Enterprise safety production abnormality early warning system based on digital twin

Abstract

The present invention discloses an enterprise safety production abnormality early warning system based on digital twins, and relates to the field of digital twin technology. The present invention includes a production equipment acquisition module, a model simulation module based on digital twins, an equipment environment test module, an equipment load test module, an equipment operation monitoring module, an execution terminal and a database. The collected equipment information is converted into a data signal, and then a digital model of the equipment is constructed, and a simulation test is performed to predict the corresponding maximum operating temperature of the equipment and judge the corresponding operation safety of the equipment. At the same time, the corresponding maximum operating load of the equipment is analyzed, and the corresponding operation stability of the equipment is judged, so as to implement timely production safety prevention and ensure the effective operation of production, so as to take remedial measures in time, improve the production efficiency of the enterprise, extend the service life of equipment, reduce the maintenance cost of the enterprise, and reduce the workload of the enterprise monitoring personnel.

Description

Technical Field

[0001] The present invention relates to the field of digital twin technology, and in particular to an enterprise safety production abnormality early warning system based on digital twin. Background Art

[0002] As digital twin technology continues to mature, its scope of application is becoming increasingly extensive, including abnormal warnings for enterprise production safety. Digital twin technology converts the collected enterprise production equipment data into data signals, and then constructs corresponding equipment models, so as to achieve real-time enterprise production safety abnormality warnings, timely identify potential safety risks and production anomalies, reduce the failure rate of production equipment, extend service life, and improve production efficiency.

[0003] The current technology for early warning of abnormal production safety in enterprises mainly uses camera monitoring equipment, and then observes the corresponding equipment operation status from the equipment operation images taken by the camera to judge the production status of the enterprise. This monitoring method mainly relies on manual safety inspections, which is relatively slow. At the same time, manual observation cannot achieve detailed and in-depth production safety inspections, which will result in residual safety hazards, fail to ensure the safe production of the enterprise, and reduce the use time of enterprise equipment and production speed. Summary of the invention

[0004] In view of the above-mentioned technical deficiencies, the purpose of the present invention is to provide an enterprise safety production abnormality early warning system based on digital twins.

[0005] To solve the above technical problems, the present invention adopts the following technical solution: The present invention provides an enterprise production safety abnormality warning system based on digital twins, including: a production equipment acquisition module, used to monitor the corresponding equipment in the enterprise production, install various sensors on the equipment, and then collect equipment information, and convert the collected equipment information into data signals.

[0006] The model simulation module based on digital twins is used to build a digital model of the equipment according to the data signals converted from the equipment information, and to perform temperature simulation tests and load simulation tests on the digital model of the equipment.

[0007] The equipment temperature test module is used to set up each temperature test group, use the equipment digital model to perform temperature tests on each temperature test group, and collect temperature test information corresponding to each temperature test group, where the temperature test information includes vibration frequency and operating speed, and then predict the corresponding maximum operating temperature of the equipment.

[0008] The equipment load test module is used to set up each load test group, use the equipment digital model to perform load tests on each load test group, and obtain the load test information corresponding to each load test group, where the load test information includes operating pressure and operating speed, and then analyze and obtain the corresponding maximum operating load of the equipment.

[0009] The equipment operation monitoring module is used to obtain the operating temperature and operating load corresponding to the current equipment, and compare them with the corresponding maximum operating temperature and maximum operating load of the equipment to determine the corresponding operating safety and operating stability of the equipment.

[0010] The execution terminal is used to issue early warning prompts when the equipment is unsafe or unstable, and display the corresponding maximum operating temperature and maximum operating load of the equipment.

[0011] Preferably, the temperature simulation test is performed, and the specific test process is as follows: F1. According to the actual temperature corresponding to the equipment, the temperature difference is preset, and the preset temperature differences are arranged in order from small to large, and corresponding temperature test groups are set, and the digital model of the equipment is simulated in each temperature test group.

[0012] F2. Set each monitoring time period, and collect the operating parameters of the equipment digital model in each time period in each temperature test group, calculate the operating parameter difference, and when the operating parameter difference is less than or equal to the operating parameter difference allowed to float, continue to execute the corresponding temperature test of the equipment digital model in each temperature test group; when the operating parameter difference is greater than the operating parameter difference allowed to float, interrupt the test and check for abnormal conditions.

[0013] F3. When the simulated operation time of the equipment digital model in each temperature test group reaches the preset total temperature test time, the operation of the equipment digital model in each temperature test group is stopped, and the temperature test information corresponding to each temperature test group is collected. After the collection is completed, the temperature test is ended.

[0014] Preferably, the prediction obtains the maximum operating temperature corresponding to the device, and the specific prediction process is as follows: by calculating the formula The performance evaluation coefficient S of the equipment corresponding to each temperature test group is obtained by analysis. f , f is the number of each temperature test group, f = 1, 2, ....., p, p is any integer greater than 2, δ ′ is the standard vibration frequency of the set equipment, μ ′ is the standard operating speed of the set equipment, δ f is the vibration frequency of the device corresponding to the fth temperature test group, μ f is the operating speed of the equipment corresponding to the fth temperature test group, w1 and w2 are the weight factors of the set vibration frequency and the operating speed, respectively, 0<w1<1, 0<w2<1.

[0015] The performance evaluation coefficients of the temperatures corresponding to each temperature test group are arranged in order from small to large, and the performance evaluation coefficients of the temperatures corresponding to each temperature test group are compared with the preset performance evaluation coefficient thresholds. When the performance evaluation coefficient is less than the preset performance evaluation coefficient threshold for the first time during the comparison process, the temperature corresponding to the temperature test group is recorded as the highest temperature, so as to predict the corresponding maximum operating temperature of the equipment.

[0016] Preferably, the load simulation test has the following specific testing process: R1. Obtain the equipment load standard from the manual corresponding to the equipment, and preset the load difference according to the equipment load standard, and arrange the preset load differences in order from small to large, set corresponding load test groups, and simulate the operation of the equipment digital model in each load test group.

[0017] R2. Set each monitoring time period, and collect the operating parameters of the equipment digital model in each time period in each load test group, calculate the operating parameter difference, and when the operating parameter difference is less than or equal to the operating parameter difference allowed to float, continue to execute the corresponding load test of the equipment digital model in each load test group; when the operating parameter difference is greater than the operating parameter difference allowed to float, interrupt the test and check for abnormal conditions.

[0018] R3. When the simulated operation time of the digital model of the equipment in each load test group reaches the preset total load test time, the operation of the digital model of the equipment in each load test group is stopped, and the load test information corresponding to each load test group is collected. After the collection is completed, the load test is ended.

[0019] Preferably, the analysis obtains the highest operating load corresponding to the equipment, and the specific analysis process is as follows: by calculating the formula The stability evaluation coefficient Y of the equipment corresponding to each load test group is obtained by analysis. s , s is the number of each load test group, s = 1, 2, ....., a, a is any integer greater than 2, λ′ is the set operating pressure, ψ′ is the set operating speed, λ s is the operating pressure of the equipment corresponding to the sth load test group, ψ s is the operating speed of the equipment corresponding to the sth load test group, ι1 and ι2 are the weight factors of the set operating pressure and operating speed, respectively, 0<ι1<1, 0<ι2<1.

[0020] The stability assessment coefficients of the loads corresponding to each load test group are arranged in order from small to large, and the stability assessment coefficients of the loads corresponding to each load test group are compared with the preset stability assessment coefficient threshold. When the stability assessment coefficient is less than the preset stability assessment coefficient threshold for the first time during the comparison process, the load corresponding to the load test group is recorded as the highest load, and the maximum operating load corresponding to the equipment is obtained by analysis.

[0021] Preferably, the judgment obtains the operating safety and operating stability corresponding to the equipment, and the specific judgment process is as follows: the operating temperature corresponding to the current equipment is compared with the maximum operating temperature corresponding to the equipment. If the operating temperature corresponding to the current equipment is greater than or equal to the maximum operating temperature corresponding to the equipment, it is judged that the equipment operation is unsafe; if the operating temperature corresponding to the current equipment is less than the maximum operating temperature corresponding to the equipment, it is judged that the equipment operation is safe.

[0022] The operating load corresponding to the current device is compared with the maximum operating load corresponding to the device. If the operating load corresponding to the current device is greater than or equal to the maximum operating load corresponding to the device, the device operation is determined to be unstable. If the operating load corresponding to the current device is less than the maximum operating load corresponding to the device, the device operation is determined to be stable.

[0023] Preferably, it also includes a database, which is used to store device information, temperature test information, load test information and the operating temperature and operating load corresponding to the current device.

[0024] Compared with the prior art, the beneficial effect of the present invention is that: the present invention provides an enterprise production safety abnormality early warning system based on digital twins, which collects corresponding equipment information and converts it into data signals, thereby constructing a digital model of the equipment and conducting simulation tests, predicting the corresponding maximum operating temperature of the equipment, and judging the corresponding operating safety of the equipment. At the same time, the corresponding maximum operating load of the equipment is analyzed, and the corresponding operating stability of the equipment is judged, so as to implement timely production safety prevention and ensure the effective operation of production, solve the shortcomings of the current technology, and intelligently simulate enterprise production equipment through digital twin technology to ensure the accuracy of production safety analysis, so as to take remedial measures in time to improve safety, thereby improving enterprise production efficiency, extending equipment service life, reducing enterprise maintenance costs, reducing the workload of enterprise monitoring personnel, and improving enterprise production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 It is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] See also Figure 1 As shown, the enterprise safety production abnormality early warning system based on digital twins includes a production equipment acquisition module, a model simulation module based on digital twins, an equipment environment testing module, an equipment load testing module, an equipment operation monitoring module, an execution terminal and a database.

[0029] The production equipment acquisition module is respectively connected to the model simulation module based on digital twins and the database, the model simulation module based on digital twins is respectively connected to the equipment environment testing module and the equipment load testing module, the equipment environment testing module is respectively connected to the equipment operation monitoring module, the execution terminal and the database, and the equipment load testing module is respectively connected to the equipment operation monitoring module, the execution terminal and the database.

[0030] The production equipment acquisition module is used to monitor the corresponding equipment in the enterprise production, install various sensors on the equipment, collect equipment information, and convert the collected equipment information into data signals.

[0031] It should be noted that the equipment information includes operating pressure, vibration frequency, operating speed, and actual temperature.

[0032] It should also be noted that a pressure sensor is installed on the equipment to collect the corresponding operating pressure of the equipment, a vibration sensor is installed on the equipment, and the vibration sensor collects the vibration frequency of the equipment through the internal piezoelectric ceramic sheet and spring weight structure, a speed sensor is installed on the equipment to collect the corresponding operating speed of the equipment, and a temperature sensor is installed on the equipment to collect the corresponding actual temperature of the equipment.

[0033] The model simulation module based on digital twins is used to build a digital model of the equipment according to the data signals converted from the equipment information, and to perform temperature simulation tests and load simulation tests on the digital model of the equipment.

[0034] It should be noted that data preprocessing is performed based on the collected equipment information, the equipment information is integrated, and the equipment data information is monitored for duplication or missing. If there is a large amount of completely repeated equipment data, the corresponding duplicate data is deleted. If there is data missing, it is judged based on the total amount of data collected by the equipment and the number of missing data. When the total amount of data corresponding to the equipment is greater than the preset value and the missing number of indicators is less than the preset value, the retained data parameters corresponding to the equipment are arranged one by one, and the corresponding mode number is selected as the mean value of the data parameter corresponding to the equipment. The mean value of the data parameter corresponding to the equipment is inserted into the place where the data is missing, and then the total amount of data is added, and the data when the data is missing is added. The total amount is compared with the total amount of data after the data is inserted. If the difference between the two is small, the missing data is deleted or filled. When the total data amount is less than the preset value and the missing indicator is greater than the preset value, the retained data parameters corresponding to the device are added and the mean is calculated to obtain the mean of the data parameters corresponding to the device, and the mean of the data parameters corresponding to the device is inserted into the place where the data is missing. The total amount of data is added again, and the total amount of data when the data is missing is compared with the total amount of data after the data is inserted. If the difference between the two is large, the indicator is deleted to complete the data preprocessing. According to the corresponding device information after preprocessing, a digital model of the device is constructed using one of the machine learning or physical models.

[0035] The equipment temperature test module is used to set up each temperature test group, use the equipment digital model to perform temperature tests on each temperature test group, and collect temperature test information corresponding to each temperature test group, where the temperature test information includes vibration frequency and operating speed, and then predict the corresponding maximum operating temperature of the equipment.

[0036] It should be noted that a speed sensor is used to obtain the corresponding running speed of the device.

[0037] As an optional implementation, the temperature simulation test is performed, and the specific test process is as follows: F1. According to the actual temperature corresponding to the equipment, preset the temperature difference, and arrange the preset temperature differences in order from small to large, set corresponding temperature test groups, and simulate the operation of the equipment digital model in each temperature test group.

[0038] F2. Set each monitoring time period, and collect the operating parameters of the equipment digital model in each time period in each temperature test group, calculate the operating parameter difference, and when the operating parameter difference is less than or equal to the operating parameter difference allowed to float, continue to execute the corresponding temperature test of the equipment digital model in each temperature test group; when the operating parameter difference is greater than the operating parameter difference allowed to float, interrupt the test and check for abnormal conditions.

[0039] F3. When the simulated operation time of the equipment digital model in each temperature test group reaches the preset total temperature test time, the operation of the equipment digital model in each temperature test group is stopped, and the temperature test information corresponding to each temperature test group is collected. After the collection is completed, the temperature test is ended.

[0040] As an optional implementation, the prediction obtains the maximum operating temperature corresponding to the device. The specific prediction process is as follows: By calculating the formula The performance evaluation coefficient S of the equipment corresponding to each temperature test group is obtained by analysis. f , f is the number of each temperature test group, f = 1, 2, ....., p, p is any integer greater than 2, δ ′ is the standard vibration frequency of the set equipment, μ ′ is the standard operating speed of the set equipment, δ f is the vibration frequency of the device corresponding to the fth temperature test group, μ f is the operating speed of the equipment corresponding to the fth temperature test group, w1 and w2 are the weight factors of the set vibration frequency and the operating speed, respectively, 0<w1<1, 0<w2<1.

[0041] It should also be noted that the operating speed and vibration frequency corresponding to each operation of the equipment are obtained from the database, and the corresponding operating speed and vibration frequency of each time are added to obtain the total operating speed and total vibration frequency corresponding to the equipment. Through mean calculation, the total operating speed and total vibration frequency obtained by adding the equipment are divided by the number of times to obtain the average operating speed value and the average vibration frequency value, and the average operating speed value and the average vibration frequency value are used as the weight factor of the operating pressure and the weight factor of the vibration frequency.

[0042] The performance evaluation coefficients of the temperatures corresponding to each temperature test group are arranged in order from small to large, and the performance evaluation coefficients of the temperatures corresponding to each temperature test group are compared with the preset performance evaluation coefficient thresholds. When the performance evaluation coefficient is less than the preset performance evaluation coefficient threshold for the first time during the comparison process, the temperature corresponding to the temperature test group is recorded as the highest temperature, so as to predict the corresponding maximum operating temperature of the equipment.

[0043] The equipment load test module is used to set up each load test group, use the equipment digital model to perform load tests on each load test group, and obtain the load test information corresponding to each load test group, where the load test information includes operating pressure and operating speed, and then analyze and obtain the corresponding maximum operating load of the equipment.

[0044] As an optional implementation, the load simulation test has the following specific testing process: R1. Obtain the equipment load standard from the manual corresponding to the equipment, and preset the load difference according to the equipment load standard, and arrange the preset load differences in order from small to large, set corresponding load test groups, and simulate the operation of the equipment digital model in each load test group.

[0045] R2. Set each monitoring time period, and collect the operating parameters of the equipment digital model in each time period in each load test group, calculate the operating parameter difference, and when the operating parameter difference is less than or equal to the operating parameter difference allowed to float, continue to execute the corresponding load test of the equipment digital model in each load test group; when the operating parameter difference is greater than the operating parameter difference allowed to float, interrupt the test and check for abnormal conditions.

[0046] R3. When the simulated operation time of the digital model of the equipment in each load test group reaches the preset total load test time, the operation of the digital model of the equipment in each load test group is stopped, and the load test information corresponding to each load test group is collected. After the collection is completed, the load test is ended.

[0047] As an optional implementation, the analysis obtains the maximum operating load corresponding to the device. The specific analysis process is as follows: By calculating the formula The stability evaluation coefficient Y of the equipment corresponding to each load test group is obtained by analysis. s , s is the number of each load test group, s = 1, 2, ....., a, a is any integer greater than 2, λ′ is the set operating pressure, ψ′ is the set operating speed, λ s is the operating pressure of the equipment corresponding to the sth load test group, ψ s is the operating speed of the equipment corresponding to the sth load test group, ι1 and ι2 are the weight factors of the set operating pressure and operating speed, respectively, 0<ι1<1, 0<ι2<1.

[0048] It should be noted that the operating pressure and operating speed corresponding to the equipment at each operation are obtained from the database, and the corresponding operating pressure and operating speed of each time are added to obtain the total operating pressure and total operating speed corresponding to the equipment. Through mean calculation, the total operating pressure and total operating speed obtained by adding the equipment are divided by the number of times to obtain the average operating pressure value and the average operating speed value, and the average operating pressure value and the average operating speed value are used as the weight factors of the operating pressure and the weight factors of the operating speed.

[0049] The stability assessment coefficients of the loads corresponding to each load test group are arranged in order from small to large, and the stability assessment coefficients of the loads corresponding to each load test group are compared with the preset stability assessment coefficient threshold. When the stability assessment coefficient is less than the preset stability assessment coefficient threshold for the first time during the comparison process, the load corresponding to the load test group is recorded as the highest load, and the maximum operating load corresponding to the equipment is obtained by analysis.

[0050] The equipment operation monitoring module is used to obtain the operating temperature and operating load corresponding to the current equipment, and compare them with the corresponding maximum operating temperature and maximum operating load of the equipment to determine the corresponding operating safety and operating stability of the equipment.

[0051] As an optional implementation, the judgment obtains the operating safety and operating stability corresponding to the equipment, and the specific judgment process is as follows: the operating temperature corresponding to the current equipment is compared with the maximum operating temperature corresponding to the equipment. If the operating temperature corresponding to the current equipment is greater than or equal to the maximum operating temperature corresponding to the equipment, it is judged that the equipment operation is unsafe; if the operating temperature corresponding to the current equipment is less than the maximum operating temperature corresponding to the equipment, it is judged that the equipment operation is safe.

[0052] The operating load corresponding to the current device is compared with the maximum operating load corresponding to the device. If the operating load corresponding to the current device is greater than or equal to the maximum operating load corresponding to the device, the device operation is determined to be unstable. If the operating load corresponding to the current device is less than the maximum operating load corresponding to the device, the device operation is determined to be stable.

[0053] The execution terminal is used to issue early warning prompts when the equipment is unsafe or unstable, and display the corresponding maximum operating temperature and maximum operating load of the equipment.

[0054] The database is used to store device information, temperature test information, load test information, and the operating temperature and operating load corresponding to the current device.

[0055] The embodiment of the present invention collects corresponding equipment information and converts it into data signals, thereby constructing a digital model of the equipment and performing simulation tests to predict the maximum operating temperature corresponding to the equipment and determine the operating safety of the equipment. At the same time, the maximum operating load corresponding to the equipment is analyzed and the operating stability of the equipment is determined. This implements timely production safety prevention and ensures the effective operation of production, solves the deficiencies in current technologies, and intelligently simulates enterprise production equipment through digital twin technology to ensure the accuracy of production safety analysis, so that remedial measures can be taken in time to improve safety, thereby improving enterprise production efficiency, extending equipment service life, reducing enterprise maintenance costs, reducing the workload of enterprise monitoring personnel, and improving enterprise production efficiency.

[0056] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they shall all fall within the protection scope of the present invention.

Claims

1. The enterprise safety production abnormality early warning system based on digital twins is characterized by: include: The production equipment acquisition module is used to monitor the corresponding equipment in the enterprise production, install various sensors on the equipment, collect equipment information, and convert the collected equipment information into data signals; The model simulation module based on digital twins is used to build a digital model of the equipment according to the data signals converted from the equipment information, and to perform temperature simulation tests and load simulation tests on the digital model of the equipment; The equipment temperature test module is used to set each temperature test group, use the equipment digital model to perform temperature tests on each temperature test group, and collect temperature test information corresponding to each temperature test group, where the temperature test information includes vibration frequency and operating speed, and then predict the corresponding maximum operating temperature of the equipment; The temperature simulation test is carried out, and the specific test process is as follows: F1. Preset the temperature difference according to the actual temperature of the equipment, and arrange the preset temperature differences in order from small to large, set the corresponding temperature test groups, and simulate the operation of the equipment digital model in each temperature test group; F2. Set each monitoring time period, and collect the operating parameters of the equipment digital model in each time period in each temperature test group, calculate the operating parameter difference, and when the operating parameter difference is less than or equal to the operating parameter difference allowed to float, continue to perform the corresponding temperature test of the equipment digital model in each temperature test group; when the operating parameter difference is greater than the operating parameter difference allowed to float, interrupt the test and check for abnormal conditions; F3. When the simulated operation time of the equipment digital model in each temperature test group reaches the preset total temperature test time, the operation of the equipment digital model in each temperature test group is stopped, and the temperature test information corresponding to each temperature test group is collected. After the collection is completed, the temperature test is ended; The prediction obtains the maximum operating temperature corresponding to the device, and the specific prediction process is as follows: By calculating the formula The performance evaluation coefficient S of the equipment corresponding to each temperature test group is obtained by analysis. f , f is the number of each temperature test group, f = 1, 2, ....., p, p is any integer greater than 2, δ ′ is the standard vibration frequency of the set equipment, μ ′ is the standard operating speed of the set equipment, δ f is the vibration frequency of the device corresponding to the fth temperature test group, μ f is the operating speed of the equipment corresponding to the fth temperature test group, w1 and w2 are the weight factors of the set vibration frequency and operating speed, respectively, 0<w1<1, 0<w2<1; The performance evaluation coefficients of the temperatures corresponding to each temperature test group are arranged in order from small to large, and the performance evaluation coefficients of the temperatures corresponding to each temperature test group are compared with the preset performance evaluation coefficient thresholds. When the performance evaluation coefficient is less than the preset performance evaluation coefficient threshold for the first time during the comparison process, the temperature corresponding to the temperature test group is recorded as the highest temperature, so as to predict the corresponding maximum operating temperature of the device; The equipment load test module is used to set each load test group, use the equipment digital model to perform load tests on each load test group, and obtain the load test information corresponding to each load test group, where the load test information includes operating pressure and operating speed, and then analyze and obtain the corresponding maximum operating load of the equipment; The load simulation test, the specific test process is as follows: R1. Obtain the equipment load standard from the manual corresponding to the equipment, and preset the load difference according to the equipment load standard, and arrange the preset load differences in order from small to large, set the corresponding load test groups, and simulate the operation of the equipment digital model in each load test group; R2. Set each monitoring time period, and collect the operating parameters of the equipment digital model in each time period in each load test group, calculate the operating parameter difference, and when the operating parameter difference is less than or equal to the operating parameter difference allowed to float, continue to execute the corresponding load test of the equipment digital model in each load test group; when the operating parameter difference is greater than the operating parameter difference allowed to float, interrupt the test and check for abnormal conditions; R3. When the simulated operation time of the equipment digital model in each load test group reaches the preset total load test time, the operation of the equipment digital model in each load test group is stopped, and the load test information corresponding to each load test group is collected. After the collection is completed, the load test is ended; The analysis obtains the highest operating load corresponding to the device. The specific analysis process is as follows: By calculating the formula The stability evaluation coefficient Y of the equipment corresponding to each load test group is obtained by analysis. s , s is the number of each load test group, s = 1, 2, ....., a, a is any integer greater than 2, λ′ is the set operating pressure, ψ′ is the set operating speed, λ s is the operating pressure of the equipment corresponding to the sth load test group, ψ s is the operating speed of the equipment corresponding to the sth load test group, ι1 and ι2 are the weight factors of the set operating pressure and operating speed, respectively, 0<ι1<1, 0<ι2<1; The stability evaluation coefficients of the loads corresponding to each load test group are arranged in order from small to large, and the stability evaluation coefficients of the loads corresponding to each load test group are compared with the preset stability evaluation coefficient thresholds. When the stability evaluation coefficient is less than the preset stability evaluation coefficient threshold for the first time during the comparison process, the load corresponding to the load test group is recorded as the highest load, so as to obtain the highest operating load corresponding to the equipment through analysis; The equipment operation monitoring module is used to obtain the operating temperature and operating load corresponding to the current equipment, and compare them with the maximum operating temperature and maximum operating load corresponding to the equipment to determine the operating safety and operating stability of the equipment; The execution terminal is used to issue early warning prompts when the equipment is unsafe or unstable, and display the corresponding maximum operating temperature and maximum operating load of the equipment.

2. The enterprise safety production abnormality early warning system based on digital twins according to claim 1 is characterized in that: The judgment obtains the operation safety and operation stability corresponding to the equipment, and the specific judgment process is as follows: Compare the current operating temperature of the device with the maximum operating temperature of the device. If the current operating temperature of the device is greater than or equal to the maximum operating temperature of the device, the device is judged to be unsafe to operate. If the current operating temperature of the device is less than the maximum operating temperature of the device, the device is judged to be safe to operate. The operating load corresponding to the current device is compared with the maximum operating load corresponding to the device. If the operating load corresponding to the current device is greater than or equal to the maximum operating load corresponding to the device, the device operation is determined to be unstable. If the operating load corresponding to the current device is less than the maximum operating load corresponding to the device, the device operation is determined to be stable.

3. The enterprise safety production abnormality early warning system based on digital twins according to claim 1 is characterized in that: It also includes a database, which is used to store device information, temperature test information, load test information, and the operating temperature and operating load corresponding to the current device.

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