Industrial equipment production management system based on industrial internet

Abstract

The invention relates to the technical field of industrial equipment management, and discloses an industrial equipment production management system based on an industrial internet, which comprises a data acquisition end, a data transmission module, a data analysis center and a result output module, according to the invention, equipment operation parameters and environment data can be acquired, and the data can be effectively transmitted to a data analysis center from an acquisition end by using an industrial Ethernet or wireless sensor network protocol, so that a basis is provided for subsequent analysis. Through data preprocessing, correlation analysis, multi-dimensional state evaluation and the like in real time, the operation state and risk of the equipment are accurately judged. Meanwhile, environment influence evaluation can be carried out, the association problem of workshop environment data and equipment operation parameters can be clarified, abnormal inducements can be found in advance, and finally analysis results are displayed to managers, so that the managers can intuitively understand equipment conditions, reasonable decision making is facilitated, and efficient and stable production of industrial equipment is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial equipment management, and in particular to an industrial equipment production management system based on the Industrial Internet. Background Art

[0002] In the field of industrial production, the stable operation of industrial equipment is crucial to production efficiency, product quality and the economic benefits of enterprises. With the rapid development of industrial Internet technology, it has become an inevitable trend to realize the intelligent management of the production process of industrial equipment. Traditional industrial equipment management often relies on manual inspections and simple data recording, which has many disadvantages.

[0003] On the one hand, manual inspections are difficult to monitor the operating status of equipment in real time and comprehensively, and some potential fault hazards are easily missed. For example, for changes in key parameters such as temperature, pressure, and speed during equipment operation, manual inspections may have a long time interval and fail to capture abnormal fluctuations in parameters in a timely manner. On the other hand, manual analysis is difficult to conduct in-depth and accurate assessments of the complex correlations between equipment operating parameters and the impact of environmental factors on equipment operation. For example, the operating parameters of equipment may change subtly under different workshop ambient temperature and humidity conditions, and it is difficult for humans to accurately determine whether such changes are normal and whether they will cause equipment failures. Moreover, the lack of a systematic and automated management system to integrate data collection, transmission, analysis, and result display has led to inefficient industrial equipment management and insufficient decision-making basis.

[0004] Therefore, there is a need for an industrial equipment production management system based on the Industrial Internet that can automatically collect various types of data in the production process of industrial equipment, use Industrial Internet technology to efficiently transmit data, conduct a comprehensive assessment of the equipment operating status through scientific data analysis methods, and intuitively display the results to managers, thereby improving the intelligence level and reliability of industrial equipment management and ensuring the smooth progress of industrial production. Summary of the invention

[0005] The purpose of the present invention is to provide an industrial equipment production management system based on the industrial Internet, which solves the technical problems raised in the background technology.

[0006] The purpose of the present invention can be achieved through the following technical solutions: An industrial equipment production management system based on the industrial Internet, comprising: The data collection end is responsible for collecting target data in the production process of industrial equipment; The data transmission module is used to transmit the collected target data using industrial Internet technology; Data analysis center, used to evaluate the operating status of the transmitted data; The result output module is used to display the results obtained by the data analysis center to relevant managers.

[0007] As a further solution of the present invention: wherein, the data transmission module adopts industrial Ethernet or wireless sensor network protocol to transmit the target data from the data acquisition end to the data analysis center.

[0008] As a further solution of the present invention: the target data includes equipment operating parameters corresponding to temperature, pressure, and rotation speed, and environmental data including corresponding characteristics of workshop temperature and workshop humidity; The equipment operation parameters are collected by installing various sensors on the industrial equipment, and the environmental data are collected by installing various sensors in the workshop corresponding to the industrial equipment.

[0009] As a further solution of the present invention: the operating status evaluation method of the data analysis center is as follows: StepA1, data preprocessing: StepA1.1. Extract equipment operating parameters of various attributes within a specified period; The temperature, pressure and speed are marked as T respectively. i , P i and N i , i=1, 2, ... n, n represents the number of time acquisition points in the specified period; Among them, T i It is expressed as the temperature value at the position of the specified equipment component corresponding to the time sampling point in the specified cycle, P i It is expressed as the pressure value at the specified equipment component position corresponding to the sampling point at the specified time within the specified cycle, N i It is expressed as the speed value at the position of the specified equipment component corresponding to the time collection point within the specified cycle; StepA1.2, calculate the mean value and standard deviation of the operating parameters of the corresponding attribute equipment within the specified period; StepA1.3, subtract the corresponding average value from the equipment operating parameter of the corresponding attribute, and then divide the result by the standard deviation to obtain the equipment operating parameters after standardization of various attributes; StepA2, data association analysis: The correlation between the various attributes of the equipment operating parameters after standardization is calculated by the Pearson correlation coefficient formula, and the correlation between temperature and pressure, the correlation between temperature and speed, and the correlation between speed and pressure are recorded as R TP , R TN and R NP ; Step A3, Equipment status assessment: StepA3.1, parameter evaluation: StepA3.1.1, extract the preset upper and lower thresholds of the equipment operation parameters; which include the upper and lower thresholds corresponding to the temperature, pressure, and rotation speed respectively; The upper and lower temperature thresholds are marked as T max and T min , the upper and lower thresholds of pressure are marked as P max and P min , the upper and lower speed thresholds are marked as N max and N min ; StepA3.1.2, before standardization, according to T i , P i and N i The corresponding average values ​​PT, PP and PN are compared with their corresponding upper and lower thresholds, and the temperature state, pressure state and speed state of the equipment are determined based on the comparison results: StepA3.2, Comprehensive evaluation: StepA3.2.1. Extract the standardized temperature value T1 i , pressure value P1 i , speed value N1 i The corresponding average values ​​are PT1, PP1, and PN1 respectively; At the same time, the preset weight coefficients corresponding to temperature, pressure and speed are extracted and marked as WT, WP and WN; StepA3.2.2, through:

[0010] Calculate the comprehensive operating status index Z of the equipment TPN ; StepA3.2.3, the comprehensive operation status index Z TPN Compare with the preset comprehensive status threshold ZY: If Z TPN >ZY, it means that the equipment has abnormal operation risk and generates a comprehensive risk signal; If Z TPN ≤ZY, it means the equipment is operating normally; StepA3.3, Association Evaluation: Step A3.3.1. Extract R TP , R TN , R NP They correspond to the preset correlation threshold intervals, and are recorded as [RTP，min , R TP，max ]、[R TN，min , R TN，max ]、[R NP，min , R NP，max ]; StepA3.3.2, each R TP , R TN , R NP The data are compared with the corresponding preset correlation threshold intervals respectively, and the correlation problems with the operating parameters of various attribute devices are determined based on the comparison results.

[0011] As a further solution of the present invention: the result in StepA1.2 includes: pass:

[0012]

[0013] Calculate the mean PT and standard deviation BT of all temperatures Ti; pass:

[0014]

[0015] The calculated mean value PP and standard deviation BP of all pressures Pi; pass:

[0016]

[0017] Calculate the mean PN and standard deviation BN of all speeds Ni.

[0018] As a further solution of the present invention: the formula in StepA1.3 is as follows:

[0019]

[0020]

[0021] Where, T1 i is the standardized temperature value, P1 i is the standardized pressure value, N1 i is the normalized speed value.

[0022] As a further solution of the present invention: the comparison method in Step A3.1.2 is as follows: If T min≤PT≤T max , then the temperature status of the device is marked as normal; If PT<T min and PT>T max If any of the following is true, the temperature status of the device is marked as abnormal; If P min ≤PP≤P max , then the pressure status of the equipment is marked as normal; If PP<P min and PP>P max If any of the following is true, the pressure status of the device is marked as abnormal; If N min ≤PN≤N max , then the speed status of the device is marked as normal; If PN<N min and PN>N max If any of the following is true, the speed status of the device is marked as abnormal.

[0023] As a further solution of the present invention: the comparison method in Step A3.3.2 is as follows: If each R TP , R TN , R NP If they are respectively within the corresponding preset correlation threshold range, it means that the equipment is operating normally; If R TP <R TP，min , it means that the correlation between temperature and pressure is lower than normally expected; If R TP >R TP，max , it means that the correlation between temperature and pressure is too close and beyond the normal level; If R TN <R TN，min , it means that there is a problem of incoordination between the speed regulation and the thermal management system; If R TN >R TN，max , it indicates that the correlation between temperature and speed is unusually close and beyond the normal range; If R PN <R PN，min , it indicates that there is a fault in the pressure regulation system or the speed control system; If R PN >R PN，max , it means that the correlation between pressure and speed is close and exceeds the normal level.

[0024] As a further solution of the present invention: in Step A2, temperature and pressure are selected for correlation calculation in the following manner: First extract the standardized temperature value T1 i And the standardized pressure value P1 i ; Then calculate all T1 i The average value and all P1 i The average values ​​are recorded as PT1 and PP1 respectively; in:

[0025]

[0026] Afterwards via:

[0027] Calculate the correlation R between temperature and pressure TP ; By analogy with the calculation method of the correlation between temperature and pressure, the correlation between temperature and rotational speed and the correlation between rotational speed and pressure are obtained respectively.

[0028] As a further solution of the present invention: the data analysis center is also used to perform environmental impact assessment on the transmitted data; As a further solution of the present invention: the environmental impact assessment method is as follows: First, extract the workshop temperature and workshop humidity within the specified period, and calculate the standardized workshop temperature and workshop humidity according to the method of Step A1; Then, according to the method of Step A1, calculate the correlation between the standardized workshop temperature and the standardized temperature value, pressure value, and speed value, and record them as R WT , R WP , R WN , and calculate the correlation between the standardized workshop humidity and the standardized temperature value, pressure value, and speed value, and record them as R HT , R HP , R HN ; Then extract R WT , R WP , R WN , R HT , R HP , R HN They correspond to the preset correlation threshold intervals, and are recorded as [R WT，min , R WT，max ]、[R WP，min , R WP，max ]、[R WN，min , R WN，max ]、[R HT，min , RHT，max ]、[R HP，min , R HP，max ]、[R HN，min , R HN，max ]; Then each R WT , R WP , R WN , R HT , R HP , R HN The data are compared with the corresponding preset correlation threshold intervals respectively, and the correlation problem between the corresponding environment data of the workshop and the equipment operation parameters is determined based on the comparison results.

[0029] As a further solution of the present invention: the comparison method in the environmental impact assessment is as follows: If each R WT , R WP , R WN , R HT , R HP , R HN If they are respectively within the corresponding preset correlation threshold range, it means that the equipment is operating normally; If R WT <R WT，min , it indicates that the correlation between workshop temperature and equipment temperature is weak; If R WT >R WT，max , it indicates that the correlation between workshop temperature and equipment temperature is too strong; If R WP <R WP，min , it indicates that there is an unreasonable negative correlation between the workshop temperature and the equipment pressure; If R WP >R WP，max , it indicates that the influence of workshop temperature on equipment pressure exceeds the normal range; If R WN <R WN，min , it indicates that there is an abnormal negative correlation between the workshop temperature and the equipment speed; If R WN >R WN，max , it indicates that the workshop temperature has too great an impact on the equipment speed; If R HT <R HT，min , it indicates that there is a negative correlation between workshop humidity and equipment temperature that does not conform to normal physical laws; If R HT >R HT，max , it indicates that the workshop humidity has too great an impact on the equipment temperature; If R HP <R HP，min, it indicates that there is an abnormal negative correlation between workshop humidity and equipment pressure; If R HP >R HP，max , it indicates that the effect of workshop humidity on equipment pressure exceeds the normal range; If R HN <R HN，min , it indicates that there is an abnormal negative correlation between workshop humidity and equipment speed; If R HN >R HN，max , it indicates that the workshop humidity has too great an impact on the equipment speed.

[0030] Beneficial effects of the present invention: The present invention is provided with a data acquisition terminal, which can be responsible for collecting various target data in the production process of industrial equipment, including equipment operation parameters and environmental data, thereby realizing the comprehensive collection of industrial equipment production-related data.

[0031] The present invention, through the data transmission module, utilizes the industrial Ethernet or wireless sensor network protocol, can effectively transmit the collected target data from the data collection end to the data analysis center, ensures the timely transmission of the data, and provides a data basis for subsequent analysis and evaluation.

[0032] The present invention can analyze data characteristics more accurately by standardizing equipment operating parameters in a data analysis center through a detailed operating status evaluation method, such as a data preprocessing stage.

[0033] The present invention calculates the correlation between the operating parameters of devices with different attributes by means of data association analysis, and further understands the intrinsic relationship between the various parameters of the devices.

[0034] The present invention, in the equipment status assessment link, uses multi-dimensional assessment methods such as parameter assessment, comprehensive assessment and correlation assessment, which can not only determine the individual status of each operating parameter (temperature, pressure, speed) of the equipment, but also comprehensively consider the overall operating status index of the equipment, and judge whether the equipment has abnormal operation risks based on this, so that the assessment results are more comprehensive and accurate.

[0035] In addition to the operation status evaluation, the data analysis center of the present invention can also perform environmental impact evaluation on the transmitted data. By calculating the correlation between the workshop temperature, workshop humidity and equipment operation parameters and comparing them with the preset correlation threshold range, the correlation problem between the workshop environment data and the equipment operation parameters can be accurately determined, which helps to discover the abnormal operation of the equipment that may be caused by environmental factors in advance.

[0036] In the present invention, the result output module can display the results obtained by the data analysis center to relevant managers, so that the managers can intuitively and clearly understand the operating status of the equipment and the impact of the environment on the equipment, thereby providing strong support for them to make reasonable production management decisions, such as taking maintenance measures in time to prevent equipment failures, adjusting production environment parameters, etc., to ensure efficient and stable production of industrial equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present invention will be further described below in conjunction with the accompanying drawings.

[0038] Figure 1 It is a system block diagram of an industrial equipment production management system based on the industrial Internet in the present invention.

[0039] Figure 2 It is a module flow diagram of a data analysis center in an industrial equipment production management system based on the industrial Internet in the present invention. DETAILED DESCRIPTION

[0040] 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.

[0041] Embodiment 1 See also Figure 1 and Figure 2 As shown, the present invention is an industrial equipment production management system based on the industrial Internet, comprising: The data collection end is responsible for collecting target data in the production process of industrial equipment; The target data includes equipment operating parameters corresponding to temperature, pressure, and speed; The target data is collected by installing various sensors on industrial equipment; The data transmission module is used to transmit the collected target data using industrial Internet technology; It uses industrial Ethernet or wireless sensor network protocols to transmit target data from the data collection end to the data analysis center; Data analysis center, used to evaluate the operating status of the transmitted data; The operating status is evaluated as follows: StepA1, data preprocessing: StepA1.1. Extract equipment operating parameters of various attributes within a specified period; And mark the temperature, pressure and speed as T respectively.i , P i and N i , i=1, 2, ... n, n represents the number of time acquisition points in the specified period; Among them, T i It is expressed as the temperature value at the position of the specified equipment component corresponding to the time sampling point in the specified cycle, P i It is expressed as the pressure value at the specified equipment component position corresponding to the sampling point at the specified time within the specified cycle, N i It is expressed as the speed value at the position of the specified equipment component corresponding to the time collection point within the specified cycle; StepA1.2, calculate the mean value and standard deviation of the operating parameters of the corresponding attribute equipment within the specified period; Calculate the mean and standard deviation of all temperatures Ti and mark them as PT and BT respectively, calculate the mean and standard deviation of all pressures Pi and mark them as PP and BP respectively, calculate the mean and standard deviation of all rotation speeds Ni and mark them as PN and BN respectively; The formula is as follows:

[0042]

[0043]

[0044]

[0045]

[0046]

[0047] StepA1.3, subtract the corresponding average value from the equipment operating parameter of the corresponding attribute, and then divide the result by the standard deviation to obtain the equipment operating parameters after standardization of various attributes; Specifically:

[0048]

[0049]

[0050] Where, T1 i is the standardized temperature value, P1 i is the standardized pressure value, N1 i is the normalized speed value; StepA2, data association analysis: The correlation between the various attributes of the equipment operation parameters corresponding to the various attributes after standardization is calculated through the Pearson correlation coefficient formula; The specific method is as follows: StepA2.1, Temperature and pressure correlation: StepA2.1.1. Extract the standardized temperature value T1 i And the standardized pressure value P1 i ; StepA2.1.2, calculate all T1 separately i The average value and all P1 i The average values ​​are recorded as PT1 and PP1 respectively; in:

[0051]

[0052] StepA2.1.3, through:

[0053] Calculate the correlation R between temperature and pressure TP ; Among them, if R TP If R is close to 1, it indicates that there is a strong positive correlation between temperature and pressure. TP If R is close to -1, it indicates that there is a strong negative correlation between temperature and pressure. TP If it is close to 0, it means that the correlation between them is weak; StepA2.2, Temperature and speed correlation: StepA2.2.1. Extract the standardized speed value N1 i ; StepA2.2.2, calculate all N1 i The average value is recorded as PN1; in:

[0054] StepA2.2.3, through:

[0055] Calculate the correlation R between temperature and speed TN ; Among them, if R TN If R is close to 1, it indicates that there is a strong positive correlation between temperature and speed. TN If it is close to -1, it indicates that the negative correlation between temperature and speed is strong; if R TN If it is close to 0, it means that the correlation between them is weak; StepA2.3, pressure and speed correlation: StepA2.3.1. Extract all N1 i The average value of PN1 and all P1 i The average value of PP1; StepA2.3.2, through:

[0056] Calculate the correlation R between speed and pressure NP ; Among them, if R NP If it is close to 1, it indicates that there is a strong positive correlation between speed and pressure. NP If it is close to -1, it indicates that there is a strong negative correlation between speed and pressure. NP If it is close to 0, it means that the correlation between them is weak; Step A3, Equipment status assessment: StepA3.1, parameter evaluation: StepA3.1.1, extract the preset upper and lower thresholds of the equipment operation parameters; which include the upper and lower thresholds corresponding to the temperature, pressure, and rotation speed respectively; The upper and lower temperature thresholds are marked as T max and T min , the upper and lower thresholds of pressure are marked as P max and P min , the upper and lower speed thresholds are marked as N max and N min ; StepA3.1.2, before standardization, according to T i , P i and N i The corresponding average values ​​PT, PP and PN are compared with their corresponding upper and lower thresholds respectively: If T min ≤PT≤T max , then the temperature status of the device is marked as normal; If PT<T min and PT>T max If any of the following is true, the temperature status of the device is marked as abnormal; If P min ≤PP≤P max , then the pressure status of the equipment is marked as normal; If PP<P min and PP>P max If any of the following is true, the pressure status of the device is marked as abnormal; If N min ≤PN≤N max , then the speed status of the device is marked as normal; If PN<N min and PN>N max If any of the following is true, the speed status of the device is marked as abnormal; StepA3.2, Comprehensive evaluation: StepA3.2.1. Extract the standardized temperature value T1 i , pressure value P1 i , speed value N1 i The corresponding average values ​​are PT1, PP1, and PN1 respectively; At the same time, the preset weight coefficients corresponding to temperature, pressure and speed are extracted and marked as WT, WP and WN; StepA3.2.2, through:

[0057] Calculate the comprehensive operating status index Z of the equipment TPN ; StepA3.2.3, the comprehensive operation status index Z TPN Compare with the preset comprehensive status threshold ZY: If Z TPN >ZY, it means that the equipment has abnormal operation risk and generates a comprehensive risk signal; If Z TPN ≤ZY, it means the equipment is operating normally; StepA3.3, Association Evaluation: Step A3.3.1. Extract R TP , R TN , R NP They correspond to the preset correlation threshold intervals, and are recorded as [R TP，min , R TP，max ]、[R TN，min , R TN，max ]、[R NP，min , R NP，max ]; StepA3.3.2, each R TP , R TN , R NP Compare with the corresponding preset correlation threshold intervals respectively: If each R TP , R TN , R NP If they are respectively within the corresponding preset correlation threshold range, it means that the equipment is operating normally; If RTP <R TP，min , it means that the correlation between temperature and pressure is lower than normally expected; In this embodiment, this may indicate that there are a variety of problems with the device; for example, the device's cooling system may fail, causing the temperature to rise but the pressure to fail to change accordingly, such as a cooling fan failure, heat accumulation inside the device, and the temperature rising but the pressure not rising according to the normal thermal expansion and contraction relationship due to poor heat dissipation. In this case, R TP or the linkage between the pressure regulating device and the temperature sensing system fails, so that the pressure cannot be adjusted according to the temperature change, such as the control signal transmission failure of the pressure regulating valve, even if the temperature changes, the pressure will not respond, resulting in R TP Deviate from the normal range; If R TP >R TP，max , it means that the correlation between temperature and pressure is too close and beyond the normal level; In this example, this may be due to a blockage or overload condition inside the equipment. For example, in a hydraulic system, if a part of the oil pipe is blocked, when the temperature rises, the liquid expands but due to the obstruction of flow, the pressure will rise sharply, causing R TP Or the workload of the equipment suddenly increases significantly, causing the equipment to bear greater pressure at high temperature, and the pressure change range exceeds the normal design range, causing R TP Exceeding the upper threshold, in which case the device may face component damage or safety risks; If R TN <R TN，min , it means that there is a problem of incoordination between the speed regulation and the thermal management system; In this embodiment, for example, the speed controller fails, causing the motor speed to be unstable or unable to increase as expected, but the temperature of the device changes due to other factors, such as changes in ambient temperature or other auxiliary heating devices, which breaks the correlation between temperature and speed, R TN Or the cooling system of the equipment is too efficient, so the temperature is hardly affected even if the speed changes greatly. For example, in some specially designed cooling systems, if the coolant flow is too large or the cooling efficiency is too high, it may mask the normal effect of the speed change on the temperature, resulting in R TN Abnormally low, this situation may make the device unable to accurately feedback the operating status, affecting the performance and life of the device; If R TN >R TN，max , it indicates that the correlation between temperature and speed is unusually close and beyond the normal range; In this embodiment, this may be due to an abnormal increase in friction of mechanical parts inside the device; for example, the bearing is severely worn, and as the speed increases, the heat generated by friction increases sharply, causing a significant increase in the correlation between temperature and speed; or there may be a problem with the electromagnetic design of the motor, such as a short circuit in the motor winding, which causes excessive heat to be generated when the speed changes, exceeding the normal temperature-speed correlation range. This may cause the motor to overheat and burn out, seriously affecting the normal operation of the device; If R PN <R PN，min , it indicates that there is a fault in the pressure regulation system or the speed control system; In this embodiment, for example, a pressure regulating valve fails, resulting in the pressure not being able to be adjusted accordingly when the speed changes, or a transmission system fails, resulting in the speed change not being able to be effectively transmitted to the compression component, thereby weakening the correlation between pressure and speed, R PN In addition, leakage in the air intake or exhaust pipes may also cause this situation, because leakage will prevent the pressure from being built up normally with changes in speed, destroying the normal relationship between pressure and speed and affecting the working efficiency and performance of the equipment.

[0058] If R PN >R PN，max , it indicates that the pressure and speed are closely related and exceed the normal level; In this embodiment, this may be due to blockage or overload inside the equipment; for example, when the exhaust pipe of the compressor is partially blocked, as the speed increases, the gas discharge is blocked and the pressure increases abnormally, resulting in R PN Beyond the normal range; or the equipment's workload exceeds the design range, requiring a higher pressure to be generated at the same speed. For example, if the compressor is operated with an excessively large compression ratio, the correlation between pressure and speed will increase abnormally. This may cause excessive pressure on equipment components, leading to mechanical failure or safety accidents; The result output module is used to display the results obtained by the data analysis center to relevant managers.

[0059] This embodiment collects key equipment operating parameters such as temperature, pressure, and rotation speed in the production process of industrial equipment through the data acquisition terminal, and uses the data analysis center to perform multi-step operating status evaluation, including data preprocessing, data correlation analysis, and equipment status evaluation, so as to fully and deeply understand the operating status of the equipment; in the equipment status evaluation link, by comparing the average value of the equipment operating parameters with the preset upper and lower thresholds, it is possible to accurately determine whether the temperature, pressure, rotation speed and other parameters are within the normal range, and timely discover possible abnormal conditions in various parameters of the equipment, which is helpful to take maintenance measures in advance and reduce production losses caused by equipment failures; with the help of comprehensive evaluation, the comprehensive operating status index of the equipment is calculated and compared with the preset comprehensive status threshold, so as to judge whether the equipment has abnormal operation risks as a whole , providing managers with an intuitive basis for judging the overall operation of the equipment, making it easier to make reasonable production arrangements and equipment maintenance decisions; through data association analysis, the correlation between temperature and pressure, temperature and speed, and pressure and speed are calculated, and compared with the preset correlation threshold range, which can not only understand the correlation between the parameters, but also predict various possible equipment faults according to the abnormal situation of the correlation, such as cooling system failure, pressure regulating device failure, speed regulation failure, etc., which is helpful to detect and solve problems in a targeted manner and improve the reliability and stability of the equipment; the result output module displays the results obtained by the data analysis center to relevant managers, so that managers can understand the equipment operation evaluation results in a timely and clear manner, so that they can make effective management decisions based on this information and improve the efficiency of production management.

[0060] Embodiment 2 As the second embodiment of the present invention, when the present application is implemented, compared with the first embodiment, the technical solution of the present embodiment is different from that of the first embodiment only in that the present embodiment is based on the first embodiment: The target data also includes environmental data of corresponding characteristics of workshop temperature and workshop humidity; The data analysis center is also used to conduct environmental impact assessments on the transmitted data; The environmental impact assessment method is as follows: First, extract the workshop temperature and workshop humidity within the specified period, and calculate the standardized workshop temperature and workshop humidity according to the method of Step A1; Then, according to the method of Step A1, calculate the correlation between the standardized workshop temperature and the standardized temperature value, pressure value, and speed value, and record them as R WT , R WP , R WN , and calculate the correlation between the standardized workshop humidity and the standardized temperature value, pressure value, and speed value, and record them as RHT , R HP , R HN ; Then extract R WT , R WP , R WN , R HT , R HP , R HN They correspond to the preset correlation threshold intervals, and are recorded as [R WT，min , R WT，max ]、[R WP，min , R WP，max ]、[R WN，min , R WN，max ]、[R HT，min , R HT，max ]、[R HP，min , R HP，max ]、[R HN，min , R HN，max ]; Then each R WT , R WP , R WN , R HT , R HP , R HN Compare with the corresponding preset correlation threshold intervals respectively: If each R WT , R WP , R WN , R HT , R HP , R HN If they are respectively within the corresponding preset correlation threshold range, it means that the equipment is operating normally; If R WT <R WT，min , it indicates that the correlation between workshop temperature and equipment temperature is weak; In this embodiment, this may be because the thermal insulation performance of the equipment is good, or the influence of the heat source of the equipment itself on the temperature far exceeds the influence of the workshop temperature; for example, for some large-scale high-power equipment, the heat generated by the internal motor, processing tool, etc. is the main determinant of the equipment temperature, and the change of the workshop temperature has little effect on it; however, this situation may also be due to the failure of the temperature sensor of the equipment, resulting in the inability to accurately reflect the real influence of the workshop temperature on the equipment temperature; If R WT >R WT，max , it indicates that the correlation between workshop temperature and equipment temperature is too strong; In this embodiment, this may mean that the cooling system of the device cannot effectively cope with the changes in the workshop temperature, or the device is too sensitive to the ambient temperature; for example, in a high-temperature workshop environment, if the device does not dissipate heat well, the temperature of the device will rise sharply when the workshop temperature rises, causing R WT Too high; in this case, the equipment may malfunction due to overheating, affecting the normal production; If R WP <R WP，min , it indicates that there is an unreasonable negative correlation between the workshop temperature and the equipment pressure; In this embodiment, this may be caused by a special equipment structure or an abnormal physical phenomenon; for example, the pressure regulating device of the equipment may experience an abnormal increase in pressure when the workshop temperature decreases. This may be because the temperature decrease causes some components to shrink, affecting the normal operation of the pressure regulating system, causing the pressure and temperature to change inversely, and the correlation is too low; If R WP >R WP，max , it indicates that the influence of workshop temperature on equipment pressure exceeds the normal range; In this embodiment, this may be because the gas or liquid inside the equipment is more sensitive to temperature changes and is interrelated with the pressure system; for example, in a workshop with large temperature changes, the equipment containing gas medium will expand as the workshop temperature rises, causing the pressure of the equipment to increase. If this pressure change exceeds the normal tolerance range of the equipment, R WP It will be too high, which may cause safety hazards to the equipment, such as pipe rupture or seal failure; If R WN <R WN，min , it indicates that there is an abnormal negative correlation between the workshop temperature and the equipment speed; In this embodiment, this may be because the change in workshop temperature affects the transmission system of the equipment or the electromagnetic characteristics of the motor, causing the speed to change inversely with the temperature; for example, in a low temperature environment, the viscosity of the lubricating oil of the equipment increases, which increases the friction between the transmission parts, thereby increasing the motor load and reducing the speed. In this case, R WN It will be lower than the normal range, which may affect the production efficiency of the equipment; If R WN >R WN，max , it indicates that the workshop temperature has too great an impact on the equipment speed; In this embodiment, this may be because the motor or other power components of the equipment are sensitive to temperature; for example, in a high temperature environment, the winding resistance of the motor increases. If the motor does not have an effective temperature compensation mechanism, the motor speed will decrease, making the correlation between the workshop temperature and the equipment speed too high; this situation may cause the equipment to fail to run at the set speed, affecting product quality or production progress; If R HT <R HT，min , it indicates that there is a negative correlation between workshop humidity and equipment temperature that does not conform to normal physical laws; In this embodiment, this may be because the change in workshop humidity leads to some special physical processes inside the equipment, causing the temperature and humidity of the equipment to change inversely; for example, in some special electronic equipment, the decrease in humidity may cause static electricity to be generated, and static electricity discharge may cause the local temperature of the equipment to decrease. This situation is relatively rare, but if it occurs, it will cause R HT Abnormally low; If R HT >R HT，max , it indicates that the workshop humidity has too great an impact on the equipment temperature; In this embodiment, this may be because the heat dissipation process of the device is closely related to humidity; for example, in a high humidity environment, the evaporation of water on the surface of the device is affected, causing the device temperature to rise, making R HT Too high; in this case, the device may experience performance degradation or failure due to excessive temperature; If R HP <R HP，min , it indicates that there is an abnormal negative correlation between workshop humidity and equipment pressure; In this embodiment, this may be due to the fact that the change in workshop humidity affects certain material properties of the equipment, causing the pressure and humidity to change inversely; for example, in some equipment using special rubber seals, the decrease in humidity may make the rubber harder, resulting in better sealing performance and lower pressure. In this case, R HP It will be lower than the normal range, which may affect the normal working state of the equipment; If R HP >R HP，max , it indicates that the effect of workshop humidity on equipment pressure exceeds the normal range; In this embodiment, this may be because the humidity change affects the gas or liquid state inside the device; for example, in a high humidity environment, the gas inside the device may absorb moisture, causing the volume to change, thereby affecting the pressure, causing R HP Too high; this situation may interfere with the pressure control system of the equipment and cause equipment failure; If R HN <R HN，min, it indicates that there is an abnormal negative correlation between workshop humidity and equipment speed; In this embodiment, this may be because the change in workshop humidity affects the electrical performance or mechanical transmission performance of the equipment, resulting in the rotation speed and humidity changing inversely; for example, in a high humidity environment, the insulation performance of the motor decreases, which may cause the motor output power to decrease and the rotation speed to decrease; and when the humidity decreases, due to factors such as static electricity, the motor rotation speed may increase abnormally. In this case, R HN It will be lower than the normal range, which may affect the operational stability of the equipment; If R HN >R HN，max , it indicates that the workshop humidity has too great an impact on the equipment speed; In this embodiment, this may be because some key components of the device are very sensitive to humidity; for example, in some high-precision electronic devices, humidity changes may affect the performance of the circuit board, and then affect the control signal of the motor, resulting in large fluctuations in the speed, making R HN Too high. This situation may cause the equipment to be unable to accurately control the speed, affecting production quality.

[0061] This embodiment adds environmental data such as workshop temperature and workshop humidity as target data on the basis of the first embodiment, and adds an environmental impact assessment function in the data analysis center. This makes the evaluation of the equipment operation status more comprehensive, not only considering the equipment's own operating parameters, but also taking into account the impact of external environmental factors on the equipment operation; by calculating the correlation between the workshop temperature and workshop humidity and the equipment temperature, pressure, and rotation speed respectively, and comparing with the corresponding preset correlation threshold interval, it is possible to deeply analyze the specific correlation between environmental factors and the equipment operation status, such as discovering the sensitivity of the equipment to the ambient temperature and humidity and the possible abnormal correlation relationship, so as to take measures in advance to deal with the impact of environmental changes on the equipment operation, such as adjusting the equipment's heat dissipation measures, improving the equipment's sealing performance, etc., which helps to improve the equipment's adaptability and stability under different environmental conditions; based on the correlation analysis results between environmental factors and equipment operating parameters, it is possible to further troubleshoot equipment failure hazards caused by environmental factors, such as the equipment heat dissipation system cannot cope with changes in workshop temperature, the equipment pressure is affected by the workshop temperature or humidity beyond the normal range, and the equipment rotation speed is abnormal due to changes in ambient humidity, etc., timely discovering and solving these problems can effectively extend the service life of the equipment and ensure the normal progress of production.

[0062] Embodiment 3 As the third embodiment of the present invention, when the present application is specifically implemented, compared with the first and second embodiments, the technical solution of this embodiment is to combine the solutions of the first and second embodiments mentioned above for implementation.

[0063] This embodiment combines the solutions of embodiment one and embodiment two to combine the advantages of both. It can not only comprehensively and deeply evaluate the equipment operation status reflected by the equipment's own operating parameters, but also fully consider the impact of environmental factors on equipment operation, thus achieving all-round control of industrial equipment production management; it provides more complete equipment operation information for relevant managers, including the operation status of each parameter of the equipment itself, the correlation between each parameter, and the correlation between environmental factors and equipment operation. Based on this rich information, managers can make more scientific and reasonable production management decisions, such as reasonably arranging production plans, accurately formulating equipment maintenance strategies, etc., thereby effectively improving the overall level of industrial equipment production management and ensuring efficient and stable operation of the production process.

[0064] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0065] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An industrial equipment production management system based on the industrial Internet, characterized in that: include: The data collection end is responsible for collecting target data in the production process of industrial equipment; The data transmission module is used to transmit the collected target data using industrial Internet technology; Data analysis center, used to conduct operation status assessment and environmental impact assessment on the transmitted data; The operating status of the data analysis center is evaluated as follows: StepA1, data preprocessing: StepA1.

1. Extract equipment operating parameters of various attributes within a specified period; And mark the temperature, pressure and speed as T respectively. i , P i and N i , i=1, 2, ... n, n represents the number of time acquisition points in the specified period; Among them, T i It is expressed as the temperature value at the position of the specified equipment component corresponding to the time sampling point in the specified cycle, P i It is expressed as the pressure value at the specified equipment component position corresponding to the sampling point at the specified time within the specified cycle, N i It is expressed as the speed value at the position of the specified equipment component corresponding to the time collection point within the specified cycle; StepA1.2, calculate the mean value and standard deviation of the operating parameters of the corresponding attribute equipment within the specified period; It includes the mean and standard deviation of all temperatures Ti, which are denoted as PT and BT, the mean and standard deviation of all pressures Pi, which are denoted as PP and BP, and the mean and standard deviation of all rotational speeds Ni, which are denoted as PN and BN; StepA1.3, subtract the corresponding average value from the equipment operating parameter of the corresponding attribute, and then divide the result by the standard deviation to obtain the equipment operating parameters after standardization of various attributes; StepA2, data association analysis: The correlation between the various attributes of the equipment operating parameters after standardization is calculated by the Pearson correlation coefficient formula, and the correlation between temperature and pressure, the correlation between temperature and speed, and the correlation between speed and pressure are recorded as R TP , R TN and R NP ; Step A3, Equipment status assessment: StepA3.1, parameter evaluation: StepA3.1.1, extract the preset upper and lower thresholds of the equipment operation parameters; which include the upper and lower thresholds corresponding to the temperature, pressure, and rotation speed respectively; The upper and lower temperature thresholds are marked as T max and T min , the upper and lower thresholds of pressure are marked as P max and P min , the upper and lower speed thresholds are marked as N max and N min ; StepA3.1.2, standardize the pre- i , P i and N i The corresponding average values ​​PT, PP and PN are compared with their corresponding upper and lower thresholds, and the temperature state, pressure state and speed state of the equipment are determined based on the comparison results: StepA3.2, Comprehensive evaluation: StepA3.2.

1. Extract the standardized temperature value T1 i , pressure value P1 i , speed value N1 i The corresponding average values ​​are PT1, PP1, and PN1 respectively; At the same time, the preset weight coefficients corresponding to temperature, pressure and speed are extracted and marked as WT, WP and WN; StepA3.2.2, through: Calculate the comprehensive operating status index Z of the equipment TPN ; StepA3.2.3, the comprehensive operation status index Z TPN Compare with the preset comprehensive status threshold ZY: If Z TPN >ZY, it means that the equipment has abnormal operation risk and generates a comprehensive risk signal; If Z TPN ≤ZY, it means the equipment is operating normally; StepA3.3, Association Evaluation: Step A3.3.

1. Extract R TP , R TN , R NP They correspond to the preset correlation threshold intervals, and are recorded as [R TP，min , R TP，max ]、[R TN，min , R TN，max ]、[R NP，min , R NP，max ]; StepA3.3.2, each R TP , R TN , R NP Compare with the corresponding preset correlation threshold intervals respectively, and determine the correlation problems with the operating parameters of various attribute devices according to the comparison results; The result output module is used to display the results obtained by the data analysis center to relevant managers.

2. According to claim 1, an industrial equipment production management system based on industrial Internet is characterized in that: The formula in StepA1.3 is as follows: Where, T1 i is the standardized temperature value, P1 i is the standardized pressure value, N1 i is the normalized speed value.

3. According to the industrial equipment production management system based on industrial Internet according to claim 1, it is characterized in that: The comparison method in StepA3.1.2 is as follows: If T min ≤PT≤T max , then the temperature status of the device is marked as normal; If PT<T min and PT>T max If any of the following is true, the temperature status of the device is marked as abnormal; If P min ≤PP≤P max , then the pressure status of the equipment is marked as normal; If PP<P min and PP>P max If any of the following is true, the pressure status of the device is marked as abnormal; If N min ≤PN≤N max , then the speed status of the device is marked as normal; If PN<N min and PN>N max If any of the following is true, the speed status of the device is marked as abnormal.

4. According to claim 1, an industrial equipment production management system based on industrial Internet is characterized in that: The comparison method in StepA3.3.2 is as follows: If each R TP , R TN , R NP If they are respectively within the corresponding preset correlation threshold range, it means that the equipment is operating normally; If R TP <R TP，min , it means that the correlation between temperature and pressure is lower than normally expected; If R TP >R TP，max , it means that the correlation between temperature and pressure is too close and beyond the normal level; If R TN <R TN，min , it means that there is a problem of incoordination between the speed regulation and the thermal management system; If R TN >R TN，max , it indicates that the correlation between temperature and speed is unusually close and beyond the normal range; If R PN <R PN，min , it indicates that there is a fault in the pressure regulation system or the speed control system; If R PN >R PN，max , it means that the correlation between pressure and speed is close and exceeds the normal level.

5. The industrial equipment production management system based on the industrial Internet according to claim 1 is characterized in that: In StepA2, temperature and pressure are selected for correlation calculation as follows: First extract the standardized temperature value T1 i And the standardized pressure value P1 i ; Then calculate all T1 i The average value and all P1 i The average values ​​are recorded as PT1 and PP1 respectively; Afterwards via: Calculate the correlation R between temperature and pressure TP ; By analogy with the calculation method of the correlation between temperature and pressure, the correlation between temperature and rotational speed and the correlation between rotational speed and pressure are obtained respectively.

6. The industrial equipment production management system based on the industrial Internet according to claim 1 is characterized in that: The environmental impact assessment method is as follows: First, extract the workshop temperature and workshop humidity within the specified period, and calculate the standardized workshop temperature and workshop humidity according to the method of Step A1; Then, according to the method of Step A1, calculate the correlation between the standardized workshop temperature and the standardized temperature value, pressure value, and speed value, and record them as R WT , R WP , R WN , and calculate the correlation between the standardized workshop humidity and the standardized temperature value, pressure value, and speed value, and record them as R HT , R HP , R HN ; Then extract R WT , R WP , R WN , R HT , R HP , R HN They correspond to the preset correlation threshold intervals, and are recorded as [R WT，min , R WT，max ]、[R WP，min , R WP，max ]、[R WN，min , R WN，max ]、[R HT，min , R HT，max ]、[R HP，min , R HP，max ]、[R HN，min , R HN，max ]; Then each R WT , R WP , R WN , R HT , R HP , R HN The data are compared with the corresponding preset correlation threshold intervals respectively, and the correlation problem between the corresponding environment data of the workshop and the equipment operation parameters is determined based on the comparison results.

7. The industrial equipment production management system based on industrial Internet according to claim 1 is characterized in that: The comparison method in environmental impact assessment is as follows: If each R WT , R WP , R WN , R HT , R HP , R HN If they are respectively within the corresponding preset correlation threshold range, it means that the equipment is operating normally; If R WT <R WT，min , it indicates that the correlation between workshop temperature and equipment temperature is weak; If R WT >R WT，max , it indicates that the workshop temperature is strongly correlated with the equipment temperature; If R WP <R WP，min , it indicates that there is an unreasonable negative correlation between workshop temperature and equipment pressure; If R WP >R WP，max , it indicates that the influence of workshop temperature on equipment pressure exceeds the normal range; If R WN <R WN，min , it indicates that there is an abnormal negative correlation between workshop temperature and equipment speed; If R WN >R WN，max , it indicates that the workshop temperature has a great influence on the equipment speed; If R HT <R HT，min , it indicates that there is a negative correlation between workshop humidity and equipment temperature that does not conform to normal physical laws; If R HT >R HT，max , it indicates that the workshop humidity has too great an impact on the equipment temperature; If R HP <R HP，min , it indicates that there is an abnormal negative correlation between workshop humidity and equipment pressure; If R HP >R HP，max , it indicates that the influence of workshop humidity on equipment pressure exceeds the normal range; If R HN <R HN，min , it indicates that there is an abnormal negative correlation between workshop humidity and equipment speed; If R HN >R HN，max , it indicates that the workshop humidity has a great influence on the equipment speed.

8. The industrial equipment production management system based on the industrial Internet according to claim 1 is characterized in that: in, The data transmission module uses industrial Ethernet or wireless sensor network protocol to transmit the target data from the data acquisition end to the data analysis center.

9. The industrial equipment production management system based on the industrial Internet according to claim 1 is characterized in that: The target data includes equipment operating parameters corresponding to temperature, pressure, and speed, as well as environmental data including corresponding characteristics of workshop temperature and workshop humidity; The equipment operation parameters are collected by installing various sensors on the industrial equipment, and the environmental data are collected by installing various sensors in the workshop corresponding to the industrial equipment.

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