System and method for monitoring health state of high-voltage frequency converter

Abstract

The invention relates to a high-voltage frequency converter health state monitoring system and method. The health state of a high-voltage frequency converter is monitored based on various parameters. The high-voltage frequency converter health state monitoring system comprises a data acquisition unit which acquires operation data of a plurality of parts of a high-voltage frequency converter in real time; the data preprocessing unit is used for preprocessing the data from the data acquisition unit; the characteristic quantity extraction unit is used for extracting characteristic parameters related to the health state of the high-voltage frequency converter from the data preprocessed by the data preprocessing unit; the data analysis unit is used for storing a health model which is calibrated when the high-voltage frequency converter leaves a factory and is used for establishing association between component temperature rise and electrical information, and comparing and analyzing the characteristic parameters and the stored health model to judge the health state grade of the high-voltage frequency converter; and the fault early warning unit is provided with an early warning threshold value corresponding to the health state grade, and when the health state grade of the high-voltage frequency converter is judged to reach the early warning threshold value, an early warning signal is generated and notified.

Description

Technical Field

[0001] The present invention relates to a system and method for monitoring the health status of high-voltage inverters. Specifically, it relates to a technology in the field of power electronic equipment monitoring that monitors and evaluates the health status of high-voltage inverters based on the integration of multiple parameters such as the load rate, efficiency, heat generation, and mechanical information of high-voltage inverters. Background Art

[0002] As a speed regulation and energy-saving device widely used in industrial production, the stable operation of high-voltage inverters is crucial for ensuring the continuity and efficiency of the production process. However, during actual operation, high-voltage inverters are affected by various factors, such as equipment aging caused by long-term operation, environmental temperature changes, load fluctuations, etc. These factors may cause failures in the internal components of high-voltage inverters, thereby affecting their normal operation and further leading to production interruptions and equipment damage.

[0003] In existing high-voltage inverter health status monitoring technologies, it is more common to only focus on a single parameter or a few parameters. For example, only temperature or current is monitored, and comprehensive consideration of multiple parameters such as the load rate, efficiency, and temperature of each part of the high-voltage inverter is lacking. In existing monitoring technologies based on only a small number of parameters or only for local areas, it is impossible to comprehensively and accurately reflect the overall health status of high-voltage inverters, and it is difficult to timely and accurately locate and evaluate the potential faults of each component of high-voltage inverters. At the same time, existing technologies do not fully utilize the health model that correlates component temperature rise with electrical information calibrated at the time of high-voltage inverter factory production for comparative analysis, resulting in limitations in the reliability and accuracy of monitoring results.

[0004] Therefore, it is desired to develop a technology that can comprehensively consider multiple parameter information and, by comparing and analyzing it online with the health model calibrated at the time of factory production, accurately locate and evaluate the health status of each component of high-voltage inverters. Such a technology has important practical significance for stably maintaining the health status of high-voltage inverters. Summary of the Invention

[0005] The present invention is made in view of the above problems of the prior art, and its purpose is to provide a high-voltage inverter health status monitoring system and method based on multi-parameter fusion, which can accurately locate and evaluate the health status of each component of high-voltage inverters and stably maintain the health status of high-voltage inverters.

[0006] An embodiment of the present invention provides a health status monitoring system for a high-voltage frequency converter, which monitors the health status of the high-voltage frequency converter based on multiple parameters. The system includes: a data acquisition unit that collects the operation data of multiple parts of the high-voltage frequency converter in real time; a data preprocessing unit that preprocesses the data from the data acquisition unit; a feature quantity extraction unit that extracts feature parameters related to the health status of the high-voltage frequency converter from the data preprocessed by the data preprocessing unit; a data analysis unit that stores a health model calibrated at the factory of the high-voltage frequency converter to establish a correlation between component temperature rise and electrical information, and compares and analyzes the feature parameters with the stored health model to determine the health status level of the high-voltage frequency converter; and a fault warning unit that sets a warning threshold corresponding to the health status level, and generates a warning signal and gives a notice when it is determined that the health status level of the high-voltage frequency converter reaches the warning threshold.

[0007] In the health status monitoring system of the high-voltage frequency converter of the present invention, the data acquisition unit includes multiple temperature sensors respectively installed at multiple parts inside the high-voltage frequency converter, and voltage sensors and current sensors installed on the input side and output side of the high-voltage frequency converter. The multiple parameters include the temperatures of the multiple parts respectively, as well as the input voltage, input current, output voltage, and output current of the high-voltage frequency converter.

[0008] In the health status monitoring system of the high-voltage frequency converter of the present invention, the feature parameters extracted by the feature quantity extraction unit include the temperature change rate, load rate, and efficiency of each of the multiple parts.

[0009] In the health status monitoring system of the high-voltage frequency converter of the present invention, the data analysis unit includes a status comparison and evaluation unit that evaluates the health status of the high-voltage frequency converter by calculating the deviation between the feature parameters and the parameters stored in the health model.

[0010] In the health status monitoring system of the high-voltage frequency converter of the present invention, it further includes a monitoring center set remotely, and the monitoring center is communicatively connected to the data acquisition unit, the data analysis unit, and the fault warning unit, and can control the data acquisition unit, the data analysis unit, and the fault warning unit via the monitoring center.

[0011] In the health status monitoring system of the high-voltage frequency converter of the present invention, the health model can be optimized according to the operating conditions of the high-voltage frequency converter.

[0012] Another embodiment of the present invention provides a method for monitoring the health status of a high-voltage frequency converter, which monitors the health status of the high-voltage frequency converter based on multiple parameters, and includes: a data acquisition step of collecting the operation data of multiple parts of the high-voltage frequency converter in real time; a data preprocessing step of preprocessing the data from the data acquisition step; a feature quantity extraction step of extracting feature parameters related to the health status of the high-voltage frequency converter from the data preprocessed by the data preprocessing step; a data analysis step of storing a health model that correlates component temperature rise with electrical information calibrated at the time of factory shipment of the high-voltage frequency converter, and comparing and analyzing the feature parameters with the stored health model to determine the health status level of the high-voltage frequency converter; and a fault warning step of determining whether the health status level of the high-voltage frequency converter reaches a warning threshold corresponding to the health status level, and generating a warning signal and giving a notice when the warning threshold is reached.

[0013] In the method for monitoring the health status of a high-voltage frequency converter of the present invention, in the data acquisition step, multiple temperature sensors respectively installed at multiple parts inside the high-voltage frequency converter, and voltage sensors and current sensors installed on the input side and output side of the high-voltage frequency converter are used, and the multiple parameters include the temperatures of the multiple parts respectively, as well as the input voltage, input current, output voltage, and output current of the high-voltage frequency converter.

[0014] In the method for monitoring the health status of a high-voltage frequency converter of the present invention, the feature parameters extracted in the feature quantity extraction step include the temperature change rates, load rates, and efficiencies of the multiple parts respectively.

[0015] In the method for monitoring the health status of a high-voltage frequency converter of the present invention, the data analysis step includes a status comparison and evaluation step, in which the health status of the high-voltage frequency converter is evaluated by calculating the deviation between the feature parameters and the parameters stored in the health model.

[0016] In the method for monitoring the health status of a high-voltage frequency converter of the present invention, the data acquisition step, the data analysis step, and the fault warning step can be executed via a remote monitoring center.

[0017] In the method for monitoring the health status of a high-voltage frequency converter of the present invention, the health model can be optimized according to the operating conditions of the high-voltage frequency converter.

[0018] Technical effects

[0019] The high-voltage inverter health status monitoring system and method according to the present invention collect temperature data such as the internal cables, transformer windings, radiators, IGBTs, capacitors, inlet air, and outlet air temperatures of the high-voltage inverter, as well as electrical information such as the input voltage and current and output voltage and current of the high-voltage inverter, and compare and analyze these data with the health model that associates component temperature rise with electrical information calibrated at the time of factory shipment, thereby accurately positioning the health status of each component of the high-voltage inverter and being able to evaluate the health status of each component of the high-voltage inverter online, thereby improving the reliability and safety of the operation of the high-voltage inverter.

[0020] The high-voltage inverter health status monitoring system and method according to the present invention perform monitoring based on multi-parameter fusion, thereby comprehensively considering temperature data of multiple parts inside the high-voltage inverter, input and output electrical parameters, and factors such as load rate and efficiency, achieving monitoring based on multi-parameter fusion, being able to comprehensively and accurately reflect the health status of the high-voltage inverter, and avoiding the limitations of single-parameter monitoring.

[0021] The high-voltage inverter health status monitoring system and method according to the present invention perform comparative evaluation based on the health model, comparing and analyzing the collected real-time data with the health model calibrated at the time of factory shipment, thereby being able to accurately judge the health status of each component and achieving early detection and accurate positioning of potential faults.

[0022] The high-voltage inverter health status monitoring system and method according to the present invention adopt an intelligent early warning and management method, that is, using intelligent algorithms such as fuzzy evaluation and neural networks for status evaluation and fault early warning, thereby improving the accuracy and reliability of early warning. At the same time, the monitoring software of the monitoring center provides a friendly human-machine interface, facilitating real-time monitoring and management by operation and maintenance personnel.

[0023] The high-voltage inverter health status monitoring system and method according to the present invention store and analyze the collected data, thereby establishing a perfect data storage and management system, being able to long-term store and analyze the historical data of the equipment, providing strong data support for the maintenance and optimization of the equipment, and helping to improve the operation efficiency and service life of the equipment. Brief Description of the Drawings

[0024] Figure 1 is a block diagram schematically showing a configuration example of the high-voltage inverter health status monitoring system of the present invention.

[0025] Figure 2 is a flowchart showing the optimization of the health standard model of the high-voltage inverter health status monitoring method of the present invention.

[0026] Figure 3It is an exemplary diagram showing the actual collected data of the high-voltage inverter health status monitoring system of the present invention.

[0027] Explanation of Symbols

[0028] 1: Remote deployment platform; 11: Monitoring software; 12: Server; 2: Local deployment controller; 21: Fault warning unit; 22: Data analysis unit; 23: Data acquisition unit; 3: High-voltage inverter; 31: Input circuit; 32: Transformer; 33: Power conversion unit; 34: Output circuit; 4: Power supply; M: Driven machinery. Detailed Implementation Manner

[0029] Other objects and advantages of the present invention will be listed in the following detailed description part, and they will also be obvious according to the description part, or can be learned by implementing the present invention. The objects and advantages of the present invention can be achieved and obtained by means and combinations specifically given below. The drawings are a part of the specification, which show the current preferred embodiments of the present invention, and together with the above-given summary description and the following detailed description of the preferred embodiments, clarify the principles of the present invention.

[0030] Figure 1 It is a block diagram schematically showing the configuration example of the high-voltage inverter health status monitoring system of the present invention.

[0031] The high-voltage inverter health status monitoring system of the present invention monitors and evaluates the health status of the high-voltage inverter 3. Generally, the high-voltage inverter 3 is arranged between the power supply 4 and the driven machinery M. Electrical energy from the power supply 4 is input into the high-voltage inverter 3 via the input circuit 31, and in the high-voltage inverter 3, the electrical energy is subjected to conversion processing through the transformer 32 and the power conversion power supply 33, etc., and then the processed electrical energy is output to the driven machinery M via the output circuit 34.

[0032] The high-voltage inverter health status monitoring system of the present invention mainly includes two parts: a remote deployment platform 1 and a local deployment controller 2. Among them, the remote deployment platform 1 mainly includes monitoring software 11 and a server 12. The local deployment controller 2 mainly includes a fault warning unit 21, a data analysis unit 22, and a data acquisition unit 23.

[0033] The data acquisition unit 23 includes a temperature sensor group and an electrical parameter sensor group.

[0034] The temperature sensor group includes multiple temperature sensors respectively installed at key components such as cables, transformer windings, radiators, IGBTs, capacitors, etc. inside the high-voltage frequency converter, as well as at the air inlet and outlet. These temperature sensors are used to collect temperature data of each part with high precision and in real time. These temperature sensors can accurately detect temperature changes and provide the detection results as data to server 12 for the subsequent health status assessment.

[0035] The electrical parameter sensor group includes voltage sensors and current sensors installed on the input side and output side of the frequency converter, which are used to collect electrical information such as input voltage, input current, output voltage, and output current of the high-voltage frequency converter. By monitoring these electrical information, important parameters such as the load rate and efficiency of the frequency converter can be calculated.

[0036] The above-mentioned temperature sensor group and electrical parameter sensor group are connected to the data acquisition unit 23. The data acquisition unit 23 converts the analog signals collected by each sensor into digital signals, and processes and stores these digital signals. The data acquisition unit 23 has the ability to collect data at high speed and process it, which can ensure the real-time and accuracy of the data.

[0037] The high-precision temperature sensors installed at key parts, air inlet, and outlet inside the high-voltage frequency converter are, for example, thermocouple temperature sensors or thermistor temperature sensors, which can ensure accurate collection of temperature data. The electrical parameter sensors installed on the input side and output side are, for example, Hall voltage sensors and Hall current sensors, which are used to collect voltage and current information. The data acquisition unit 23 is composed of a high-performance single-chip microcomputer and an embedded system. It converts the analog signals collected by the sensors into digital signals through an A / D converter, and transmits data such as digital signals to the data analysis unit 22 through a serial port, Ethernet interface, etc.

[0038] The data analysis unit 22 includes a health model storage unit, a data preprocessing unit, a feature quantity extraction unit, and a state comparison and assessment unit.

[0039] The health model storage unit stores a health standard model that correlates component temperature rise with electrical information calibrated when the high-voltage frequency converter leaves the factory. The health standard model storage unit uses database technology to store the data of the health standard model calibrated when the high-voltage frequency converter leaves the factory. This health standard model is established based on experimental data and theoretical analysis, and reflects the relationship between the temperature rise of each component and electrical parameters under the normal operating state of the frequency converter.

[0040] A detailed description is given of the establishment of a health standard model. The health standard model for high-voltage inverters includes health indicators, failure modes, health status assessment, and maintenance strategies. The health standard model is established through data collection, preprocessing, model selection, training, and verification. Moreover, it can be achieved by combining physical models, statistical models, and machine learning models with tools such as Matlab.

[0041] The data preprocessing unit performs preprocessing such as screening, filtering, and normalization on the data transmitted from the data collection unit, thereby removing noise and outliers and improving the quality and usability of the data. The data preprocessing unit uses the median filtering algorithm to filter the collected data received to remove noise interference.

[0042] The feature quantity extraction unit extracts feature parameters related to the health status of the high-voltage inverter from the preprocessed data, such as the temperature change rate, load rate, efficiency, etc. of each part of the high-voltage inverter. The feature quantity extraction unit can accurately extract the key feature parameters reflecting the operating state of the high-voltage inverter by using signal processing algorithms. The feature quantity extraction unit uses the wavelet transform algorithm to extract the feature parameters of temperature and electrical signals.

[0043] The state comparison and evaluation unit compares and analyzes the extracted feature parameters with the parameters of the health standard model stored in the health model storage unit, and evaluates the health status of each component of the inverter by calculating the deviation between the actual parameters and the model parameters. The state comparison and evaluation unit adopts intelligent algorithms such as fuzzy evaluation and neural networks, and can thus accurately judge the health status level of each component on the basis of considering multiple factors. The state comparison and evaluation unit uses the fuzzy neural network algorithm, takes the extracted feature parameters as inputs, and outputs the health status level of each component through the trained fuzzy neural network model.

[0044] The fault warning unit 21 includes a warning rule setting unit, a warning signal generating unit, and a warning information display unit.

[0045] The warning rule setting unit sets warning rules and thresholds corresponding to different health status levels according to the actual operating conditions of the high-voltage inverter and past operating data. The warning rules can be comprehensively judged according to various parameters, thereby improving the accuracy of warning. The warning rule setting unit sets the thresholds of parameters such as temperature, load rate, and efficiency corresponding to different health status levels according to the rated parameters and actual operating conditions of the inverter.

[0046] When the status comparison and evaluation unit determines that the health status of a certain component of the high-voltage frequency converter reaches the warning level, the warning signal generation unit generates corresponding warning signals according to the warning rules. The warning signals include audible and visual alarm signals, SMS alarm signals, email alarm signals, etc. The warning signal generation unit uses an audible and visual alarm, an SMS modem, and an email sending unit to generate audible and visual alarm signals, SMS alarm signals, and email alarm signals respectively.

[0047] The warning information display unit displays the warning signals and the status information of the equipment involved in the warning signals on the monitoring interface for the operation and maintenance personnel to timely understand the current operation status of the equipment. The warning information display unit adopts an interface design that enables the operation and maintenance personnel to intuitively and clearly understand the operation status of the equipment, thereby being able to quickly and accurately convey the warning information. The warning information display unit uses a liquid crystal display screen to display the warning signals and equipment status information in an intuitive chart and text form.

[0048] The remote deployment platform 1 can also be called a monitoring center, which is composed of a computer and includes monitoring software 11 and a data storage server 12.

[0049] The data storage server 12 is used to store the original acquisition data received from the data acquisition unit 23, the feature data preprocessed by the data analysis unit 22, and the historical health status information of the high-voltage frequency converter. The data storage server is composed of storage devices with large capacity and high reliability, thereby being able to ensure the security and integrity of the data. The data storage server adopts an enterprise-level hard disk array and has the functions of large-capacity storage and data redundancy backup.

[0050] The monitoring software 11 is installed in the computer of the server 12 arranged in the monitoring center 1 and is communicatively connected to the data acquisition unit 23, the data analysis unit 22, the fault warning unit 21, etc., thereby being able to realize the real-time monitoring, data analysis, and warning management of the health status of the high-voltage frequency converter. The monitoring software 11 can realize functions such as data query, report generation, and trend analysis through a human-machine interface. The monitoring software 11 is developed using a C / S or B / S architecture and has functions such as real-time data display, historical data query, report generation, and trend analysis.

[0051] The high-voltage frequency converter health status monitoring method of the present invention is run in the high-voltage frequency converter health status monitoring system of the present invention. Figure 2 It is a flowchart showing the optimization of the health standard model of the high-voltage frequency converter health status monitoring method of the present invention. As Figure 2 shown, the high-voltage frequency converter health status monitoring method of the present invention can optimize the optimization of the health standard model.

[0052] Specifically, in the method for monitoring the health status of a high-voltage frequency converter according to the present invention, step S1 for optimizing the health standard model of the high-voltage frequency converter can be implemented. Generally, the health standard model calibrated at the time of the factory shipment of the high-voltage frequency converter does not need to be optimized. However, due to reasons such as equipment aging, environmental temperature changes, and load fluctuations caused by long-term operation, the health model needs to be optimized, which will be specifically described below.

[0053] In the method for monitoring the health status of a high-voltage frequency converter according to the present invention, when it is determined that the health model needs to be optimized, optimization step S1 is executed. Using the health standard model calibrated at the time of the factory shipment of the high-voltage frequency converter, which establishes the correlation between component temperature rise and electrical information, warning rules and thresholds corresponding to different health status levels are set according to the past operation data of the high-voltage frequency converter. As Figure 2 shown, if it is determined that the optimization of the health model of the high-voltage frequency converter is completed, then model deployment step S6 for deploying the health model of the high-voltage frequency converter is executed. If it is determined that the optimization of the health model of the high-voltage frequency converter is not completed, then steps S2 to S5 for optimizing the model are executed.

[0054] In data acquisition step S2, at regular time intervals (such as 1 minute), data acquisition unit 23 uses each sensor to collect temperature, voltage, and current data of each monitoring point of the high-voltage frequency converter, and transmits the data to data analysis unit 22 through data acquisition unit 23. As described above, the temperature data of parts such as the internal cables, transformer windings, radiators, IGBTs, capacitors, incoming air, and outgoing air of the high-voltage frequency converter are collected in real time using the temperature sensor group. The electrical parameter sensor group is used to collect electrical information such as the input voltage, input current, output voltage, and output current of the frequency converter. Further, the analog signals collected are converted into digital signals by data acquisition unit 23, and preliminary processing and storage are performed.

[0055] Next, in the data analysis step S3, the data analysis unit 22 preprocesses the data collected by the data acquisition unit 23, thereby removing noise and outliers. Then, characteristic parameters are extracted, and important indicators such as the load rate and efficiency are calculated. Moreover, the extracted characteristic parameters are compared and analyzed with the model parameters in the health model, and the health status levels of the components in the high-voltage frequency converter are evaluated through the fuzzy neural network algorithm. The preprocessing of the collected data includes screening, filtering, normalization processing, etc. Characteristic parameters related to the health status of the frequency converter are extracted from the preprocessed data, such as the temperature change rate, load rate, efficiency, etc. of each component. The load rate can be calculated by the ratio of the input power to the rated power, and the efficiency can be calculated by the ratio of the output power to the input power. The extracted characteristic parameters are compared and analyzed with the parameters of the health model in the health model storage unit, thereby calculating the deviation between the actual parameters and the model parameters. Further, intelligent algorithms such as fuzzy evaluation and neural network are used to comprehensively evaluate the comparison result, that is, the deviation, thereby judging the health status levels of the components in the high-voltage frequency converter.

[0056] Next, in the fault warning step S4, when the state evaluation result reaches the warning level, the fault warning unit 21 generates a corresponding warning signal according to the preset warning rules and displays the warning information on the monitoring interface. The operation and maintenance personnel can check and process the high-voltage frequency converter equipment in a timely manner according to the warning information. Whether the health status of each component in the high-voltage frequency converter reaches the warning level is judged according to the preset warning rules and thresholds. When it is judged that the health status reaches the warning level, a corresponding warning signal is generated. The warning signal includes an audible and visual alarm signal, a text message alarm signal, an email alarm signal, etc. The warning signal and the relevant equipment status information are displayed on the monitoring interface to remind the operation and maintenance personnel to check and process the high-voltage frequency converter equipment in a timely manner.

[0057] Next, in the data storage and management step S5, the original data collected by the data acquisition unit 23, the characteristic data preprocessed by the data analysis unit 22, and the historical health status information of the high-voltage frequency converter equipment are all stored in the data storage server 12. The monitoring software 11 installed in the data storage server 12 regularly backs up and clears the stored data, and at the same time provides functions such as data query, analysis, and report generation to support the operation and maintenance personnel to provide a decision-making basis for the maintenance and management of the equipment.

[0058] Finally, based on the optimized health model of the high-voltage frequency converter, the model deployment step S6 of deploying the health model of the high-voltage frequency converter is executed. In this way, by optimizing the health model of the high-voltage frequency converter, the health status of each component can be accurately judged, and early detection and accurate positioning of potential faults can be realized.

[0059] Figure 3 is an illustrative diagram showing the actual data of the high-voltage inverter health status monitoring system of the present invention. In Figure 3 , E[x] represents the electrical condition vector, which is composed of voltage, current information, etc. A[x] represents the environmental condition vector, which is composed of temperature, humidity, altitude, etc. R[x] represents the load information, which is composed of rotational speed, torque, etc. e[x] represents the electrical state health index vector, which is composed of power factor, harmonics, etc. t[x] represents the heat-related state index, which is composed of cable temperature rise, transformer winding temperature rise, device temperature rise, etc. m[x] represents the mechanical-related state index, which is composed of noise, vibration, etc. x = 1, 2, 3…, N, and N represents the number of elements of different vectors. And, Figure 3 the condition vectors and health index vectors shown in can be extended according to actual needs. The operation and maintenance personnel can call up the Figure 3 state health index as shown, and can understand the operation status of the high-voltage inverter equipment in a timely manner.

[0060] Thus, according to the high-voltage inverter health status monitoring system and method of the present invention, by performing monitoring based on multi-parameter fusion, the temperature data of multiple parts inside the high-voltage inverter, input and output electrical parameters, and factors such as load rate and efficiency are comprehensively considered, realizing the fusion monitoring of multi-parameters, and being able to comprehensively and accurately reflect the health status of the high-voltage inverter, avoiding the limitations of monitoring based on a single or a small number of parameters.

[0061] As mentioned above, several embodiments of the present invention have been described, but these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other ways, and various omissions, substitutions, and changes can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are included in the invention described in the claims and its equivalent scope.

Claims

1. A high-voltage inverter health status monitoring system monitors the health status of a high-voltage inverter based on multiple parameters, comprising: A data acquisition unit for collecting operating data of multiple parts of the high-voltage inverter in real time; A data preprocessing unit, which preprocesses the data from the data acquisition unit; A feature extraction unit, which extracts feature parameters related to the health status of the high-voltage inverter from the data preprocessed by the data preprocessing unit; A data analysis unit stores a health model of the high-voltage inverter calibrated at the factory to associate component temperature rise with electrical information, and compares and analyzes the characteristic parameters with the stored health model to determine the health status level of the high-voltage inverter; as well as The fault warning unit is set with a warning threshold corresponding to the above health status level. When it is determined that the health status level of the above high-voltage inverter reaches the warning threshold, a warning signal is generated and a notification is made.

2. The high-voltage inverter health status monitoring system according to claim 1, wherein: The data acquisition unit includes a plurality of temperature sensors respectively installed at a plurality of locations inside the high-voltage inverter, and a voltage sensor and a current sensor installed at the input side and the output side of the high-voltage inverter. The above-mentioned various parameters include the respective temperatures of the above-mentioned multiple parts, and the input voltage, input current, output voltage and output current of the above-mentioned high-voltage inverter.

3. The high-voltage inverter health status monitoring system according to claim 1, wherein: The characteristic parameters extracted by the characteristic quantity extraction unit include a temperature change rate, a load factor, and an efficiency of each of the plurality of parts.

4. The high-voltage inverter health status monitoring system according to claim 1, wherein: The data analysis unit includes a status comparison and evaluation unit, which evaluates the health status of the high-voltage inverter by calculating the deviation between the characteristic parameter and the parameter stored in the health model.

5. The high-voltage inverter health status monitoring system according to any one of claims 1 to 4, wherein: It also includes a remote monitoring center, which is communicatively connected to the data acquisition unit, the data analysis unit, and the fault warning unit. The data acquisition unit, the data analysis unit, and the fault warning unit can be controlled via the monitoring center.

6. The high-voltage inverter health status monitoring system according to any one of claims 1 to 4, wherein: The health model can be optimized according to the operating conditions of the high-voltage inverter.

7. A method for monitoring the health status of a high-voltage inverter, which monitors the health status of a high-voltage inverter based on multiple parameters, comprising: A data collection step, collecting operating data of multiple parts of the high-voltage inverter in real time; A data preprocessing step, preprocessing the data from the above data collection step; A feature extraction step of extracting feature parameters related to the health status of the high-voltage inverter from the data preprocessed by the data preprocessing step; A data analysis step, storing a health model that associates component temperature rise with electrical information and is calibrated when the high-voltage inverter is shipped from the factory, and comparing and analyzing the characteristic parameters with the stored health model to determine the health status level of the high-voltage inverter; as well as The fault warning step determines whether the health status level of the high-voltage inverter reaches a warning threshold corresponding to the health status level, and generates a warning signal and makes a notification when the warning threshold is reached.

8. The high voltage inverter health status monitoring method according to claim 7, wherein: In the data collection step, a plurality of temperature sensors respectively installed at a plurality of locations inside the high-voltage inverter, and a voltage sensor and a current sensor installed at the input side and the output side of the high-voltage inverter are used. The above-mentioned various parameters include the temperatures of the above-mentioned various parts, and the input voltage, input current, output voltage and output current of the high-voltage inverter.

9. The high-voltage inverter health status monitoring method according to claim 7, wherein: The characteristic parameters extracted in the characteristic quantity extraction step include a temperature change rate, a load factor, and an efficiency of each of the plurality of parts.

10. The method for monitoring the health status of a high-voltage inverter according to claim 7, wherein: The data analysis step includes a state comparison and evaluation step, in which the health state of the high-voltage inverter is evaluated by calculating the deviation between the characteristic parameter and the parameter stored in the health model.

11. The method for monitoring the health status of a high-voltage inverter according to any one of claims 7 to 10, wherein: The data collection step, the data analysis step, and the fault warning step can be performed via a monitoring center located remotely.

12. The method for monitoring the health status of a high-voltage inverter according to any one of claims 7 to 10, wherein: The health model can be optimized according to the operating conditions of the high-voltage inverter.

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