A method for extracting physical parameters of sensitive electronic devices

Abstract

The present invention discloses a method for extracting physical parameters of sensitive electronic devices, which specifically relates to the field of parameter extraction and includes the following steps: step S1, obtaining the application scenario of the sensitive electronic device and determining the priority of the physical parameter extraction of the sensitive electronic device; step S2, dividing the priority into a first priority, a second priority and a third priority, determining the sub-priority factors of the first priority, the second priority and the third priority and extracting them; step S3, judging the relationship between the sub-priority factors and the environmental coefficient, eliminating the influence of the environmental coefficient on the sub-priority factors; step S4, optimizing the characteristics of the sub-priority factors. The present invention significantly shortens the extraction time of key parameters, meets the real-time control requirements, can accurately match complex environmental changes, reduce error accumulation, improve parameter stability, ensure that each parameter obtains sufficient computing resources at the appropriate stage, and maximize compensation efficiency.

Description

Technical Field

[0001] The present invention relates to the field of parameter extraction, and more particularly to a method for extracting physical parameters of sensitive electronic devices. Background Art

[0002] Sensitive electronic devices are electronic components or devices that are highly sensitive to changes in the external environment and can convert these changes into electrical or other detectable signals. Their core characteristic is their ability to respond to specific stimuli and convert this response into a processable electrical signal, thereby realizing functions such as perception, measurement, and control.

[0003] In fields such as aerospace, medical equipment, and industrial automation, extracting the physical parameters of sensitive electronic devices is critical to ensuring device reliability and performance. These parameters typically include electrical parameters (such as impedance and threshold voltage), thermal parameters (such as thermal resistance and temperature coefficient), and mechanical parameters (such as stress sensitivity and vibration frequency). The accuracy of these parameters directly impacts the device's operational stability in extreme environments.

[0004] However, existing parameter extraction methods have the following technical bottlenecks:

[0005] Traditional methods use a unified processing strategy for multiple parameters without prioritizing them based on the application scenario (such as real-time performance and accuracy requirements). For example, in industrial production lines with multiple sensors collecting data in parallel, redundant processing of low-value parameters often leads to delayed extraction of key parameters, making it impossible to meet real-time control requirements.

[0006] Environmental factors such as temperature, humidity, and electromagnetic interference can significantly affect parameter stability (for example, for every 10°C increase in temperature, the leakage current of semiconductor devices may increase by an order of magnitude). However, existing methods mostly use fixed compensation models that cannot dynamically adapt to complex environmental changes, resulting in error accumulation.

[0007] When extracting multiple parameters, computing resources (such as CPU / GPU computing power) are not intelligently scheduled based on the parameter compensation potential. For example, even after a parameter reaches compensation saturation (error rate decreases gradually), it still occupies a large amount of resources, while parameters in the rapid improvement period are insufficiently compensated due to insufficient resources.

[0008] In order to solve the above problems, a technical solution is now provided. Summary of the Invention

[0009] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method for extracting physical parameters of a sensitive electronic device to solve the problems raised in the above-mentioned background technology.

[0010] To achieve the above object, the present invention provides the following technical solutions:

[0011] A method for extracting physical parameters of sensitive electronic devices comprises the following steps:

[0012] Step S1, obtaining application scenarios of sensitive electronic devices and determining the priority of extracting physical parameters of the sensitive electronic devices;

[0013] Step S2, dividing the priorities into a first priority, a second priority, and a third priority, determining and extracting sub-priority factors of the first priority, the second priority, and the third priority;

[0014] Step S3, determining the relationship between the sub-priority factor and the environmental coefficient, and eliminating the influence of the environmental coefficient on the sub-priority factor;

[0015] Step S4, optimizing the characteristics of the sub-priority factors, and sequentially obtaining first-tier extraction parameter information, second-tier extraction parameter information, and third-tier extraction parameter information of the physical parameters of the sensitive electronic device;

[0016] Step S5: Analyze the first extraction echelon parameter information, the second extraction echelon parameter information, and the third extraction echelon parameter information to determine the optimal extraction method.

[0017] In a preferred embodiment, in step S1, the physical parameters of the sensitive electronic device include electrical parameters, thermal parameters and mechanical parameters, and the application scenario of the sensitive electronic device is obtained. According to the application scenario of the sensitive electronic device, the priority of extracting the physical parameters of the sensitive electronic device is determined.

[0018] In a preferred embodiment, in step S2, the first priority is divided into a first priority sub-priority factor level one, a first priority sub-priority factor level two, and a first priority sub-priority factor level three;

[0019] dividing the second priority into a second priority sub-priority factor level one, a second priority sub-priority factor level two, and a second priority sub-priority factor level three;

[0020] dividing the third priority into a third priority sub-priority factor level one, a third priority sub-priority factor level two, and a third priority sub-priority factor level three;

[0021] Sub-priority factors of the first priority, the second priority, and the third priority are determined and extracted.

[0022] In a preferred embodiment, in step S3, the environmental coefficient includes a temperature environmental coefficient, a humidity environmental coefficient, and an electromagnetic interference environmental coefficient;

[0023] Get the sub-priority factor in the temperature environment coefficient by 3D points Point cloud clusters composed of

[0024] Calculate the geometric center of the point cloud cluster, construct the covariance matrix of the point cloud cluster, perform eigenvalue decomposition on the covariance matrix to obtain the linear direction, project the point cloud cluster onto the linear direction, calculate the maximum difference of the projection, and obtain the error coefficient of the sub-priority factor under the temperature environment coefficient;

[0025] Get the sub-priority factor in the humidity environment coefficient by 3D points Point cloud clusters composed of

[0026] Calculate the geometric center of the point cloud cluster, construct the covariance matrix of the point cloud cluster, perform eigenvalue decomposition on the covariance matrix to obtain the linear direction, project the point cloud cluster onto the linear direction, calculate the maximum difference of the projection, and obtain the error coefficient 2 of the sub-priority factor under the humidity environment coefficient;

[0027] Obtain the sub-priority factor in the electromagnetic interference environment coefficient by 3D points Point cloud clusters composed of

[0028] Calculate the geometric center of the point cloud cluster, construct the covariance matrix of the point cloud cluster, perform eigenvalue decomposition on the covariance matrix to obtain the linear direction, project the point cloud cluster onto the linear direction, calculate the maximum difference of the projection, and obtain the error coefficient three of the sub-priority factor under the electromagnetic interference environment coefficient.

[0029] In a preferred embodiment, in step S4, the error impact threshold of the first priority sub-priority factor level one, the first priority sub-priority factor level two, and the first priority sub-priority factor level three is set to one;

[0030] Setting the error impact threshold 2 for the second priority sub-priority factor level 1, the second priority sub-priority factor level 2, and the second priority sub-priority factor level 3;

[0031] Setting the error impact threshold of the third priority sub-priority factor level 1, the third priority sub-priority factor level 2, and the third priority sub-priority factor level 3 to three;

[0032] The error coefficients within the error influence threshold 1, error influence threshold 2 and error influence threshold 3 are deleted, and the remaining error coefficients are compensated. The first extraction echelon parameter information, the second extraction echelon parameter information and the third extraction echelon parameter information of the physical parameters of the sensitive electronic device are obtained through the compensation time.

[0033] In a preferred embodiment, in step S5, the compensation time of each error coefficient is plotted. and error rate In the curve graph, the horizontal axis represents the compensation time and the vertical axis represents the error rate;

[0034] Set the critical error rate coefficient , use the critical error rate coefficient line to divide the curve into two areas, representing the parts within the critical error rate coefficient and the parts outside the critical error rate coefficient respectively, and use the compensation time corresponding to the part within the critical error rate coefficient to re-determine the first extraction echelon parameter information, the second extraction echelon parameter information and the third extraction echelon parameter information.

[0035] In a preferred embodiment, the compensation time Add together to get the total compensation time ;

[0036] Determine the ratio of the compensation time corresponding to the first priority, the second priority, and the third priority to the total compensation time, and determine the optimal priority;

[0037] Determining the ratio of the compensation time of the first priority sub-priority factor level 1, the first priority sub-priority factor level 2, and the first priority sub-priority factor level 3 to the first priority, and determining the optimal first priority sub-priority factor level;

[0038] Determining the ratio of the compensation time to the second priority level for the second priority sub-priority factor level 1, the second priority sub-priority factor level 2, and the second priority sub-priority factor level 3 to determine the optimal second priority sub-priority factor level;

[0039] The ratio of the compensation time of the third priority sub-priority factor level 1, the third priority sub-priority factor level 2 and the third priority sub-priority factor level 3 to the third priority is determined to determine the optimal third priority sub-priority factor level.

[0040] In a preferred embodiment, for the error coefficient of each priority level, the difference between the error coefficient interval time and the compensation time of each priority level is calculated, that is, ;

[0041] Add up all the differences to get the total difference, which is ;

[0042] Calculate the critical error rate coefficient using the following formula:

[0043] ;

[0044] Where, .

[0045] The technical effects and advantages of the method for extracting physical parameters of sensitive electronic devices of the present invention are as follows:

[0046] 1. Determine the parameter extraction priority based on the application scenario and divide the priority sub-factors to ensure that key parameters are processed first in scenarios such as multi-sensor parallel acquisition on industrial production lines, avoid redundant processing of low-value parameters, significantly shorten the key parameter extraction time, and meet real-time control requirements;

[0047] 2. Through point cloud cluster analysis, covariance matrix, and eigenvalue decomposition, the impact of environmental factors such as temperature, humidity, and electromagnetic interference on parameters is quantified as error coefficients, achieving an upgrade from "qualitative description" to "quantitative evaluation." By setting thresholds and drawing compensation time-error rate curves, the compensation strategy is dynamically adjusted to accurately match complex environmental changes, reduce error accumulation, and improve parameter stability.

[0048] 3. Through threshold filtering and hierarchical compensation, critical error rate analysis, and priority sub-level compensation time ratio calculation, resources are preferentially allocated to parameters with high compensation potential to avoid resource waste. At the same time, by calculating the difference between the error coefficient interval time and the compensation time, resource allocation is dynamically adjusted to ensure that each parameter obtains sufficient computing resources at the appropriate stage, thereby maximizing compensation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 The figure is a flow chart of a method for extracting physical parameters of a sensitive electronic device according to the present invention. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0051] Example 1

[0052] Figure 1 The present invention provides a method for extracting physical parameters of sensitive electronic devices, which specifically includes the following steps:

[0053] Step S1, obtaining application scenarios of sensitive electronic devices and determining the priority of extracting physical parameters of the sensitive electronic devices;

[0054] Step S2, dividing the priorities into a first priority, a second priority, and a third priority, determining and extracting sub-priority factors of the first priority, the second priority, and the third priority;

[0055] Step S3, determining the relationship between the sub-priority factor and the environmental coefficient, and eliminating the influence of the environmental coefficient on the sub-priority factor;

[0056] Step S4, optimizing the characteristics of the sub-priority factors, and sequentially obtaining first-tier extraction parameter information, second-tier extraction parameter information, and third-tier extraction parameter information of the physical parameters of the sensitive electronic device;

[0057] Step S5: Analyze the first extraction echelon parameter information, the second extraction echelon parameter information, and the third extraction echelon parameter information to determine the optimal extraction method.

[0058] In step S1, the physical parameters of the sensitive electronic device include electrical parameters, thermal parameters and mechanical parameters, and the application scenario of the sensitive electronic device is obtained. According to the application scenario of the sensitive electronic device, the priority of extracting the physical parameters of the sensitive electronic device is determined.

[0059] Different application scenarios have different requirements for parameters. If you do not prioritize them, you may spend too much time and money on minor parameters (such as test equipment usage, manpower investment, etc.) while ignoring key parameters. For example:

[0060] Devices in the aerospace field pay more attention to mechanical parameters (resistance to vibration and impact). Prioritizing the extraction of mechanical parameters can quickly screen devices that meet the requirements and reduce redundant testing of electrical parameters.

[0061] In high-temperature environments (such as automotive engine control modules), thermal parameters (thermal conductivity, thermal resistance) must be extracted first to avoid device failure due to insufficient heat dissipation design.

[0062] After clarifying the priorities, parameter testing can be carried out in sequence, shortening the time from R&D to mass production.

[0063] In step S2, the first priority is divided into a first priority sub-priority factor level one, a first priority sub-priority factor level two, and a first priority sub-priority factor level three;

[0064] dividing the second priority into a second priority sub-priority factor level one, a second priority sub-priority factor level two, and a second priority sub-priority factor level three;

[0065] dividing the third priority into a third priority sub-priority factor level one, a third priority sub-priority factor level two, and a third priority sub-priority factor level three;

[0066] Sub-priority factors of the first priority, the second priority, and the third priority are determined and extracted.

[0067] The sub-levels under each priority level can correspond to the needs of different dimensions in the scene.

[0068] First priority sub-level 1: corresponds to the most stringent core parameters in the scenario (such as "anti-cosmic ray radiation" in the mechanical parameters of aerospace components);

[0069] First priority sub-level 2: corresponding to secondary core parameters (such as vibration frequency range);

[0070] First priority sub-level three: corresponding to auxiliary core parameters (such as shock response time).

[0071] By layering, we avoid applying a one-size-fits-all approach to parameters within the same priority level and ensure that resources are accurately invested in the most critical sub-factors.

[0072] In step S3, the environmental coefficients include a temperature environmental coefficient, a humidity environmental coefficient, and an electromagnetic interference environmental coefficient;

[0073] Get the sub-priority factor in the temperature environment coefficient by 3D points Point cloud clusters composed of

[0074] Calculate the geometric center of the point cloud cluster, construct the covariance matrix of the point cloud cluster, perform eigenvalue decomposition on the covariance matrix to obtain the linear direction, project the point cloud cluster onto the linear direction, calculate the maximum difference of the projection, and obtain the error coefficient of the sub-priority factor under the temperature environment coefficient;

[0075] Get the sub-priority factor in the humidity environment coefficient by 3D points Point cloud clusters composed of

[0076] Calculate the geometric center of the point cloud cluster, construct the covariance matrix of the point cloud cluster, perform eigenvalue decomposition on the covariance matrix to obtain the linear direction, project the point cloud cluster onto the linear direction, calculate the maximum difference of the projection, and obtain the error coefficient 2 of the sub-priority factor under the humidity environment coefficient;

[0077] Obtain the sub-priority factor in the electromagnetic interference environment coefficient by 3D points Point cloud clusters composed of

[0078] Calculate the geometric center of the point cloud cluster, construct the covariance matrix of the point cloud cluster, perform eigenvalue decomposition on the covariance matrix to obtain the linear direction, project the point cloud cluster onto the linear direction, calculate the maximum difference of the projection, and obtain the error coefficient three of the sub-priority factor under the electromagnetic interference environment coefficient.

[0079] Calculate the geometric center of the point cloud cluster ;

[0080] in ;

[0081] Constructing the covariance matrix of point cloud clusters :

[0082] ;

[0083] Pair covariance matrix Perform eigenvalue decomposition:

[0084] ;

[0085] is the eigenvalue, are eigenvalues ​​and eigenvectors;

[0086] Project a point cloud cluster onto a linear direction:

[0087] ;

[0088] Calculate the maximum difference of the projection and get the error coefficient :

[0089] .

[0090] This method converts the environmental impact on device parameters into quantifiable and comparable error coefficients, and through geometric and statistical analysis of point cloud clusters, achieves an upgrade from "qualitative description" to "quantitative evaluation." This method not only accurately locates environmentally sensitive parameters but also provides a data-driven decision-making basis for device design, selection, and testing. It is particularly suitable for scenarios such as aerospace and industrial control that require extremely high environmental adaptability. By comparing and tracking error coefficients horizontally and vertically, the reliability and stability of sensitive electronic devices in complex environments can be systematically improved.

[0091] In step S4, the error impact thresholds of the first priority sub-priority factor level 1, the first priority sub-priority factor level 2, and the first priority sub-priority factor level 3 are set to one;

[0092] Setting the error impact threshold 2 for the second priority sub-priority factor level 1, the second priority sub-priority factor level 2, and the second priority sub-priority factor level 3;

[0093] Setting the error impact threshold of the third priority sub-priority factor level 1, the third priority sub-priority factor level 2, and the third priority sub-priority factor level 3 to three;

[0094] The error coefficients within the error influence threshold 1, error influence threshold 2 and error influence threshold 3 are deleted, and the remaining error coefficients are compensated. The first extraction echelon parameter information, the second extraction echelon parameter information and the third extraction echelon parameter information of the physical parameters of the sensitive electronic device are obtained through the compensation time.

[0095] Through "threshold filtering + graded compensation," precise focus and dynamic optimization of parameter extraction are achieved. On the one hand, low-impact errors are eliminated to improve extraction efficiency, enabling rapid output of key parameters. On the other hand, high-impact errors are compensated for to ensure that extraction accuracy meets scenario requirements. This approach prioritizes resources (computational effort, time, and hardware) to the parameters that have the greatest impact on the extraction results, significantly improving extraction efficiency while maintaining accuracy. It is particularly suitable for parameter extraction scenarios in complex electronic systems that require real-time performance, accuracy, and cost.

[0096] In step S5, the compensation time of each error coefficient is plotted and error rate In the curve graph, the horizontal axis represents the compensation time and the vertical axis represents the error rate;

[0097] Set the critical error rate coefficient , use the critical error rate coefficient line to divide the curve into two areas, representing the parts within the critical error rate coefficient and the parts outside the critical error rate coefficient respectively, and use the compensation time corresponding to the part within the critical error rate coefficient to re-determine the first extraction echelon parameter information, the second extraction echelon parameter information and the third extraction echelon parameter information.

[0098] Will compensate time Add together to get the total compensation time ;

[0099] Determine the ratio of the compensation time corresponding to the first priority, the second priority, and the third priority to the total compensation time, and determine the optimal priority;

[0100] Determining the ratio of the compensation time of the first priority sub-priority factor level 1, the first priority sub-priority factor level 2, and the first priority sub-priority factor level 3 to the first priority, and determining the optimal first priority sub-priority factor level;

[0101] Determining the ratio of the compensation time to the second priority level for the second priority sub-priority factor level 1, the second priority sub-priority factor level 2, and the second priority sub-priority factor level 3 to determine the optimal second priority sub-priority factor level;

[0102] The ratio of the compensation time of the third priority sub-priority factor level 1, the third priority sub-priority factor level 2 and the third priority sub-priority factor level 3 to the third priority is determined to determine the optimal third priority sub-priority factor level.

[0103] For the error coefficient of each priority, the difference between the error coefficient interval time and the compensation time of each priority is calculated, that is, ;

[0104] Add up all the differences to get the total difference, which is ;

[0105] Calculate the critical error rate coefficient using the following formula:

[0106] ;

[0107] Where, .

[0108] Through hierarchical time analysis based on "priority-sublevel" and dynamic error rate thresholding, we achieve two-way optimization of "efficiency improvement" and "accuracy assurance" during parameter extraction. Its core value lies in: based on data quantification, it precisely allocates compensation resources to high-value links, avoiding "overcompensation" or "undercompensation," and ultimately forming an adaptive parameter extraction optimization mechanism.

[0109] Example 2

[0110] Based on the application scenarios of automotive engine control modules, the first priority is determined to be thermal parameters (thermal conductivity, thermal resistance) and electrical parameters (anti-electromagnetic interference capability, signal transmission stability); the second priority is mechanical parameters (anti-vibration performance); the third priority is secondary electrical parameters (static power consumption), which are extracted periodically.

[0111] First priority:

[0112] Sub-priority factor level 1: thermal parameters for high temperature resistance (to ensure stable operation at 150°C in the engine compartment), electrical parameters for high-frequency electromagnetic interference resistance (to avoid interference with the engine ignition system);

[0113] Sub-priority factor level 2: thermal cycle life in thermal parameters and signal transmission delay in electrical parameters;

[0114] Sub-priority factor level three: thermal diffusivity in thermal parameters and power supply ripple rejection ratio in electrical parameters.

[0115] Second priority: anti-vibration frequency range in mechanical parameters (matching engine vibration frequency).

[0116] Third priority: static power consumption among the secondary electrical parameters.

[0117] For the temperature environment coefficient, we collected three-dimensional point cloud clusters of sub-priority factors at different temperatures (80°C-150°C). By calculating the geometric center, covariance matrix and eigenvalue decomposition, we obtained the error coefficients of thermal parameters under temperature environment. Similarly, we obtained the error coefficients under humidity environment (such as moisture on rainy days) and electromagnetic interference environment (engine electromagnetic environment) to quantify the impact of the environment on the parameters.

[0118] The error impact threshold for the first-priority sub-factor, Level 1, is set low (e.g., error rate no more than 2%). Error coefficients exceeding the threshold are compensated primarily, such as by optimizing the heat dissipation structure to reduce thermal resistance errors. Error coefficients within the threshold are pruned to reduce the computational effort. Based on the compensation time, thermal parameters (high temperature tolerance) and key electrical parameters are assigned to the first extraction tier, vibration parameters to the second, and static power consumption to the third.

[0119] By plotting the compensation time versus error rate curve for the error coefficient and setting a critical error rate coefficient, we found that the high-temperature tolerance compensation time for thermal parameters was long, but the error rate decreased significantly, making them high-value compensation outside the critical error rate coefficient. However, some minor electrical parameters had long compensation times but little improvement in error rate, and were reclassified as the third extraction tier. Ultimately, by optimizing the compensation strategy, we increased ECU parameter extraction efficiency by 30%, while ensuring that the accuracy of key parameters met automotive industry standards.

[0120] Example 3

[0121] For medical blood glucose sensors, their application scenarios require high precision, low latency and stability, and they need to focus on electrical parameters (signal accuracy) and mechanical parameters (anti-deformation ability).

[0122] The first priority is electrical parameters (signal sensitivity, anti-noise capability); the second priority is mechanical parameters (the bending resistance of the sensor probe); and the third priority is thermal parameters (parameter stability at room temperature).

[0123] First priority:

[0124] Sub-priority factor level 1: signal sensitivity (directly affects blood glucose measurement accuracy) and baseline drift resistance in electrical parameters;

[0125] Sub-priority factor level 2: response time and noise suppression ratio among electrical parameters;

[0126] Sub-priority factor level three: long-term stability in electrical parameters.

[0127] Second priority: the minimum bending radius of the probe in the mechanical parameters (to avoid damage during use).

[0128] Third priority: temperature coefficient of thermal parameters (parameter fluctuations within the range of 20°C-40°C).

[0129] In a humid environment (such as human sweat), the point cloud clusters of the sub-priority factors are obtained, and the error coefficients are calculated through the covariance matrix and eigenvalue decomposition to quantify the impact of humidity on signal accuracy. At the same time, the error coefficients are calculated in electromagnetic interference environments (such as electromagnetic radiation from hospital equipment) and temperature environments.

[0130] For the first-priority sub-factor, Level 1, a strict error impact threshold (no more than 1%) is set. The error coefficient of signal sensitivity is compensated primarily, for example, by using digital filtering algorithms to improve accuracy. Parameters with temperature coefficient errors within the threshold are removed from the third-priority sub-factor. Based on compensation time, key electrical parameters such as signal sensitivity and noise immunity are placed in the first tier of extraction, followed by probe bending resistance in the second tier and temperature stability in the third tier.

[0131] By plotting compensation time-error rate curves and calculating critical error rate coefficients, it was found that the compensation time for some mechanical parameters was long but had limited improvement in overall accuracy, so they were adjusted to the third extraction tier. Meanwhile, while signal sensitivity compensation for electrical parameters was time-consuming, it significantly reduced the error rate, maintaining it in the first extraction tier. Ultimately, this method improved the accuracy of blood glucose sensor parameter extraction by 25% and reduced testing time by 30%, meeting the high-precision and rapid delivery requirements of medical equipment.

[0132] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters and thresholds in the formulas are set by technicians in this field according to actual conditions.

[0133] The above embodiments can be implemented in whole or in part via software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in the embodiments of this application are fully or partially performed. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired means (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0134] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0135] In the several embodiments provided in this application, it should be understood that the disclosed methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units described is merely a logical functional division, and actual implementation may have other division methods. In addition, the coupling or direct coupling or communication connection shown or discussed may be through some interface, indirect coupling or communication connection of devices or units, and may be electrical, mechanical, or other forms.

[0136] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, and may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment as needed.

[0137] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0138] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program code.

[0139] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0140] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for extracting physical parameters of sensitive electronic devices, characterized in that: The steps include: Step S1, obtaining application scenarios of sensitive electronic devices and determining the priority of extracting physical parameters of the sensitive electronic devices; In step S1, the physical parameters of the sensitive electronic device include electrical parameters, thermal parameters, and mechanical parameters, and the application scenario of the sensitive electronic device is obtained. According to the application scenario of the sensitive electronic device, the priority of extracting the physical parameters of the sensitive electronic device is determined; Step S2, dividing the priorities into a first priority, a second priority, and a third priority, determining and extracting sub-priority factors of the first priority, the second priority, and the third priority; Step S3, determining the relationship between the sub-priority factor and the environmental coefficient, and eliminating the influence of the environmental coefficient on the sub-priority factor; In step S3, the environmental coefficients include a temperature environmental coefficient, a humidity environmental coefficient, and an electromagnetic interference environmental coefficient; Get the sub-priority factor in the temperature environment coefficient by 3D points Point cloud clusters composed of Calculate the geometric center of the point cloud cluster, construct the covariance matrix of the point cloud cluster, perform eigenvalue decomposition on the covariance matrix to obtain the linear direction, project the point cloud cluster onto the linear direction, calculate the maximum difference of the projection, and obtain the error coefficient of the sub-priority factor under the temperature environment coefficient; Get the sub-priority factor in the humidity environment coefficient by 3D points Point cloud clusters composed of Calculate the geometric center of the point cloud cluster, construct the covariance matrix of the point cloud cluster, perform eigenvalue decomposition on the covariance matrix to obtain the linear direction, project the point cloud cluster onto the linear direction, calculate the maximum difference of the projection, and obtain the error coefficient 2 of the sub-priority factor under the humidity environment coefficient; Obtain the sub-priority factor in the electromagnetic interference environment coefficient by 3D points Point cloud clusters composed of Calculate the geometric center of the point cloud cluster, construct the covariance matrix of the point cloud cluster, perform eigenvalue decomposition on the covariance matrix to obtain the linear direction, project the point cloud cluster onto the linear direction, calculate the maximum difference of the projection, and obtain the error coefficient three of the sub-priority factor under the electromagnetic interference environment coefficient; Step S4, optimizing the characteristics of the sub-priority factors, and sequentially obtaining first-tier extraction parameter information, second-tier extraction parameter information, and third-tier extraction parameter information of the physical parameters of the sensitive electronic device; Step S5: Analyze the first extraction echelon parameter information, the second extraction echelon parameter information, and the third extraction echelon parameter information to determine the optimal extraction method.

2. A method for extracting physical parameters of sensitive electronic devices according to claim 1, characterized in that: In step S2, the first priority is divided into a first priority sub-priority factor level one, a first priority sub-priority factor level two, and a first priority sub-priority factor level three; dividing the second priority into a second priority sub-priority factor level one, a second priority sub-priority factor level two, and a second priority sub-priority factor level three; dividing the third priority into a third priority sub-priority factor level one, a third priority sub-priority factor level two, and a third priority sub-priority factor level three; Sub-priority factors of the first priority, the second priority, and the third priority are determined and extracted.

3. The method for extracting physical parameters of a sensitive electronic device according to claim 2, wherein: In step S4, the error impact thresholds of the first priority sub-priority factor level 1, the first priority sub-priority factor level 2, and the first priority sub-priority factor level 3 are set to one; Setting the error impact threshold 2 for the second priority sub-priority factor level 1, the second priority sub-priority factor level 2, and the second priority sub-priority factor level 3; Setting the error impact threshold of the third priority sub-priority factor level 1, the third priority sub-priority factor level 2, and the third priority sub-priority factor level 3 to three; The error coefficients within the error influence threshold 1, error influence threshold 2 and error influence threshold 3 are deleted, and the remaining error coefficients are compensated. The first extraction echelon parameter information, the second extraction echelon parameter information and the third extraction echelon parameter information of the physical parameters of the sensitive electronic device are obtained through the compensation time.

4. The method for extracting physical parameters of a sensitive electronic device according to claim 3, wherein: In step S5, the compensation time of each error coefficient is plotted and error rate In the curve graph, the horizontal axis represents the compensation time and the vertical axis represents the error rate; Set the critical error rate coefficient , use the critical error rate coefficient line to divide the curve into two areas, representing the parts within the critical error rate coefficient and the parts outside the critical error rate coefficient respectively, and use the compensation time corresponding to the part within the critical error rate coefficient to re-determine the first extraction echelon parameter information, the second extraction echelon parameter information and the third extraction echelon parameter information.

5. The method for extracting physical parameters of a sensitive electronic device according to claim 4, characterized in that: Will compensate time Add together to get the total compensation time ; Determine the ratio of the compensation time corresponding to the first priority, the second priority, and the third priority to the total compensation time, and determine the optimal priority; Determining the ratio of the compensation time of the first priority sub-priority factor level 1, the first priority sub-priority factor level 2, and the first priority sub-priority factor level 3 to the first priority, and determining the optimal first priority sub-priority factor level; Determining the ratio of the compensation time to the second priority level for the second priority sub-priority factor level 1, the second priority sub-priority factor level 2, and the second priority sub-priority factor level 3 to determine the optimal second priority sub-priority factor level; The ratio of the compensation time of the third priority sub-priority factor level 1, the third priority sub-priority factor level 2 and the third priority sub-priority factor level 3 to the third priority is determined to determine the optimal third priority sub-priority factor level.

6. The method for extracting physical parameters of a sensitive electronic device according to claim 5, characterized in that: For the error coefficient of each priority, the difference between the error coefficient interval time and the compensation time of each priority is calculated, that is, ; Add up all the differences to get the total difference, which is ; Calculate the critical error rate coefficient using the following formula: ； Where, .

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