Evaluation method for verifying radiation effect characterization parameters of component in-orbit application

Abstract

The invention relates to an evaluation method for on-orbit application verification radiation effect characterization parameters of a component. The evaluation method comprises the following steps: step 1, analyzing radiation sensitivity characteristics of a device according to information of the verification device; step 2, establishing a device function model according to a typical component application scene; step 3, according to the device irradiation sensitive characteristics obtained in the step 1, establishing a corresponding relation of an irradiation effect mapping device function model, and giving a device irradiation sensitive parameter table; 4, designing an on-orbit application verification system according to the device irradiation sensitive parameter table in the step 3; step 5, analyzing a space irradiation environment where the on-orbit application verification system in the step 4 is located; and step 6, according to the working range of the device function model parameter designed by the on-orbit application verification system in the step 4, estimating the parameter change condition of the device related irradiation sensitive parameter under the space irradiation environment condition analyzed in the step 5, and giving a device application parameter degradation evaluation index.

Description

Technical Field

[0001] This invention belongs to the field of space radiation effect evaluation test of components, and relates to an evaluation method for on-orbit verification and characterization parameters of radiation effect of components. Background Technology

[0002] With the increasing complexity of spacecraft and the continuous evolution of component manufacturing processes, the space radiation effects of electronic components are exhibiting new characteristics. On-orbit verification technology for component radiation effects provides important reference for improving the reliability of aerospace electronic systems in the space environment. Future development requires continued advancements in high-precision, intelligent on-orbit monitoring technologies to enhance online diagnosis and prediction capabilities of radiation effects, construct a shared database of on-orbit radiation behavior of components, and verify and correct ground reliability test results through on-orbit applications.

[0003] Patent CN103699939A, "A Method for Establishing an Application Verification Process for Aerospace Components," addresses the application verification needs of aerospace components and discloses a method for establishing an application verification process for aerospace components. This method includes application verification work analysis, establishment of a process logic structure model, optimization calculation and adjustment, and process compliance. This method can guide the implementation of application verification.

[0004] Patent CN107894760A, "An Application Verification Platform for Aerospace Components Based on an Equivalent Excitation Test Module," provides a method for constructing an application verification platform for aerospace components based on an equivalent excitation test module. It establishes a component application verification simulation test system architecture based on an equivalent device, uses actual hardware resources to simulate the real application state of the model, and achieves compatibility and universality of the verification device while ensuring the effectiveness and sufficiency of the verification.

[0005] Patent CN105893664A, "A System-Level Single-Event Effect Characterization Parameter and Evaluation Method," discloses a system-level single-event effect characterization parameter and evaluation method. This method proposes to use the system's single-event event rate to quantitatively characterize the overall impact of the single-event effect on the system from the perspective of the system's overall response to the single-event effect and the consequences of the single-event effect. It also proposes to use the hazard degree and quantifiable analysis of the consequences of the single-event effect on the system. Summary of the Invention

[0006] To address the aforementioned issues, this invention provides on-orbit verification and characterization parameters and evaluation methods for the radiation effects of electronic components. Based on the radiation sensitivity characteristics of electronic components and combined with typical operating conditions, this method establishes on-orbit verification and characterization parameters and evaluation methods for the radiation effects of electronic components. This method can be used for the quantitative control of on-orbit application verification of the radiation effects of electronic components.

[0007] The purpose of this invention is to provide a method for evaluating radiation effect characterization parameters in on-orbit application verification of components, characterized by comprising the following steps: Step 1: Analyze the radiation sensitivity characteristics of the device based on the information of the verification device; Step 2: Establish a functional model of the components based on typical application scenarios; Step 3: Based on the device irradiation sensitivity characteristics obtained in Step 1, establish the correspondence between the irradiation effect and the device functional model, and provide a table of device irradiation sensitivity parameters. Step 4: Based on the device irradiation sensitivity parameter table from Step 3, design an on-orbit application verification system; Step 5: Analyze the space irradiation environment of the on-orbit application verification system in Step 4; Step 6: Based on the working range of the device functional model parameters designed in Step 4 for the on-orbit application verification system, estimate the parameter changes of the device-related radiation-sensitive parameters under the space irradiation environment conditions analyzed in Step 5, and give the device application parameter degradation evaluation index.

[0008] Preferably, in step 1, the information of the verification device includes: internal structure diagram, functional block diagram, historical radiation test data, and historical on-orbit data of similar devices; the radiation-sensitive processes of the components are identified through the acquired information.

[0009] Preferably, the radiation-sensitive process identification of components includes CMOS process, BICMOS process, and bipolar process; wherein, The CMOS process identification parameters include: gate oxide thickness, feature size, and well structure; The BiCMOS process identification parameters include: the width of the base region of interest and the resistivity of the epitaxial layer; The bipolar process identification parameters include: gate oxide thickness, feature size, and trap structure.

[0010] Preferably, in step 2, based on typical component application scenarios, the component's logic function is used as the underlying event, and the component's function is abstracted into an input-processing-output model; Identify parameters that reflect the core performance of the device and are susceptible to radiation, and clarify the key states of the device, such as normal operation, performance degradation, and functional failure, and their judgment conditions.

[0011] Preferably, the damage effects on devices caused by the space radiation environment include total dose effect, single-event effect, and displacement damage. Total dose effect: causes device parameter drift, which is mapped to performance parameters in the functional model; Single-event effects include single-event transient effects, single-event flip, single-event interruption, single-event latch-up, and displacement effects; among which: Single-event transients: cause signal glitches and data errors; and are reflected in the abnormal logic outputs and analog signals in the functional model. Single-event flip: Causes data bits to flip, resulting in an error in the state mapping of the functional model; Single-particle functional interruption: Causes a functional interruption, making the functional module mapped to the functional model unavailable; Single-event latch-up: Causes device latch-up, which is mapped to an abnormally large current in the functional model.

[0012] Displacement damage: leads to decreased gain in bipolar devices, increased dark current in optoelectronic devices, and reduced efficiency; The performance parameters mapped to the relevant functional model include photodetector responsivity, laser efficiency, and increased voltage drop of the linear regulator's regulating tube. The parameters should have a clear and quantifiable correlation with radiation effects; be measurable or inferable in orbit; and cover failure modes and functional degradation.

[0013] Preferably, in step 4, The on-orbit application verification system includes parameter excitation signals, acquisition and output signals, signal processing, data processing algorithms, data compression and formatting, health status judgment, and implementation of communication protocols with the satellite platform data management system.

[0014] Preferably, in step 5, This study analyzes the space radiation environment by examining its variations with orbital position and time, including particle types and energy spectra, radiation dose, and single-event effect predictions. The particle types and energy spectrum are calculated as follows: the main particles encountered in the orbit, including protons, electrons, heavy ion fluxes and energy spectrum distributions. The radiation dose calculation: Total dose effect: Calculate the total ionizing dose during the mission, taking into account the effect of spacecraft shielding thickness; Displacement effect: Calculate displacement damage dose; The single-event effect prediction considers device cross-sectional data, orbital particle flux, shielding, and angle factor to calculate the single-event upset rate, single-event latch-up rate, and single-event interruption rate of key devices.

[0015] Preferably, in step 6, Degradation baseline establishment: Baseline values ​​for each sensitive parameter are established using ground test data and device parameters; Define degradation metrics: Absolute deviation: The difference between the current measured value of a parameter and the baseline value; Relative rate of change: The percentage change in a parameter relative to the baseline value; Cumulative effect index: The cumulative value of total dose effect provided by radiation dosimeters or estimated based on environmental models; Single-event event counting: single-event flip counting, single-event latch-up event generation techniques, single event; Device irradiation sensitivity parameter threshold: the extreme values ​​of device parameters after changes under irradiation, including maximum and minimum values. When the device parameters exceed the extreme value range, the device can be determined to have failed.

[0016] Preferably, in step 6, the threshold is set as follows: Based on ground test data and engineering margins, set device parameter degradation warning thresholds: when parameters begin to show measurable degradation but do not affect functionality, it indicates the need for attention and enhanced monitoring; based on system-level requirements and device failure thresholds, set failure thresholds: when parameter degradation has reached or is close to the limits that the system function can tolerate, it may affect functional performance or indicate impending failure.

[0017] The beneficial effects of this invention include: The invention proposes a method for characterizing and evaluating radiation effects in on-orbit applications of electronic components. This method starts from the sensitive characteristics of the component, combines it with its specific application functions, quantifies the space radiation environment, and forms measurable and evaluable performance degradation indicators. It provides a systematic implementation framework for the on-orbit verification of radiation effects of electronic components. By implementing this method, the risks of on-orbit application of components can be verified, and real-world on-orbit environmental data reveals the actual radiation response of the component, compensating for the shortcomings of ground-based tests (such as low-energy proton effects, real shielding conditions, and long-term effects).

[0018] By applying verification radiation effect characterization parameters and evaluation methods, key degradation parameters of the radiation effect of components are continuously tracked for on-orbit verification, enabling fault early warning and status assessment; verifying whether the components meet the design life and reliability requirements in actual application environments; and dynamically updating the remaining life prediction of the components based on the measured degradation rate to optimize maintenance strategies. Attached Figure Description

[0019] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Determine the list of verification devices, and then press Figure 1 Perform the steps shown.

[0022] Step 1: Analyze the radiation sensitivity characteristics of the device based on the information of the verification device.

[0023] Objective: To identify radiation-sensitive process steps and key functional units based on the inherent properties of the device.

[0024] Input: Detailed device information, process information, internal structure diagram, functional block diagram, previous radiation test data (ground-based accelerated test), and historical on-orbit data of similar devices.

[0025] 1. Process Analysis: CMOS process: Focus on gate oxide thickness (TID sensitivity), feature size (SEE sensitivity, the smaller the node, the more sensitive), and well structure (affecting the single-event latch-up (SEL) threshold).

[0026] Bipolar / BiCMOS process: Focus on base region width and epitaxial layer resistivity (affecting displacement damage and gain degradation).

[0027] Optoelectronic devices (CCD / CMOS image sensors, lasers, detectors): Focus on the increase in dark current, decrease in charge transfer efficiency, and decrease in responsivity caused by displacement damage.

[0028] Power devices: Pay attention to threshold voltage drift (total dose effect) and on-resistance changes (displacement damage).

[0029] 2. Functional Analysis: Identify core functional modules (such as CPU core, memory array, ADC / DAC module, voltage reference source, and power drive unit).

[0030] Analyze the potential failure modes of each module under radiation environment (such as memory bit flip SEU, function interrupt SEFI, register lock-up SEL, operational amplifier offset voltage drift, and deterioration of ADC differential nonlinearity DNL / integral nonlinearity INL).

[0031] Identify the process steps and functional modules of the device to be verified that are most susceptible to TID, SEE, and DDD.

[0032] Step 2: Establish functional models of components based on typical application scenarios.

[0033] Establish a functional model of the device in the target aerospace application scenario, and clarify its input, output, internal state, performance indicators and their interrelationships.

[0034] Device datasheets, circuit schematics, system-level functional requirements, and on-orbit mission profiles (operating modes, duty cycles).

[0035] 1. Abstract Modeling: Abstracting the function of a device into an input-processing-output model. For example: CPU / MCU: Instruction execution, data processing, peripheral control state machine model.

[0036] Memory: Storage cell array, read / write control logic model.

[0037] ADC: A sampling, quantization, and encoding process model that focuses on resolution, accuracy, and linearity.

[0038] LDO: Voltage feedback, error amplification, power regulation model, focusing on output voltage accuracy, ripple, and load regulation.

[0039] 2. Key parameter identification: Identify parameters that reflect the core performance of the device and are susceptible to radiation (such as operating current, propagation delay, noise figure, gain, accuracy, and power consumption).

[0040] 3. State Definition: Clearly define the key states of the device, such as normal operation, performance degradation, and functional failure, and their judgment conditions.

[0041] Based on the above information, a functional model of the device is established, including a functional block diagram, a state machine description, a list of core performance parameters and their normal ranges.

[0042] Step 3: Based on the device irradiation sensitivity characteristics obtained in Step 1, establish the correspondence between the irradiation effect and the device functional model, and provide a table of device irradiation sensitivity parameters.

[0043] Based on the first two steps, the device's radiation sensitivity characteristics and device functional model are established, and the causal relationship between radiation effects and device functional / performance degradation is formed, resulting in a list of radiation-sensitive parameters to be monitored.

[0044] 1. Effect-function mapping: Total dose effect: mainly causes parameter drift (threshold voltage V) th Drift, increased leakage current, decreased gain, and increased power consumption. These are performance parameters mapped to the functional model (such as op-amp offset voltage, comparator threshold, and LDO output voltage accuracy).

[0045] Single-event effect: Transient effects (SET): These cause signal glitches and data errors. They are mapped to momentary anomalies in the logic outputs and analog signal links of the functional model.

[0046] SEU, SEFI, SEL: Cause data bit flipping, function interruption, latch-up. Mapped to state errors in the functional model (register value error, state machine deadlock), functional module unavailability, abnormally high current.

[0047] Displacement damage primarily affects minority carrier lifetime and mobility, leading to decreased gain in bipolar devices, increased dark current in optoelectronic devices, and reduced efficiency. This is reflected in performance parameters of relevant functional models (such as photodetector responsivity, laser efficiency, and increased voltage drop across the regulator tube of a linear regulator).

[0048] 2. Generate a sensitive parameter table: List all parameters that need to be monitored and can directly or indirectly reflect the effects of radiation. Parameters should include: It has a clear and quantifiable correlation with radiation effects.

[0049] Measurable or inferable in orbit.

[0050] It covers the main failure modes and degradation paths.

[0051] Example parameters: Static / Dynamic Power Consumption Current Key node voltages (such as reference voltage, LDO output voltage) Timing parameters (such as critical path delay, clock frequency stability) Digital functionality correctness (through specific test modes or EDAC statistics) Simulated performance (gain, bandwidth, offset, signal-to-noise ratio - may require dedicated test stimulus) Specific function register state Temperature (auxiliary analysis) Obtain a table of radiation sensitivity parameters for the device, including parameter name, physical meaning, normal range, expected radiation degradation trend, correlation with radiation effect type, and measurement method / inference method.

[0052] Step 4: Based on the device irradiation sensitivity parameter table in Step 3, design an on-orbit application verification system.

[0053] Design and implement a system capable of real-time or periodic monitoring of parameters in a radiation sensitivity parameter table for a device. Inputs include: radiation sensitivity parameter table, platform constraints (power consumption, size, weight, interfaces, data processing capabilities), and on-orbit mission profile.

[0054] 1. Hardware Design: Dedicated monitoring circuit: Design or select high-precision ADCs, voltage / current sensors, signal conditioning circuits, and test excitation sources (such as DACs for ADC self-tests and pattern generators for logic tests).

[0055] Interface adaptation: Ensures electrical compatibility and safe isolation with the device under test (DUT).

[0056] Data acquisition control: Design the acquisition timing and triggering logic (periodic, event-triggered, command-triggered).

[0057] Radiation hardening: Necessary radiation hardening design (such as TMR, EDAC, SEL protection) is carried out on the key parts of the monitoring system itself (such as control FPGA / MCU, memory).

[0058] 2. Software / Firmware Design: Implement parameter acquisition and control logic.

[0059] Implement data processing algorithms (such as filtering, averaging, and feature extraction).

[0060] Implement data compression and formatting.

[0061] To achieve preliminary assessment and alerts on health status.

[0062] Implement the communication protocol with the satellite platform data management system.

[0063] 3. Data strategy design: Sampling frequency: determined based on the rate of change of parameters and the rate of change of the radiation environment.

[0064] Data storage: local cache size and download strategy (download all data, download changed data, download statistical results).

[0065] Triggering mechanisms: time-triggered, instruction-triggered, and abnormal event-triggered (such as detecting a single-event transient).

[0066] Step 5: Analyze the space irradiation environment of the on-orbit application verification system described in Step 4.

[0067] The precise quantification of the space radiation environment in the system's orbit provides environmental input for degradation assessment. This is achieved through satellite orbital parameters (altitude, inclination, eccentricity), mission lifetime, space environment models, and solar activity forecasts.

[0068] Core task: 1. Particle types and energy spectrum: Calculate the flux and energy spectrum distribution of the main particles (protons, electrons, heavy ions) encountered in the orbit.

[0069] 2. Radiation dose calculation: TID: Calculates the total ionizing dose during the mission, taking into account the effect of spacecraft shielding thickness.

[0070] DDD: Calculates displacement damage dose, mainly focusing on optoelectronic devices and bipolar devices.

[0071] SEE rate prediction: Calculate the single-event upset rate, single-event latch-up rate, and single-event failure rate of key components (including the monitoring system itself). Consider device cross-sectional data (obtained from ground-based heavy ion / proton experiments), orbital particle flux, shielding, and angle factor.

[0072] 3. Environmental profile: Analyze the changes in radiation environment with orbital position (such as crossing the South Atlantic Anomaly (SAA) and polar regions) and time (solar activity cycle, solar particle events (SPE)).

[0073] The orbital radiation environment analysis includes predictions of TID / DDD cumulative curves, predicted key SEE rates, and descriptions of environmental profile characteristics.

[0074] Table 1 Overview of Typical Earth Orbit Radiation Environment Characteristics Step 6: Based on the working range of the device functional model parameters designed in Step 4 for the on-orbit application verification system, estimate the parameter changes of the device's relevant radiation-sensitive parameters under the space irradiation environment conditions analyzed in Step 5, and provide evaluation indicators for device application parameter degradation.

[0075] By combining the environmental data from step 5 with the analysis from the previous steps, quantitative parameter degradation evaluation indicators and thresholds are established to determine the on-orbit health status of devices, estimate their lifespan, and trigger response measures.

[0076] 1. Degradation baseline establishment: Using data from the initial on-orbit period (when the cumulative dose is low) or ground calibration, establish “healthy” baseline values ​​for each sensitive parameter.

[0077] 2. Definition of degradation index: Absolute deviation: The difference between the current measured value of a parameter and the baseline value.

[0078] Relative rate of change: The percentage change in a parameter relative to the baseline value.

[0079] Cumulative effect indicators: such as TID cumulative value (provided by radiation dosimeters or estimated based on environmental models).

[0080] SEE event count: SEU count, SEL event occurrence flag, SEFI event occurrence count and recovery status.

[0081] 3. Threshold setting: Warning threshold: Parameters begin to show measurable degradation, indicating a need for attention and enhanced monitoring, but functionality is still far from being affected. This threshold is set based on ground test data and engineering margins.

[0082] Alarm / Tolerance Threshold: Parameter degradation has reached or is approaching the limits that the system function can tolerate, which may affect task performance or indicate impending failure. Set based on system-level requirements and device failure thresholds.

[0083] 4. Evaluation Methods and Outputs: A parameter system for evaluating the on-orbit radiation effects of devices is established, including: Current values, absolute deviations, and relative rates of change of each sensitive parameter; Key parameter change trend chart (overlaid with TID / DDD cumulative curve); SEE event statistics (type, frequency, location correlation); Current status assessment (normal / warning / alarm); Remaining lifetime estimate based on the current degradation rate; Consistency analysis of the expected environmental model.

[0084] Clearly define the indicators, calculation methods, thresholds at each level, report formats, and handling recommendations.

[0085] 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 description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A method for evaluating radiation effect characterization parameters in on-orbit application verification of components, characterized in that, It includes the steps: Step 1, analyze the radiation sensitivity characteristics of the device according to the information of the verification device; Step 2, establish a device function model according to the application scenarios of typical components; Step 3, establish the corresponding relationship between the radiation effect mapping device function model according to the radiation sensitivity characteristics of the device obtained in Step 1, and give the device radiation sensitivity parameter table; Step 4, design an on-orbit application verification system according to the device radiation sensitivity parameter table in Step 3; Step 5, analyze the space radiation environment where the on-orbit application verification system in Step 4 is located; Step 6, estimate the parameter change of the device-related radiation sensitivity parameters under the space radiation environment conditions analyzed in Step 5 according to the working range of the device function model parameters designed in the on-orbit application verification system in Step 4, and give the device application parameter degradation evaluation index.

2. The method as described in claim 1, characterized in that, In Step 1, the information of the verification device includes: internal structure diagram, functional block diagram, historical radiation test data, historical on-orbit data of similar devices; identify the radiation effect sensitive process of the components through the obtained information.

3. The method as described in claim 2, characterized in that, The identification of the radiation effect sensitive process of the components includes CMOS process, BiCMOS process, bipolar process; among which, The identification parameters of the CMOS process include: gate oxide layer thickness, feature size, well structure; The identification parameters of the BiCMOS process include: concerned base region width, epitaxial layer resistivity; The identification parameters of the bipolar process include: gate oxide layer thickness, feature size, well structure.

4. The method as described in claim 1, characterized in that, In Step 2, according to the application scenarios of typical components, taking the logic function of the device as the basic event, abstract the device function into an input - processing - output model; Determine the parameters that reflect the core performance of the device and are vulnerable to radiation, and clarify the key states such as normal operation, performance degradation, and function failure of the device and their determination conditions.

5. The method as described in claim 1, characterized in that, The damage effects caused by the space radiation environment to the device include total dose effect, single event effect, and displacement damage. Among which, Total dose effect: causes parameter drift of the device, and maps to the performance parameters in the function model; Single event effect includes single event transient effect, single event upset, single event functional interrupt, single event latch-up, displacement effect; among which: Single event transient: causes signal glitches and data errors; maps to the abnormal of the logic output and analog signal in the function model; Single event upset: causes data bit flipping, and maps to the state error in the function model; [[ID=I19]]Single event functional interrupt: causes functional interrupt, and maps to the unavailable function module in the function model; Single event latch-up: causes device latch-up, and maps to the abnormal large current in the function model.

6. Displacement damage: causes the gain of bipolar devices to decrease, the dark current of optoelectronic devices to increase, and the efficiency to decrease; The performance parameters mapped to the relevant function models include the responsivity of photodetectors, the efficiency of lasers, and the increase of the voltage drop of the adjustment tube of linear voltage regulators; The parameters should have a clear and quantifiable association with the radiation effect; Can be measured on orbit or indirectly inferred; cover failure modes and function degradation.

7. The method as described in claim 1, characterized in that, In Step 4, The on-orbit application verification system includes parameter excitation signals, acquisition of output signals, signal processing, data processing algorithms, data compression and formatting, health status judgment, and implementation of the communication protocol with the satellite platform's data management system.

8. The method as described in claim 1, characterized in that, In Step 5, This study analyzes the space radiation environment by examining its variations with orbital position and time, including particle types and energy spectra, radiation dose, and single-event effect predictions. The particle types and energy spectrum are calculated as follows: the main particles encountered in the orbit, including protons, electrons, heavy ion fluxes and energy spectrum distributions. The radiation dose calculation: Total dose effect: Calculate the total ionizing dose during the mission, taking into account the effect of spacecraft shielding thickness; Displacement effect: Calculate displacement damage dose; The single-event effect prediction considers device cross-sectional data, orbital particle flux, shielding, and angle factor to calculate the single-event upset rate, single-event latch-up rate, and single-event interruption rate of key devices.

9. The method as described in claim 1, characterized in that, In step 6, Degradation baseline establishment: Baseline values ​​for each sensitive parameter are established using ground test data and device parameters; Define degradation metrics: Absolute deviation: The difference between the current measured value of a parameter and the baseline value; Relative rate of change: The percentage change in a parameter relative to the baseline value; Cumulative effect index: The cumulative value of total dose effect provided by radiation dosimeters or estimated based on environmental models; Single-event event counting: single-event flip counting, single-event latch-up event generation techniques, single event; Device irradiation sensitivity parameter threshold: the extreme values ​​of device parameters after changes under irradiation, including maximum and minimum values. When the device parameters exceed the extreme value range, the device can be determined to have failed.

10. The method as described in claim 8, characterized in that, In step 6, the threshold setting is as follows: Based on ground test data and engineering margins, set device parameter degradation warning thresholds: when parameters begin to show measurable degradation but do not affect functionality, it indicates the need for attention and enhanced monitoring; based on system-level requirements and device failure thresholds, set failure thresholds: when parameter degradation has reached or is close to the limits that the system function can tolerate, it may affect functional performance or indicate impending failure.

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