing of the information of the water surface floating photovoltaic power generation system in the airport flight area, the utilization rate and accuracy of the information are improved. By dividing the preset functional areas and operation types, the fine management and optimization of the system are realized. This helps the system administrator better understand the running state and performance of the system and timely discover and solve potential problems. The preprocessed system area information and operation type information are more standardized and unified. This helps to discover the rules and trends of system operation. Through the packaged extraction of area type information, comprehensive and detailed data support is provided for decision makers. This helps decision makers better understand the actual situation of the system, quickly make decisions, and improve decision efficiency and accuracy.

[0155] In an embodiment of the present application, the test analysis module comprises:

[0156] The category test module is configured to set the corresponding category test parameters of the preset operation type for each preset operation type of each preset functional area;

[0157] The category test result data corresponding to the corresponding category test parameters is obtained;

[0158] The category test calculation module is configured to calculate the category test coefficient of the corresponding preset operation type according to the category test result data;

[0159] The calculation formula of the category test coefficient is:

[0160]

[0161] Wherein, ZC is the category test coefficient, q is the preset number of functional areas, b is the number of category test indexes, B sia is the actual data of the a-th test index of the i-th area of the category, B yia is the preset data of the a-th test index of the i-th area of the category, Z q is the preset weight of the category; the test index includes each category of test purpose.

[0162] The category test coefficient is compared with a preset category test threshold to obtain a category test analysis result.

[0163] A category determination module is configured to perform test analysis and determination on the corresponding preset running category according to the category test analysis result, and obtain a category test determination result.

[0164] A region test calculation module is configured to calculate a region test coefficient of each region according to each category test coefficient of each preset running category of each preset functional region.

[0165] The calculation formula of the region test coefficient is:

[0166]

[0167] Wherein, QC is the region test coefficient, e is the total number of preset running categories in the calculation region, ZC so is the category test coefficient of the o-th preset running category in the calculation region, ZC yo is the category preset coefficient of the o-th preset running category in the calculation region, U q is the preset weight of the calculation region.

[0168] The region test coefficient is compared with a preset region test threshold to obtain a region test analysis result.

[0169] A region determination module is configured to perform test analysis and determination on the corresponding preset functional region according to the region test analysis result, and obtain a region test determination result.

[0170] The working principle of the above technical solution is: for each preset running category of each preset functional area, corresponding category test parameters are set according to the design requirements, performance standards and test requirements of the system. These parameters include test conditions (such as light intensity, temperature, humidity, etc.), test time, test method, test index, etc. Under the set test conditions, the corresponding test method is executed to obtain the category test result data under the corresponding category test parameters. These data include power generation, efficiency, stability index, failure rate, etc. According to the obtained category test result data, the category test coefficient of the corresponding preset running category is calculated. This coefficient reflects the performance of the running category under the current test conditions. The calculated category test coefficient is compared with the preset category test threshold to analyze whether the running category meets the expected performance standard. According to the comparison result, the category test analysis result is obtained, and the test analysis of the corresponding preset running category is determined, and the category test determination result (such as qualified, unqualified, need to be further optimized, etc.) is obtained. For each preset functional area, the area test coefficient of the area is calculated according to the category test coefficients of all preset running categories in the area. This coefficient reflects the overall performance of the area. The calculated area test coefficient is compared with the preset area test threshold to analyze whether the area meets the expected performance standard. According to the comparison result, the area test analysis result is obtained, and the test analysis of the corresponding preset functional area is determined, and the area test determination result (such as overall performance is good, there is a performance bottleneck, need to pay attention to, etc.) is obtained.

[0171] The technical effect of the above technical solution is: by setting corresponding test parameters for each preset running category of each preset functional area, the fine testing and evaluation of system performance is realized. This helps to find the performance differences in different areas and running categories. By calculating the category test coefficient and the area test coefficient, and comparing them with the preset test threshold, the objective evaluation of system performance is realized. This helps to avoid subjective speculation and bias, and improves the accuracy and reliability of the evaluation result. According to the category test analysis result and the area test analysis result, the advantages and disadvantages of the system performance can be determined. This helps to improve the overall performance of the system, reduce the operating cost, and improve the economic benefit. Through the standardized test process and parameter setting, the efficiency and consistency of the test are improved. This helps to reduce the test time and cost, while ensuring the accuracy and comparability of the test results.

[0172] In an embodiment of the present application, the operation analysis module comprises:

[0173] The category operation monitoring module is used to monitor the actual operation of each preset running category of each preset functional area;

[0174] The category operation data of the actual operation is obtained;

[0175] The category operation calculation module is used to calculate the category operation coefficient of the corresponding preset operation category based on the category operation data;

[0176] The formula for calculating the operating coefficient of the aforementioned type is as follows:

[0177]

[0178] Where ZY is the category operation coefficient, q is the number of preset functional areas, n is the number of category operation indicators, and X sil To calculate the actual data for the l-th operational indicator of the i-th region of a category, X yil Z is the preset data for calculating the l-th operational indicator of the i-th region of a certain category. q The preset weights are used to calculate the categories; the operational indicators include various categories of operational objectives.

[0179] The category operation coefficient is compared with the preset category operation threshold to obtain the category operation analysis results;

[0180] The category operation determination module is used to perform operation analysis and determination on the corresponding preset operation category based on the category operation analysis results, and obtain the category operation determination results.

[0181] The regional operation calculation module is used to calculate the regional operation coefficient of each region based on the operation coefficient of each type of each preset operation category in each preset functional region.

[0182] The formula for calculating the regional operating coefficient is as follows:

[0183]

[0184] Where QY is the regional operation coefficient, e is the total number of preset operation types in the calculation area, ZYso is the type operation coefficient of the o-th preset operation type in the calculation area, and ZY yo To calculate the preset coefficient for the o-th preset operation type within the region, U q Preset weights for the calculation region;

[0185] The regional operation coefficient is compared with the preset regional operation threshold to obtain the regional operation analysis results;

[0186] The regional operation determination module is used to perform operation analysis and determination on the corresponding preset functional areas based on the regional operation analysis results, and obtain the regional operation determination results.

[0187] The working principle of the above technical solution is: continuous actual operation monitoring is performed on each preset operation category of each preset functional area. This usually involves installing sensors, using remote monitoring systems or data acquisition systems to collect data about system performance, status and environmental conditions in real time or periodically. From the actual operation data obtained from the monitoring process, data directly related to each preset operation category is extracted, including power generation, efficiency, failure rate, response time and other key performance indicators. The category operation coefficient of the corresponding preset operation category is calculated according to the collected category operation data. This coefficient reflects the performance of the operation category in actual operation. The calculated category operation coefficient is compared with the preset category operation threshold to evaluate whether the operation category meets the established performance standards and requirements. According to the comparison result, the category operation analysis result is obtained, and the operation analysis of the corresponding preset operation category is determined, and the category operation determination result is obtained. For each preset functional area, the area operation coefficient of the area is calculated according to the category operation coefficients of all preset operation categories in the area. This coefficient reflects the actual operation performance of the area as a whole. The calculated area operation coefficient is compared with the preset area operation threshold to evaluate whether the area meets the established performance standards and requirements. According to the comparison result, the area operation analysis result is obtained, and the operation analysis of the corresponding preset functional area is determined, and the area operation determination result is obtained.

[0188] The technical effect of the above technical solution is: through continuous actual operation monitoring, the performance status of the system can be grasped in real time, potential problems can be found and solved in time, and the stability and reliability of the system can be improved. Using category operation coefficient and area operation coefficient as evaluation index, the performance of the system and each operation category can be objectively and accurately reflected, avoiding subjective speculation and bias. According to the category operation analysis result and the area operation analysis result, the advantages and disadvantages of the system performance can be determined, and the overall performance and efficiency of the system can be improved. Through continuous monitoring and analysis of system performance, potential failure points can be predicted, measures can be taken in time for prevention, and the possibility and influence of failure can be reduced. The automated and intelligent monitoring system can reduce manual intervention, improve management efficiency, and ensure the accuracy and consistency of data.

[0189] In one embodiment of the present application, the deviation warning module comprises:

[0190] The difference calculation module is configured to calculate the difference between the category operation coefficient and the category test coefficient of the same preset operation category in the same preset functional area to obtain a category test operation difference value.

[0191] The deviation determination module is configured to compare the category test operation difference value with a preset category difference threshold to obtain a category difference comparison result.

[0192] a deviation determination is made on the category test run according to the category deviation comparison result, and a category deviation determination result is obtained;

[0193] a region test run deviation is obtained by calculating the difference between the region run coefficient and the region test coefficient of the same preset function region;

[0194] an abnormality early warning module is configured to compare the region test run deviation with a preset region deviation threshold, and obtain a region deviation comparison result;

[0195] a test abnormality early warning is triggered for the corresponding category and region according to the category deviation comparison result and the region deviation comparison result.

[0196] The working principle of the above technical solution is as follows: for the same preset running category in the same preset function region, the category run coefficient in the actual running is compared with the category test coefficient obtained under the test condition, and a difference is calculated. This difference reflects the deviation degree between the actual running performance and the test performance, and is recorded as the category test run deviation. The calculated category test run deviation is compared with the preset category deviation threshold. If the difference exceeds the threshold, it means that there is a large deviation between the actual running performance and the test performance, and further investigation or adjustment may be needed. According to the comparison result, a deviation determination is made on the category test run, and a category deviation determination result is obtained. For the same preset function region, the region run coefficient is compared with the region test coefficient obtained under the test condition, and a region test run deviation is obtained. This difference reflects the deviation degree between the actual running performance and the test performance of the entire region. The calculated region test run deviation is compared with the preset region deviation threshold. If the difference exceeds the threshold, it means that there is a significant deviation between the actual running performance and the test performance of the region, which may mean that there is an abnormality or potential problem in the region. The corresponding category and region are comprehensively determined in combination with the category deviation comparison result and the region deviation comparison result. If a category or a region is determined to have a deviation or an abnormality, a test abnormality early warning is triggered, prompting the management personnel to further investigate, analyze or take necessary maintenance measures.

[0197] The technical effects of the above solution are as follows: By calculating the difference between type-based test runs and the difference between regional test runs, the deviation between actual operating performance and test performance can be assessed more accurately, thereby improving the precision and accuracy of performance monitoring. The type-based deviation judgment and regional anomaly early warning mechanisms can promptly identify potential problems in actual operation, providing timely decision support for managers and preventing further deterioration or more serious consequences. By promptly identifying and resolving performance deviations or anomalies, the overall system performance can be optimized, improving system stability and reliability, and reducing failure rates and maintenance costs. Automated and intelligent monitoring, analysis, and early warning systems can reduce manual intervention, improve management efficiency, and ensure data accuracy and consistency. Through continuous monitoring and analysis of performance data, shortcomings in the system can be continuously identified and improved, promoting continuous system improvement and optimization, and enhancing overall operating efficiency and economic benefits.

[0198] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A test method for a floating photovoltaic power generation system on the water surface of an airport flight area, characterized in that, The testing method includes: S1. Obtain information on the floating photovoltaic power generation system in the airport flight area, divide the preset functional area information and its preset operation type information, and extract the area type information; S2. Perform corresponding type tests and corresponding area tests on each preset operation type of each preset functional area to obtain type test judgment results and area test judgment results; Wherein, S2 includes: Set the corresponding test parameters for each preset operation type for each preset functional area; Obtain the type test result data corresponding to the corresponding type test parameters; Calculate the type test coefficient for the corresponding preset operating type based on the type test result data; The category test coefficients are compared with preset category test thresholds to obtain category test analysis results; Based on the test analysis results of the aforementioned types, test analysis and judgment are performed on the corresponding preset operating types to obtain the type test judgment results; Calculate the regional test coefficient for each region based on the test coefficient for each type of each preset operation type in each preset functional area; The regional test coefficients are compared with the preset regional test thresholds to obtain the regional test analysis results; Based on the regional test analysis results, the corresponding preset functional areas are tested and analyzed to determine the regional test results. S3. Monitor the actual operation of each preset functional area and each preset operation type, and perform operation analysis on each preset functional area and each preset operation type based on the actual operation monitoring data to obtain the type operation judgment result and the area operation judgment result. S4. Conduct test and operation difference analysis on the same preset functional areas and the same preset operation types and areas respectively, obtain the difference analysis results of types and operations, and then issue corresponding warnings.

2. The test method for a floating photovoltaic power generation system in the flight area of ​​an airport according to claim 1, characterized in that, S1 includes: Information on floating photovoltaic power generation systems in the airport flight area is obtained, and the information on floating photovoltaic power generation systems is classified according to preset functional area types to obtain system area information for multiple preset functional areas. The system area information is classified according to preset operation types to obtain operation type information for multiple preset operation types; The system area information and operation type information are preprocessed to obtain preprocessed system area information and operation type information; The information on each operational type of each system region is packaged and extracted to obtain the region type information.

3. The test method for a floating photovoltaic power generation system in the flight area of ​​an airport according to claim 1, characterized in that, S3 includes: Monitor the actual operation of each preset operation type in each preset functional area; Obtain the actual operational data for the aforementioned types of operations; Calculate the type operation coefficient corresponding to the preset operation type based on the type operation data; The category operation coefficient is compared with the preset category operation threshold to obtain the category operation analysis results; Based on the operation analysis results of the aforementioned types, an operation analysis and determination are performed on the corresponding preset operation types to obtain the operation determination results of the types; Calculate the regional operation coefficient for each region based on the operation coefficient of each type of each preset operation category in each preset functional area; The regional operation coefficient is compared with the preset regional operation threshold to obtain the regional operation analysis results; Based on the regional operation analysis results, the corresponding preset functional areas are analyzed and judged to obtain regional operation judgment results.

4. The test method for a floating photovoltaic power generation system in the flight area of ​​an airport according to claim 1, characterized in that, S4 includes: The difference between the type operation coefficient and the type test coefficient of the same preset operation type in the same preset functional area is calculated to obtain the type test operation difference. The difference between the test results of each type is compared with a preset difference threshold for each type to obtain the difference comparison result. Based on the comparison results of the differences between the categories, deviation judgment is performed on the category test run to obtain the category deviation judgment result; The difference between the regional operation coefficient and the regional test coefficient of the same preset functional area is calculated to obtain the regional test operation difference. The regional test run difference is compared with a preset regional difference threshold to obtain the regional difference comparison result; Based on the comparison results of species differences and regional differences, test anomaly warnings are issued for the corresponding species and corresponding regions.

5. A test platform for a floating photovoltaic power generation system in the flight area of ​​an airport, characterized in that, The testing platform includes: The monitoring and segmentation module is used to acquire information on the floating photovoltaic power generation system in the airport flight area, segment the preset functional areas and their preset operation types, and extract the area type information. The test analysis module is used to perform corresponding type tests and corresponding area tests on each preset operation type of each preset functional area, and obtain the type test judgment results and area test judgment results. The test analysis module includes: The category testing module is used to set the corresponding category testing parameters for each preset operation category of each preset functional area; Obtain the type test result data corresponding to the corresponding type test parameters; The category test calculation module is used to calculate the category test coefficient for the corresponding preset running category based on the category test result data; The category test coefficients are compared with preset category test thresholds to obtain category test analysis results; The category determination module is used to perform test analysis and determination on the corresponding preset running category based on the category test analysis results, and obtain the category test determination results. The regional test calculation module is used to calculate the regional test coefficient for each region based on the test coefficient for each type of each preset operation type in each preset functional region. The regional test coefficients are compared with the preset regional test thresholds to obtain the regional test analysis results; The region determination module is used to perform test analysis and determination on the corresponding preset functional regions based on the region test analysis results, and obtain the region test determination results. The operation analysis module is used to monitor the actual operation of each preset functional area and each preset operation type. Based on the actual operation monitoring data, it performs operation analysis on each preset functional area and each preset operation type to obtain the operation judgment results of the type and the operation judgment results of the area. The deviation warning module is used to perform test and operation difference analysis on the same preset functional areas and the same preset operation types and areas, obtain the difference analysis results of types and operations, and then issue corresponding warnings.

6. The test platform for a floating photovoltaic power generation system in an airport flight area according to claim 5, characterized in that, The monitoring segmentation module includes: The area division module is used to obtain information on the floating photovoltaic power generation system in the airport flight area, classify the information on the floating photovoltaic power generation system according to the preset functional area types, and obtain system area information of multiple preset functional areas; The category classification module is used to classify the system area information according to preset operation categories to obtain operation category information for multiple preset operation categories; The preprocessing module is used to preprocess the system area information and operation type information to obtain preprocessed system area information and operation type information; The packaging module is used to package and extract each type of operational information for each system region to obtain region type information.

7. The test platform for a floating photovoltaic power generation system in an airport flight area according to claim 5, characterized in that, The operation analysis module includes: The category operation monitoring module is used to monitor the actual operation of each preset operation category in each preset functional area. Obtain the actual operational data for the aforementioned types of operations; The category operation calculation module is used to calculate the category operation coefficient of the corresponding preset operation category based on the category operation data; The category operation coefficient is compared with the preset category operation threshold to obtain the category operation analysis results; The category operation determination module is used to perform operation analysis and determination on the corresponding preset operation category based on the category operation analysis results, and obtain the category operation determination results. The regional operation calculation module is used to calculate the regional operation coefficient of each region based on the operation coefficient of each type of each preset operation category in each preset functional region. The regional operation coefficient is compared with the preset regional operation threshold to obtain the regional operation analysis results; The regional operation determination module is used to perform operation analysis and determination on the corresponding preset functional areas based on the regional operation analysis results, and obtain the regional operation determination results.

8. The test platform for a floating photovoltaic power generation system in an airport flight area according to claim 5, characterized in that, The deviation early warning module includes: The difference calculation module is used to calculate the difference between the type operation coefficient and the type test coefficient of the same preset operation type in the same preset functional area to obtain the type test operation difference. The deviation determination module is used to compare the difference between the test run of the type with a preset type difference threshold to obtain the type difference comparison result; Based on the comparison results of the differences between the categories, deviation judgment is performed on the category test run to obtain the category deviation judgment result; The difference between the regional operation coefficient and the regional test coefficient of the same preset functional area is calculated to obtain the regional test operation difference. The anomaly warning module is used to compare the regional test run difference with a preset regional difference threshold to obtain the regional difference comparison result; Based on the comparison results of species differences and regional differences, test anomaly warnings are issued for the corresponding species and corresponding regions.

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