Compressor cooling health management system and method

Abstract

The invention relates to the technical field of compressor maintenance, and discloses a compressor cooling health management system and method, and the system comprises a collection module which is used for collecting, storing and classifying the temperature and voltage data of a compressor, and a processing module which is used for carrying out the cleaning, normalization processing and feature extraction of the collected data, and building a compressor parameter monitoring model. The analysis module is used for carrying out fault diagnosis and performance evaluation on the compressor cooling system, the feedback control module is used for formulating a control strategy of the compressor cooling system and executing and adjusting the control strategy, and the parameter report is generated and displayed through a visual screen. Emergency shutdown caused by sudden failures is avoided, and the maintenance cost and the production loss are reduced.

Description

Technical Field

[0001] The invention relates to the technical field of compressor maintenance and discloses a compressor cooling health management system and method. Background Art

[0002] Although the health management of compressor cooling systems has made significant technological progress, it still faces many challenges and room for improvement, especially in terms of data processing, prediction accuracy, cost-effectiveness balance and technology integration, which require continuous optimization and improvement. The cost of establishing and maintaining a compressor health management system may be high, especially for small and medium-sized enterprises, which may require a balance between input and benefits. Most of the market adopts physical thermal management, and there is still room for improvement in the accuracy of prediction and diagnosis, especially in complex working conditions and changing environments. It is difficult to update the compressor temperature and voltage changes in real time, which greatly increases the compressor failure rate and reduces the life of the compressor, increasing the company's later maintenance costs. At this time, there is an urgent need for a compressor cooling health management system that can solve real-time monitoring and performance evaluation through an algorithm model and automatically generate control strategies.

[0003] For example, the existing Chinese patent with publication number CN115962590A provides an air-replenishing enthalpy-increasing energy storage thermal management system in which an intermediate refrigerant is first cooled and then evaporated, including: a compressor; a heat exchange device, which is configured to be connected between the compressor and the intermediate heat exchange device; the intermediate heat exchange device is configured to output the refrigerant in two ways, wherein the first part of the refrigerant returns to the intermediate heat exchange device to evaporate, to take away part of the heat of the second part of the refrigerant and then directly returns to the compressor, and the second part of the refrigerant cooperates with the heat exchange device to exchange heat and then returns to the compressor.

[0004] However, the above patent has the following problems: the thermal management system of the compressor mainly monitors data through physical monitoring, and controls temperature through physical cooling;

[0005] Although the above-mentioned refrigerant heat exchange system has optimized thermal management in hardware, its response speed and flexibility are not as good as those of the artificial intelligence control system when faced with rapidly changing operating conditions. In addition, the physical heat exchange system lacks this intelligent adaptive capability, making it difficult to perform dynamic optimization during operation. Summary of the invention

[0006] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0007] In order to solve the above technical problems, the main purpose of the present invention is to provide a compressor cooling health management system, comprising:

[0008] A collection module, comprising a sensor unit for collecting compressor temperature and voltage and a data classification unit for classifying and storing the collected data;

[0009] A processing module, including a data cleaning unit for processing data, a feature extraction unit for extracting features from the processed data, and a compressor parameter monitoring model for establishing a data algorithm model and performing real-time monitoring and prediction of the data;

[0010] An analysis module, including a diagnosis unit for performing fault diagnosis on data, a performance evaluation unit for evaluating the performance of the compressor, and a maintenance unit for controlling and maintaining the compressor;

[0011] The feedback control module includes a control unit for receiving a control strategy and adjusting the compressor cooling system through the control strategy, a report generation unit for generating a compressor cooling management system report, and a user interaction and feedback unit for displaying real-time data of the compressor and adjusting and controlling parameters of the compressor cooling system.

[0012] As a preferred solution of a compressor cooling health management system of the present invention, wherein:

[0013] The sensor unit includes a temperature sensor and a voltage sensor;

[0014] The temperature sensor is used to collect the temperature value of the compressor cooling system;

[0015] The voltage sensor is used to collect the operating voltage of the motor and electronic control system of the compressor cooling system.

[0016] As a preferred solution of a compressor cooling health management system of the present invention, wherein:

[0017] The sensor unit includes a temperature sensor and a voltage sensor;

[0018] The temperature sensor is used to collect the temperature value of the compressor cooling system;

[0019] The voltage sensor is used to collect the operating voltage of the motor and the electronic control system of the compressor cooling system.

[0020] As a preferred solution of a compressor cooling health management system of the present invention, wherein:

[0021] The data classification unit is used to preliminarily process and classify the collected sensor data, and the data classification includes summarizing according to the timestamp, sensor type and collection location dimensions;

[0022] The data cleaning unit includes identifying abnormal values ​​of the collected voltage data and temperature data, processing the abnormal values, and finally unifying the processed data into a unified format and unit to ensure that the data collected by different sensors can be compared and integrated.

[0023] As a preferred solution of a compressor cooling health management system of the present invention, wherein:

[0024] Through data normalization, the data is unified into a unified format and unit. The calculation expression is as follows:

[0025]

[0026] Where x is the voltage data and temperature data of the compressor cooling system after normalization, x 1 The voltage data and temperature data of the first time series of the first set of unprocessed data, x 2 The voltage data and temperature data of the second time series of the first set of unprocessed data, x 3 The voltage data and temperature data of the third time series of the first set of data, x n is the voltage data and temperature data of the nth time series of the first group of data, max{} is the maximum value function, and min{} is the minimum value function;

[0027] Detect outliers through standard deviation, automatically mark abnormal data points, and selectively remove abnormal data points based on preset thresholds;

[0028] The feature extraction unit is used to extract the processed voltage data and temperature data, and extract features for establishing a compressor parameter monitoring model. The calculation expression is as follows:

[0029]

[0030] Among them, λ is the compressor timing temperature characteristic value and voltage characteristic value, x' 1 is the voltage and current data at the first moment after processing, x' 2 is the voltage and current data at the second moment after processing, x' t are the voltage data and current data at the tth moment after processing, and Δx is the preset normal value of the voltage data and the current data.

[0031] As a preferred solution of a compressor cooling health management system of the present invention, wherein:

[0032] By establishing the compressor parameter monitoring model, the voltage and temperature and other parameters of the compressor are monitored in real time, so as to timely detect possible faults or abnormal conditions. If abnormal data appears, the abnormal data is analyzed by the diagnosis unit to determine the existence of the fault, and the potential fault is analyzed at the same time, and the voltage and temperature of the compressor cooling system are evaluated by the performance evaluation unit;

[0033] If the voltage and temperature of the compressor cooling system are at normal levels, no control maintenance instruction is output. If the voltage and temperature of the compressor cooling system are at abnormal levels, the voltage and temperature of the compressor cooling system are controlled by the maintenance unit and monitored by the compressor parameter monitoring model.

[0034] As a preferred solution of a compressor cooling health management system of the present invention, wherein:

[0035] The compressor parameter monitoring model, the calculation expression is as follows:

[0036]

[0037] Where, f(x) is the compressor parameter monitoring output, ω k is the hidden layer weight coefficient of the kth group of data, x k is the real-time data input of the compressor, Δb is the error coefficient, k is an ordinal number ranging from 1, 2, 3, ..., n, and n is any positive integer;

[0038] The diagnostic unit, the calculation expression is as follows:

[0039]

[0040] Wherein, η is the error value between the actual parameters of the compressor cooling system and the theoretical parameters of the compressor cooling system, is the value of the pth time sequence in the mth group of compressor actual voltage and temperature data, f 0 (x) is the parameter data of the normal operation of the compressor cooling system, and M is the total number of groups.

[0041] As a preferred solution of a compressor cooling health management system of the present invention, wherein:

[0042] The performance evaluation unit, the calculation expression is as follows:

[0043]

[0044] Where ΔT is the compressor cooling system health performance coefficient, f(x) is the compressor parameter monitoring output, and x k is the real-time data input of the compressor, ω is the weight coefficient of the current input data in the hidden layer, and ΔE is the expected performance of the compressor cooling system;

[0045] The performance evaluation unit is used to evaluate and monitor the performance of the compressor and analyze various performance indicators;

[0046] The maintenance unit analyzes the compressor maintenance strategy and identifies potential problems of the equipment through historical data, real-time monitoring results and performance evaluation results;

[0047] As a preferred solution of a compressor cooling health management system of the present invention, wherein:

[0048] The control unit includes receiving control strategies, executing control strategies and adjusting control strategies;

[0049] The receiving control strategy is used to obtain the control strategy from the compressor parameter monitoring model and the diagnostic unit;

[0050] The execution control strategy is used to execute the compressor cooling system control strategy;

[0051] The control strategy is adjusted by receiving the performance parameter output by the performance evaluation unit to adjust the compressor cooling system parameters and the control strategy.

[0052] As a preferred solution of a compressor cooling health management system of the present invention, wherein:

[0053] The report generation unit includes data listing, analysis and aggregation, and report generation and distribution;

[0054] The data list is used to record the operation data of the compressor and its cooling system monitored by the sensor unit and the compressor parameter monitoring model;

[0055] The analysis and summary are used to analyze the recorded data and generate reports on system performance, fault diagnosis, and maintenance requirements;

[0056] The report generation and distribution is used to automatically generate regular and on-demand system operation reports;

[0057] The user interaction and feedback unit includes real-time data display, parameter adjustment and feedback mechanisms.

[0058] A compressor cooling health management method is implemented based on the above compressor cooling health management system, comprising:

[0059] S1. Collect various parameters of the compressor through sensors;

[0060] S2, cleaning the collected data, and extracting features after cleaning;

[0061] S3, establishing a parameter monitoring model, and evaluating various parameters and performances of the compressor through the parameter monitoring model;

[0062] S4. Diagnose the faulty parts and give maintenance suggestions;

[0063] S5. Analyze the monitoring results, automatically adjust the operating parameters of the compressor, and issue maintenance warnings to maintenance personnel;

[0064] S6. Query system status and receive warning information through the user interface, collect user opinions and suggestions through the user feedback mechanism, and continuously optimize the system.

[0065] Beneficial effects of the present invention:

[0066] The present invention not only improves the operating efficiency and reliability of the compressor, but also significantly reduces operating costs and improves overall safety. By real-time monitoring of key performance parameters of the compressor (such as temperature, pressure, flow rate, etc.), the system can ensure that the equipment operates in the best working condition.

[0067] The present invention significantly improves energy utilization efficiency and compression efficiency by intelligently adjusting operating parameters to adapt to different working conditions. By using data analysis and machine learning technology, the system can predict potential failures and performance degradation, thereby achieving preventive maintenance.

[0068] The present invention is carried out before a fault occurs, avoiding emergency shutdowns caused by sudden faults, reducing maintenance costs and production losses. The real-time monitoring and early warning system can promptly detect potential safety hazards, such as overheating, leakage, etc., so that preventive measures can be taken to avoid accidents and ensure the safety of the production site. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0070] Figure 1 A system composition diagram of a compressor cooling health management system according to the present invention;

[0071] Figure 2 This is a flow chart of a compressor cooling health management method of the present invention. DETAILED DESCRIPTION

[0072] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0073] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0074] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0075] Embodiment 1:

[0076] like Figure 1 As shown, a compressor cooling health management system comprises:

[0077] A collection module, comprising a sensor unit for collecting compressor temperature and voltage and a data classification unit for classifying and storing the collected data;

[0078] Wherein, the sensor unit includes a temperature sensor and a voltage sensor;

[0079] The temperature sensor is used to collect the temperature value of the compressor cooling system, and the fast response capability and high sensitivity of the temperature sensor ensure that the real-time temperature changes are reflected;

[0080] The voltage sensor is used to collect the working voltage of the motor and electronic control system of the compressor cooling system. The voltage sensor can measure AC or DC voltage to ensure power supply stability and safety. At the same time, the voltage sensor should have high precision and low noise characteristics to provide reliable voltage data.

[0081] Furthermore, the data classification unit uses an embedded processor or microcontroller to perform preliminary processing and classification of the collected sensor data. Data classification includes summarizing by timestamp, sensor type, collection location and other dimensions to achieve local data caching and classified storage functions to ensure that data is not lost when communication is interrupted. The data classification unit also has data compression and encryption functions to improve data storage efficiency and security.

[0082] A processing module, including a data cleaning unit for processing data, a feature extraction unit for extracting features from the processed data, and a compressor parameter monitoring model for establishing a data algorithm model and performing real-time monitoring and prediction of the data;

[0083] The data cleaning unit includes identifying abnormal values ​​of the collected voltage and temperature data, processing the abnormal values, and finally unifying the processed data into a unified format and unit to ensure that the data collected by different sensors can be compared and integrated;

[0084] Furthermore, the data is normalized to a unified format and unit, and the calculation expression is as follows:

[0085]

[0086] Where x is the voltage data and temperature data of the compressor cooling system after normalization, x 1 The voltage data and temperature data of the first time series of the first set of unprocessed data, x 2 The voltage data and temperature data of the second time series of the first set of unprocessed data, x 3 The voltage data and temperature data of the third time series of the first set of data, x n is the voltage data and temperature data of the nth time series of the first group of data, max{} is the maximum value function, and min{} is the minimum value function;

[0087] Furthermore, outliers are detected through standard deviation, abnormal data points are automatically marked, and abnormal data points are selectively removed based on a preset threshold;

[0088] The feature extraction unit is used to extract the processed voltage data and temperature data and extract features for establishing a compressor parameter monitoring model. The calculation expression is as follows:

[0089]

[0090] Among them, λ is the compressor timing temperature characteristic value and voltage characteristic value, x' 1 is the voltage and current data at the first moment after processing, x' 2 is the voltage and current data at the second moment after processing, x' t is the voltage data and current data at the tth moment after processing, Δx is the preset normal value of the voltage data and the current data;

[0091] An analysis module, including a diagnosis unit for performing fault diagnosis on data, a performance evaluation unit for evaluating the performance of the compressor, and a maintenance unit for controlling and maintaining the compressor;

[0092] By establishing a compressor parameter monitoring model, the voltage and temperature of the compressor are monitored in real time to detect possible faults or abnormal conditions in a timely manner. If abnormal data appears, the abnormal data is analyzed by the diagnosis unit to determine the existence of the fault and analyze the potential fault. The voltage and temperature of the compressor cooling system are evaluated by the performance evaluation unit.

[0093] If the voltage and temperature of the compressor cooling system are at normal levels, no control maintenance instruction is output; if the voltage and temperature of the compressor cooling system are at abnormal levels, the voltage and temperature of the compressor cooling system are controlled by the maintenance unit and monitored by the compressor parameter monitoring model;

[0094] The compressor parameter monitoring model, the calculation expression is as follows:

[0095]

[0096] Where, f(x) is the compressor parameter monitoring output, ω k is the hidden layer weight coefficient of the kth group of data, x k is the real-time data input of the compressor, Δb is the error coefficient, k is an ordinal number ranging from 1, 2, 3, ..., n, and n is any positive integer;

[0097] Diagnostic unit, the calculation expression is as follows:

[0098]

[0099] Wherein, η is the error value between the actual parameters of the compressor cooling system and the theoretical parameters of the compressor cooling system, is the value of the pth time sequence in the mth group of compressor actual voltage and temperature data, f 0 (x) is the parameter data of the normal operation of the compressor cooling system, and M is the total number of groups;

[0100] Performance evaluation unit, the calculation expression is as follows:

[0101]

[0102] Where ΔT is the compressor cooling system health performance coefficient, f(x) is the compressor parameter monitoring output, and x k is the real-time data input of the compressor, ω is the weight coefficient of the current input data in the hidden layer, and ΔE is the expected performance of the compressor cooling system;

[0103] The performance evaluation unit is designed to evaluate and monitor the performance of the compressor. It analyzes various performance indicators such as power consumption, efficiency, temperature, vibration, etc. and compares them with preset performance standards. In this way, the performance evaluation unit can help operators understand the working status of the compressor, detect performance degradation or abnormal conditions in a timely manner, and provide data support for formulating improvement plans.

[0104] The maintenance unit analyzes the compressor maintenance needs and identifies potential equipment problems based on historical data, real-time monitoring results, and performance evaluation results, and provides early warning for repair and maintenance work. This helps reduce unexpected downtime, improve maintenance efficiency, and optimize maintenance plans, thereby reducing maintenance costs.

[0105] The feedback control module includes a control unit for receiving a control strategy and adjusting the compressor cooling system through the control strategy, a report generation unit for generating a compressor cooling management system report, and a user interaction and feedback unit for displaying real-time data of the compressor and adjusting and controlling parameters of the compressor cooling system.

[0106] The control unit includes receiving control strategy, executing control strategy and adjusting control strategy;

[0107] The receiving control strategy obtains the control strategy from the compressor parameter monitoring model and the diagnostic unit of the system. The control strategy includes adjusting the operating parameters of the cooling system (such as temperature set point, voltage set point, etc.) to optimize the performance of the compressor.

[0108] The execution control strategy is applied to the compressor cooling system to achieve precise control of the cooling process by adjusting the control devices (such as valves, pumps, fans, etc.).

[0109] The report generation unit includes data listing, analysis and summary, and report generation and distribution;

[0110] Collect operating data of the compressor and its cooling system from various sensors and monitoring equipment, including temperature, pressure, flow, vibration, etc.

[0111] The data list is used to record the operating data of the compressor and its cooling system monitored by the sensor unit and the compressor parameter monitoring model.

[0112] Analysis and Summary Analyze the collected data to generate reports on system performance, fault diagnosis, maintenance requirements, etc.

[0113] Report generation and distribution Automatically generate regular or on-demand system operation reports. These reports can be daily, weekly, monthly, or special reports after specific events (such as failures). Distribute to relevant operations and management personnel via email, management system, or physical printing.

[0114] The user interaction and feedback unit includes real-time data display, parameter adjustment and feedback mechanisms;

[0115] A user interface (UI) is provided to display the real-time data of the compressor cooling system. The interface usually includes various charts, dashboards and alarm information to intuitively reflect the current status of the system.

[0116] The interface allows users to manually adjust cooling system control parameters such as set temperature, flow rate, etc. These adjustments can take effect immediately to address specific operational needs or in response to system alarms.

[0117] The user interface provides a feedback mechanism that allows operators to record and report system problems, operational suggestions, or adjustment effects. This feedback information can be used for subsequent improvement and optimization of the system.

[0118] The feedback control module ensures that the compressor cooling health management system can operate efficiently and reliably, and can respond to various operating requirements and fault conditions in a timely manner, improving the reliability of the system.

[0119] Embodiment 2:

[0120] like Figure 2 As shown, a compressor cooling health management method includes:

[0121] S1. Collect various parameters of the compressor through sensors;

[0122] S2, cleaning the collected data, and extracting features after cleaning;

[0123] S3, establishing a parameter monitoring model, and evaluating various parameters and performances of the compressor through the parameter monitoring model;

[0124] S4. Diagnose the faulty parts and give maintenance suggestions;

[0125] S5. Analyze the monitoring results, automatically adjust the operating parameters of the compressor, and issue maintenance warnings to maintenance personnel;

[0126] S6. Query system status and receive warning information through the user interface, collect user opinions and suggestions through the user feedback mechanism, and continuously optimize the system.

[0127] Embodiment three:

[0128] In this embodiment, a computer device is provided, including a memory and a processor, the memory is used to store instructions, and the processor is used to execute the instructions, so that the device implements the above-mentioned compressor cooling health management method.

[0129] Embodiment 4:

[0130] A computer-readable storage medium having a rewritable computer program stored thereon;

[0131] When the computer program runs on a computer device, the computer device is caused to execute the above-mentioned compressor cooling health management method.

[0132] Importantly, it should be noted that the construction and arrangement of the present application shown in a plurality of different exemplary embodiments are only exemplary. Although only two embodiments are described in detail in this disclosure, it should be readily understood by those who refer to this disclosure that many modifications are possible, for example, the size, scale, structure, shape and ratio of various elements, and parameter values ​​(e.g., temperature, pressure, etc.), installation arrangement, use of materials, color, directional changes, etc., without substantially departing from the novel teachings and advantages of the subject matter described in the application. For example, the element shown as integrally formed can be composed of multiple parts or elements, the position of the element can be inverted or otherwise changed, and the nature or number or position of the discrete element can be changed or changed. Therefore, all such modifications are intended to be included in the scope of the present invention. The order or sequence of any process or method step can be changed or reordered according to an alternative embodiment. Any "device plus function" clause is intended to cover the structure of the execution function described in this article, and is not only structurally equivalent but also equivalent structure. Without departing from the scope of the present invention, other replacements, modifications, changes and omissions can be made in the design, operating conditions and arrangement of the exemplary embodiment. Therefore, the invention is not limited to a specific embodiment, but extends to numerous modifications still falling within the scope of the appended claims.

[0133] Additionally, in order to provide a concise description of exemplary embodiments, all features of an actual embodiment (ie, those features that are not relevant to the best mode presently contemplated for carrying out the invention or those that are not relevant to implementing the invention) may not be described.

[0134] It should be understood that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but for those of ordinary skill having the benefit of this disclosure, the development effort will be a routine task of design, fabrication, and production without undue experimentation.

[0135] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A compressor cooling health management system, characterized in that: include: A collection module, comprising a sensor unit for collecting compressor temperature and voltage and a data classification unit for classifying and storing the collected data; A processing module, including a data cleaning unit for processing data, a feature extraction unit for extracting features from the processed data, and a compressor parameter monitoring model for establishing a data algorithm model and performing real-time monitoring and prediction of the data; An analysis module, including a diagnosis unit for performing fault diagnosis on data, a performance evaluation unit for evaluating the performance of the compressor, and a maintenance unit for controlling and maintaining the compressor; The feedback control module includes a control unit for receiving a control strategy and adjusting the compressor cooling system through the control strategy, a report generation unit for generating a compressor cooling management system report, and a user interaction and feedback unit for displaying real-time data of the compressor and adjusting and controlling parameters of the compressor cooling system.

2. A compressor cooling health management system according to claim 1, characterized in that: The sensor unit includes a temperature sensor and a voltage sensor; The temperature sensor is used to collect the temperature value of the compressor cooling system; The voltage sensor is used to collect the operating voltage of the motor and the electronic control system of the compressor cooling system.

3. A compressor cooling health management system according to claim 2, characterized in that: The data classification unit is used to preliminarily process and classify the collected sensor data, and the data classification includes summarizing according to the timestamp, sensor type and collection location dimensions; The data cleaning unit includes identifying abnormal values ​​of the collected voltage data and temperature data, processing the abnormal values, and finally unifying the processed data into a unified format and unit.

4. A compressor cooling health management system according to claim 3, characterized in that: Through data normalization, the data is unified into a unified format and unit. The calculation expression is as follows: Wherein, x is the voltage data and temperature data of the cooling system of the compressor after normalization, x1 is the voltage data and temperature data of the first time series of the unprocessed first set of data, x2 is the voltage data and temperature data of the second time series of the unprocessed first set of data, x3 is the voltage data and temperature data of the third time series of the first set of data, and x n is the voltage data and temperature data of the nth time series of the first group of data, max{} is the maximum value function, and min{} is the minimum value function; Detect outliers through standard deviation, automatically mark abnormal data points, and selectively remove abnormal data points based on preset thresholds; The feature extraction unit is used to extract the processed voltage data and temperature data, and extract features for establishing a compressor parameter monitoring model. The calculation expression is as follows: Among them, λ is the compressor time series temperature characteristic value and voltage characteristic value, x'1 is the voltage data and current data at the first moment after processing, x'2 is the voltage data and current data at the second moment after processing, and x' t are the voltage data and current data at the tth moment after processing, and Δx is the preset normal value of the voltage data and the current data.

5. A compressor cooling health management system according to claim 4, characterized in that: By establishing the compressor parameter monitoring model, the voltage and temperature parameters of the compressor are monitored in real time, so as to detect possible faults or abnormal conditions in time. If abnormal data appears, the abnormal data is analyzed by the diagnosis unit to determine the existence of the fault, and the potential fault is analyzed at the same time, and the voltage and temperature of the compressor cooling system are evaluated by the performance evaluation unit; If the voltage and temperature of the compressor cooling system are at normal levels, no control maintenance instruction is output. If the voltage and temperature of the compressor cooling system are at abnormal levels, the voltage and temperature of the compressor cooling system are controlled by the maintenance unit and monitored by the compressor parameter monitoring model.

6. A compressor cooling health management system according to claim 5, characterized in that: The compressor parameter monitoring model, the calculation expression is as follows: Where, f(x) is the compressor parameter monitoring output, ω k is the hidden layer weight coefficient of the kth group of data, x k is the real-time data input of the compressor, Δb is the error coefficient, k is an ordinal number ranging from 1, 2, 3, ..., n, and n is any positive integer; The diagnostic unit, the calculation expression is as follows: Wherein, η is the error value between the actual parameters of the compressor cooling system and the theoretical parameters of the compressor cooling system, is the value of the pth time sequence in the mth group of compressor actual voltage and temperature data, f0(x) is the parameter data of the normal operation of the compressor cooling system, and M is the total number of groups.

7. A compressor cooling health management system according to claim 6, characterized in that: The performance evaluation unit, the calculation expression is as follows: Where ΔT is the compressor cooling system health performance coefficient, f(x) is the compressor parameter monitoring output, and x k is the real-time data input of the compressor, ω is the weight coefficient of the current input data in the hidden layer, and ΔE is the expected performance of the compressor cooling system; The performance evaluation unit is used to evaluate and monitor the performance of the compressor and analyze various performance indicators; The maintenance unit analyzes the compressor maintenance strategy and identifies potential problems of the equipment through historical data, real-time monitoring results and performance evaluation results.

8. A compressor cooling health management system according to claim 7, characterized in that: The control unit includes receiving control strategies, executing control strategies and adjusting control strategies; The receiving control strategy is used to obtain the control strategy from the compressor parameter monitoring model and the diagnostic unit; The execution control strategy is used to execute the compressor cooling system control strategy; The control strategy is adjusted by receiving the performance parameter output by the performance evaluation unit to adjust the compressor cooling system parameters and the control strategy.

9. A compressor cooling health management system according to claim 8, characterized in that: The report generation unit includes data listing, analysis and aggregation, and report generation and distribution; The data list is used to record the operation data of the compressor and its cooling system monitored by the sensor unit and the compressor parameter monitoring model; The analysis and summary are used to analyze the recorded data and generate reports on system performance, fault diagnosis, and maintenance requirements; The report generation and distribution is used to automatically generate regular and on-demand system operation reports; The user interaction and feedback unit includes real-time data display, parameter adjustment and feedback mechanisms.

10. A compressor cooling health management method, implemented based on a compressor cooling health management system according to any one of claims 1 to 9, characterized in that: include: S1. Collect various parameters of the compressor through sensors; S2, cleaning the collected data, and extracting features after cleaning; S3, establishing a parameter monitoring model, and evaluating various parameters and performances of the compressor through the parameter monitoring model; S4. Diagnose the faulty parts and give maintenance suggestions; S5. Analyze the monitoring results, automatically adjust the operating parameters of the compressor, and issue maintenance warnings to maintenance personnel; S6. Query system status and receive warning information through the user interface, collect user opinions and suggestions through the user feedback mechanism, and continuously optimize the system.

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