WO2022133825A1 - 元件、功能模块和系统的剩余寿命评估方法、装置和系统 - Google Patents

元件、功能模块和系统的剩余寿命评估方法、装置和系统 Download PDF

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WO2022133825A1
WO2022133825A1 PCT/CN2020/138699 CN2020138699W WO2022133825A1 WO 2022133825 A1 WO2022133825 A1 WO 2022133825A1 CN 2020138699 W CN2020138699 W CN 2020138699W WO 2022133825 A1 WO2022133825 A1 WO 2022133825A1
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Prior art keywords
components
functional modules
remaining life
sensitive
systems
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PCT/CN2020/138699
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English (en)
French (fr)
Inventor
刘臻
陈维刚
庞建国
朱怡
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西门子股份公司
西门子（中国）有限公司
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Priority to CN202080097738.8A priority Critical patent/CN115190976A/zh
Priority to DE112020006521.9T priority patent/DE112020006521T5/de
Priority to PCT/CN2020/138699 priority patent/WO2022133825A1/zh
Publication of WO2022133825A1 publication Critical patent/WO2022133825A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/28—Testing of electronic circuits, e.g. by signal tracer
    • G01R31/2832—Specific tests of electronic circuits not provided for elsewhere
    • G01R31/2836—Fault-finding or characterising
    • G01R31/2837—Characterising or performance testing, e.g. of frequency response
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/28—Testing of electronic circuits, e.g. by signal tracer
    • G01R31/2832—Specific tests of electronic circuits not provided for elsewhere
    • G01R31/2836—Fault-finding or characterising
    • G01R31/2846—Fault-finding or characterising using hard- or software simulation or using knowledge-based systems, e.g. expert systems, artificial intelligence or interactive algorithms
    • G01R31/2848—Fault-finding or characterising using hard- or software simulation or using knowledge-based systems, e.g. expert systems, artificial intelligence or interactive algorithms using simulation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/26—Testing of individual semiconductor devices
    • G01R31/27—Testing of devices without physical removal from the circuit of which they form part, e.g. compensating for effects surrounding elements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/28—Testing of electronic circuits, e.g. by signal tracer
    • G01R31/282—Testing of electronic circuits specially adapted for particular applications not provided for elsewhere
    • G01R31/2827—Testing of electronic protection circuits
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/28—Testing of electronic circuits, e.g. by signal tracer
    • G01R31/2832—Specific tests of electronic circuits not provided for elsewhere
    • G01R31/2836—Fault-finding or characterising
    • G01R31/2843—In-circuit-testing
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/327—Testing of circuit interrupters, switches or circuit-breakers

Definitions

  • the present invention relates to the field of predictive maintenance, and in particular, to a method, device and system for evaluating the remaining life of components, functional modules and systems.
  • Predictive maintenance or condition-based maintenance is a more effective maintenance strategy than reactive and preventive maintenance.
  • Predictive maintenance, or condition-based maintenance is more targeted, based on a diagnostic assessment of factors such as age of equipment, environmental stress, etc. Therefore, Remaining Useful Life (RUL) is a key step in predictive maintenance.
  • the objects of predictive maintenance include devices, units (module circuits), and systems, and are mainly used for diagnosing status and judging service life.
  • Remaining useful life is based on failure state (empirical or physical model) and/or operation or device, unit (module circuit), system environmental conditions.
  • Figure 1 is a failure rate curve (Failure Rate Curve), namely a bathtub curve (Bathtub Curve), its abscissa is time, and its ordinate is failure rate.
  • the failure rate curve includes early failure stage A, random failure stage B and failure stage C.
  • the early failure stage A is mainly aimed at the exit detection performed when the product is in the factory, that is, after the initialization of the semiconductor device.
  • the present invention is applicable to the random failure stage B, which is considered to be excessive stress (such as power surge) that occurs randomly, specifically, the product is used for a period of time and the device is unreliable, and the remaining life is judged.
  • Failure stage C is the intrinsic life due to wear and tear. When a device enters the failure phase failure, the failure rate tends to increase immediately.
  • the remaining service life For the calculation of the remaining service life, it focuses on the question of how long the remaining time of the random failure phase is, or the wear or aging degree of the device, unit (module circuit), system based on the usage situation. Since the electronic trip unit (ETC, Electronic Trip Unit) of the circuit breaker has many components and different failure mechanisms, it is difficult to calculate the remaining service life of the electronic trip unit.
  • ETC Electronic Trip Unit
  • One solution of the prior art is to provide a method for predicting the remaining life of a power system of a power plant electronic device, which includes sensors that collect data and predict life based on an aging model.
  • aging models are used to calculate the remaining life of the system, such as Palmgren-Miner, Arrhenius and Coffin-Mansion, Eyring.
  • Another solution in the prior art is to detect the aging of electronic equipment based on equipment and environmental conditions, which uses data collected from sensors, such as temperature sensors, shock sensors.
  • the scheme then calculates the aging acceleration factor based on an algorithm related to the acceleration factor related to the device and environmental conditions to estimate the remaining life of the device.
  • a first aspect of the present invention provides a method for evaluating the remaining life of components, functional modules and systems, which includes the following steps: S1, selecting the components, functional modules and sensitive devices in the system that can characterize aging indicators to determine a state 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, It obtains the parameters of the sensitive device under the condition that the sensitive device applies stress and calculates the remaining life of each of the sensitive devices under different stress conditions based on a physical model or an empirical model and a cumulative damage model; S3, according to the above for The calculation result of the remaining life of each sensitive device and the weights represented by all the sensitive devices calculate the remaining life of the entire component, functional module and system.
  • components, functional modules and systems include electronic trip units.
  • step S1 further includes the following steps: analyzing the electronic trip unit, and selecting a sensitive device in the electronic trip unit that can characterize the aging index to determine a state detection strategy, wherein the analysis strategy includes based on The failure rate table calculates the mean time between failures, and performs sensitivity analysis and reliability analysis based on the simulation, wherein the analysis strategy conditions include operating parameters and environmental parameters.
  • the remaining life evaluation method further includes the following steps: when a sensitive device that can characterize the aging index cannot be selected from the components, functional modules and systems, selecting a replacement device for execution, wherein the replacement period should be Satisfy any one or more of the following: compared with the component, functional module and system, the replacement device has a smaller mean time between failures; has a failure mechanism corresponding to the component, functional module and system; has Sensitive to stress factors consistent with the described components, functional modules and systems; can be applied to physical failure models or empirical models.
  • step S2 further includes the following steps: by acquiring the parameters of the sensitive device and collecting the environmental parameters and operating parameters under the condition of applying stress to the sensitive device, and calculating different parameters based on a physical model or an empirical model and a cumulative damage model. The remaining life of each of the sensitive devices under stress conditions.
  • a second aspect of the present invention provides a remaining life assessment system for components, functional modules, and systems, comprising: a processor; and a memory coupled to the processor, the memory having instructions stored therein, the instructions in When executed by the processor, the electronic device is caused to perform an action, the action comprising:
  • S1 select the components, functional modules and sensitive devices in the system that can characterize the aging index to determine a state detection strategy, wherein the sensitive devices include core components or secondary circuits;
  • S2 apply at least one of the sensitive devices A detection circuit, wherein the detection circuit is a bypass circuit as the element, functional module and system, which obtains the sensitive device parameters and based on a physical model or an empirical model by obtaining the sensitive device parameters under the condition of stress applied to the sensitive device And the cumulative damage model calculates the remaining life of each of the sensitive devices under different stress conditions;
  • S3 according to the above calculation results of the remaining life of each sensitive device and the weights represented by all the sensitive devices Calculate the entire component, functional module and The remaining life of the system.
  • components, functional modules and systems include electronic trip units.
  • the action S1 further includes: analyzing the electronic trip unit, and selecting a sensitive device in the electronic trip unit that can characterize the aging index to determine a state detection strategy, wherein the analysis strategy includes a failure rate-based detection strategy.
  • the table calculates the mean time between failures, and performs sensitivity analysis and reliability analysis based on simulation, wherein the analysis strategy conditions include operating parameters and environmental parameters.
  • the remaining life evaluation method further includes the following actions: when a sensitive device that can characterize the aging index cannot be selected from the components, functional modules and systems, selecting a replacement device for execution, wherein the replacement period should be Satisfy any one or more of the following: compared with the component, functional module and system, the replacement device has a smaller mean time between failures; has a failure mechanism corresponding to the component, functional module and system; has Sensitive to stress factors consistent with the described components, functional modules and systems; can be applied to physical failure models or empirical models.
  • the action S2 also includes: acquiring parameters of the sensitive device and collecting environmental parameters and operating parameters when the sensitive device is stressed, and calculating different stress conditions based on a physical model or an empirical model and a cumulative damage model the remaining life of each of the sensitive devices.
  • a third aspect of the present invention provides a device for evaluating the remaining life of components, functional modules, and systems, including: a selection device that selects the components, functional modules, and sensitive devices in the system that can characterize aging indicators to determine a state detection strategy , wherein the sensitive devices include core components or secondary circuits;
  • a detection computing device that applies 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 can be used in the case of stress applied to the sensitive device. Acquiring parameters of the sensitive device and calculating the remaining life of each of the sensitive devices under different stress conditions based on a physical model or an empirical model and a cumulative damage model; a computing device, which is based on the above calculation results for the remaining life of each sensitive device and The weights represented by all sensitive devices calculate the remaining lifetime of the entire component, functional module and system.
  • a fourth aspect of the present invention provides a computer program product tangibly stored on a computer-readable medium and comprising computer-executable instructions which, when executed, cause at least one processor to perform a The method described in the first aspect of the present invention.
  • a fifth aspect of the present invention provides a computer-readable medium having stored thereon computer-executable instructions which, when executed, cause at least one processor to perform the method according to the first aspect of the present invention.
  • the invention can evaluate the aging degree of components, functional modules and systems, especially electronic tripping devices, which is very important reference information for technical maintenance planning decisions.
  • the present invention can perform a condition detection function with low cost, and can be used as a design for new product integration.
  • the invention can reduce the computational complexity of the life prediction of the electronic trip unit.
  • the present invention is also highly accurate due to the application of physical failure models based on component failure mechanisms. Also, the present invention is timely due to the online condition detection circuit.
  • Figure 1 is the failure rate curve
  • FIG. 2 is a schematic diagram of a detection circuit of a method for evaluating the remaining life of components, functional modules and systems according to a specific embodiment of the present invention
  • FIG. 3 is an edge computing mode architecture diagram of a method for evaluating the remaining life of components, functional modules and systems according to a specific embodiment of the present invention
  • FIG. 4 is a cloud computing model architecture diagram of a method for evaluating the remaining life of components, functional modules and systems according to a specific embodiment of the present invention
  • FIG. 5 is a circuit connection diagram of a sensitive device and a detection circuit thereof of the remaining life evaluation mechanism of the components, functional modules and systems according to a specific embodiment of the present invention.
  • the invention first determines the state detection strategy of the electronic trip unit, and then the selected sensitive devices that can characterize the aging index are integrated into the ETU for monitoring. Finally, the remaining lifetimes of the entire components, functional modules and systems are calculated based on the acquired state information of the sensitive devices.
  • the elements, functional modules and systems comprise electronic trip units.
  • the present invention is especially suitable for being applied to an electronic trip unit.
  • the present invention will be described below by taking an electronic trip unit as an example.
  • a first aspect of the present invention provides a method for evaluating the remaining life of components, functional modules and systems, including the following steps:
  • step S1 is performed to select the components, functional modules and sensitive devices in the system that can characterize the aging index to determine a state detection strategy, wherein the sensitive devices include core components or secondary circuits.
  • the sensitive device includes not only the device but also the secondary circuit.
  • the step S1 further includes the following sub-steps: analyzing the electronic trip unit, and selecting a sensitive device in the electronic trip unit that can represent an aging index to determine a state detection strategy.
  • key devices and secondary circuits should be determined in the elements, functional modules and systems first, and then sensitive devices should be selected in the key devices and secondary circuits.
  • the analysis strategy includes calculating the mean time between failures based on the failure rate table, and performing sensitivity analysis and reliability analysis based on simulation, wherein the analysis strategy conditions include operating parameters and environmental parameters.
  • the state detection strategy of the electronic trip unit is first determined, and the design of the electronic trip unit is analyzed based on the component level, functional module level and system level, including calculating the mean time between failures based on the failure rate table, and sensitivity based on simulation. Analysis (AC, DC and transients for Monte Carlo simulations) and reliability testing (eg accelerated life testing) where conditions are considered including operating parameters applied to the electronic trip unit, environmental parameters. Based on the analysis results, key components or secondary circuits are determined, and then representative sensitive components are selected and integrated into the circuit of the electronic trip unit, which can represent the core components and secondary circuits.
  • the remaining life evaluation method further includes the following steps: when a sensitive device that can characterize the aging index cannot be selected from the components, functional modules and systems, selecting a replacement device for execution, wherein the replacement period should satisfy any of the following requirements: One or any of the following:
  • the replacement device Compared with the component, functional module and system, the replacement device has a smaller mean time between failures
  • the second is that the key components and secondary circuits do not have any models or models that are too complex to calculate the remaining service life based on the condition detection information. For example, some key components cannot be used to calculate the remaining service life, for example, they are too complicated or there is no reference model, select components with similar sensitivity that can be calculated instead. Where the model (physical failure model or empirical model) is clear, the remaining service life can be estimated based on condition detection information. Therefore, the remaining life of the sensitive device can be representative of the entire electronic trip unit without having to detect all components of the electronic trip unit and calculate their remaining life.
  • step S2 is performed to 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 can pass through the sensitive device under the condition of stress.
  • the detection circuit is a bypass circuit for the components, functional modules and systems, which can pass through the sensitive device under the condition of stress.
  • the step S2 further includes the following steps: acquiring parameters of the sensitive device and collecting environmental parameters and operating parameters under the condition of stress applied to the sensitive device, and calculating different parameters based on a physical model or an empirical model and a cumulative damage model The remaining life of each of the sensitive devices under stress conditions.
  • to detect the sensitive device is to add a detection circuit to the sensitive device of the electronic trip unit.
  • a detection circuit to the sensitive device of the electronic trip unit.
  • the sensitive device substituted as a bypass circuit does not affect the main function of the electronic trip unit and can sense the same stress.
  • a plurality of sensitive devices and their detection circuits are integrated into the electronic trip unit to represent the aging degree of different points of the electronic trip unit.
  • sensors are integrated in the electronic trip unit to 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 source is the monitoring circuit, the sensor that collects the environmental parameters, and the life under different stress conditions is calculated based on the physical model or the empirical model.
  • the algorithm of the lifetime model is for sensitive devices, which can execute data from monitoring circuits and/or sensors.
  • the life model needs to be based on the failure physics model or empirical model, such as Arrhenius model, Inverse Power Law, Eyring model, etc.
  • a remaining lifetime calculation of the sensitive device is then performed based on the cumulative damage model.
  • the cumulative damage model is a linear cumulative damage, which calculates the remaining life based on the cumulative damage model according to the life and the time of operation (input).
  • cumulative damage models include Miner's rule.
  • the sensitive device may include multiple secondary circuits and devices, so the detection circuit detects all the secondary circuits and devices.
  • 2 is a schematic diagram of a detection circuit of a method for evaluating the remaining life of components, functional modules and systems according to a specific embodiment of the present invention.
  • the components, functional modules and systems include a first secondary circuit SC 1 , a second secondary circuit SC 2 and a third secondary circuit SC 3 which are connected in series in sequence.
  • a first device C 1 is connected between the first secondary circuit SC 1 and the second secondary circuit SC 2 , and the other end of the first device C 1 is connected with a first detection circuit MC 1 .
  • a second device C 2 is connected between the second secondary circuit SC 2 and the third secondary circuit SC 3 , and a second detection circuit MC 2 is connected to the other end of the second device C 2 .
  • the first detection circuit MC1 and the second detection circuit MC2 are both connected to the controller C.
  • at least one sensor S is also connected to the controller C.
  • the sensor S is used to collect environmental parameters and operating parameters, for example, a temperature sensor is used to collect temperature parameters, a vibration sensor is used to collect vibration parameters, and a humidity sensor is used to collect humidity parameters.
  • the first detection circuit MC 1 and the second detection circuit MC 2 are used to detect the above-mentioned device and/or the secondary circuit under the condition of applying stress to obtain the parameters of the device and/or the secondary circuit, and then the controller C is based on the physical model or experience.
  • the model, as well as the cumulative damage model, calculates the remaining life of each device and/or secondary circuit under different stress conditions.
  • step S3 is performed to calculate the remaining life of the entire component, functional module and system according to the above calculation result of the remaining life of each sensitive device and the weights represented by all the sensitive devices. Among them, how many sensitive devices are in the whole system, and the relationship between the sensitive devices and the circuits they represent can represent their respective weights.
  • FIG. 3 is an edge computing mode architecture diagram of a method for evaluating the remaining life of components, functional modules and systems according to a specific embodiment of the present invention.
  • the hardware architecture required for applying the remaining life evaluating device provided by the present invention is shown in FIG. 3 .
  • 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.
  • the hardware architecture includes optional sensors 130 that monitor environmental conditions, such as temperature sensors, humidity sensors, and vibration sensors.
  • the controller 110 includes signal processing means 112 , remaining life calculation means 114 and maintenance plan decision means 116 .
  • the edge device-based controller 110 receives the signals from the above-mentioned real-time condition detection circuit 120 and the sensor 130, the remaining service life calculation means 114 executes the above signals based on an algorithm, and then the maintenance plan decision means 116 decides based on the remaining life information. Maintenance plans for modules and systems.
  • the controller 110 includes an MCU.
  • FIG. 3 is a cloud computing model architecture diagram of a method for evaluating the remaining life of components, functional modules and systems according to a specific embodiment of the present invention, the hardware mechanism 200 of which includes a controller 210, a cloud platform 240, a real-time Condition detection circuit 220 and sensor 230 .
  • the controller 210 is in particular an MCU, which is cloud-based.
  • the controller 210 includes a signal processing device 212 that receives signals from the real-time condition detection circuit 220 and the sensor 230 , and then executes the signals and sends the signals to the cloud platform 240 .
  • the cloud platform 240 has a remaining life calculation device 242 and a maintenance plan decision device 244.
  • the remaining life calculation device 242 executes the above-mentioned signal based on an algorithm and calculates the remaining life, and optimizes the algorithm through machine learning, and then the maintenance plan decision device 244 determines the remaining life based on the remaining life information.
  • Components, functional modules and system maintenance plans That is to say, in this embodiment, part of the calculation needs to rely on the cloud, only signal processing is performed locally, and the cloud is responsible for the calculation. Algorithmic calculations can also be updated and optimized.
  • the circuit structure includes a power circuit P 3 , other circuits OC 3 , a resistor R 3 , a capacitor C 3 , an operational amplifier OPA, a controller M 3 , and a temperature sensor S 3 .
  • the power circuit P 3 is connected to other circuits OC 3
  • a resistor R 3 is connected between the power circuit P 3 and the other circuits OC 3
  • the other end of the resistor R 3 is connected to a capacitor C 3 as a sensitive device .
  • the operational amplifier OPA is used as a detection circuit, and its input terminals are respectively connected between the resistor R 3 and the connection point between the P 3 and other circuits OC 3 , the connection point between the resistor R 3 and the capacitor C 3 , the capacitor Connection point between C3 and ground.
  • the operational amplifier OPA is connected to the analog - to - digital conversion module in the controller M3, and the controller M3 is also connected to a temperature sensor S3 . In this embodiment, the remaining life of the entire electronic trip device is calculated by calculating the aging degree of the capacitor C 3 .
  • the operational amplifier OPA is used as a detection circuit to collect signals and send them to the controller M 3 .
  • Other circuits OC 3 include electronic trip devices.
  • the capacitor C3 of electrolytic aluminum is selected as the sensitive device, so the capacitor C3 and its detection circuit are integrated into the power circuit P3 of the electronic trip unit to serve as a bypass circuit. Then the current - voltage signal of capacitor C3 is monitored. A temperature sensor S3 is integrated into the electronic trip unit to monitor the ambient temperature.
  • ESR equivalent series resistance
  • the remaining life of capacitor C 3 is based on the failure physical model, and the remaining life of capacitor C 3 is:
  • ESR limit is the predicted ESR value when the service life of capacitor C 3 is terminated
  • ESR(0) is the initial value of capacitor C 3
  • Ea ESR is the activation energy when considering ESR as an indicator of aging
  • k is Boltz Mann's constant (8617*10-5eV/K)
  • Ta is the aging temperature
  • T' is the ambient temperature (eg 85°C)
  • a 1 and B 1 are parameters related to the capacitor type, so the remaining life of the sensitive device is:
  • RUL COMP i is the remaining lifetime of the i -th sensitive device, and ki is a weight parameter based on the sensitive device.
  • a second aspect of the present invention provides a remaining life assessment system for components, functional modules, and systems, comprising: a processor; and a memory coupled to the processor, the memory having instructions stored therein, the instructions in When executed by the processor, the electronic device is caused to perform an action, the action comprising:
  • S1 select the components, functional modules and sensitive devices in the system that can characterize the aging index to determine a state detection strategy, wherein the sensitive devices include core components or secondary circuits;
  • S2 apply at least one of the sensitive devices A detection circuit, wherein the detection circuit is a bypass circuit as the element, functional module and system, which obtains the sensitive device parameters and based on a physical model or an empirical model by obtaining the sensitive device parameters under the condition of stress applied to the sensitive device And the cumulative damage model calculates the remaining life of each of the sensitive devices under different stress conditions;
  • S3 according to the above calculation results of the remaining life of each sensitive device and the weights represented by all the sensitive devices Calculate the entire component, functional module and The remaining life of the system.
  • components, functional modules and systems include electronic trip units.
  • the action S1 further includes: analyzing the electronic trip unit, and selecting a sensitive device in the electronic trip unit that can characterize the aging index to determine a state detection strategy, wherein the analysis strategy includes a failure rate-based detection strategy.
  • the table calculates the mean time between failures, and performs sensitivity analysis and reliability analysis based on simulation, wherein the analysis strategy conditions include operating parameters and environmental parameters.
  • the remaining life evaluation method further includes the following actions: when a sensitive device that can characterize the aging index cannot be selected from the components, functional modules and systems, selecting a replacement device for execution, wherein the replacement period should be Satisfy any one or more of the following: compared with the component, functional module and system, the replacement device has a smaller mean time between failures; has a failure mechanism corresponding to the component, functional module and system; has Sensitive to stress factors consistent with the described components, functional modules and systems; can be applied to physical failure models or empirical models.
  • the action S2 also includes: acquiring parameters of the sensitive device and collecting environmental parameters and operating parameters when the sensitive device is stressed, and calculating different stress conditions based on a physical model or an empirical model and a cumulative damage model the remaining life of each of the sensitive devices.
  • a third aspect of the present invention provides a device for evaluating the remaining life of components, functional modules, and systems, including: a selection device that selects the components, functional modules, and sensitive devices in the system that can characterize aging indicators to determine a state detection strategy , wherein the sensitive devices include core components or secondary circuits;
  • a detection computing device that applies 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 can be used in the case of stress applied to the sensitive device. Acquiring parameters of the sensitive device and calculating the remaining life of each of the sensitive devices under different stress conditions based on a physical model or an empirical model and a cumulative damage model; a computing device, which is based on the above calculation results for the remaining life of each sensitive device and The weights represented by all sensitive devices calculate the remaining lifetime of the entire component, functional module and system.
  • a fourth aspect of the present invention provides a computer program product tangibly stored on a computer-readable medium and comprising computer-executable instructions which, when executed, cause at least one processor to perform a The method described in the first aspect of the present invention.
  • a fifth aspect of the present invention provides a computer-readable medium having stored thereon computer-executable instructions which, when executed, cause at least one processor to perform the method according to the first aspect of the present invention.
  • the invention can evaluate the aging degree of components, functional modules and systems, especially electronic tripping devices, which is very important reference information for technical maintenance planning decisions.
  • the present invention can perform the condition detection function, and the cost is low, and it can be used as a design for new product integration.
  • the invention can reduce the computational complexity of the life prediction of the electronic trip unit.
  • the present invention is also highly accurate due to the application of physical failure models based on component failure mechanisms. Also, the present invention is timely due to the online condition detection circuit.

Abstract

元件、功能模块和系统的剩余寿命评估方法、装置和系统，方法包括如下步骤：S1，选择元件、功能模块和系统中能表征老化指标的敏感器件，以确定状态检测策略，敏感器件包括核心元器件或次级电路；S2，对至少一个敏感器件施加一个检测电路，其中，检测电路是作为元件、功能模块和系统的旁路电路，其通过在敏感器件施加应力获取敏感器件参数并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个敏感器件的剩余寿命；S3，根据上述针对每个敏感器件的剩余寿命计算结果以及所有敏感器件所代表的权重计算出整个元件、功能模块和系统的剩余寿命。该系统和方法计算精确度高，并降低了计算复杂度。

Description

元件、功能模块和系统的剩余寿命评估方法、装置和系统 技术领域
本发明涉及预测性维护领域，尤其涉及元件、功能模块和系统的剩余寿命评估方法、装置和系统。
背景技术
预测性维护或者基于条件维护是比被动性维护和预防性维护更加有效的维护策略。预测性维护或者基于条件维护更有针对性，其基于因素的诊断评估，例如装置使用年限、环境应力等。因此，剩余使用寿命(RUL，Remaining Useful Life)是预测性维护的关键步骤。预测性维护针对的对象包括器件、单元(模块电路)、系统，主要用于诊断状态，判断使用寿命。
剩余使用寿命基于故障状态(经验或者物理模型)和/或操作或者器件、单元(模块电路)、系统环境条件。
图1是失效率曲线(Failure Rate Curve)，即浴盆曲线(Bathtub Curve)，其横坐标为时间，其纵坐标为失效率。失效率曲线包括早期故障阶段A、随机故障阶段B和失效阶段C。对于电子器件来说，早期故障阶段A主要针对产品在工厂时执行的出场检测，即半导体装置初始化的操作以后。本发明适用于随机故障阶段B，被认为是随机发生的过多压力(例如电涌)，具体地是产品使用一段时间器件不可靠了，判断多少剩余寿命。失效阶段C是由于损耗和故障带来的内在寿命。当一个设备进入失效阶段故障，失效率立刻趋于增加。
对于剩余使用寿命的计算，其集中体现在随机故障阶段的剩余时间多长的问题，或者基于使用情况的器件、单元(模块电路)、系统的损耗或者老化程度。由于断路器的电子脱扣单元(ETC，Electronic Trip Unit)具有许多元件和不同的故障机构，很难计算电子脱扣单元的剩余使用寿命。
现有技术的一种方案是提供了发电厂电子设备的电力系统的剩余寿命预测方法，其包括基于老化模型收集数据和预测寿命的传感器。其中，老化模型用于计算系统剩余寿命，例如Palmgren-Miner、Arrhenius和Coffin-Mansion, Eyring。
现有技术另一个方案是基于设备和环境条件检测电子设备的老化，其采用了从传感器采集的数据，例如温度传感器、震动传感器。然后，本方案基于相关与设备和环境条件的加速因素的算法来计算老化加速因子，以评估设备的剩余寿命。
发明内容
本发明第一方面提供了元件、功能模块和系统的剩余寿命评估方法，其中，包括如下步骤：S1，选择所述元件、功能模块和系统中能表征老化指标的敏感器件，以确定状态检测策略，其中所述敏感器件包括核心元器件或次级电路；S2，对至少一个所述敏感器件施加一个检测电路，其中，所述检测电路是作为所述元件、功能模块和系统的旁路电路，其通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命；S3,根据上述针对每个敏感器件的剩余寿命计算结果以及所有敏感器件所代表的权重计算出整个元件、功能模块和系统的剩余寿命。
进一步地，所述元件、功能模块和系统包括电子脱扣单元。
进一步地，所述步骤S1还包括如下步骤：分析所述电子脱扣单元，选择所述电子脱扣单元中能表征老化指标的敏感器件，以确定状态检测策略，其中，所述分析策略包括基于失效率表计算平均无故障时间，基于仿真进行敏感性分析以及可靠性分析，其中，所述分析策略条件包括运行参数、环境参数。
进一步地，所述剩余寿命评估方法还包括如下步骤：当无法从所述元件、功能模块和系统中选择能表征老化指标的敏感器件时，则选择替代器件来执行，其中，所述替代期间应当满足以下任一项或任多项：和该元件、功能模块和系统相比，所述替代器件具有更小的平均无故障时间；具有对应于所述元件、功能模块和系统的失效机理；具有与所述元件、功能模块和系统一致地对应力因素敏感；能够应用于物理失效模型或经验模型。
进一步地，所述步骤S2还包括如下步骤：通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并采集环境参数和运行参数，并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件 的剩余寿命。
本发明第二方面提供了元件、功能模块和系统的剩余寿命评估系统，其中，包括：处理器；以及与所述处理器耦合的存储器，所述存储器具有存储于其中的指令，所述指令在被处理器执行时使所述电子设备执行动作，所述动作包括：
S1，选择所述元件、功能模块和系统中能表征老化指标的敏感器件，以确定状态检测策略，其中所述敏感器件包括核心元器件或次级电路；S2，对至少一个所述敏感器件施加一个检测电路，其中，所述检测电路是作为所述元件、功能模块和系统的旁路电路，其通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命；S3,根据上述针对每个敏感器件的剩余寿命计算结果以及所有敏感器件所代表的权重计算出整个元件、功能模块和系统的剩余寿命。
进一步地，所述元件、功能模块和系统包括电子脱扣单元。
进一步地，所述动作S1还包括：分析所述电子脱扣单元，选择所述电子脱扣单元中能表征老化指标的敏感器件，以确定状态检测策略，其中，所述分析策略包括基于失效率表计算平均无故障时间，基于仿真进行敏感性分析以及可靠性分析，其中，所述分析策略条件包括运行参数、环境参数。
进一步地，所述剩余寿命评估方法还包括如下动作：当无法从所述元件、功能模块和系统中选择能表征老化指标的敏感器件时，则选择替代器件来执行，其中，所述替代期间应当满足以下任一项或任多项：和该元件、功能模块和系统相比，所述替代器件具有更小的平均无故障时间；具有对应于所述元件、功能模块和系统的失效机理；具有与所述元件、功能模块和系统一致地对应力因素敏感；能够应用于物理失效模型或经验模型。
进一步地，所述动作S2还包括：通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并采集环境参数和运行参数，并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命。
本发明第三方面提供了元件、功能模块和系统的剩余寿命评估装置，其中，包括：选择装置，其选择所述元件、功能模块和系统中能表征老化指标的敏感器件，以确定状态检测策略，其中所述敏感器件包括核心元器件或次 级电路；
检测计算装置，其对至少一个所述敏感器件施加一个检测电路，其中，所述检测电路是作为所述元件、功能模块和系统的旁路电路，其通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命；计算装置，其根据上述针对每个敏感器件的剩余寿命计算结果以及所有敏感器件所代表的权重计算出整个元件、功能模块和系统的剩余寿命。
本发明第四方面提供了计算机程序产品，所述计算机程序产品被有形地存储在计算机可读介质上并且包括计算机可执行指令，所述计算机可执行指令在被执行时使至少一个处理器执行根据本发明第一方面所述的方法。
本发明第五方面提供了计算机可读介质，其上存储有计算机可执行指令，所述计算机可执行指令在被执行时使至少一个处理器执行根据本发明第一方面所述的方法。
本发明能够评估元件、功能模块和系统的老化程度，特别是电子脱扣装置，这对于技术维护计划决定是非常重要的参考信息。本发明能够执行条件检测功能，且造价低，其能够作为新产品整合的一个设计。本发明能够减少电子脱扣单元的寿命预测的运算复杂度。由于基于元件故障机构的物理故障模型的应用，本发明精确度也很高。并且，由于在线条件检测电路，本发明是适时的。
附图说明
图1是失效率曲线；
图2是根据本发明一个具体实施例的元件、功能模块和系统的剩余寿命评估方法的检测电路示意图；
图3是根据本发明一个具体实施例的元件、功能模块和系统的剩余寿命评估方法的边缘计算模式架构图；
图4是根据本发明一个具体实施例的元件、功能模块和系统的剩余寿命评估方法的云计算模式架构图；
图5是根据本发明一个具体实施例的元件、功能模块和系统的剩余寿命评估机制的敏感器件及其检测电路的电路连接图。
具体实施方式
以下结合附图，对本发明的具体实施方式进行说明。
本发明首先确定电子脱扣单元的状态检测策略，然后选中的能表征老化指标的敏感器件集成到ETU里面进行监控。最后，根据获取的敏感器件的状态信息来计算整个元件、功能模块和系统的剩余寿命。
根据本发明的一个优选实施例，所述元件、功能模块和系统包括电子脱扣单元。其中，本发明尤其适合应用于电子脱扣单元。下面以电子脱扣单元为例对本发明进行说明。
本发明第一方面提供了元件、功能模块和系统的剩余寿命评估方法，其中，包括如下步骤：
首先执行步骤S1，选择所述元件、功能模块和系统中能表征老化指标的敏感器件，以确定状态检测策略，其中所述敏感器件包括核心元器件或次级电路。其中，所述敏感器件不仅包括器件还包括次级电路。具体地，所述步骤S1还包括如下子步骤：分析所述电子脱扣单元，选择所述电子脱扣单元中能表征老化指标的敏感器件，以确定状态检测策略。其中，首先应该在所述元件、功能模块和系统中确定关键器件和次级电路，然后在所述关键器件和次级电路中选区敏感器件。
其中，所述分析策略包括基于失效率表计算平均无故障时间，基于仿真进行敏感性分析以及可靠性分析，其中，所述分析策略条件包括运行参数、环境参数。
具体地，首先确定电子脱扣单元的状态检测策略，基于元件级、功能模块级和系统级来分析电子脱扣单元的设计，其中包括基于失效率表计算平均无故障时间，基于仿真进行敏感性分析(蒙特卡罗模拟的AC、DC和瞬态)以及可靠性测试(例如加速寿命测试)，其中考虑的条件包括应用到电子脱扣单元的运行参数、环境参数。基于分析结果，确定关键元器件或次级电路，然后选择代表性的敏感器件并集成到电子脱扣单元的电路中，其能够代表核心元器件和次级电路。
其中，敏感器件包括两种。一种是元件、功能模块和系统具有能够计算剩余使用寿命的敏感器件。另一种是有些关键元器件无法用于计算剩余寿命，比如过于复杂者没有可以参照的模型，就应该选择具有相似敏感程度可以计算的元器件来替代。
所述剩余寿命评估方法还包括如下步骤：当无法从所述元件、功能模块和系统中选择能表征老化指标的敏感器件时，则选择替代器件来执行，其中，所述替代期间应当满足以下任一项或任多项：
和该元件、功能模块和系统相比，所述替代器件具有更小的平均无故障时间；
具有对应于所述元件、功能模块和系统的失效机理，比如受热就会短路；
具有与所述元件、功能模块和系统一致地对应力因素敏感，其中，所述应力包括温度、电压、电流；
能够应用于物理失效模型或经验模型。
第二种是在关键元器件和次级电路不具备基于条件检测信息计算剩余使用寿命任何模型或者模型过于复杂，比如，有些关键元器件无法用于计算剩余寿命，比如太复杂了或者没有可以参照的模型，就去选择具有相似敏感程度可以计算的元器件来替代。其中，模型(物理失效模型或者经验模型)是清楚的，剩余使用寿命能够基于条件检测信息来评估。因此，敏感器件的剩余寿命能够代表整个电子脱扣单元，而不用检测电子脱扣单元的所有元件并且计算他们的剩余寿命。
然后执行步骤S2，对至少一个所述敏感器件施加一个检测电路，其中，所述检测电路是作为所述元件、功能模块和系统的旁路电路，其通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命。优选地，所述步骤S2还包括如下步骤：通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并采集环境参数和运行参数，并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命。
具体地，检测敏感器件即对电子脱扣单元的敏感器件加一个检测电路。把敏感器件(替代)作为一个旁路电路，对电子脱扣单元的主要功能不产生影响，能感应到同样的应力。这样可以实时检测敏感器件的条件。可选地，多个敏感器件及其检测电路整合到电子脱扣单元，以代表电子脱扣单元不同点的老化程度。可选地，当环境条件应该被检测时，传感器整合在电子脱扣单元中来获取参数，例如温度、湿度和振动，这些参数被发送到电子脱扣单元的控制器里。然后计算电子脱扣单元的剩余使用寿命。数据来源是监控电 路，采集环境参数的传感器，基于物理模型或者经验模型计算的是不同应力条件下寿命。其中，寿命模型的算法是针对敏感器件，其可以执行从监控电路和/或传感器来的数据。寿命模型需要基于故障物理学模型或者经验模型，例如Arrhenius model、Inverse Power Law、Eyring model等。接着基于累积损伤模型执行敏感器件的剩余寿命计算。其中，累计损伤模型是线性累积损伤，其根据寿命和工作的时间(输入)基于累计损伤模型计算剩余寿命。例如，累计损伤模型包括Miner’s rule。
其中，敏感器件可以包括多个次级电路和器件，因此检测电路对所有次级电路和器件进行检测。图2是根据本发明一个具体实施例的元件、功能模块和系统的剩余寿命评估方法的检测电路示意图。如图2所示，在元件、功能模块和系统中包括依次串联的第一次级电路SC 1、第二次级电路SC 2和第三次级电路SC 3。在所述第一次级电路SC 1和第二次级电路SC 2之间连接有一个第一器件C 1，所述第一器件C 1的另一端连接有第一检测电路MC 1。在所述第二次级电路SC 2和第三次级电路SC 3之间连接有一个第二器件C 2，所述第二器件C 2的另一端连接有第二检测电路MC 2。所述第一检测电路MC 1和第二检测电路MC 2都连接于控制器C。此外，控制器C还连接有至少一个传感器S。其中，传感器S用于采集环境参数和运行参数，例如温度传感器用于采集温度参数，振动传感器用于采集振动参数，湿度传感器用于采集湿度参数。第一检测电路MC 1和第二检测电路MC 2用于检测上述器件和/或次级电路施加应力的情况下获取该器件和/或次级电路的参数，然后控制器C基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个器件和/或次级电路的剩余寿命。
最后执行步骤S3,根据上述针对每个敏感器件的剩余寿命计算结果以及所有敏感器件所代表的权重计算出整个元件、功能模块和系统的剩余寿命。其中，整个系统中有多少个敏感器件，敏感器件及其所代表电路之间的关系可以代表各自权重。
图3是根据本发明一个具体实施例的元件、功能模块和系统的剩余寿命评估方法的边缘计算模式架构图，应用本发明提供的剩余寿命评估装置需要的硬件架构如图3所示，硬件架构100包括具有敏感器件的实时条件检测电路120，其是一个旁路电路，因此并不会影响到电子脱扣单元的任何功能。该硬件架构包括监控环境条件的可选传感器130，例如温度传感器、湿度传感器 和振动传感器。控制器110包括信号处理装置112、剩余寿命计算装置114和维持计划决定装置116。基于边缘设备的控制器110接收从上述实时条件检测电路120和传感器130来的信号，剩余使用寿命计算装置114基于算法执行上述信号，然后维持计划决定装置116决定基于剩余寿命信息针对该元件、功能模块和系统的维持计划。优选地，所述控制器110包括MCU。
根据本发明一个变化例，图3是根据本发明一个具体实施例的元件、功能模块和系统的剩余寿命评估方法的云计算模式架构图，其硬件机构200包括控制器210、云平台240、实时条件检测电路220和传感器230。控制器210特别地为一个MCU，该MCU是基于云的。控制器210包括信号处理装置212，其接收从实时条件检测电路220和传感器230来的信号，然后执行上述信号并发送给云平台240。云平台240具有剩余寿命计算装置242和维持计划决定装置244，剩余寿命计算装置242基于算法执行上述信号并计算剩余寿命，并且通过机器学习优化算法，然后维持计划决定装置244基于剩余寿命信息决定该元件、功能模块和系统维持计划。也就是说，在本实施例中，一部分计算要借助云，本地只进行信号处理，运算由云来负责，这是因为执行本发明需要运算量，本地计算能力低，云计算能力强大，且云还可以进行算法计算的更新和优化。
下面结合一个具体应用场景对本发明进行说明。如图5所示，电路架构包括电源电路P 3、其他电路OC 3、电阻R 3、电容C 3、运算放大器OPA、控制器M 3、温度传感器S 3。具体地，电源电路P 3连接于其他电路OC 3，电源电路P 3和其他电路OC 3之间连接有一个电阻R 3，所述电阻R 3的另一端连接有一个作为敏感器件的电容C 3。运算放大器OPA用于充当检测电路，其输入端分别连接于电阻R 3以及所述P 3和其他电路OC 3的连接点之间，所述电阻R 3和电容C 3之间的连接点，电容C 3和接地端之间的连接点。运算放大器OPA连接于所述控制器M 3中的模拟数字转换模块，此外控制器M 3还连接于一个温度传感器S 3。在本实施例中，通过计算电容C 3的老化程度来计算整个电子脱扣装置的剩余寿命，运算放大器OPA用于充当检测电路采集信号并发送给控制器M 3，其他电路OC 3包括电子脱扣装置的子电路供电部分。
其中，按照本发明的步骤S 1，电解铝的电容C 3被选为敏感器件，因此电容C 3及其检测电路整合到电子脱扣单元的电源电路P 3充当旁路电路。则电容C 3的电流电压信号被监控。温度传感器S 3被整合到电子脱扣单元以监控环境 温度。
其中，预测电解铝的电容C 3的剩余寿命有很多办法，可以采用等效串联电阻(ESR，equivalent series resistance)方法。等效串联电阻通过纹波电流电压来计算，因此电容器的ESR为：
Figure PCTCN2020138699-appb-000001
电容C 3的剩余寿命是基于失效物理模型，电容C 3的剩余寿命为：
Figure PCTCN2020138699-appb-000002
其中，ESR limit为当电容C 3的使用寿命中止时的预测ESR值，ESR(0)为电容C 3的初始值，Ea ESR为当考虑ESR为衰老的指标的激活能量，k为玻耳兹曼常量(8617*10-5eV/K)，Ta为时效温度，T’为环境温度(例如85℃)，A 1和B 1是与电容器类型有关的参数，因此，敏感器件的剩余寿命为：
Figure PCTCN2020138699-appb-000003
RUL COMP i为第i个敏感器件的剩余寿命，k i为基于敏感器件的权重参数。
本发明第二方面提供了元件、功能模块和系统的剩余寿命评估系统，其中，包括：处理器；以及与所述处理器耦合的存储器，所述存储器具有存储于其中的指令，所述指令在被处理器执行时使所述电子设备执行动作，所述动作包括：
S1，选择所述元件、功能模块和系统中能表征老化指标的敏感器件，以确定状态检测策略，其中所述敏感器件包括核心元器件或次级电路；S2，对至少一个所述敏感器件施加一个检测电路，其中，所述检测电路是作为所述元件、功能模块和系统的旁路电路，其通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命；S3,根据上述针对每个敏感器件的剩余寿命计算结果以及所有敏感器件所代表的权重计算出整个元件、功能模块和系统的剩余寿命。
进一步地，所述元件、功能模块和系统包括电子脱扣单元。
进一步地，所述动作S1还包括：分析所述电子脱扣单元，选择所述电子 脱扣单元中能表征老化指标的敏感器件，以确定状态检测策略，其中，所述分析策略包括基于失效率表计算平均无故障时间，基于仿真进行敏感性分析以及可靠性分析，其中，所述分析策略条件包括运行参数、环境参数。
进一步地，所述剩余寿命评估方法还包括如下动作：当无法从所述元件、功能模块和系统中选择能表征老化指标的敏感器件时，则选择替代器件来执行，其中，所述替代期间应当满足以下任一项或任多项：和该元件、功能模块和系统相比，所述替代器件具有更小的平均无故障时间；具有对应于所述元件、功能模块和系统的失效机理；具有与所述元件、功能模块和系统一致地对应力因素敏感；能够应用于物理失效模型或经验模型。
进一步地，所述动作S2还包括：通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并采集环境参数和运行参数，并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命。
本发明第三方面提供了元件、功能模块和系统的剩余寿命评估装置，其中，包括：选择装置，其选择所述元件、功能模块和系统中能表征老化指标的敏感器件，以确定状态检测策略，其中所述敏感器件包括核心元器件或次级电路；
检测计算装置，其对至少一个所述敏感器件施加一个检测电路，其中，所述检测电路是作为所述元件、功能模块和系统的旁路电路，其通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命；计算装置，其根据上述针对每个敏感器件的剩余寿命计算结果以及所有敏感器件所代表的权重计算出整个元件、功能模块和系统的剩余寿命。
本发明第四方面提供了计算机程序产品，所述计算机程序产品被有形地存储在计算机可读介质上并且包括计算机可执行指令，所述计算机可执行指令在被执行时使至少一个处理器执行根据本发明第一方面所述的方法。
本发明第五方面提供了计算机可读介质，其上存储有计算机可执行指令，所述计算机可执行指令在被执行时使至少一个处理器执行根据本发明第一方面所述的方法。
本发明能够评估元件、功能模块和系统的老化程度，特别是电子脱扣装置，这对于技术维护计划决定是非常重要的参考信息。本发明能够执行条件 检测功能，且造价低，其能够作为新产品整合的一个设计。本发明能够减少电子脱扣单元的寿命预测的运算复杂度。由于基于元件故障机构的物理故障模型的应用，本发明精确度也很高。并且，由于在线条件检测电路，本发明是适时的。
尽管本发明的内容已经通过上述优选实施例作了详细介绍，但应当认识到上述的描述不应被认为是对本发明的限制。在本领域技术人员阅读了上述内容后，对于本发明的多种修改和替代都将是显而易见的。因此，本发明的保护范围应由所附的权利要求来限定。此外，不应将权利要求中的任何附图标记视为限制所涉及的权利要求；“包括”一词不排除其它权利要求或说明书中未列出的装置或步骤；“第一”、“第二”等词语仅用来表示名称，而并不表示任何特定的顺序。

Claims (13)

  1. 元件、功能模块和系统的剩余寿命评估方法，其中，包括如下步骤：
    S1，选择所述元件、功能模块和系统中能表征老化指标的敏感器件，以确定状态检测策略，其中所述敏感器件包括核心元器件或次级电路；
    S2，对至少一个所述敏感器件施加一个检测电路，其中，所述检测电路是作为所述元件、功能模块和系统的旁路电路，其通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命；
    S3,根据上述针对每个敏感器件的剩余寿命计算结果以及所有敏感器件所代表的权重计算出整个元件、功能模块和系统的剩余寿命。
  2. 根据权利要求1所述的元件、功能模块和系统的剩余寿命评估方法，其特征在于，所述元件、功能模块和系统包括电子脱扣单元。
  3. 根据权利要求2所述的元件、功能模块和系统的剩余寿命评估方法，其特征在于，所述步骤S1还包括如下步骤：
    分析所述电子脱扣单元，选择所述电子脱扣单元中能表征老化指标的敏感器件，以确定状态检测策略，
    其中，所述分析策略包括基于失效率表计算平均无故障时间，基于仿真进行敏感性分析以及可靠性分析，
    其中，所述分析策略条件包括运行参数、环境参数。
  4. 根据权利要求1所述的元件、功能模块和系统的剩余寿命评估方法，其特征在于，所述剩余寿命评估方法还包括如下步骤：当无法从所述元件、功能模块和系统中选择能表征老化指标的敏感器件时，则选择替代器件来执行，其中，所述替代期间应当满足以下任一项或任多项：
    和该元件、功能模块和系统相比，所述替代器件具有更小的平均无故障时间；
    具有对应于所述元件、功能模块和系统的失效机理；
    具有与所述元件、功能模块和系统一致地对应力因素敏感；
    能够应用于物理失效模型或经验模型。
  5. 根据权利要求1所述的元件、功能模块和系统的剩余寿命评估方法，其特征在于，所述步骤S2还包括如下步骤：通过在所述敏感器件施加应力的 情况下获取所述敏感器件参数并采集环境参数和运行参数，并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命。
  6. 元件、功能模块和系统的剩余寿命评估系统，其中，包括：
    处理器；以及
    与所述处理器耦合的存储器，所述存储器具有存储于其中的指令，所述指令在被处理器执行时使所述电子设备执行动作，所述动作包括：
    S1，选择所述元件、功能模块和系统中能表征老化指标的敏感器件，以确定状态检测策略，其中所述敏感器件包括核心元器件或次级电路；
    S2，对至少一个所述敏感器件施加一个检测电路，其中，所述检测电路是作为所述元件、功能模块和系统的旁路电路，其通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命；
    S3,根据上述针对每个敏感器件的剩余寿命计算结果以及所有敏感器件所代表的权重计算出整个元件、功能模块和系统的剩余寿命。
  7. 根据权利要求6所述的元件、功能模块和系统的剩余寿命评估系统，其特征在于，所述元件、功能模块和系统包括电子脱扣单元。
  8. 根据权利要求7所述的元件、功能模块和系统的剩余寿命评估系统，其特征在于，所述动作S1还包括：
    分析所述电子脱扣单元，选择所述电子脱扣单元中能表征老化指标的敏感器件，以确定状态检测策略，
    其中，所述分析策略包括基于失效率表计算平均无故障时间，基于仿真进行敏感性分析以及可靠性分析，
    其中，所述分析策略条件包括运行参数、环境参数。
  9. 根据权利要求6所述的元件、功能模块和系统的剩余寿命评估系统，其特征在于，所述剩余寿命评估方法还包括如下动作：当无法从所述元件、功能模块和系统中选择能表征老化指标的敏感器件时，则选择替代器件来执行，其中，所述替代期间应当满足以下任一项或任多项：
    和该元件、功能模块和系统相比，所述替代器件具有更小的平均无故障时间；
    具有对应于所述元件、功能模块和系统的失效机理；
    具有与所述元件、功能模块和系统一致地对应力因素敏感；
    能够应用于物理失效模型或经验模型。
  10. 根据权利要求6所述的元件、功能模块和系统的剩余寿命评估系统，其特征在于，所述动作S2还包括：通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并采集环境参数和运行参数，并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命。
  11. 元件、功能模块和系统的剩余寿命评估装置，其中，包括：
    选择装置，其选择所述元件、功能模块和系统中能表征老化指标的敏感器件，以确定状态检测策略，其中所述敏感器件包括核心元器件或次级电路；
    检测计算装置，其对至少一个所述敏感器件施加一个检测电路，其中，所述检测电路是作为所述元件、功能模块和系统的旁路电路，其通过在所述敏感器件施加应力的情况下获取所述敏感器件参数并基于物理模型或者经验模型以及累积损伤模型计算不同应力条件下的每个所述敏感器件的剩余寿命；
    计算装置，其根据上述针对每个敏感器件的剩余寿命计算结果以及所有敏感器件所代表的权重计算出整个元件、功能模块和系统的剩余寿命。
  12. 计算机程序产品，所述计算机程序产品被有形地存储在计算机可读介质上并且包括计算机可执行指令，所述计算机可执行指令在被执行时使至少一个处理器执行根据权利要求1至5中任一项所述的方法。
  13. 计算机可读介质，其上存储有计算机可执行指令，所述计算机可执行指令在被执行时使至少一个处理器执行根据权利要求1至5中任一项所述的方法。
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