Remaining life assessment method, apparatus and system for components, functional modules and systems

Abstract

The application discloses a method, device and system for evaluating the residual life of elements, functional modules and systems. The method comprises the following steps: S1, selecting sensitive devices capable of representing aging indexes in elements, functional modules and systems to determine a state detection strategy, wherein the sensitive devices comprise core components or secondary circuits; S2, applying a detection circuit to at least one sensitive device, wherein the detection circuit is a bypass circuit of the elements, functional modules and systems, and the residual life of each sensitive device under different stress conditions is calculated based on a physical model or an empirical model and a cumulative damage model by applying stress to the sensitive device; and S3, calculating the residual life of the entire element, functional module and system according to the residual life calculation results of each sensitive device and the weights represented by all the sensitive devices. The system and method have high calculation accuracy and low calculation complexity.

Description

Technical Field

[0001] This invention relates to the field of predictive maintenance, and more particularly to methods, apparatus and systems for assessing the remaining life of components, functional modules and systems. Background Technology

[0002] Predictive maintenance, or condition-based maintenance, is a more effective maintenance strategy than reactive and preventative maintenance. It is more targeted, based on factor-based diagnostic assessments such as the device's service life and environmental stresses. Therefore, remaining useful life (RUL) is a key step in predictive maintenance. Predictive maintenance targets devices, units (module circuits), and systems, primarily for diagnosing their condition and determining their service life.

[0003] The remaining service life is based on the fault condition (empirical or physical model) and / or the operating or device, unit (module circuit), and system environmental conditions.

[0004] Figure 1 This is the failure rate curve, also known as the bathtub curve, with time on the x-axis and the failure rate on the y-axis. The failure rate curve includes early failure stage A, random failure stage B, and final failure stage C. For electronic devices, early failure stage A primarily refers to the factory testing performed on the product, i.e., after the semiconductor device initialization operation. This invention applies to random failure stage B, which is considered to be randomly occurring excessive stress (e.g., power surges), specifically, when the device becomes unreliable after a period of use, determining its remaining lifespan. Final failure stage C is the inherent lifespan due to wear and tear and faults. When a device enters the final failure stage, the failure rate immediately tends to increase.

[0005] The calculation of remaining service life focuses on the remaining time during random failure phases, or on the wear and tear or aging of components, units (module circuits), and systems based on usage conditions. Because the electronic trip unit (ETC) of a circuit breaker has many components and different failure mechanisms, it is difficult to calculate the remaining service life of the electronic trip unit.

[0006] One existing approach provides a method for predicting the remaining lifetime of power systems for power plant electronic equipment, which includes sensors that collect data based on aging models and predict lifetime. The aging models used to calculate the remaining lifetime of the system include, for example, Palmgren-Miner, Arrhenius, and Coffin-Mansion, Eyring.

[0007] Another existing approach is to detect the aging of electronic equipment based on device and environmental conditions, which uses data collected from sensors such as temperature and vibration sensors. This approach then calculates an aging acceleration factor based on algorithms related to acceleration factors in relation to device and environmental conditions to assess the remaining lifespan of the device. Summary of the Invention

[0008] The first aspect of the present invention provides a method for assessing the remaining lifetime of components, functional modules, and systems, comprising the following steps: S1, selecting sensitive devices in the components, functional modules, and systems that can characterize aging indicators to determine a condition detection strategy, wherein the sensitive devices include core components or secondary circuits; S2, applying a detection circuit to at least one of the sensitive devices, wherein the detection circuit serves as a bypass circuit for the components, functional modules, and systems, and acquires the parameters of the sensitive devices under stress and calculates the remaining lifetime of each of the sensitive devices under different stress conditions based on a physical model, an empirical model, and a cumulative damage model; S3, calculating the remaining lifetime of the entire component, functional module, and system based on the remaining lifetime calculation results for each sensitive device and the weights represented by all sensitive devices.

[0009] Furthermore, the components, functional modules, and systems include an electronic trip unit.

[0010] Furthermore, step S1 also includes the following steps: analyzing the electronic trip unit, selecting sensitive devices in the electronic trip unit that can characterize aging indicators, and determining a state detection strategy. The analysis strategy includes calculating the mean time between failures based on a failure rate table, performing sensitivity analysis and reliability analysis based on simulation, and the analysis strategy conditions include operating parameters and environmental parameters.

[0011] Furthermore, the remaining life assessment method also includes the following steps: when it is impossible to select a sensitive device that can characterize aging indicators from the component, functional module, and system, a replacement device is selected for execution, wherein the replacement period should meet any one or more of the following: compared with the component, functional module, and system, the replacement device has a shorter mean time between failures; has a failure mechanism corresponding to the component, functional module, and system; has the same sensitivity to stress factors as the component, functional module, and system; and can be applied to physical failure models or empirical models.

[0012] Furthermore, step S2 also includes the following steps: obtaining the parameters of the sensitive device and collecting environmental and operating parameters by applying stress to the sensitive device, and calculating the remaining life of each of the sensitive devices under different stress conditions based on a physical model or empirical model and a cumulative damage model.

[0013] A second aspect of the present invention provides a system for assessing the remaining lifetime of components, functional modules, and systems, comprising: a processor; and a memory coupled to the processor, the memory having instructions stored therein, the instructions causing the electronic device to perform actions when executed by the processor, the actions including:

[0014] S1, Select sensitive devices that can characterize aging indicators in the components, functional modules, and systems to determine the condition detection strategy, wherein the sensitive devices include core components or secondary circuits; S2, Apply a detection circuit to at least one of the sensitive devices, wherein the detection circuit is a bypass circuit for the components, functional modules, and systems, which obtains the parameters of the sensitive devices under stress and calculates the remaining lifetime of each of the sensitive devices under different stress conditions based on a physical model, an empirical model, and a cumulative damage model; S3, Calculate the remaining lifetime of the entire component, functional module, and system based on the above calculation results of the remaining lifetime for each sensitive device and the weights represented by all sensitive devices.

[0015] Furthermore, the components, functional modules, and systems include an electronic trip unit.

[0016] Furthermore, action S1 also includes: analyzing the electronic trip unit, selecting sensitive devices in the electronic trip unit that can characterize aging indicators, and determining a state detection strategy. The analysis strategy includes calculating the mean time between failures based on a failure rate table, performing sensitivity analysis and reliability analysis based on simulation, and the analysis strategy conditions include operating parameters and environmental parameters.

[0017] Furthermore, the remaining life assessment method also includes the following action: when it is impossible to select a sensitive device that can characterize aging indicators from the component, functional module, and system, a replacement device is selected to perform the replacement, wherein the replacement period should meet any one or more of the following: compared with the component, functional module, and system, the replacement device has a shorter mean time between failures; has a failure mechanism corresponding to the component, functional module, and system; has the same sensitivity to stress factors as the component, functional module, and system; and can be applied to physical failure models or empirical models.

[0018] Furthermore, action S2 also includes: acquiring the parameters of the sensitive device and collecting environmental and operating parameters by applying stress to the sensitive device, and calculating the remaining life of each of the sensitive devices under different stress conditions based on a physical model or empirical model and a cumulative damage model.

[0019] A third aspect of the present invention provides an apparatus for assessing the remaining lifetime of components, functional modules, and systems, comprising: a selection device that selects sensitive devices in the components, functional modules, and systems that can characterize aging indicators to determine a condition detection strategy, wherein the sensitive devices include core components or secondary circuits.

[0020] A detection computing device applies a detection circuit to at least one of the sensitive devices, wherein the detection circuit serves as a bypass circuit for the component, functional module, and system. It acquires parameters of the sensitive device under stress and calculates the remaining lifetime of each of the sensitive devices under different stress conditions based on a physical model, an empirical model, and a cumulative damage model. A computing device calculates the remaining lifetime of the entire component, functional module, and system based on the remaining lifetime calculation results for each sensitive device and the weights represented by all sensitive devices.

[0021] A fourth aspect of the present invention provides a computer program product tangibly stored on a computer-readable medium and comprising computer-executable instructions that, when executed, cause at least one processor to perform the method according to a first aspect of the present invention.

[0022] A fifth aspect of the present invention provides a computer-readable medium having computer-executable instructions stored thereon, which, when executed, cause at least one processor to perform the method according to the first aspect of the present invention.

[0023] This invention can assess the aging degree of components, functional modules, and systems, especially electronic tripping devices, which is crucial reference information for determining technical maintenance plans. This invention can perform condition detection functions at a low cost and can be integrated into the design of new products. This invention reduces the computational complexity of predicting the lifespan of electronic tripping units. Due to the application of a physical fault model based on component failure mechanisms, this invention also boasts high accuracy. Furthermore, due to the online condition detection circuit, this invention is timely. Attached Figure Description

[0024] Figure 1 It is the failure rate curve;

[0025] Figure 2 This is a schematic diagram of a detection circuit for a method of assessing the remaining lifetime of components, functional modules, and systems according to a specific embodiment of the present invention.

[0026] Figure 3 This is an edge computing mode architecture diagram of a method for assessing the remaining lifetime of components, functional modules, and systems according to a specific embodiment of the present invention.

[0027] Figure 4This is a cloud computing model architecture diagram of a method for assessing the remaining lifetime of components, functional modules, and systems according to a specific embodiment of the present invention.

[0028] Figure 5 This is a circuit connection diagram of a sensitive device and its detection circuit for a remaining lifetime assessment mechanism of elements, functional modules, and systems according to a specific embodiment of the present invention. Detailed Implementation

[0029] The specific embodiments of the present invention will be described below with reference to the accompanying drawings.

[0030] This invention first determines the status detection strategy of the electronic trip unit (ETU), then integrates selected sensitive devices that characterize aging indicators into the ETU for monitoring. Finally, the remaining lifetime of the entire component, functional module, and system is calculated based on the acquired status information of the sensitive devices.

[0031] According to a preferred embodiment of the present invention, the elements, functional modules, and system include an electronic trip unit. The present invention is particularly suitable for application to electronic trip units. The present invention will now be described using an electronic trip unit as an example.

[0032] The first aspect of the present invention provides a method for assessing the remaining lifetime of components, functional modules, and systems, comprising the following steps:

[0033] First, step S1 is executed, selecting sensitive devices that can characterize aging indicators within the components, functional modules, and systems to determine a state detection strategy. These sensitive devices include core components or secondary circuits. Specifically, the sensitive devices include not only core components but also secondary circuits. Step S1 further includes the following sub-step: analyzing the electronic trip unit and selecting sensitive devices within the electronic trip unit that can characterize aging indicators to determine a state detection strategy. This involves first identifying key components and secondary circuits within the components, functional modules, and systems, and then selecting sensitive devices from among these key components and secondary circuits.

[0034] The analysis strategy includes calculating the mean time between failures (MTBF) based on a failure rate table, performing sensitivity analysis and reliability analysis based on simulation, and the analysis strategy conditions include operating parameters and environmental parameters.

[0035] Specifically, the state detection strategy of the electronic trip unit is first determined. The design of the electronic trip unit is analyzed at the component level, functional module level, and system level. This includes calculating the mean time between failures (MTBF) based on the failure rate table, performing sensitivity analysis based on simulation (Monte Carlo simulations of AC, DC, and transient conditions), and reliability testing (e.g., accelerated life testing). The conditions considered include the operating parameters and environmental parameters applied to the electronic trip unit. Based on the analysis results, key components or secondary circuits are identified. Then, representative sensitive devices are selected and integrated into the circuitry of the electronic trip unit, representing the core components and secondary circuits.

[0036] Sensitive devices fall into two categories. One type consists of components, functional modules, and systems that possess sensitive devices capable of calculating their remaining lifetime. The other type involves critical components that cannot be used to calculate their remaining lifetime, such as those that are too complex to be referenced by a suitable model. In such cases, components with similar sensitivity that can be calculated should be selected as substitutes.

[0037] The remaining lifetime assessment method further includes the following steps: when it is impossible to select a sensitive device that can characterize aging indicators from the components, functional modules, and systems, a replacement device is selected to perform the assessment, wherein the replacement period should satisfy any one or more of the following:

[0038] Compared to the component, functional module, and system, the alternative device has a shorter mean time between failures (MTBF).

[0039] It has a failure mechanism corresponding to the aforementioned components, functional modules, and systems, such as short circuits caused by heat.

[0040] It is sensitive to stress factors consistent with the components, functional modules, and systems, wherein the stress includes temperature, voltage, and current;

[0041] It can be applied to physical failure models or empirical models.

[0042] The second approach is used when critical components and secondary circuits lack a model for calculating remaining lifetime based on conditional detection information, or the model is too complex. For example, some critical components cannot be used to calculate remaining lifetime because they are too complex or there is no comparable model. In this case, components with similar sensitivity that can be calculated are selected as substitutes. Here, the model (physical failure model or empirical model) is clear, and the remaining lifetime can be assessed based on conditional detection information. Therefore, the remaining lifetime of the sensitive component can represent the entire electronic trip unit, without needing to test all components of the electronic trip unit and calculate their remaining lifetimes.

[0043] Then, step S2 is executed, applying a detection circuit to at least one of the sensitive devices. This detection circuit serves as a bypass circuit for the components, functional modules, and system. It acquires the parameters of the sensitive device under stress and calculates the remaining lifetime of each sensitive device under different stress conditions based on a physical model, an empirical model, and a cumulative damage model. Preferably, step S2 further includes the following steps: acquiring the parameters of the sensitive device under stress, collecting environmental and operational parameters, and calculating the remaining lifetime of each sensitive device under different stress conditions based on a physical model, an empirical model, and a cumulative damage model.

[0044] Specifically, detecting the sensitive device involves adding a detection circuit to the sensitive device of the electronic trip unit. The sensitive device (as a bypass circuit) is used as a bypass circuit, without affecting the main function of the electronic trip unit, and can sense the same stress. This allows for real-time monitoring of the sensitive device's condition. Optionally, multiple sensitive devices and their detection circuits are integrated into the electronic trip unit to represent the aging degree at different points within the electronic trip unit. Optionally, when environmental conditions should be monitored, sensors integrated into the electronic trip unit acquire parameters such as temperature, humidity, and vibration, which are sent to the electronic trip unit's controller. The remaining service life of the electronic trip unit is then calculated. The data sources are the monitoring circuit and sensors that collect environmental parameters; the lifespan is calculated under different stress conditions based on a physical or empirical model. The lifespan model algorithm is specific to the sensitive device and can execute data from the monitoring circuit and / or sensors. The lifespan model needs to be based on a fault physics model or empirical model, such as the Arrhenius model, Inverse Power Law, Eyring model, etc. Then, the remaining service life of the sensitive device is calculated based on a cumulative damage model. The cumulative damage model is a linear cumulative damage model that calculates the remaining lifetime based on the lifetime and the time spent working (input). For example, the cumulative damage model includes Miner's rule.

[0045] The sensitive device may include multiple secondary circuits and devices, so the detection circuit detects all secondary circuits and devices. Figure 2 This is a schematic diagram of a detection circuit for a method of assessing the remaining lifetime of components, functional modules, and systems according to a specific embodiment of the present invention. Figure 2As shown, the components, functional modules, and system include a first-stage circuit SC1, a second-stage circuit SC2, and a third-stage circuit SC3 connected in series. A first device C1 is connected between the first-stage circuit SC1 and the second-stage circuit SC2, and the other end of the first device C1 is connected to a first detection circuit MC1. A second device C2 is connected between the second-stage circuit SC2 and the third-stage circuit SC3, and the other end of the second device C2 is connected to a second detection circuit MC2. Both the first detection circuit MC1 and the second detection circuit MC2 are connected to a controller C. In addition, the controller C is also connected to at least one sensor S. The sensor S is used to collect environmental parameters and operating parameters, such as a temperature sensor for collecting temperature parameters, a vibration sensor for collecting vibration parameters, and a humidity sensor for collecting humidity parameters. The first detection circuit MC1 and the second detection circuit MC2 are used to detect the stress applied to the aforementioned devices and / or secondary circuits and obtain the parameters of the devices and / or secondary circuits. Then, the controller C calculates the remaining life of each device and / or secondary circuit under different stress conditions based on a physical model, an empirical model, and a cumulative damage model.

[0046] Finally, step S3 is executed to calculate the remaining lifetime of the entire component, functional module, and system based on the remaining lifetime calculation results for each sensitive device and the weights represented by all sensitive devices. The number of sensitive devices in the entire system and the relationships between the sensitive devices and the circuits they represent can represent their respective weights.

[0047] Figure 3 This is an edge computing mode architecture diagram of the remaining lifetime assessment method of the present invention, including components, functional modules, and systems according to a specific embodiment. The hardware architecture required for applying the remaining lifetime assessment device provided by the present invention is as follows: Figure 3 As shown, the hardware architecture 100 includes a real-time condition detection circuit 120 with sensitive devices, which is a bypass circuit and therefore does not affect any function of the electronic trip unit. This hardware architecture includes optional sensors 130 for monitoring environmental conditions, such as temperature, humidity, and vibration sensors. The controller 110 includes a signal processing unit 112, a remaining lifetime calculation unit 114, and a maintenance plan determination unit 116. The edge-based controller 110 receives signals from the aforementioned real-time condition detection circuit 120 and sensors 130. The remaining lifetime calculation unit 114 executes the signals based on an algorithm, and then the maintenance plan determination unit 116 determines a maintenance plan for the component, functional module, and system based on the remaining lifetime information. Preferably, the controller 110 includes an MCU.

[0048] According to a variation of the present invention, Figure 3This is a cloud computing architecture diagram of a method for assessing the remaining lifetime of components, functional modules, and systems according to a specific embodiment of the present invention. Its hardware structure 200 includes a controller 210, a cloud platform 240, a real-time condition detection circuit 220, and a sensor 230. The controller 210 is specifically a cloud-based MCU. The controller 210 includes a signal processing unit 212, which receives signals from the real-time condition detection circuit 220 and the sensor 230, executes the signals, and sends them to the cloud platform 240. The cloud platform 240 has a remaining lifetime calculation unit 242 and a maintenance plan determination unit 244. The remaining lifetime calculation unit 242 executes the signals based on an algorithm and calculates the remaining lifetime, and optimizes the algorithm through machine learning. Then, the maintenance plan determination unit 244 determines the maintenance plan for the component, functional module, and system based on the remaining lifetime information. In other words, in this embodiment, some calculations are performed using the cloud; local processing is only performed, while the cloud handles the computation. This is because executing the present invention requires computational resources, local computing power is low, cloud computing power is strong, and the cloud can also update and optimize the algorithm calculations.

[0049] The invention will now be described using a specific application scenario. For example... Figure 5 As shown, the circuit architecture includes a power supply circuit P3, other circuits OC3, a resistor R3, a capacitor C3, an operational amplifier OPA, a controller M3, and a temperature sensor S3. Specifically, the power supply circuit P3 is connected to other circuits OC3, and a resistor R3 is connected between the power supply circuit P3 and other circuits OC3. The other end of the resistor R3 is connected to a capacitor C3, which serves as a sensing device. The operational amplifier OPA acts as a detection circuit, and its input terminals are connected to the resistor R3 and the connection points between P3 and other circuits OC3, the connection point between the resistor R3 and the capacitor C3, and the connection point between the capacitor C3 and the ground terminal. The operational amplifier OPA is connected to the analog-to-digital converter module in the controller M3. In addition, the controller M3 is also connected to a temperature sensor S3. In this embodiment, the remaining lifespan of the entire electronic tripping device is calculated by calculating the aging degree of the capacitor C3. The operational amplifier OPA acts as a detection circuit to collect signals and send them to the controller M3. The other circuits OC3 include the power supply section of the sub-circuit of the electronic tripping device.

[0050] In step S1 of this invention, the electrolytic aluminum capacitor C3 is selected as the sensitive device. Therefore, capacitor C3 and its detection circuit are integrated into the power supply circuit P3 of the electronic trip unit to act as a bypass circuit. The current and voltage signals of capacitor C3 are then monitored. Temperature sensor S3 is integrated into the electronic trip unit to monitor the ambient temperature.

[0051] There are many methods to predict the remaining life of capacitor C3 in electrolytic aluminum production, one of which is the equivalent series resistance (ESR) method. The equivalent series resistance is calculated using ripple current and voltage; therefore, the capacitor's ESR is:

[0052]

[0053] The remaining lifetime of capacitor C3 is based on a failure physics model, and the remaining lifetime of capacitor C3 is:

[0054]

[0055] Among them, ESR limit Let Ea be the predicted ESR value when capacitor C3 reaches the end of its service life, and ESR(0) be the initial value of capacitor C3. ESR When considering the activation energy as an indicator of aging, k is the Boltzmann constant (8617*10-5eV / K), Ta is the aging temperature, T' is the ambient temperature (e.g., 85℃), and A1 and B1 are parameters related to the capacitor type, therefore, the remaining lifetime of the sensitive device is:

[0056]

[0057] RUL COMP i Let k be the remaining lifetime of the i-th sensitive device. i These are weighting parameters based on the sensitive device.

[0058] A second aspect of the present invention provides a system for assessing the remaining lifetime of components, functional modules, and systems, comprising: a processor; and a memory coupled to the processor, the memory having instructions stored therein, the instructions causing the electronic device to perform actions when executed by the processor, the actions including:

[0059] S1, Select sensitive devices that can characterize aging indicators in the components, functional modules, and systems to determine the condition detection strategy, wherein the sensitive devices include core components or secondary circuits; S2, Apply a detection circuit to at least one of the sensitive devices, wherein the detection circuit is a bypass circuit for the components, functional modules, and systems, which obtains the parameters of the sensitive devices under stress and calculates the remaining lifetime of each of the sensitive devices under different stress conditions based on a physical model, an empirical model, and a cumulative damage model; S3, Calculate the remaining lifetime of the entire component, functional module, and system based on the above calculation results of the remaining lifetime for each sensitive device and the weights represented by all sensitive devices.

[0060] Furthermore, the components, functional modules, and systems include an electronic trip unit.

[0061] Furthermore, action S1 also includes: analyzing the electronic trip unit, selecting sensitive devices in the electronic trip unit that can characterize aging indicators, and determining a state detection strategy. The analysis strategy includes calculating the mean time between failures based on a failure rate table, performing sensitivity analysis and reliability analysis based on simulation, and the analysis strategy conditions include operating parameters and environmental parameters.

[0062] Furthermore, the remaining life assessment method also includes the following action: when it is impossible to select a sensitive device that can characterize aging indicators from the component, functional module, and system, a replacement device is selected to perform the replacement, wherein the replacement period should meet any one or more of the following: compared with the component, functional module, and system, the replacement device has a shorter mean time between failures; has a failure mechanism corresponding to the component, functional module, and system; has the same sensitivity to stress factors as the component, functional module, and system; and can be applied to physical failure models or empirical models.

[0063] Furthermore, action S2 also includes: acquiring the parameters of the sensitive device and collecting environmental and operating parameters by applying stress to the sensitive device, and calculating the remaining life of each of the sensitive devices under different stress conditions based on a physical model or empirical model and a cumulative damage model.

[0064] A third aspect of the present invention provides an apparatus for assessing the remaining lifetime of components, functional modules, and systems, comprising: a selection device that selects sensitive devices in the components, functional modules, and systems that can characterize aging indicators to determine a condition detection strategy, wherein the sensitive devices include core components or secondary circuits.

[0065] A detection computing device applies a detection circuit to at least one of the sensitive devices, wherein the detection circuit serves as a bypass circuit for the component, functional module, and system. It acquires parameters of the sensitive device under stress and calculates the remaining lifetime of each of the sensitive devices under different stress conditions based on a physical model, an empirical model, and a cumulative damage model. A computing device calculates the remaining lifetime of the entire component, functional module, and system based on the remaining lifetime calculation results for each sensitive device and the weights represented by all sensitive devices.

[0066] A fourth aspect of the present invention provides a computer program product tangibly stored on a computer-readable medium and comprising computer-executable instructions that, when executed, cause at least one processor to perform the method according to a first aspect of the present invention.

[0067] A fifth aspect of the present invention provides a computer-readable medium having computer-executable instructions stored thereon, which, when executed, cause at least one processor to perform the method according to the first aspect of the present invention.

[0068] This invention can assess the aging degree of components, functional modules, and systems, especially electronic tripping devices, which is crucial reference information for determining technical maintenance plans. This invention can perform condition detection functions at a low cost and can be integrated into the design of new products. This invention reduces the computational complexity of predicting the lifespan of electronic tripping units. Due to the application of a physical fault model based on component failure mechanisms, this invention also boasts high accuracy. Furthermore, due to the online condition detection circuit, this invention is timely.

[0069] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above. Therefore, the scope of protection of the present invention should be defined by the appended claims. Furthermore, no reference numerals in the claims should be construed as limiting the scope of the claims; the word "comprising" does not exclude any means or steps not listed in other claims or the specification; the words "first," "second," etc., are used only to indicate names and do not indicate any specific order.

Claims

1. Methods for assessing the remaining life of components, functional modules, and systems, wherein, Includes the following steps: S1, Select sensitive devices that can characterize aging indicators in the components, functional modules and systems to determine the state detection strategy, wherein the sensitive devices include core components or secondary circuits; wherein the components, functional modules and systems include electronic trip units; S2, applying a detection circuit to at least one of the sensitive devices, wherein the detection circuit serves as a bypass circuit for the components, functional modules, and system, and acquires the parameters of the sensitive device under stress and calculates the remaining lifetime of each of the sensitive devices under different stress conditions based on a physical model, an empirical model, and a cumulative damage model; S3. Based on the remaining lifetime calculation results for each sensitive device and the weights represented by all sensitive devices, calculate the remaining lifetime of the entire component, functional module and system. When a sensitive device capable of characterizing aging indicators cannot be selected from the components, functional modules, and systems, an alternative device is selected to perform the operation. The alternative device should satisfy one or more of the following conditions: Compared to the component, functional module, and system, the alternative device has a shorter mean time between failures (MTBF). It has a failure mechanism corresponding to the aforementioned components, functional modules, and system; It exhibits sensitivity to stress factors consistent with the components, functional modules, and systems described herein; It can be applied to physical failure models or empirical models.

2. The method for assessing the remaining life of components, functional modules, and systems according to claim 1, characterized in that, Step S1 further includes the following steps: Analyze the electronic trip unit, select sensitive devices within the electronic trip unit that can characterize aging indicators, and determine the state detection strategy. The analysis strategy includes calculating the mean time between failures (MTBF) based on a failure rate table, and performing sensitivity and reliability analysis based on simulation. The analysis strategy conditions include operating parameters and environmental parameters.

3. The method for assessing the remaining life of components, functional modules, and systems according to claim 1, characterized in that, Step S2 further includes the following steps: obtaining the parameters of the sensitive device and collecting environmental and operating parameters by applying stress to the sensitive device, and calculating the remaining life of each of the sensitive devices under different stress conditions based on a physical model or empirical model and a cumulative damage model.

4. A system for assessing the remaining lifespan of components, functional modules, and systems, wherein, include: processor; as well as A memory coupled to the processor, the memory having instructions stored therein, the instructions which, when executed by the processor, cause the electronic device to perform actions, the actions including: S1, Select a sensitive device that can characterize aging indicators from the components, functional modules, and systems to determine a condition detection strategy, wherein the sensitive device includes core components or secondary circuits; wherein the components, functional modules, and systems include electronic trip units; when it is not possible to select a sensitive device that can characterize aging indicators from the components, functional modules, and systems, a substitute device is selected to perform the operation, wherein the substitute device should meet any one or more of the following requirements: compared with the component, functional module, and system, the substitute device has a shorter mean time between failures; has a failure mechanism corresponding to the component, functional module, and system; has a stress factor sensitivity consistent with the component, functional module, and system; and can be applied to physical failure models or empirical models; S2, applying a detection circuit to at least one of the sensitive devices, wherein the detection circuit serves as a bypass circuit for the components, functional modules, and system, and acquires the parameters of the sensitive device under stress and calculates the remaining lifetime of each of the sensitive devices under different stress conditions based on a physical model, an empirical model, and a cumulative damage model; S3. Based on the remaining lifetime calculation results for each sensitive device and the weights represented by all sensitive devices, calculate the remaining lifetime of the entire component, functional module and system.

5. The system for assessing the remaining lifespan of components, functional modules, and systems according to claim 4, characterized in that, The action S1 also includes: Analyze the electronic trip unit, select sensitive devices within the electronic trip unit that can characterize aging indicators, and determine the state detection strategy. The analysis strategy includes calculating the mean time between failures (MTBF) based on a failure rate table, and performing sensitivity and reliability analysis based on simulation. The analysis strategy conditions include operating parameters and environmental parameters.

6. The system for assessing the remaining lifespan of components, functional modules, and systems according to claim 5, characterized in that, The action S2 further includes: acquiring the parameters of the sensitive device and collecting environmental and operating parameters by applying stress to the sensitive device, and calculating the remaining life of each of the sensitive devices under different stress conditions based on a physical model, an empirical model, and a cumulative damage model.

7. Devices for assessing the remaining life of components, functional modules, and systems, wherein, include: The selection device selects sensitive devices in the components, functional modules, and systems that can characterize aging indicators to determine a condition detection strategy, wherein the sensitive devices include core components or secondary circuits; wherein the components, functional modules, and systems include electronic trip units. A detection computing device applies a detection circuit to at least one of the sensitive devices, wherein the detection circuit serves as a bypass circuit for the components, functional modules, and system, and acquires parameters of the sensitive devices under stress and calculates the remaining lifetime of each of the sensitive devices under different stress conditions based on a physical model, an empirical model, and a cumulative damage model; The computing device calculates the remaining lifetime of the entire component, functional module and system based on the remaining lifetime calculation results for each sensitive device and the weights represented by all sensitive devices. When a sensitive device capable of characterizing aging indicators cannot be selected from the components, functional modules, and systems, an alternative device is selected to perform the operation. The alternative device should satisfy one or more of the following conditions: Compared to the component, functional module, and system, the alternative device has a shorter mean time between failures (MTBF). It has a failure mechanism corresponding to the aforementioned components, functional modules, and system; It exhibits sensitivity to stress factors consistent with the components, functional modules, and systems described herein; It can be applied to physical failure models or empirical models.

8. A computer program product tangibly stored on a computer-readable medium and comprising computer-executable instructions that, when executed, cause at least one processor to perform the method according to any one of claims 1 to 3.

9. A computer-readable medium having stored thereon computer-executable instructions, which, when executed, cause at least one processor to perform the method according to any one of claims 1 to 3.

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