Inspection and detection data management system and method based on Internet of Things

Abstract

The invention relates to the technical field of data management, in particular to an inspection and detection data management system and method based on the Internet of Things. Analyzing the influence of the material on the equipment based on the characteristic condition data of the detection sample material of the corresponding detection equipment, analyzing the influence of the detection workpiece on the abnormal operation of the equipment in the detection process, and analyzing the equipment damage based on the evolution analysis result of the abnormal operation of the corresponding detection equipment and the analysis result of the influence of the material on the equipment. According to the method, the influence of the material on the abnormal equipment is synthesized to perform equipment damage analysis in the detection process, the maintenance period is set based on the equipment damage analysis result, the maintenance period is dynamically regulated and controlled by detecting the matching of the material and the equipment damage condition, and the punctuality and safety of equipment maintenance are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and particularly to an inspection and testing data management system and method based on the Internet of Things. Background Art

[0002] Currently, the maintenance of detection equipment mainly adopts a fixed-cycle mode. However, in actual operation, the wear degree of the equipment is significantly affected by the characteristics of the detection materials. For example, when a metal hardness tester detects materials with a hardness above HRC60, the indenter life is shortened by 40% compared to the conventional working conditions. The traditional method does not consider the material-equipment interaction, resulting in: insufficient maintenance (maintaining the equipment according to the standard cycle under high wear conditions) leading to equipment failures; over-maintenance (performing early maintenance on low-load equipment) causing waste of resources. For example, in the patent application No. CN202411293773.3, a maintenance management system for metering equipment based on data analysis is disclosed, which includes an equipment management unit, a maintenance management unit, a maintenance cycle analysis unit, a usage statistical analysis unit, and an environmental statistical analysis unit. In this invention, when maintaining metering equipment, instead of maintaining the metering equipment at fixed-frequency maintenance intervals, the usage of the metering equipment is analyzed based on the workload and working hours of the metering equipment, and the usage is used as the basis for maintaining the metering equipment. At the same time, the external environment of the metering equipment is analyzed, and the environmental interference factors caused by environmental factors are fully considered, making the maintenance of the metering equipment more in line with the actual situation. However, the above-mentioned prior art ignores the material-equipment interaction, resulting in low punctuality and safety of equipment maintenance. To solve these problems, the present application designs an inspection and testing data management system and method based on the Internet of Things. Summary of the Invention

[0003] In order to overcome the defects and deficiencies existing in the prior art, the present invention provides an inspection and testing data management system and method based on the Internet of Things.

[0004] To achieve the above object, the present invention adopts the following technical solutions: In the first aspect, the present invention provides an inspection and testing data management method based on the Internet of Things, including the following steps: S1. Obtain the operation status of the corresponding detection equipment and the characteristic data of the detection sample materials of the corresponding detection equipment; S2. Conduct an analysis on the evolution of abnormal operation of the detection equipment based on the operation status of the corresponding detection equipment; S3. Conduct an analysis on the impact of materials on the equipment based on the characteristic data of the detection sample materials of the corresponding detection equipment; S4. Conduct an equipment damage analysis based on the analysis results of the evolution of abnormal operation of the corresponding detection equipment and the analysis results of the impact of materials on the equipment; S5. Set the maintenance cycle based on the analysis results of equipment damage.

[0005] In one implementation of the present invention, the operating conditions of the corresponding detection equipment include data on the change in measurement accuracy of the equipment for standard items, as well as data on the damage condition of the detection equipment and circuit operating data. Among them, the circuit operating data includes circuit operating voltage and current condition data, and the characteristic condition data of the detected sample material includes data on the shape, hardness, magnetic properties, and types of parameters to be measured of the material in future batches. Among them, the shape condition of the material is obtained through the corresponding image acquisition terminal, and the damage condition of the measurement equipment during detection is analyzed through the corresponding material shape condition and hardness condition data. At the same time, the damage of the material to the equipment circuit is analyzed by the influence of the magnetic field intensity condition of the material on the circuit operating data.

[0006] In one implementation of the present invention, in step S2, the analysis of the evolution of abnormal operation of the detection equipment based on the operating conditions of the corresponding detection equipment includes the following specific steps: S21. Obtain data on the change in measurement accuracy of the equipment for standard items and data on the damage condition of the detection equipment; S22. Conduct an abnormal operation analysis of the equipment based on the data on the change in measurement accuracy of the equipment for standard items and the data on the damage condition of the detection equipment. Among them, the calculation formula for the abnormal operation analysis of the equipment is: , where V() is the volume of the image in the parentheses, is the image of the measurement end when the measurement equipment is not damaged, is the image of the real-time measurement end of the measurement equipment, exp() is the exponential power of the natural constant e, mi is the real-time measurement result of the equipment for the standard item, and mc is the standard measurement result of the standard item. Here, the damage to the measurement end during the measurement process is analyzed by analyzing the change in the image of the measurement end during the measurement process, and the abnormality of the equipment measurement is analyzed through the comprehensive measurement accuracy. S23. Obtain the circuit operating data of the corresponding detection equipment, and conduct a circuit abnormality analysis based on the circuit operating data of the corresponding detection equipment. Among them, the circuit abnormality analysis formula is: , where N is the type of circuit operating data, xj is the specific value of the jth type of operating data during the operation of the corresponding detection equipment, and xjm is the standard value of the jth type of operating data during the operation of the corresponding detection equipment.

[0007] In one implementation of the present invention, in step S3, the analysis of the influence of the material on the equipment based on the characteristic condition data of the detected sample material of the corresponding detection equipment includes the following specific steps: S31. Obtain the shape condition data and hardness condition data of the future batch of materials, and conduct an analysis on the risk of equipment collision caused by the movement of the materials during measurement based on the shape condition data and hardness condition data of the future batch of materials. The equipment collision risk analysis formula is as follows: , where is the safe distance between the measurement end and the workpiece during measurement, Lz is the real-time distance between the measurement end and the workpiece during measurement, km is the hardness of the measurement end, kx is the hardness of the article, is the angle at the nearest corner from the workpiece to the measurement end during measurement, corresponds to the sharpness of the workpiece corner. Understanding the influence of the shape, position, and corresponding hardness of the workpiece on the risk of collision with the measurement end helps to accurately evaluate the risk degree of the workpiece colliding with the measurement end during the measurement process; S32. Obtain the magnetic condition of the corresponding workpiece, and conduct an abnormal electromagnetic interference assessment based on the magnetic condition of the corresponding workpiece. The abnormal electromagnetic interference assessment formula is as follows: , where Tr is the magnetic field intensity generated by the workpiece, and Ts is the magnetic field intensity that the measurement equipment can safely withstand. In this step, the abnormality of electromagnetic interference is analyzed through the influence of the magnetic field of the corresponding workpiece on the equipment.

[0008] In an implementation manner of the present invention, in step S4, based on the analysis result of the abnormal evolution of the corresponding detection equipment operation and the analysis result of the influence of the material on the equipment, equipment damage analysis is carried out, including the following specific contents: S41. Obtain the analysis result of equipment operation abnormality and the analysis result of equipment collision risk, and conduct an analysis on the risk of equipment operation based on the analysis result of equipment operation abnormality and the analysis result of equipment collision risk. The equipment operation risk analysis formula is as follows: , this step comprehensively considers the aging abnormality of the equipment and the collision risk of the workpiece to the equipment, and analyzes the risk degree of future equipment operation. The operation risk degree of the aging equipment under the action of the collision risk is analyzed; S42. Obtain the assessment result of abnormal electromagnetic interference and the analysis result of circuit abnormality, and conduct an assessment on the risk of circuit operation based on the assessment result of abnormal electromagnetic interference and the analysis result of circuit abnormality. The circuit operation risk assessment formula is as follows: , in this way, the risk situation of the circuit operation of the electrical signal abnormal equipment under the influence of electromagnetic interference is analyzed; S43. Obtain the obtained analysis result of equipment operation risk and the assessment result of circuit operation risk, and perform weighted summation to obtain the analysis result of equipment damage.

[0009] In an implementation manner of the present invention, in step S5, based on the analysis result of equipment damage, the maintenance cycle is set, including the following specific contents: The obtained device damage analysis result is divided by the device damage analysis threshold to obtain the device damage ratio, and the maintenance cycle of the corresponding detection device is obtained by dividing the set maintenance cycle by the device damage ratio.

[0010] In a second aspect, the present invention also provides an inspection and testing data management system based on the Internet of Things, including: A data acquisition module for acquiring the operating conditions of the corresponding detection device and the characteristic data of the detection sample material of the corresponding detection device; An operating anomaly evolution analysis module for performing an analysis of the evolution of operating anomalies of the detection device based on the operating conditions of the corresponding detection device; A device impact analysis module for performing an analysis of the impact of the material on the device based on the characteristic data of the detection sample material of the corresponding detection device; A device damage analysis module for performing device damage analysis based on the analysis result of the evolution of operating anomalies of the corresponding detection device and the analysis result of the impact of the material on the device; A maintenance cycle setting module for setting the maintenance cycle based on the device damage analysis result.

[0011] In a third aspect, an electronic device provided by the present invention includes: a processor and a memory. Among them, a computer program that can be called by the processor is stored in the memory, and the processor executes an inspection and testing data management method based on the Internet of Things by calling the computer program stored in the memory.

[0012] In a fourth aspect, a computer-readable storage medium provided by the present invention stores instructions, and when the instructions run on a computer, the computer is made to execute an inspection and testing data management method based on the Internet of Things.

[0013] Compared with the prior art, the present invention has the following advantages and beneficial effects: An analysis of the evolution of operating anomalies of the detection device is performed based on the operating conditions of the corresponding detection device to analyze the operating anomalies of the detection device. An analysis of the impact of the material on the device is performed based on the characteristic data of the detection sample material of the corresponding detection device to analyze the impact of the detected workpiece on the operating anomalies of the device during the detection process. Device damage analysis is performed based on the analysis result of the evolution of operating anomalies of the corresponding detection device and the analysis result of the impact of the material on the device. Comprehensive analysis of the impact of the material on the abnormal device is carried out for device damage analysis during the detection process. The maintenance cycle is set based on the device damage analysis result, and the maintenance cycle is dynamically adjusted by detecting the matching degree between the detection material and the device damage situation, improving the timeliness and safety of device maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Other features, purposes, and advantages of the present invention will become more obvious by reading the detailed description of the non-limiting embodiments with reference to the following drawings: Figure 1 It is a schematic diagram of the overall process of the method embodiment of the present invention; Figure 2 It is a working flowchart of S2 in the method embodiment of the present invention; Figure 3 It is a working flowchart of S4 in the method embodiment of the present invention; Figure 4 It is a schematic structural diagram in the system embodiment of the present invention. Detailed implementation manners

[0015] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. Without conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0016] Embodiment 1

[0017] As Figures 1 to 3 shown, this embodiment provides an inspection and testing data management method based on the Internet of Things, which specifically includes the following steps: S1. Obtain the operation status of the corresponding detection device and the data on the characteristics of the detection sample material of the corresponding detection device; In this embodiment, the operation status of the corresponding detection device includes the data on the change in the measurement accuracy of the device for standard items, the data on the damage status of the detection device, and the circuit operation data. Among them, the circuit operation data includes the circuit operation voltage and current status data, and the data on the characteristics of the detection sample material includes the shape status data, hardness status data, magnetic status data, and the type of parameters to be measured of the future batch of materials. Among them, the shape status of the material is obtained through the corresponding image acquisition terminal, and the damage status of the measurement device during detection is analyzed through the corresponding material shape status and hardness status data. At the same time, the damage of the material to the device circuit is analyzed by the influence of the magnetic field intensity of the material on the circuit operation data, and the obtained data is stored in the corresponding storage module; Exemplarily, in this embodiment, if the corresponding detection type is the size or hardness qualification detection of production workpieces, then the data on the type of parameters to be measured of the material is the size or hardness qualification detection of production workpieces. Since the hardness of the workpiece is required for the analysis of the equipment collision risk in this embodiment, the hardness of the workpiece is used as an approximate value in the analysis of the equipment collision risk, and the preferred approximate value is the hardness of the standard production workpiece; At the same time, in this embodiment, the data acquisition methods are all conventional technical means in the art, such as collecting current through a current sensor and collecting shape through an image sensor; S2. Perform an analysis of the evolution of abnormal operation of the detection device based on the operating conditions of the corresponding detection device; In this embodiment, performing an analysis of the evolution of abnormal operation of the detection device based on the operating conditions of the corresponding detection device includes the following specific steps: S21. Obtain data on the change in the measurement accuracy of the device for standard items and data on the damage condition of the detection device; S22. Perform an analysis of abnormal device operation based on the data on the change in the measurement accuracy of the device for standard items and the data on the damage condition of the detection device. Among them, the calculation formula for the analysis of abnormal device operation is: , where is the volume of the image in the parentheses, is the image at the measurement end when the measurement device is not damaged, is the image at the real-time measurement end of the measurement device, is the power of the natural constant e. mi is the real-time measurement result of the device for standard items, and mc is the standard measurement result of the standard item. Here, by analyzing the change in the image at the measurement end during the measurement process, the damage to the measurement end during the measurement process is analyzed. At the same time, by comprehensively considering the measurement accuracy, the abnormality of the device measurement is analyzed. Not only the deviation of the measurement data is considered, but also the physical state of the device is introduced, which can more comprehensively reflect the device abnormality. For example, if the measurement is distorted due to mechanical wear of the device, even if the current error is small, the physical damage can still affect the analysis of the abnormal operation of the device; S23. Obtain the circuit operation data of the corresponding detection device, and perform an analysis of circuit abnormality based on the circuit operation data of the corresponding detection device. Among them, the formula for the analysis of circuit abnormality is: , where N is the type of circuit operation data, xj is the specific value of the jth type of operation data during the operation of the corresponding detection device, and xjm is the standard value of the jth type of operation data during the operation of the corresponding detection device; Exemplarily, the circuit operation data here includes the device operating current and the data on the device operating voltage. The quality of the device circuit is evaluated by the difference between the specific value of the operation data and the standard value of the operation data. For example, the standard values of the device operating current and operating voltage are 5A and 220V respectively. Due to its own defects, the real-time operating current and voltage are 4.8A and 210V. Therefore, the calculation of the circuit abnormality analysis value is: (5 - 4.8) / 5 + (220 - 210) / 220 = 0.09; S3. Perform an analysis of the impact of materials on the device based on the data on the characteristics of the detection sample materials of the corresponding detection device; In this embodiment, performing an analysis of the impact of materials on the device based on the data on the characteristics of the detection sample materials of the corresponding detection device includes the following specific steps: S31. Obtain the shape data and hardness data of the materials in the future batches, and conduct an analysis on the risk of equipment collision caused by the movement of the materials during measurement based on the shape data and hardness data of the materials in the future batches. The formula for the risk analysis of equipment collision is as follows: , where is the safe distance between the measuring end and the workpiece during measurement, Lz is the real-time distance between the measuring end and the workpiece during measurement, km is the hardness of the measuring end, kx is the hardness of the item, is the angle at the nearest corner from the workpiece to the measuring end during measurement, corresponds to the sharpness of the workpiece corner. Understanding the influence of the shape, position, and corresponding hardness of the workpiece on the risk of collision with the measuring end helps to accurately evaluate the risk degree of the workpiece colliding with the measuring end during measurement. By integrating the shape sharpness, hardness ratio, and real-time distance, this formula can quantify the collision risk; S32. Obtain the magnetic condition of the corresponding workpiece, and conduct an evaluation on the electromagnetic interference anomaly based on the magnetic condition of the corresponding workpiece. The formula for the evaluation of electromagnetic interference anomaly is as follows: , where Tr is the magnetic field intensity generated by the workpiece, and Ts is the magnetic field intensity that the measuring equipment can safely withstand. In this step, the anomaly of electromagnetic interference is analyzed through the influence of the magnetic field of the corresponding workpiece on the equipment; S4. Conduct equipment damage analysis based on the analysis results of the abnormal evolution of the operation of the corresponding detection equipment and the analysis results of the influence of the materials on the equipment; In this embodiment, conducting equipment damage analysis based on the analysis results of the abnormal evolution of the operation of the corresponding detection equipment and the analysis results of the influence of the materials on the equipment includes the following specific contents: S41. Obtain the analysis results of equipment operation anomaly and the analysis results of equipment collision risk. Conduct equipment operation risk analysis based on the analysis results of equipment operation anomaly and the analysis results of equipment collision risk. The formula for equipment operation risk analysis is as follows: . In this step, the aging anomaly of the equipment and the collision risk of the workpiece to the equipment are comprehensively considered to analyze the future equipment operation risk and the operation risk degree of the aging equipment under the action of the collision risk; S42. Obtain the evaluation results of electromagnetic interference anomaly and the analysis results of circuit anomaly. Conduct circuit operation risk assessment based on the evaluation results of electromagnetic interference anomaly and the analysis results of circuit anomaly. The formula for circuit operation risk assessment is as follows: . In this way, the circuit operation risk situation of the electrical signal abnormal equipment under the influence of electromagnetic interference is analyzed; S43. Obtain the obtained equipment operation risk analysis results and circuit operation risk assessment results, and conduct weighted summation to obtain the equipment damage analysis results; S5. Set the maintenance cycle based on the equipment damage analysis results; In this embodiment, setting the maintenance cycle based on the equipment damage analysis result includes the following specific contents: For the obtained equipment damage analysis result, divide the equipment damage analysis result by the equipment damage analysis threshold to obtain the equipment damage ratio, and divide the set maintenance cycle by the equipment damage ratio to obtain the maintenance cycle of the corresponding detection equipment; Exemplarily, the set maintenance cycle here is the maintenance cycle of the equipment during original production.

[0018] It should be noted that in this embodiment, the acquisition methods of the set parameters (such as various weighting weights and equipment damage analysis thresholds, etc.) in this embodiment are obtained by those skilled in the art through experiments based on historical data. The specific example of the experimental method is: obtain the operation conditions of the historical corresponding detection equipment and the data of the characteristics of the detection sample materials of the corresponding detection equipment, as well as the equipment maintenance cycle, analyze the best equipment sorting results of the operation conditions under the influence of the equipment maintenance cycle, substitute the operation conditions of the corresponding detection equipment and the data of the characteristics of the detection sample materials of the corresponding detection equipment into each step of this embodiment to obtain the maintenance cycle, and perform iterative fitting of the data based on the obtained results of the maintenance cycle and the equipment maintenance cycle results fitting software, output the set parameter values of this embodiment that meet the maximum judgment accuracy rate, and obtain and optimize the set parameters of this embodiment through historical data and experiments, which can significantly improve the judgment accuracy rate and early warning effect of the system. The specific benefits include improving the judgment accuracy rate. The specific process includes data collection, data preprocessing, parameter initialization, model training and testing, data fitting and parameter optimization, and parameter verification and iteration, which can provide a scientific basis for the management of inspection and detection data.

[0019] It should be noted that in this embodiment, this embodiment has the following benefits and advantages. Based on the operation conditions of the corresponding detection equipment, analyze the evolution of the abnormal operation of the detection equipment, analyze the abnormal operation of the detection equipment, based on the data of the characteristics of the detection sample materials of the corresponding detection equipment, analyze the influence of the material on the equipment, analyze the influence of the detected workpiece on the abnormal operation of the equipment during the detection process, perform equipment damage analysis based on the corresponding analysis results of the evolution of the abnormal operation of the detection equipment and the analysis results of the influence of the material on the equipment, comprehensively analyze the influence of the material on the abnormal equipment during the detection process for equipment damage analysis, set the maintenance cycle based on the equipment damage analysis result, and dynamically adjust the maintenance cycle by matching the detection material and the equipment damage situation, improving the timeliness and safety of equipment maintenance.

[0020] Embodiment 2

[0021] Such as Figure 4As shown in the figure, the present embodiment provides an inspection and testing data management system based on the Internet of Things, including: a data acquisition module, which is used to acquire the operation status of the corresponding testing equipment and the characteristic data of the testing sample materials of the corresponding testing equipment; An operation anomaly evolution analysis module, which conducts an analysis of the evolution of operation anomalies of the testing equipment based on the operation status of the corresponding testing equipment; An equipment impact analysis module, which conducts an analysis of the impact of materials on the equipment based on the characteristic data of the testing sample materials of the corresponding testing equipment; An equipment damage analysis module, which conducts an analysis of equipment damage based on the analysis results of the evolution of operation anomalies of the corresponding testing equipment and the analysis results of the impact of materials on the equipment; A maintenance cycle setting module, which sets the maintenance cycle based on the equipment damage analysis results.

[0022] Embodiment 3

[0023] An electronic device according to an embodiment of the present invention includes: a processor and a memory. Among them, a computer program that can be called by the processor is stored in the memory, and the processor executes an inspection and testing data management method based on the Internet of Things by calling the computer program stored in the memory. It should be noted that: all computer programs of the inspection and testing data management method based on the Internet of Things are implemented using the C language.

[0024] Embodiment 4

[0025] The present embodiment proposes a computer-readable storage medium, on which a rewritable computer program is stored; When the computer program runs on a computer device, the computer device is enabled to execute the above-mentioned inspection and testing data management method based on the Internet of Things.

[0026] Each embodiment in the present invention is described in a progressive manner. For the parts that are the same or similar among the embodiments, reference can be made to each other. The key point of each embodiment is to illustrate the differences from other embodiments. In particular, for the embodiments of Internet of Things devices and media, since they are basically similar to the method embodiments, the description is relatively simple, and for the relevant parts, reference can be made to the partial description of the method embodiments.

[0027] The systems and media provided by the embodiments of the present invention correspond one-to-one with the methods. Therefore, the systems and media also have beneficial technical effects similar to those of the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the systems and media will not be elaborated here.

[0028] Those skilled in the art should understand that the embodiments of the present invention may provide a method, a system, or a computer program product. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, 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 disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0029] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices produce means for realizing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 block or multiple blocks.

[0030] These computer program instructions can 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, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means that realize the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 block or multiple blocks.

[0031] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0032] The memory may include non-permanent memory in the computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0033] A computer-readable medium includes permanent and non-permanent, removable and non-removable media that can implement information storage by any method or technology. 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 technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer-readable medium does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0034] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0035] The above are only embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the scope of the claims of the present invention.

Claims

1. An inspection and testing data management method based on the Internet of Things, characterized in that Including the following steps: S1. Obtain the operation status of the corresponding detection device and the data on the characteristics of the detection sample material of the corresponding detection device; S2. Conduct an analysis of the evolution of abnormal operation of the detection device based on the operation status of the corresponding detection device; S3. Conduct an analysis of the impact of the material on the device based on the data on the characteristics of the detection sample material of the corresponding detection device; S4. Conduct an analysis of device damage based on the results of the analysis of the evolution of abnormal operation of the corresponding detection device and the results of the analysis of the impact of the material on the device; Including the following specific contents: S41. Obtain the analysis results of abnormal device operation and the analysis results of device collision risk, and conduct device operation risk analysis based on the analysis results of abnormal device operation and the analysis results of device collision risk. Among them, the device operation risk analysis formula is: , where Xc is the analysis result of abnormal device operation, and Sw is the analysis result of device collision risk; S42. Obtain the electromagnetic interference anomaly evaluation result and the circuit anomaly analysis result, and conduct a circuit operation hazard assessment based on the electromagnetic interference anomaly evaluation result and the circuit anomaly analysis result. Among them, the circuit operation hazard assessment formula is: , where Dc is the circuit anomaly analysis result and Gr is the electromagnetic interference anomaly evaluation result; S43. Obtain the obtained results of the analysis of device operation hazards and the results of the assessment of circuit operation hazards, and perform weighted summation to obtain the results of device damage analysis; S5. Set the maintenance cycle based on the results of device damage analysis.

2. The inspection and testing data management method based on the Internet of Things according to claim 1, wherein The analysis of the evolution of abnormal operation of the detection device based on the operation status of the corresponding detection device includes the following specific steps: S21. Obtain the data on the change in the measurement accuracy of the device for standard items and the data on the damage status of the detection device; S22. Conduct an analysis of abnormal operation of the device based on the data on the change in the measurement accuracy of the device for standard items and the data on the damage status of the detection device; S23. Obtain the circuit operation data of the corresponding detection device, and perform circuit anomaly analysis based on the circuit operation data of the corresponding detection device. Among them, the circuit anomaly analysis formula is: , where N is the type of circuit operation data, xj is the specific value of the jth type of operation data during the operation of the corresponding detection device, and xjm is the standard value of the jth type of operation data during the operation of the corresponding detection device.

3. The method for managing inspection and testing data based on the Internet of Things according to claim 2, wherein, The analysis of the impact of the material on the device based on the data on the characteristics of the detection sample material of the corresponding detection device includes the following specific steps: S31. Obtain the shape condition data and hardness condition data of the future batch of materials, and conduct an analysis on the risk of equipment collision caused by the movement of the materials during measurement based on the shape condition data and hardness condition data of the future batch of materials. The equipment collision risk analysis formula is as follows: , where is the safe distance between the measurement end and the workpiece during measurement, Lz is the real-time distance between the measurement end and the workpiece during measurement, km is the hardness of the measurement end, kx is the hardness of the item, is the angle at the nearest corner from the workpiece to the measurement end during measurement; S32. Obtain the magnetic condition of the corresponding workpiece, and conduct electromagnetic interference anomaly evaluation based on the magnetic condition of the corresponding workpiece. Among them, the electromagnetic interference anomaly evaluation formula is: , where Tr is the magnetic field strength generated by the workpiece, and Ts is the magnetic field strength that the measuring device can safely withstand.

4. The inspection and testing data management method based on the Internet of Things according to claim 3, characterized in that The setting of the maintenance cycle based on the results of device damage analysis includes the following specific contents: Obtain the obtained results of device damage analysis, divide the results of device damage analysis by the device damage analysis threshold to obtain the device damage ratio, and obtain the maintenance cycle of the corresponding detection device by dividing the set maintenance cycle by the device damage ratio.

5. The inspection and testing data management method based on the Internet of Things according to claim 2, wherein The calculation formula for analyzing the abnormal operation of the device is as follows: , where is the volume of the image in the brackets, is the image of the measuring end of the measuring device without damage, is the image of the real-time measuring end of the measuring device, is the power of the natural constant e, mi is the real-time measurement result of the device for the standard item, and mc is the standard measurement result of the standard item.

6. The inspection and testing data management method based on the Internet of Things according to claim 1, characterized in that The operation status of the corresponding detection device includes the data on the change in the measurement accuracy of the device for standard items, the data on the damage status of the detection device, and the circuit operation data. Among them, the circuit operation data includes the circuit operation voltage and current situation data, and the data on the characteristics of the detection sample material includes the shape situation data, hardness situation data, magnetic situation data, and the data on the types of parameters to be measured of the future batch of materials. Among them, the shape situation of the material is obtained through the corresponding image acquisition terminal.

7. An inspection and testing data management system based on the Internet of Things, which is implemented based on the inspection and testing data management method based on the Internet of Things described in any one of claims 1-6, characterized in that, The system includes: A data acquisition module for obtaining the operation status of the corresponding detection device and the data on the characteristics of the detection sample material of the corresponding detection device; An abnormal operation evolution analysis module for conducting an analysis of the evolution of abnormal operation of the detection device based on the operation status of the corresponding detection device; A device impact analysis module for conducting an analysis of the impact of the material on the device based on the data on the characteristics of the detection sample material of the corresponding detection device; A device damage analysis module for conducting an analysis of device damage based on the results of the analysis of the evolution of abnormal operation of the corresponding detection device and the results of the analysis of the impact of the material on the device; A maintenance cycle setting module for setting the maintenance cycle based on the results of device damage analysis.

8. An electronic device, comprising: A processor and a memory. Among them, the memory stores a computer program that can be called by the processor. It is characterized in that the processor executes the method for managing inspection and detection data based on the Internet of Things as described in any one of claims 1-6 by calling the computer program stored in the memory.

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