An air compressor operation safety supervision system based on data analysis

Abstract

The present invention belongs to the technical field of air compressor operation control, and specifically is an air compressor operation safety supervision system based on data analysis, including a supervision platform, an air compressor abnormality diagnosis module, an air output detection module, a cooling deviation evaluation module and a background supervision terminal; the present invention performs abnormal diagnosis on the operation process of the air compressor through the air compressor abnormality diagnosis module, and makes corresponding improvement measures when generating abnormal diagnosis early warning signals, thereby reducing the operation risk of the air compressor and ensuring the operation stability and operation safety of the air compressor, and when generating abnormal diagnosis qualified signals, reasonably analyzes and accurately judges the operation effect and cooling control performance of the air compressor through the air output detection module and the cooling deviation evaluation module, thereby further improving the safety and stability of the air compressor operation process, having a high degree of intelligence, and significantly reducing the difficulty of operation supervision of the air compressor.

Description

Technical Field

[0001] This invention relates to the field of air compressor operation control technology, specifically an air compressor operation safety monitoring system based on data analysis. Background Technology

[0002] An air compressor, also known as an air compressor, is an important industrial piece of equipment. Its main function is to convert the mechanical energy of a prime mover into gas pressure energy, thereby producing compressed air. Air compressors are widely used in various industrial fields, such as manufacturing, construction, food processing, power, and steel industries.

[0003] Currently, the safety supervision of air compressor operation mostly relies on manual inspection and the simple monitoring functions built into the equipment. This cannot achieve comprehensive and real-time safety supervision, which is not conducive to improving the safety and stability of the air compressor operation process. The low level of intelligence significantly increases the difficulty of operation supervision.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to provide a data analysis-based air compressor operation safety monitoring system, which solves the problems of existing technologies being unable to achieve comprehensive and real-time safety monitoring of air compressors, which is not conducive to improving the safety and stability of air compressor operation, having low intelligence level, and being difficult to monitor operation.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A data analysis-based air compressor operation safety monitoring system includes a monitoring platform, an air compressor anomaly diagnosis module, an air output detection module, a cooling deviation assessment module, and a back-end monitoring terminal. The air compressor anomaly diagnosis module is used to diagnose anomalies during the operation of the air compressor, generate anomaly diagnosis pass signals or anomaly diagnosis warning signals through analysis, and send the anomaly diagnosis warning signals to the back-end monitoring terminal via the monitoring platform, while sending the anomaly diagnosis pass signals to the air output detection module and the cooling deviation assessment module via the monitoring platform.

[0008] When the air output detection module receives a qualified abnormality diagnosis signal, it analyzes the air compressor's air compression output performance and generates either a normal air output signal or an abnormal air output signal. The abnormal air output signal is then sent to the back-end monitoring terminal via the monitoring platform. When the cooling deviation assessment module receives a qualified abnormality diagnosis signal, it analyzes the air compressor's cooling deviation status and generates either a qualified cooling signal or a cooling warning signal. The cooling warning signal is then sent to the back-end monitoring terminal via the monitoring platform. The back-end monitoring terminal issues corresponding warnings when it receives the abnormality diagnosis warning signal, the abnormal air output signal, or the cooling warning signal.

[0009] Furthermore, the monitoring platform is connected to the emergency judgment module. The emergency judgment module analyzes and determines whether the air compressor needs to be stopped, and generates a high emergency signal or a low emergency signal. The low emergency signal is sent to the air compressor abnormality diagnosis module through the monitoring platform, and the high emergency signal is sent to the back-end monitoring terminal through the monitoring platform. When the back-end monitoring terminal receives the high emergency signal, it issues a corresponding warning.

[0010] Furthermore, the specific analysis process of the urgency judgment module includes:

[0011] The start time of the corresponding operation of the air compressor is collected, and the time difference between the current time and the start time of the corresponding operation is calculated to obtain the real-time running time. The current running time is compared with the preset real-time running time threshold. If the real-time running time exceeds the preset real-time running time threshold, a high emergency signal for operation stop is generated; if the real-time running time does not exceed the preset real-time running time threshold, a precise analysis of the air compressor operation stop is performed.

[0012] Furthermore, the specific analysis process for precise analysis of air compressor operation and shutdown is as follows:

[0013] The system collects the end time of the air compressor's previous operation, calculates the stop time by comparing the start time of the corresponding operation with the end time of the previous operation, and calculates the average of all real-time operating power of the air compressor during the corresponding operation to obtain the power check value. The system also marks the total time during which the real-time operating power exceeds the preset real-time operating power threshold as the high load operating time value.

[0014] The operation and shutdown accuracy assessment value is obtained by numerically calculating the real-time running time, shutdown time, power detection value and high load running time value. The operation and shutdown accuracy assessment value is compared with the preset operation and shutdown accuracy assessment threshold. If the operation and shutdown accuracy assessment value exceeds the preset operation and shutdown accuracy assessment threshold, a high operation and shutdown emergency signal is generated; if the operation and shutdown accuracy assessment value does not exceed the preset operation and shutdown accuracy assessment threshold, a low operation and shutdown emergency signal is generated.

[0015] Furthermore, the specific operation process of the air compressor fault diagnosis module includes:

[0016] The outlet temperature of the air compressor head is collected, and the deviation of the outlet temperature from the preset suitable temperature standard value is marked as the head temperature detection value. The head temperature deviation value is calculated by averaging all head temperature detection values ​​within a unit time. In addition, the real-time vibration data of the air compressor head is collected, and the head vibration value is calculated by averaging all real-time vibration data within a unit time.

[0017] The system collects real-time noise data generated during the operation of the air compressor, compares the real-time noise data with a preset real-time noise data threshold, and determines that the air compressor is in an abnormal noise state if the real-time noise data exceeds the preset noise data threshold. The system also obtains the total duration of the air compressor in an abnormal noise state per unit time and marks it as the abnormal noise time value, and marks the maximum single duration of the abnormal noise state per unit time as the abnormal noise amplitude value.

[0018] The abnormal value of the air compressor is obtained by numerically calculating the compressor head temperature deviation value, compressor head vibration value, abnormal noise time value, and abnormal noise amplitude value. The abnormal value of the air compressor is compared with the preset abnormal value threshold. If the abnormal value of the air compressor exceeds the preset abnormal value threshold, an abnormal diagnosis warning signal is generated; if the abnormal value of the air compressor does not exceed the preset abnormal value threshold, an abnormal diagnosis qualified signal is generated.

[0019] Furthermore, the specific operation process of the air output detection module includes:

[0020] Several detection periods are set within a unit time. The analysis is used to determine whether the corresponding detection period is an abnormal transmission period. The number of abnormal transmission periods within a unit time is obtained and marked as abnormal transmission detection value. The average value of the output flow bias of all detection periods within a unit time is calculated to obtain the output flow analysis value. The average value of the output pressure bias of all detection periods within a unit time is calculated to obtain the output pressure analysis value.

[0021] The air output condition value is obtained by numerically calculating the abnormal output detection value, output flow analysis value, and output pressure analysis value. The air output condition value is then compared with a preset air output condition threshold. If the air output condition value exceeds the preset air output condition threshold, an abnormal air output signal is generated; if the air output condition value does not exceed the preset air output condition threshold, a normal air output signal is generated.

[0022] Furthermore, the specific analysis process for determining whether the corresponding detection period is an out-of-transmission period is as follows:

[0023] The system collects the air flow data output by the air compressor during the corresponding testing period and marks it as the output flow test value; it also collects the pressure value of the compressed air generated by the air compressor during the corresponding testing period and marks it as the output pressure test value; it marks the deviation value between the output flow test value and the current corresponding preset standard output flow test value as the output flow deviation value; and it marks the deviation value between the output pressure test value and the current corresponding preset standard output pressure test value as the output pressure deviation value.

[0024] The output current bias value and output voltage bias value are compared with the preset output current bias threshold and preset output voltage bias threshold respectively. If the output current bias value or output voltage bias value exceeds the corresponding preset threshold, the corresponding detection period is marked as an abnormal output period.

[0025] Furthermore, the specific operation process of the cooling deviation assessment module includes:

[0026] The average flow velocity of the coolant cooling the air compressor per unit time is collected and marked as the cooling delivery value. The deviation of the cooling delivery value from the set standard coolant delivery value is marked as the cooling delivery inspection value. Input liquid condition value and input liquid hazard value are obtained through input side liquid inspection analysis. The cooling delivery inspection value, input liquid condition value and input liquid hazard value are numerically calculated to obtain the cooling deviation evaluation value. The cooling deviation evaluation value is numerically compared with the preset cooling deviation threshold. If the cooling deviation evaluation value exceeds the preset cooling deviation threshold, a cooling warning signal is generated. If the cooling deviation evaluation value does not exceed the preset cooling deviation threshold, a cooling qualified signal is generated.

[0027] Furthermore, the specific analysis process for the input-side liquid analysis is as follows:

[0028] The system collects liquid information from the coolant input side of the air compressor, including temperature data, viscosity data, and impurity particle data of the input coolant. It then performs numerical calculations on the temperature data, viscosity data, and impurity particle data to obtain the actual liquid condition value. Finally, it calculates the average of all actual liquid condition values ​​within a unit of time to obtain the input liquid condition value, and marks the number of actual liquid condition values ​​exceeding the preset actual liquid condition threshold within a unit of time as the input liquid condition risk value.

[0029] Compared with the prior art, the beneficial effects of the present invention are:

[0030] 1. In this invention, the air compressor abnormality diagnosis module performs abnormality diagnosis on the operation process of the air compressor. When an abnormality diagnosis warning signal is generated, corresponding improvement measures are taken to reduce the operation risk of the air compressor. When an abnormality diagnosis qualified signal is generated, the air output detection module and the cooling deviation assessment module perform reasonable analysis and accurate judgment on the operation effect and cooling control performance of the air compressor, ensuring the safety and stability of the air compressor operation process. It has a high degree of intelligence and significantly reduces the difficulty of monitoring the operation of the air compressor.

[0031] 2. In this invention, the urgency judgment module analyzes the situation to determine whether the air compressor needs to be stopped. When a low urgency signal is generated, the air compressor abnormality diagnosis module performs abnormality diagnosis on the air compressor. When a high urgency signal is generated, the background monitoring terminal issues a corresponding warning to promptly stop the air compressor from running, avoid damage to the air compressor due to prolonged operation, improve the service life of the air compressor, and ensure its operational safety. Attached Figure Description

[0032] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0033] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0034] Figure 2 This is a system block diagram of Embodiment 2 of the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] Example 1: As Figure 1 As shown, the present invention proposes a data analysis-based air compressor operation safety monitoring system, which includes a monitoring platform, an air compressor anomaly diagnosis module, an air output detection module, a cooling deviation assessment module, and a back-end monitoring terminal;

[0037] The air compressor anomaly diagnosis module is used to diagnose anomalies during air compressor operation. It analyzes and generates either a qualified anomaly diagnosis signal or an anomaly diagnosis warning signal, and sends the warning signal to the back-end monitoring terminal via the monitoring platform. Upon receiving the warning signal, the back-end monitoring terminal issues a corresponding alert. This effectively monitors abnormal behavior during air compressor operation and provides timely feedback, allowing managers to take appropriate corrective measures, such as promptly suspending air compressor operation to reduce operational risks and ensure operational stability and safety. The specific operation process of the air compressor anomaly diagnosis module is as follows:

[0038] The outlet temperature of the air compressor head is collected, and the deviation of the outlet temperature from the preset suitable temperature standard value is marked as the head temperature detection value. The head temperature deviation value is calculated by averaging all head temperature detection values ​​within a unit time. In addition, the real-time vibration data of the air compressor head (i.e., the data value of the real-time vibration amplitude) is collected, and the head vibration value is calculated by averaging all real-time vibration data within a unit time.

[0039] The system collects real-time noise data (i.e., noise decibel values) generated during the operation of the air compressor. It compares the real-time noise data with a preset real-time noise data threshold. If the real-time noise data exceeds the preset noise data threshold, it determines that the air compressor is in an abnormal noise state. It obtains the total duration of the air compressor in an abnormal noise state per unit time and marks it as the abnormal noise time value. It also marks the maximum single duration of the abnormal noise state per unit time as the abnormal noise amplitude value.

[0040] Using the formula QN=a1 QW+a2 QR+(a3) QK+a4 The compressor abnormality value QN is obtained by numerically calculating the compressor head temperature deviation value QW, compressor head vibration value QR, abnormal noise duration value QK, and abnormal noise amplitude value QP. Among them, a1, a2, a3, and a4 are preset proportional coefficients with values ​​greater than zero. Furthermore, the larger the value of the compressor abnormality value QN, the more abnormal the operating condition of the air compressor is, and the greater the potential safety hazard.

[0041] The abnormal air compressor value QN is compared with the preset abnormal air compressor threshold. If the abnormal air compressor value QN exceeds the preset abnormal air compressor threshold, it indicates that the air compressor is operating abnormally and there is a significant safety hazard, so an abnormal diagnosis warning signal is generated. If the abnormal air compressor value QN does not exceed the preset abnormal air compressor threshold, it indicates that the air compressor is operating normally and there is a minor safety hazard, so an abnormal diagnosis qualified signal is generated.

[0042] The air compressor anomaly diagnosis module sends a qualified anomaly diagnosis signal to the air output detection module via the monitoring platform. Upon receiving the qualified signal, the air output detection module analyzes the air compressor's air compression output performance, generating either a normal or abnormal air output signal. The abnormal signal is then sent to the back-end monitoring terminal via the monitoring platform. Upon receiving the abnormal signal, the back-end monitoring terminal issues a corresponding warning. This allows for a reasonable analysis and accurate judgment of the air compressor's operating performance, enabling management personnel to promptly investigate and implement appropriate control measures to ensure the air compressor's optimal operating effect. The specific operation process of the air output detection module is as follows:

[0043] Several detection periods are set within a unit of time. The analysis is used to determine whether the corresponding detection period is an abnormal output period. Specifically, the air flow data output by the air compressor in the corresponding detection period is collected and marked as the output flow detection value, and the pressure value of the compressed air generated by the air compressor in the corresponding detection period is collected and marked as the output pressure detection value. The deviation value between the output flow detection value and the current corresponding preset standard output flow detection value is marked as the output flow deviation value, and the deviation value between the output pressure detection value and the current corresponding preset standard output pressure detection value is marked as the output pressure deviation value.

[0044] The output flow deviation value and output pressure deviation value are compared with the preset output flow deviation threshold and preset output pressure deviation threshold respectively. If the output flow deviation value or output pressure deviation value exceeds the corresponding preset threshold, it indicates that the air compressor's operating effect is poor during the corresponding detection period. Then, the corresponding detection period is marked as an abnormal output period.

[0045] The number of abnormal transmission periods within a unit time is obtained and marked as abnormal transmission detection values. The average value of the output flow deviation of all detection periods within a unit time is calculated to obtain the output flow analysis value. The average value of the output pressure deviation of all detection periods within a unit time is calculated to obtain the output pressure analysis value.

[0046] Through formula The air output condition value TM is obtained by numerically calculating the output flow detection value TP, the output flow separation value TF, and the output pressure separation value TG. Among them, ry1, ry2, and ry3 are preset proportional coefficients, and the values ​​of ry1, ry2, and ry3 are all positive numbers. Furthermore, the larger the value of the air output condition value TM, the worse the overall operating performance of the air compressor.

[0047] The air output condition value TM is compared with the preset air output condition threshold. If the air output condition value TM exceeds the preset air output condition threshold, it indicates that the overall operation of the air compressor is poor, and an air output abnormality signal is generated. If the air output condition value TM does not exceed the preset air output condition threshold, it indicates that the overall operation of the air compressor is good, and an air output normal signal is generated.

[0048] The air compressor anomaly diagnosis module sends a qualified anomaly diagnosis signal to the cooling deviation assessment module via the monitoring platform. Upon receiving the qualified anomaly diagnosis signal, the cooling deviation assessment module analyzes the air compressor's cooling deviation status, generating either a qualified cooling signal or a cooling warning signal. The cooling warning signal is then sent to the back-end monitoring terminal via the monitoring platform. Upon receiving the cooling warning signal, the back-end monitoring terminal issues a corresponding warning. This system analyzes and accurately reflects the air compressor's cooling control performance, enabling managers to take timely cooling control measures to ensure effective cooling and further improve the safety and stability of the air compressor's operation. The specific operation process of the cooling deviation assessment module is as follows:

[0049] The average flow velocity of the coolant cooling the air compressor per unit time is collected and marked as the cooling delivery value. The deviation of the cooling delivery value from the set standard coolant delivery value is marked as the cooling delivery test value. Liquid information on the coolant input side of the air compressor is collected, including the temperature data, viscosity data (the better the fluidity of the coolant, the smaller the viscosity data value), and impurity particle data (i.e., the amount of impurity particles in the input coolant).

[0050] Using the formula YL=(wq1) YW+wq2 YS+wq3 The temperature data YW, viscosity data YS, and impurity particle data YF are numerically calculated to obtain the actual liquid condition value YL. Among them, wq1, wq2, and wq3 are preset proportional coefficients with values ​​greater than zero. The larger the value of the actual liquid condition value YL, the worse the quality of the input coolant at the corresponding moment, which is not conducive to ensuring the cooling effect on the air compressor. The average value of all actual liquid conditions within a unit time is calculated to obtain the input liquid condition value, and the number of actual liquid conditions exceeding the preset actual liquid condition threshold within a unit time is marked as the input liquid condition risk value.

[0051] Through formula The cooling deviation value LP is obtained by numerically calculating the cooling input test value SY, the input liquid condition value SW, and the input liquid risk value SF. Among them, rg1, rg2, and rg3 are preset ratio coefficients, and the values ​​of rg1, rg2, and rg3 are all greater than zero. Furthermore, the larger the value of the cooling deviation value LP, the worse the overall cooling control status of the air compressor.

[0052] The cooling deviation value LP is compared with the preset cooling deviation threshold. If the cooling deviation value LP exceeds the preset cooling deviation threshold, it indicates that the overall cooling control of the air compressor is poor, and a cooling warning signal is generated. If the cooling deviation value LP does not exceed the preset cooling deviation threshold, it indicates that the overall cooling control of the air compressor is good, and a cooling qualified signal is generated.

[0053] Example 2: Figure 2 As shown, the difference between this embodiment and embodiment 1 is that the monitoring platform is connected to the operation urgency judgment module. The operation urgency judgment module analyzes and judges whether it is necessary to stop the operation of the air compressor, and generates an operation high emergency signal or an operation low emergency signal. The operation low emergency signal is sent to the air compressor abnormality diagnosis module through the monitoring platform. When the air compressor abnormality diagnosis module receives the operation low emergency signal, it performs abnormality diagnosis of the air compressor.

[0054] The high-emergency shutdown signal is sent from the monitoring platform to the back-end monitoring terminal. Upon receiving the high-emergency shutdown signal, the back-end monitoring terminal issues a corresponding warning to promptly stop the air compressor from operation, preventing damage caused by prolonged operation, extending the service life of the air compressor, and ensuring its operational safety. The specific analysis process of the shutdown urgency judgment module is as follows:

[0055] The start time of the corresponding operation of the air compressor is collected, and the time difference between the current time and the start time of the corresponding operation is calculated to obtain the real-time running time. The larger the value of the real-time running time, the more timely it is necessary to stop the air compressor to allow the air to rest. The current running time is compared with the preset real-time running time threshold. If the real-time running time exceeds the preset real-time running time threshold, a high emergency stop signal is generated.

[0056] If the real-time running time does not exceed the preset real-time running time threshold, then a precise analysis of the air compressor's operation and shutdown is performed. Specifically, the end time of the air compressor's previous adjacent operation is collected, the time difference between the start time of the corresponding operation and the end time of the previous adjacent operation is calculated to obtain the shutdown time, and the average of all real-time operating power collected during the corresponding operation process is calculated to obtain the power detection value. The total time during which the real-time operating power exceeds the preset real-time operating power threshold during the corresponding operation process is marked as the high load operating time value.

[0057] Through formula The real-time running time MY, the stop time MK, the power detection value MP, and the high load running time value MS are numerically calculated to obtain the operation and stop accuracy evaluation value MF. Among them, q1, q2, q3, and q4 are preset proportional coefficients, and the values ​​of q1, q2, q3, and q4 are all positive numbers. Furthermore, the larger the value of the operation and stop accuracy evaluation value MF, the more timely it is necessary to stop the air compressor.

[0058] The operation stop accuracy assessment value MF is compared with the preset operation stop accuracy assessment threshold. If the operation stop accuracy assessment value MF exceeds the preset operation stop accuracy assessment threshold, it indicates that the air compressor needs to be stopped in time, and a high operation stop emergency signal is generated. If the operation stop accuracy assessment value MF does not exceed the preset operation stop accuracy assessment threshold, it indicates that the air compressor does not need to be stopped in time, and a low operation stop emergency signal is generated.

[0059] The working principle of this invention is as follows: During operation, the air compressor anomaly diagnosis module performs anomaly diagnosis on the air compressor, generating either a qualified anomaly diagnosis signal or an anomaly diagnosis warning signal. When an anomaly diagnosis warning signal is generated, corresponding improvement measures are taken to reduce the operational risk of the air compressor and ensure its operational stability and safety. Furthermore, when a qualified anomaly diagnosis signal is generated, the air output detection module analyzes the air compressor's air compression output performance, and the cooling deviation assessment module analyzes the cooling deviation of the air compressor. When an air output anomaly signal or a cooling warning signal is generated, the back-end monitoring terminal issues a corresponding warning. This allows for reasonable analysis and accurate judgment of the air compressor's operational performance and cooling control, further improving the safety and stability of the air compressor's operation. It boasts a high degree of intelligence and significantly reduces the difficulty of monitoring the operation of the air compressor.

[0060] The above formulas are all dimensionless numerical calculations. These formulas are derived from software simulations using collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to actual conditions. The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. The preferred embodiments do not describe all details exhaustively, nor do they limit the invention to specific implementations. Obviously, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. An air compressor operation safety supervision system based on data analysis, characterized in that: It includes a supervision platform, an air compressor abnormality diagnosis module, an air output detection module, a cooling deviation evaluation module and a background supervision terminal; the air compressor abnormality diagnosis module is used to perform abnormality diagnosis on the air compressor during its operation, generate abnormality diagnosis qualified signals or abnormality diagnosis early warning signals through analysis, and send the abnormality diagnosis early warning signals to the background supervision terminal via the supervision platform, and send the abnormality diagnosis qualified signals to the air output detection module and the cooling deviation evaluation module via the supervision platform; When the air output detection module receives the abnormal diagnosis qualified signal, it analyzes the air compression output performance of the air compressor, generates an air output normal detection signal or an air output detection abnormal signal through the analysis, and sends the air output detection abnormal signal to the background monitoring end through the monitoring platform; When the cooling deviation assessment module receives an abnormal diagnosis qualified signal, it will analyze the cooling deviation status of the air compressor, generate a cooling qualified signal or a cooling warning signal through analysis, and send the cooling warning signal to the background supervision end through the supervision platform; the background supervision end will issue a corresponding warning when it receives an abnormal diagnosis warning signal, an air transmission inspection abnormality signal or a cooling warning signal; The specific operation process of the cooling deviation evaluation module includes: The average flow rate of the coolant used to cool the air compressor per unit time is collected and marked as the cooling delivery value, and the deviation value of the cooling delivery value compared to the set standard coolant delivery value is marked as the cooling delivery inspection value; And through input side liquid inspection analysis to obtain input liquid condition value and input liquid risk value, the cooling input inspection value, input liquid condition value and input liquid risk value are numerically calculated to obtain a cooling bias value, if the cooling bias value exceeds the preset cooling bias threshold, a cooling warning signal is generated; if the cooling bias value does not exceed the preset cooling bias threshold, a cooling qualified signal is generated; The specific analysis process of input side liquid inspection is as follows: Liquid information on the coolant input side of the air compressor is collected, including the temperature data, viscosity data and impurity particle data of the input coolant, the temperature data, viscosity data and impurity particle data are numerically calculated to obtain the liquid actual value, all liquid actual values ​​per unit time are averaged to obtain the input liquid condition value, and the number of liquid actual values ​​that exceed the preset liquid actual threshold per unit time is marked as the input liquid risk value.

2. The air compressor operation safety supervision system based on data analysis according to claim 1 is characterized in that: The supervision platform is communicated with the operation emergency judgment module. The operation emergency judgment module determines whether it is necessary to stop the operation of the air compressor through analysis, and generates a high emergency signal or a low emergency signal. The low emergency signal is sent to the air compressor abnormal diagnosis module via the supervision platform, and the high emergency signal is sent to the background supervision end via the supervision platform. When the background supervision end receives the high emergency signal, it will issue a corresponding warning.

3. The air compressor operation safety supervision system based on data analysis according to claim 2 is characterized in that: The specific analysis process of the operation emergency judgment module includes: The start time of the corresponding operation of the air compressor is collected, and the time difference between the current time and the start time of the corresponding operation is calculated to obtain the real-time operation time. The current operation time is numerically compared with the preset real-time operation time threshold. If the real-time operation time exceeds the preset real-time operation time threshold, a high emergency signal for stopping is generated; if the real-time operation time does not exceed the preset real-time operation time threshold, a precise analysis of the operation of the air compressor is performed.

4. The air compressor operation safety supervision system based on data analysis according to claim 3 is characterized in that: The specific analysis process of accurate analysis of air compressor operation is as follows: The end time of the last operation of the air compressor is collected, and the time difference between the start time of the corresponding operation of the air compressor and the end time of the last operation is calculated to obtain the stop time, and all the real-time operating powers of the air compressor during the corresponding operation are collected to calculate the average to obtain the power inspection value, and the total time during which the real-time operating power exceeds the preset real-time operating power threshold during the corresponding operation is marked as the high-load operation time value; The operation precision evaluation value is obtained by numerically calculating the real-time operation time, stop time, power inspection value and high-load operation time value, and the operation precision evaluation value is numerically compared with the preset operation precision evaluation threshold. If the operation precision evaluation value exceeds the preset operation precision evaluation threshold, an operation high emergency signal is generated; If the operation accuracy assessment value does not exceed the preset operation accuracy assessment threshold, an operation low emergency signal is generated.

5. The air compressor operation safety supervision system based on data analysis according to claim 1 is characterized in that: The specific operation process of the air compressor abnormality diagnosis module includes: The outlet temperature of the air compressor head is collected, and the deviation value of the outlet temperature of the head compared with the preset suitable temperature standard value is marked as the head temperature detection value, and the head temperature deviation value is obtained by averaging all the head temperature detection values ​​within a unit time; and the real-time vibration data of the air compressor head is collected, and the head vibration value is obtained by averaging all the real-time vibration data within a unit time; And collect the real-time noise data generated when the air compressor is running, compare the real-time noise data with the preset real-time noise data threshold, if the real-time noise data exceeds the preset noise data threshold, it is judged that the air compressor is in an abnormal noise state; obtain the total duration of the air compressor in the abnormal noise state per unit time and mark it as the abnormal noise condition value, and mark the maximum single duration of the abnormal noise state per unit time as the abnormal noise duration amplitude; The air compressor abnormal diagnostic value is obtained by numerically calculating the head temperature deviation value, head vibration value, abnormal sound time value and abnormal sound sustained amplitude, and the air compressor abnormal diagnostic value is numerically compared with the preset air compressor abnormal diagnostic threshold. If the air compressor abnormal diagnostic value exceeds the preset air compressor abnormal diagnostic threshold, an abnormal diagnosis warning signal is generated; if the air compressor abnormal diagnostic value does not exceed the preset air compressor abnormal diagnostic threshold, an abnormal diagnosis qualified signal is generated.

6. The air compressor operation safety supervision system based on data analysis according to claim 1 is characterized in that: The specific operation process of the air output detection module includes: A number of detection periods are set within a unit time, and analysis is performed to determine whether the corresponding detection period is an abnormal output period, the number of abnormal output periods within a unit time is obtained and marked as abnormal output detection values, and the output flow deviation values ​​of all detection periods within a unit time are averaged to obtain an output flow analysis value, and the output pressure deviation values ​​of all detection periods within a unit time are averaged to obtain an output pressure analysis value; The air output condition value is obtained by numerically calculating the abnormal output detection value, output flow rate value and output pressure value, and the air output condition value is numerically compared with the preset air output condition threshold. If the air output condition value exceeds the preset air output condition threshold, an air output detection abnormal signal is generated; if the air output condition value does not exceed the preset air output condition threshold, an air output detection normal signal is generated.

7. The air compressor operation safety supervision system based on data analysis according to claim 6 is characterized in that: The specific analysis process of determining whether the corresponding detection period is an abnormal output period is as follows: The air flow data output by the air compressor during the corresponding detection period is collected and marked as the output flow detection value, and the pressure value of the compressed air generated by the air compressor during the corresponding detection period is collected and marked as the output pressure detection value; the deviation value between the output flow detection value and the current corresponding preset standard output flow detection value is marked as the output flow deviation value, and the deviation value between the output pressure detection value and the current corresponding preset standard output pressure detection value is marked as the output pressure deviation value; The output flow deviation value and the output pressure deviation value are numerically compared with the preset output flow deviation threshold and the preset output pressure deviation threshold respectively. If the output flow deviation value or the output pressure deviation value exceeds the corresponding preset threshold, the corresponding detection period is marked as an abnormal output period.

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