A health management system and method for mining power electronic equipment

Abstract

This invention discloses a health management system and method for mining power electronic equipment, relating to the field of health management technology for mining power electronic equipment. The system includes a data acquisition unit, an aging model unit, an aging detection unit, and a life extension management unit. This invention determines the aging degree of a target power device by using actual operating voltage, collector current at actual turn-off time, actual turn-off time, actual thermistor resistance, junction temperature detection model, and turn-off time prediction model. Based on the aging degree of the target power device, it determines life extension management measures, thereby achieving the purpose of monitoring the aging degree of power electronic devices and applying corresponding life extension management.

Description

Technical Field

[0001] This invention relates to the field of health management technology for mining power electronic equipment, and in particular to a health management system and method for mining power electronic equipment. Background Technology

[0002] In recent years, with the continuous improvement of my country's technological level, coal mining enterprises have achieved certain development, which has also placed higher demands on the reliability of mining power electronic equipment. Modern power electronic circuits, due to their advantages such as low noise, high efficiency, and high power density, are widely used in the drive systems of major electrical equipment in coal mines, such as mine hoists, coal mine belt conveyors, water pumps, and fans, playing a crucial role in power conversion. However, due to the harsh operating environment and large load variations of mining power electronic equipment, it is prone to failure, leading to certain economic losses and personal dangers. Therefore, monitoring the operating status of mining power electronic equipment is an important means and basis for ensuring its safety performance.

[0003] Power electronic devices are a core component of mining power electronic equipment. Modern mining power electronic equipment mostly achieves its required functions through the switching control of power electronic devices, such as MOSFETs and IGBTs. As the core component of mining power electronic equipment, the reliability of power electronic devices has become a crucial factor in the safe operation of such equipment, and their health status is essential for its safety and effectiveness. However, industrial surveys show that power electronic devices are among the most prone to failure in mining power electronic equipment, accounting for 34% of failures. The causes of power electronic device failure can be broadly categorized into sudden failure and aging failure. Sudden failure occurs when power electronic devices are suddenly subjected to stresses such as voltage, current, and temperature exceeding their rated range; it is instantaneous and unpredictable. Aging failure occurs when power electronic devices are continuously subjected to electrothermal stress under normal operating conditions, leading to continuous performance degradation. This type of failure is slow, cumulative, and inevitable. If aging power electronic devices are not detected and addressed promptly, catastrophic failures can occur.

[0004] During the operation of mining power electronic equipment, power fluctuations, environmental changes, and intermittent operation can accelerate the aging and failure of power electronic devices, thereby reducing the reliability of mining power electronic equipment. Therefore, monitoring the aging degree of power electronic devices and implementing corresponding life extension management is of great significance for mining power electronic equipment. Summary of the Invention

[0005] The purpose of this invention is to provide a health management system and method for mining power electronic equipment, which can monitor the aging degree of power electronic devices and apply corresponding life extension management.

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

[0007] A health management system for mining power electronic equipment includes: a data acquisition unit, an aging model unit, an aging detection unit, and a life extension management unit.

[0008] The output of the data acquisition unit is connected to the first input of the aging detection unit; the output of the aging model unit is connected to the second input of the aging detection unit; and the output of the aging detection unit is connected to the input of the life extension management unit.

[0009] The data acquisition unit is used to acquire the operating parameters of the target power device under actual operating conditions, and to process the operating parameters to obtain the operating data of the target power device; the target power device is a power device in mining power electronic equipment; the operating data includes the actual operating voltage, the collector current at the actual turn-off time, the actual turn-off time, and the actual thermistor resistance value;

[0010] The aging model unit is used to store the junction temperature detection model and the shutdown time prediction model.

[0011] The aging detection unit is used to determine the aging degree of the target power device based on the operating data, the junction temperature detection model, and the turn-off time prediction model; the aging degree includes no aging, slight aging, and severe aging.

[0012] The life extension management unit is used to determine life extension management measures when the aging degree of the target power device is slight aging or severe aging; the life extension management measures are used to extend the life of the target power device.

[0013] Optionally, the data acquisition unit includes a sensor module, an information processing module, and an information output module;

[0014] The sensor module is used to collect the operating parameters of the target power device under actual operating conditions.

[0015] The information processing module is used to process the operating parameters to obtain the operating data of the target power device;

[0016] The information output module is used to output the operating data of the target power device.

[0017] Optionally, the aging model unit includes a first storage module, a second storage module, an aging threshold calculation module, and a model output module;

[0018] The first storage module is used to store the junction temperature detection model; the junction temperature detection model is a two-dimensional data model characterizing the relationship between the thermistor resistance and junction temperature under different aging degrees;

[0019] The second storage module is used to store the turn-off time prediction model; the turn-off time prediction model is a three-dimensional data model that characterizes the relationship between turn-off time, operating voltage and collector current at turn-off time under different aging conditions.

[0020] The aging threshold calculation module is used to calculate a first relative deviation value and a second relative deviation value; the first relative deviation value and the second relative deviation value are used to classify the aging degree of the power device;

[0021] The model output module is used to output the junction temperature detection model, the shutdown time prediction model, the first relative deviation value, and the second relative deviation value.

[0022] Optionally, the aging detection unit includes a junction temperature detection module, a prediction module, a comparison module, and an aging determination module;

[0023] The junction temperature detection module is used to determine the actual junction temperature of the target power device based on the actual thermistor resistance value and the junction temperature detection model.

[0024] The prediction module is used to determine the predicted turn-off time of the target power device based on the actual operating voltage, the collector current at the actual turn-off time, the actual junction temperature, and the turn-off time prediction model.

[0025] The comparison module is used to determine the absolute value of the difference between the actual shutdown time and the predicted shutdown time as the actual deviation value;

[0026] The aging determination module is used for:

[0027] The actual deviation value is compared with the first relative deviation value and the second relative deviation value, respectively.

[0028] When the actual deviation value is less than or equal to the first relative deviation value, the aging degree of the target power device is determined to be unaged;

[0029] When the actual deviation value is greater than the first relative deviation value and the actual deviation value is less than the second relative deviation value, the aging degree of the target power device is determined to be slight aging.

[0030] When the actual deviation value is greater than or equal to the second relative deviation value, the aging degree of the target power device is determined to be severe aging.

[0031] Optionally, the life extension management unit is used for:

[0032] When the target power device is only slightly aged, the life extension management measures are determined to be timely improvement of device cooling capacity and reduction of load power.

[0033] When the target power device is severely aged, the life extension management measure is determined to be replacing the target power device.

[0034] A method for health management of mining power electronic equipment includes:

[0035] An aging calibration experiment is performed on the marked power device to obtain experimental data of the marked power device; the experimental data includes experimental turn-off time, experimental operating voltage, collector current at experimental turn-off time, experimental junction temperature, and experimental thermistor resistance value; the marked power device is a power device of the same specification as the target power device; the target power device is a power device in mining power electronic equipment;

[0036] Based on the experimental data of the labeled power devices, a junction temperature detection model and a turn-off time prediction model were constructed.

[0037] Monitor and record the operating parameters of the target power device under actual operating conditions;

[0038] Based on the operating parameters, the junction temperature detection model, and the turn-off time prediction model, the aging degree of the target power device is determined; the aging degree includes no aging, slight aging, and severe aging.

[0039] When the aging degree of the target power device is slight aging or severe aging, life extension management measures are determined; the life extension management measures are used to extend the life of the target power device.

[0040] Optionally, determining the aging degree of the target power device based on the operating parameters, the junction temperature detection model, and the turn-off time prediction model specifically includes:

[0041] The operating parameters are preprocessed to obtain the operating data of the target power device; the operating data includes the actual operating voltage, the collector current at the actual turn-off time, the actual turn-off time, and the actual thermistor resistance value.

[0042] The actual junction temperature of the target power device is determined based on the actual thermistor resistance value and the junction temperature detection model.

[0043] The predicted turn-off time of the target power device is determined based on the actual junction temperature, the actual operating voltage, the collector current at the actual turn-off time, and the turn-off time prediction model.

[0044] The aging degree of the target power device is determined based on the actual shutdown time and the predicted shutdown time.

[0045] Optionally, determining the aging degree of the target power device based on the actual turn-off time and the predicted turn-off time specifically includes:

[0046] The absolute value of the difference between the actual shutdown time and the predicted shutdown time is determined as the actual deviation value;

[0047] When the actual deviation value is less than or equal to the first relative deviation value, the aging degree of the target power device is determined to be unaged;

[0048] When the actual deviation value is greater than the first relative deviation value and the actual deviation value is less than the second relative deviation value, the aging degree of the target power device is determined to be slight aging.

[0049] When the actual deviation value is greater than or equal to the second relative deviation value, the aging degree of the target power device is determined to be severe aging.

[0050] Optionally, when the target power device is at a slightly aged or severely aged level, life extension management measures are determined, specifically including:

[0051] When the target power device is only slightly aged, the life extension management measures are determined to be timely improvement of device cooling capacity and reduction of load power.

[0052] When the target power device is severely aged, the life extension management measure is determined to be replacing the target power device.

[0053] Optionally, the construction of the junction temperature detection model and turn-off time prediction model based on the experimental data of the marked power device specifically includes:

[0054] Based on the experimental junction temperature and the experimental thermistor resistance value, a junction temperature detection model is constructed; the junction temperature detection model is a two-dimensional data model characterizing the relationship between thermistor resistance value and junction temperature under different aging degrees.

[0055] Based on the experimental turn-off time, the experimental operating voltage, and the collector current at the experimental turn-off moment, a turn-off time prediction model is constructed; the turn-off time prediction model is a three-dimensional data model characterizing the relationship between turn-off time, operating voltage, and collector current at the turn-off moment under different aging degrees.

[0056] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0057] The purpose of this invention is to provide a health management system and method for mining power electronic equipment, which can monitor the aging degree of power electronic devices and apply corresponding life extension management.

[0058] To achieve the above objectives, the present invention provides the following solution:

[0059] This invention provides a health management system and method for mining power electronic equipment, comprising: a data acquisition unit, an aging model unit, an aging detection unit, and a life extension management unit. This invention determines the aging degree of target power devices by using actual operating voltage, collector current at actual turn-off time, actual turn-off time, actual thermistor resistance, junction temperature detection model, and turn-off time prediction model. Based on the aging degree of the target power devices, it determines life extension management measures, thereby achieving the purpose of monitoring the aging degree of power electronic devices and applying corresponding life extension management. Attached Figure Description

[0060] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0061] Figure 1 A structural block diagram of a health management system for mining power electronic equipment provided in an embodiment of the present invention;

[0062] Figure 2 This is a schematic diagram of a data acquisition unit provided in an embodiment of the present invention;

[0063] Figure 3 This is a schematic diagram of the structure of an aging model unit provided in an embodiment of the present invention;

[0064] Figure 4 This is a schematic diagram of an aging detection unit provided in an embodiment of the present invention;

[0065] Figure 5 This is a flowchart illustrating the health management method for mining power electronic equipment provided in an embodiment of the present invention. Detailed Implementation

[0066] 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.

[0067] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0068] Example 1

[0069] like Figure 1 As shown in the figure, this embodiment provides a health management system for mining power electronic equipment based on the power device turn-off time, including a data acquisition unit 1, an aging model unit 2, an aging detection unit 3, and a life extension management unit 4.

[0070] The output of the data acquisition unit 1 is connected to the first input of the aging detection unit 3; the output of the aging model unit 2 is connected to the second input of the aging detection unit 3; and the output of the aging detection unit 3 is connected to the input of the life extension management unit.

[0071] The data acquisition unit 1 is used to acquire the operating parameters of the target power device under actual operating conditions, process the operating parameters to obtain the operating data of the target power device, and then transmit the operating data to the aging detection unit 3; the target power device is a power device in mining power electronic equipment; the operating data includes the actual operating voltage, the collector current at the actual turn-off time, the actual turn-off time, and the actual thermistor resistance value.

[0072] The aging model unit 2 is used to store junction temperature detection models and turn-off time prediction models at different voltages obtained through aging calibration experiments.

[0073] The aging detection unit 3 is used to determine the aging degree of the target power device based on the working data, the junction temperature detection model, and the turn-off time prediction model; the aging degree includes no aging, slight aging, and severe aging.

[0074] The life extension management unit 4 is used to determine life extension management measures when the aging degree of the target power device is slight aging or severe aging; the life extension management measures are used to extend the life of the target power device.

[0075] Furthermore, the life extension management unit is used for:

[0076] When the target power device is only slightly aged, the life extension management measures are determined to be timely improvement of device cooling capacity and reduction of load power.

[0077] When the target power device is severely aged, the life extension management measure is determined to be replacing the target power device.

[0078] like Figure 2 As shown, the data acquisition unit 1 described in this embodiment includes: a sensor module 11, an information processing module 12, and an information output module 13.

[0079] Sensor module 11 is used to collect the operating parameters of the target power device under actual operating conditions.

[0080] Information processing module 12 is used to process the operating parameters to obtain the operating data of the target power device; the operating data includes the actual operating voltage U and the collector current I at the actual turn-off time. c Actual shutdown time t off2 And data such as the actual resistance value of the thermistor.

[0081] The information output module 13 is used to output the working data of the target power device and transmit the working data to the aging detection unit 3.

[0082] like Figure 3 As shown, the aging model unit 2 described in this embodiment includes: a first storage module (i.e., storage module 1 in the figure) 21, a second storage module (i.e., storage module 2 in the figure) 22, an aging threshold calculation module 23, and a model output module 24.

[0083] The first storage module 21 is used to store a junction temperature detection model; the junction temperature detection model is used to characterize the thermistor resistance and junction temperature (R0) under different aging degrees. j -T j A two-dimensional data model between ( ), which was obtained from aging calibration experiments.

[0084] The second storage module 22 is used to store the turn-off time prediction model; the turn-off time prediction model is a model that characterizes the turn-off time, operating voltage, and collector current (I) at the turn-off moment under different aging conditions. c -t off -T j A three-dimensional data model between ( ).

[0085] The aging threshold calculation module 23 is used to calculate the relative deviation of the turn-off time under different aging degrees of the device, and then determine the reference thresholds δ1 and δ2 of the relative deviation of the turn-off time used to determine the aging degree, that is, to calculate the first relative deviation value and the second relative deviation value; the first relative deviation value and the second relative deviation value are used to classify the aging degree of the power device.

[0086] The model output module 24 is used to output the junction temperature detection model, the shutdown time prediction model, the first relative deviation value and the second relative deviation value to the aging detection unit 3.

[0087] like Figure 4 As shown, the aging detection unit 3 includes: junction temperature detection module 31, prediction module 32, comparison module 33 and aging determination module 34.

[0088] Junction temperature detection module 31 is used to determine the actual junction temperature of the target power device based on the actual thermistor resistance value and the junction temperature detection model.

[0089] In practical applications, the power device module usually integrates a thermistor, so the junction temperature of the power device can be determined by measuring the resistance of the thermistor.

[0090] Prediction module 32 is used to determine the predicted turn-off time t of the target power device based on the actual operating voltage, the collector current at the actual turn-off time, the actual junction temperature, and the turn-off time prediction model. off1 .

[0091] Comparison module 33 is used to compare the actual shutdown time t off2 and the predicted shutdown time t off1 The absolute value of the difference between them is determined as the actual deviation value δ.

[0092] The aging judgment module 34 is used to determine the aging degree of the target power device based on the magnitude of the actual deviation value δ, and to provide different aging warnings.

[0093] Comparison module 33 transmits the actual deviation value δ to aging judgment module 34. When the actual measured turn-off time t off2 Compared with the predicted value t off1 When the relative deviation value δ≤δ1, an indication of "health" is provided; when the relative deviation value δ1≤δ≤δ2, a warning of "slight aging" is provided; when the relative deviation value δ≥δ2, a warning of "severe aging" is provided.

[0094] The aging determination module 34 is further used for:

[0095] The actual deviation value δ is compared with the first relative deviation value δ1 and the second relative deviation value δ2, respectively.

[0096] When the actual deviation value δ is less than or equal to the first relative deviation value δ1, the aging degree of the target power device is determined to be unaged.

[0097] When the actual deviation value δ is greater than the first relative deviation value δ1 and the actual deviation value is less than the second relative deviation value δ2, the aging degree of the target power device is determined to be slight aging.

[0098] When the actual deviation value δ is greater than or equal to the second relative deviation value δ2, the aging degree of the target power device is determined to be severe aging.

[0099] When the target power device experiences slight aging, the following measures should be taken: (1) Improve the device's cooling capacity in a timely manner, such as increasing the heat dissipation capacity of the radiator; (2) Reduce the load power, such as correcting the load command of the mining equipment and reducing the operating current. For example, when the power device inside the mine hoist experiences slight aging, the command curve of the mine hoist can be corrected in a timely manner to reduce its acceleration, or the speed of the cooling fan of the mine hoist can be increased to slow down the aging rate of the device.

[0100] When the target power device becomes severely aged, the aged device should be replaced promptly. For example, when the power device inside a mine hoist becomes severely aged, it needs to be replaced immediately.

[0101] The mine power electronic equipment health management system based on power device turn-off time provided by this invention includes target power devices such as insulated gate bipolar transistor (IGBT) modules and silicon carbide metal-oxide semiconductor field-effect transistor (SiC MOSFET) modules.

[0102] In this embodiment of the invention, the shutdown time t is utilized. off The health status of power devices is monitored using characteristic parameters; wherein, the characteristic parameters include, but are not limited to, the off-time t. off Specifically:

[0103] In this embodiment of the invention, the aging calibration experiment is conducted offline. This experiment measures the internal thermistor value R of the power device under different voltage conditions and at different aging stages, based on the power device's health status and aging degree. j collector current I at turn-off time c Off time t off and junction temperature T j Perform fitting to obtain R. j -T j Two-dimensional data models and Ic-t off -T j Three-dimensional data model.

[0104] Example 2

[0105] Based on an aging monitoring model, this embodiment proposes a health management method for mining power electronic equipment based on the power device turn-off time.

[0106] like Figure 5 As shown in the figure, this embodiment provides a health management method for mining power electronic equipment based on the power device turn-off time, which includes the following steps:

[0107] Step 501: Perform an aging calibration experiment on the marked power device to obtain experimental data of the marked power device; the experimental data includes experimental turn-off time, experimental operating voltage, collector current at experimental turn-off time, experimental junction temperature, and experimental thermistor resistance value; the marked power device is a power device of the same specification as the target power device; the target power device is a power device in mining power electronic equipment.

[0108] Step 502: Based on the experimental data of the marked power device, construct a junction temperature detection model and a turn-off time prediction model.

[0109] Step 503: Monitor and record the operating parameters of the target power device under actual operating conditions.

[0110] Step 504: Based on the operating parameters, the junction temperature detection model, and the turn-off time prediction model, determine the aging degree of the target power device; the aging degree includes no aging, slight aging, and severe aging.

[0111] Step 505: When the aging degree of the target power device is slight aging or severe aging, determine the life extension management measures; the life extension management measures are used to extend the life of the target power device.

[0112] Furthermore, determining the aging degree of the target power device based on the operating parameters, the junction temperature detection model, and the turn-off time prediction model specifically includes:

[0113] The operating parameters are preprocessed to obtain the operating data of the target power device; the operating data includes the actual operating voltage, the collector current at the actual turn-off time, the actual turn-off time, and the actual thermistor resistance value.

[0114] The actual junction temperature of the target power device is determined based on the actual thermistor resistance value and the junction temperature detection model.

[0115] The predicted turn-off time of the target power device is determined based on the actual junction temperature, the actual operating voltage, the collector current at the actual turn-off time, and the turn-off time prediction model.

[0116] The aging degree of the target power device is determined based on the actual shutdown time and the predicted shutdown time.

[0117] Specifically, determining the aging degree of the target power device based on the actual turn-off time and the predicted turn-off time includes:

[0118] The absolute value of the difference between the actual shutdown time and the predicted shutdown time is determined as the actual deviation value; when the actual deviation value is less than or equal to the first relative deviation value, the aging degree of the target power device is determined to be unaged; when the actual deviation value is greater than the first relative deviation value and less than the second relative deviation value, the aging degree of the target power device is determined to be slightly aged; when the actual deviation value is greater than or equal to the second relative deviation value, the aging degree of the target power device is determined to be severely aged.

[0119] Furthermore, when the target power device is at a slight aging or severe aging level, life extension management measures are determined, specifically including:

[0120] When the target power device is only slightly aged, the life extension management measures are determined to be timely improvement of device cooling capacity and reduction of load power.

[0121] When the target power device is severely aged, the life extension management measure is determined to be replacing the target power device.

[0122] Furthermore, the construction of the junction temperature detection model and the turn-off time prediction model based on the experimental data of the labeled power device specifically includes:

[0123] Based on the experimental junction temperature and the experimental thermistor resistance value, a junction temperature detection model is constructed; the junction temperature detection model is a two-dimensional data model characterizing the relationship between thermistor resistance value and junction temperature under different aging degrees.

[0124] Based on the experimental turn-off time, the experimental operating voltage, and the collector current at the experimental turn-off moment, a turn-off time prediction model is constructed; the turn-off time prediction model is a three-dimensional data model characterizing the relationship between turn-off time, operating voltage, and collector current at the turn-off moment under different aging degrees.

[0125] This invention discloses a health management system and method for mining power electronic equipment, comprising: constructing a junction temperature detection model and a turn-off time prediction model based on experimental data obtained through aging calibration experiments; monitoring and recording the operating parameters of power devices in mining power electronic equipment under actual operating conditions, judging the health status and aging degree of power devices in real time, and providing aging warnings; and taking different measures to extend the lifespan of power device modules according to their aging degree. This invention uses the turn-off time of power devices as a characteristic parameter to judge the health status of power devices and adopt different lifespan extension management strategies. It is simple, reliable, and highly practical for industrial applications, solving the problem of difficult testing of mining power electronic equipment, ensuring its safety performance, and possessing certain development potential.

[0126] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0127] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A health management system for mining power electronic equipment, characterized in that, include: Data acquisition unit, aging model unit, aging detection unit, and life extension management unit; The output terminal of the data acquisition unit is connected to the first input terminal of the aging detection unit; The output of the aging model unit is connected to the second input of the aging detection unit; the output of the aging detection unit is connected to the input of the life extension management unit. The data acquisition unit is used to acquire the operating parameters of the target power device under actual operating conditions, and to process the operating parameters to obtain the operating data of the target power device; the target power device is a power device in mining power electronic equipment; the target power device includes an insulated gate bipolar transistor module and a silicon carbide metal-oxide-semiconductor field-effect transistor module; The operating data includes the actual operating voltage, the collector current at the actual turn-off time, the actual turn-off time, and the actual thermistor resistance value. The aging model unit is used to store the junction temperature detection model and the shutdown time prediction model. The aging model unit includes a first storage module, a second storage module, an aging threshold calculation module, and a model output module; The first storage module is used to store the junction temperature detection model; the junction temperature detection model is a two-dimensional data model characterizing the relationship between the thermistor resistance and junction temperature under different aging degrees; The second storage module is used to store the turn-off time prediction model; the turn-off time prediction model is a three-dimensional data model that characterizes the relationship between turn-off time, operating voltage and collector current at turn-off time under different aging conditions. The aging threshold calculation module is used to calculate a first relative deviation value and a second relative deviation value; the first relative deviation value and the second relative deviation value are used to classify the aging degree of the power device; The model output module is used to output the junction temperature detection model, the turn-off time prediction model, the first relative deviation value, and the second relative deviation value; The aging detection unit is used to determine the aging degree of the target power device based on the operating data, the junction temperature detection model, and the turn-off time prediction model; the aging degree includes no aging, slight aging, and severe aging. The aging detection unit includes a junction temperature detection module, a prediction module, a comparison module, and an aging determination module. The junction temperature detection module is used to determine the actual junction temperature of the target power device based on the actual thermistor resistance value and the junction temperature detection model. The prediction module is used to determine the predicted turn-off time of the target power device based on the actual operating voltage, the collector current at the actual turn-off time, the actual junction temperature, and the turn-off time prediction model. The comparison module is used to determine the absolute value of the difference between the actual shutdown time and the predicted shutdown time as the actual deviation value; The aging determination module is used for: The actual deviation value is compared with the first relative deviation value and the second relative deviation value, respectively. When the actual deviation value is less than or equal to the first relative deviation value, the aging degree of the target power device is determined to be unaged; When the actual deviation value is greater than the first relative deviation value and the actual deviation value is less than the second relative deviation value, the aging degree of the target power device is determined to be slight aging. When the actual deviation value is greater than or equal to the second relative deviation value, the aging degree of the target power device is determined to be severe aging; The life extension management unit is used to determine life extension management measures when the aging degree of the target power device is slight aging or severe aging; the life extension management measures are used to extend the life of the target power device.

2. The health management system for mining power electronic equipment according to claim 1, characterized in that, The data acquisition unit includes a sensor module, an information processing module, and an information output module; The sensor module is used to collect the operating parameters of the target power device under actual operating conditions. The information processing module is used to process the operating parameters to obtain the operating data of the target power device; The information output module is used to output the operating data of the target power device.

3. The health management system for mining power electronic equipment according to claim 1, characterized in that, The life extension management unit is used for: When the target power device is only slightly aged, the life extension management measures are determined to be improving the device's cooling capacity and reducing the load power. When the target power device is severely aged, the life extension management measure is determined to be replacing the target power device.

4. A method for health management of mining power electronic equipment, characterized in that, include: An aging calibration experiment is performed on the marked power device to obtain experimental data. The experimental data includes experimental turn-off time, experimental operating voltage, collector current at experimental turn-off time, experimental junction temperature, and experimental thermistor resistance value. The marked power device is a power device of the same specifications as the target power device. The target power device is a power device in mining power electronic equipment. The target power device includes an insulated gate bipolar transistor module and a silicon carbide metal-oxide-semiconductor field-effect transistor module. Based on the experimental data of the labeled power devices, a junction temperature detection model and a turn-off time prediction model are constructed, specifically including: Based on the experimental junction temperature and the experimental thermistor resistance value, a junction temperature detection model is constructed; the junction temperature detection model is a two-dimensional data model characterizing the relationship between thermistor resistance value and junction temperature under different aging degrees. Based on the experimental turn-off time, the experimental operating voltage, and the collector current at the experimental turn-off moment, a turn-off time prediction model is constructed; the turn-off time prediction model is a three-dimensional data model characterizing the relationship between turn-off time, operating voltage, and collector current at the turn-off moment under different aging degrees. Monitor and record the operating parameters of the target power device under actual operating conditions; Based on the operating parameters, the junction temperature detection model, and the turn-off time prediction model, the aging degree of the target power device is determined; the aging degree includes no aging, slight aging, and severe aging. The determination of the aging degree of the target power device based on the operating parameters, the junction temperature detection model, and the turn-off time prediction model specifically includes: The operating parameters are preprocessed to obtain the operating data of the target power device; the operating data includes the actual operating voltage, the collector current at the actual turn-off time, the actual turn-off time, and the actual thermistor resistance value. The actual junction temperature of the target power device is determined based on the actual thermistor resistance value and the junction temperature detection model. The predicted turn-off time of the target power device is determined based on the actual junction temperature, the actual operating voltage, the collector current at the actual turn-off time, and the turn-off time prediction model. The aging degree of the target power device is determined based on the actual turn-off time and the predicted turn-off time, specifically including: The absolute value of the difference between the actual shutdown time and the predicted shutdown time is determined as the actual deviation value; When the actual deviation value is less than or equal to the first relative deviation value, the aging degree of the target power device is determined to be unaged; When the actual deviation value is greater than the first relative deviation value and the actual deviation value is less than the second relative deviation value, the aging degree of the target power device is determined to be slight aging. When the actual deviation value is greater than or equal to the second relative deviation value, the aging degree of the target power device is determined to be severe aging; When the aging degree of the target power device is slight aging or severe aging, life extension management measures are determined; the life extension management measures are used to extend the life of the target power device.

5. The method for health management of mining power electronic equipment according to claim 4, characterized in that, When the target power device is classified as slightly aged or severely aged, life extension management measures are determined, specifically including: When the target power device is only slightly aged, the life extension management measures are determined to be timely improvement of device cooling capacity and reduction of load power. When the target power device is severely aged, the life extension management measure is determined to be replacing the target power device.

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