A substation monitoring terminal hardware module whole-cycle trust and multi-source interference collaborative adaptation method, system, device and medium

Abstract

The present application relates to the technical field of substation monitoring terminal safe operation, and particularly relates to a substation monitoring terminal hardware module full-cycle trusted and multi-source interference collaborative adaptation method, system, device and medium. Based on the trusted execution environment, initial trusted access is completed for the hardware module of the substation monitoring terminal, running behavior data and output data are continuously collected, and a trusted state quantitative parameter is generated through multi-dimensional weighted calculation; multi-type environmental physical quantities in the substation are collected, a multi-interference source coupling correction term is introduced, and an interference intensity quantitative parameter is generated in combination with the trusted state quantitative parameter; based on the two parameters, synchronous driving of hardware operation configuration parameter adaptive adjustment and original collection data associated correction are performed, and final monitoring data is output, so that the technical problem that the terminal full-cycle autonomous controllable ability and collection accuracy cannot be collaboratively guaranteed under the complex interference environment of the substation is solved.

Description

Technical Field

[0001] This invention relates to the field of substation monitoring terminal safety operation technology, and in particular to a method, system, device and medium for full-cycle reliability and multi-source interference collaborative adaptation of substation monitoring terminal hardware modules. Background Technology

[0002] Substations are core nodes in power systems, and the stable operation of their monitoring terminals directly affects the overall security and reliability of the power system. With the continuous advancement of power system digitalization, modular substation monitoring terminals are gradually adopting hardware architectures based on domestically developed operating systems. Through the modular integration and deployment of functions such as data acquisition, control, and communication, they enable real-time monitoring and control of substation operating status, becoming the core carrier for the autonomous and controllable operation of substations.

[0003] However, existing modular substation monitoring terminals have significant technical shortcomings in achieving independent controllability. At the trusted verification level, existing terminals typically rely solely on one-time authentication upon access to determine the trustworthiness of hardware modules, failing to establish a closed-loop trusted assessment system covering the entire operational lifecycle of the hardware module. After initial authentication, the compliance of the hardware module's behavior and the validity of its output data remain largely unregulated during operation. This makes it impossible to effectively identify and address the risks of unauthorized tampering and data distortion that occur after authentication. The effective boundary of independent controllability is limited to the moment of access, failing to meet the requirements for secure management of hardware modules throughout their entire operational lifecycle in unattended substation scenarios.

[0004] At the interference adaptation level, substation sites simultaneously experience multiple types of physical field interference, including spatial electromagnetic interference, grid harmonics, ambient temperature changes, and equipment vibration, with coupling and superposition effects between these interference sources. Existing terminals typically collect and compensate for each type of interference independently, neglecting the superposition and amplification effect caused by multiple interference sources acting simultaneously, resulting in insufficient accuracy in the quantification of interference impact. Furthermore, existing terminals do not coordinate the calculation of the reliability status of hardware modules with the degree of interference impact at the site. In extreme operating scenarios where the reliability of modules decreases and the interference intensity increases simultaneously, the terminal cannot guarantee the accuracy of the hardware-collected data. Summary of the Invention

[0005] In view of the problems existing in the prior art, the present invention is proposed.

[0006] Therefore, the problem to be solved by this invention is how to solve the core technical problem that existing terminals cannot simultaneously guarantee the full-cycle autonomous control capability and the acquisition accuracy in extreme scenarios.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide a method for full-cycle trusted and multi-source interference collaborative adaptation of a substation monitoring terminal hardware module, comprising: based on a trusted execution environment, collecting inherent physical characteristic data of the hardware module accessing the substation monitoring terminal to complete the initial trusted access of the hardware module; 1 Collect operational behavior data and output data of hardware modules to generate a quantitative parameter of trust status that reflects the trustworthiness of the hardware module throughout its entire lifecycle. Collect various types of environmental physical quantities at the substation site, and combine them with the reliable state quantification parameters to generate interference intensity quantification parameters that reflect the degree of coupling influence of multiple interference sources; Based on the quantization parameters of the trusted state and the quantization parameters of the interference intensity, the operating configuration parameters of the hardware module are adjusted to complete the dynamic reconstruction of the hardware module's resources, the original data collected by the hardware module is correlated and corrected, and the final monitoring data is output.

[0008] As a preferred embodiment of the substation monitoring terminal hardware module full-cycle trust and multi-source interference collaborative adaptation method described in this invention, the initial trust access of the hardware module includes comparing the collected inherent physical feature data with the standard feature data pre-stored in the secure storage area, and simultaneously confirming that the secure partition of the trusted execution environment is in a compliant operating state. Under the premise that the inherent physical characteristic data matches the standard characteristic data and the security partition compliance status meets the requirements, the access authorization of the hardware module is completed; the hardware module that fails the verification is automatically isolated by the monitoring terminal and does not participate in subsequent data collection and command execution.

[0009] As a preferred embodiment of the substation monitoring terminal hardware module full-cycle reliability and multi-source interference collaborative adaptation method described in this invention, the generation of reliable state quantification parameters includes: verifying the matching degree between the operation behavior data and the preset compliance rules, and verifying the consistency between the output data and the same source data of adjacent hardware modules. Based on the compliance level of the inherent physical characteristics of the hardware module, the compliance level of its operational behavior, the validity level of its output data, and the operational status of the trusted execution environment's secure partition, the trusted state quantification parameters are generated through weighted calculations across various dimensions. When the operational status of a security partition does not meet compliance requirements, the calculation results of the three dimensions—the compliance level of inherent physical characteristics, the compliance level of operational behavior, and the validity level of output data—are not included in the generation of the trusted state quantification parameters.

[0010] As a preferred embodiment of the full-cycle reliable and multi-source interference collaborative adaptation method for the hardware module of a substation monitoring terminal described in this invention, the generation of interference intensity quantification parameters includes collecting spatial electromagnetic interference data, power grid harmonic data, ambient temperature data and equipment vibration data at the substation site, converting each type of physical quantity into a unified form of relative intensity parameters, and eliminating the dimensional differences between different physical quantities. Based on the relative intensity parameters of each type of interference and their corresponding weighted proportions, and combined with the correction term for the coupling and superposition effect generated when multiple interference sources act simultaneously, the weighted calculation of the comprehensive impact of multi-source interference is completed. The weighted calculation results are corrected using the credible state quantization parameter to generate the interference intensity quantization parameter.

[0011] As a preferred embodiment of the full-cycle reliable and multi-source interference collaborative adaptation method of the hardware module of the substation monitoring terminal described in this invention, wherein: the coupling superposition effect correction term is calculated by the modal recognition method to capture the superposition amplification effect generated when multiple types of interference sources act simultaneously; The weighting percentages for each type of interference are set according to the installation location and anti-interference characteristics of the hardware modules: hardware modules installed in the high-voltage switch room are assigned a higher weighting percentage for electromagnetic interference, while hardware modules installed in the main transformer equipment are assigned a higher weighting percentage for vibration and temperature.

[0012] As a preferred embodiment of the substation monitoring terminal hardware module full-cycle reliability and multi-source interference collaborative adaptation method described in this invention, the adjustment of the hardware module's operating configuration parameters includes adjusting the sampling rate parameter, gain parameter, interface configuration parameter and redundancy parameter, and reconstructing the hardware module's acquisition channel, communication channel and backup resources based on the adjusted operating configuration parameters, without interrupting the overall operation of the monitoring terminal during the reconstruction process. The process of correlating and correcting the raw data collected by the hardware module includes calculating the hardware resource correction coefficient related to the adjustment range of the running configuration and the error compensation coefficient related to the compensation range of the acquisition error, and applying the two correction coefficients simultaneously to the correction calculation of the raw data collected. The corresponding coefficients in the calculation are updated and corrected in real time based on the adjustment results of the running configuration parameters, and the data correction range is kept synchronized with the hardware configuration adjustment status throughout the process.

[0013] As a preferred embodiment of the full-cycle trust and multi-source interference collaborative adaptation method for the hardware module of a substation monitoring terminal described in this invention, the generation of the trust state quantification parameter, the generation of the interference intensity quantification parameter, the adjustment of the operation configuration parameter, and the correlation correction of the original collected data are executed cyclically according to a preset time cycle, the execution order within each cycle is fixed, and the execution result of each cycle covers the corresponding parameter of the previous cycle. Data interaction between hardware modules and between the monitoring terminal and the substation back-end system are all accomplished through a distributed soft bus. The hardware module is connected and removed through a distributed soft bus to achieve plug-and-play recognition. When connected, it automatically completes communication adaptation and data channel setup. When removed, it automatically closes the corresponding data channel and releases system resources.

[0014] Secondly, embodiments of the present invention provide a full-cycle trusted and multi-source interference collaborative adaptation system for hardware modules of substation monitoring terminals, which includes a trusted computing verification module configured to collect inherent physical characteristic data of hardware modules accessing the substation monitoring terminal based on a trusted execution environment, complete the initial trusted access of the hardware modules, and generate trusted state quantification parameters. The interference calculation module is configured to collect various types of environmental physical quantities at the substation site and, in conjunction with the reliable state quantification parameters, generate interference intensity quantification parameters. The hardware scheduling module is configured to adaptively adjust the operating configuration parameters of the hardware module based on the trusted state quantization parameter and the interference intensity quantization parameter. The data processing module is configured to correlate and correct the raw data collected by the hardware module based on the trusted state quantization parameter and the interference intensity quantization parameter, and output the final monitoring data.

[0015] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the substation monitoring terminal hardware module full-cycle reliability and multi-source interference collaborative adaptation method as described in the first aspect of the present invention are implemented.

[0016] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the substation monitoring terminal hardware module full-cycle reliability and multi-source interference collaborative adaptation method as described in the first aspect of the present invention are implemented.

[0017] The beneficial effects of this invention are as follows: By comparing inherent physical characteristics and confirming compliance with security partitions, the trusted control scope of hardware modules is extended from the moment of access to the entire operating cycle. A trusted state quantification parameter is generated using a four-dimensional weighted average of identity compliance, behavior compliance, data validity, and security partition status. Furthermore, the security partition status serves as a pre-gating mechanism, addressing the problem of long-term uncontrolled module behavior and data after one-time authentication in traditional solutions. A multi-interference source modal coupling correction term is introduced to overcome the shortcomings of traditional solutions, which independently quantify various interferences and ignore the coupling superposition effect, leading to low quantization. The trusted state quantification parameter is incorporated into the interference intensity calculation, establishing a two-way linkage between the module's trusted state and the impact of on-site interference. The invention synchronously drives two execution chains: hardware configuration adjustment and data correlation correction. Any adjustment to hardware parameters is reflected in the data correction coefficient in real time, breaking the isolated operation mode of the two in traditional solutions. Without adding additional components, it achieves coordinated assurance of terminal autonomous controllability and acquisition accuracy in complex interference environments of substations. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart of a method for collaborative adaptation of full-lifecycle reliability and multi-source interference to hardware modules of substation monitoring terminals; Figure 2 A computer device diagram illustrating the full-cycle reliability and multi-source interference collaborative adaptation method for the hardware module of a substation monitoring terminal. Figure 3 A flowchart of the initial trust verification process for the modular substation monitoring terminal hardware of Dianhong, which is a method for full-cycle trust and multi-source interference collaborative adaptation of the hardware module of the substation monitoring terminal. Figure 4 A logic block diagram for calculating the full-cycle autonomous and controllable reliability of the hardware module of the substation monitoring terminal in the form of a collaborative adaptation method for full-cycle reliability and multi-source interference. Figure 5 A logic block diagram for calculating the interference impact coefficient of a method for co-adapting the full-cycle reliability and multi-source interference of hardware modules for substation monitoring terminals. Figure 6 A flowchart illustrating the hardware operation parameter adjustment and resource reconfiguration process for a full-cycle reliable and multi-source interference collaborative adaptation method for substation monitoring terminal hardware modules. Detailed Implementation

[0020] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0021] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0023] Example 1 Reference Figure 1 This is the first embodiment of the present invention, which provides a method for full-cycle reliable and multi-source interference collaborative adaptation of a substation monitoring terminal hardware module, including: S100: Based on a trusted execution environment, it collects the inherent physical characteristic data of the hardware modules accessing the substation monitoring terminal to complete the initial trusted access of the hardware modules; Collect operational and output data from hardware modules to generate a quantitative parameter of the trustworthiness status that reflects the trustworthiness of the hardware module throughout its entire lifecycle.

[0024] S200: Collects various types of environmental physical quantities at the substation site, and combines them with reliable state quantification parameters to generate interference intensity quantification parameters that reflect the degree of coupling influence of multiple interference sources.

[0025] S300: Based on the trusted state quantization parameter and the interference intensity quantization parameter, adjust the operating configuration parameters of the hardware module, complete the dynamic reconstruction of the hardware module resources, perform correlation correction on the original data collected by the hardware module, and output the final monitoring data.

[0026] It should be noted that substation sites simultaneously experience four types of physical field interference: spatial electromagnetic interference, power grid harmonics, ambient temperature fluctuations, and equipment vibration. When multiple types of interference sources act simultaneously, they produce a coupling and superposition effect. The overall impact exceeds the calculation results of the independent superposition of each interference. Traditional solutions only quantify a single type of interference independently, failing to capture the multi-source coupling amplification effect, resulting in an underestimation of the interference quantification results. This, in turn, affects the accuracy of subsequent hardware configuration adjustments and data corrections. At the same time, existing terminals typically stop at access authentication for trusted management of hardware modules. After authentication, the module's operational behavior and output data lack continuous verification, and changes in the module's trusted state are not incorporated into the interference quantification and data correction process. Consequently, when the module's trusted level decreases, the terminal cannot synchronously adjust the compensation strategy.

[0027] S100 continuously collects operational behavior data and output data, and generates a trusted state quantification parameter based on multi-dimensional weighted calculations. This extends trusted management to the entire operating cycle of the module and serves as a common input basis for S200 and S300. S200 introduces the trusted state quantification parameter into the multi-interference source coupling strength quantification calculation, generating an interference strength quantification parameter that simultaneously reflects the degree of on-site interference and the trusted state of the module, which is then transmitted to S300. S300 uses these two parameters as dual driving bases to simultaneously complete hardware operation configuration adjustments and original data association corrections. The two execution chains are synchronized throughout the process, ensuring that the final monitoring data always adapts to the current hardware configuration and on-site interference state. This comprehensively solves the technical problem of the inability to coordinate the full-cycle autonomous controllability of the monitoring terminal and high-precision data acquisition in substation scenarios.

[0028] Example 2 Reference Figure 1 - Figure 6 This is the second embodiment of the present invention. The complete technical solution of this embodiment is implemented based on a modular substation monitoring terminal equipped with the Elec-Hong industrial-grade operating system (hereinafter referred to as Elec-Hong system). This monitoring terminal includes multiple domestically produced hardware modules, including a voltage acquisition module, a current acquisition module, a switch quantity control module, a communication module, and an environmental sensing module. The electrical interfaces and communication protocols of all hardware modules are customized according to the Elec-Hong system's adaptation standards. The operating data and status information of the hardware modules can be directly transmitted to the designated data area of ​​the Elec-Hong system, achieving bidirectional interaction between the system and the hardware without the need for additional conversion devices. During the terminal's power-on startup process, the Elec-Hong system prioritizes the initialization of the Trusted Execution Environment (TEE) security partition before loading the hardware module's adaptation driver. This ensures that the entire startup process is within the control scope of the trusted environment, preventing unauthorized module access or program tampering during startup, and adapting to the security control requirements of long-term continuous operation of the terminal in unattended substation scenarios.

[0029] In this embodiment, step S100, based on a trusted execution environment, collects the inherent physical characteristic data of the hardware module connected to the substation monitoring terminal, completes the initial trusted access of the hardware module, collects the operating behavior data and output data of the hardware module, and generates a trusted state quantification parameter reflecting the trustworthiness of the hardware module throughout its entire lifecycle, including the following steps A1-A2: A1: Complete the initial trusted access of the hardware module, including comparing the collected inherent physical feature data with the standard feature data pre-stored in the secure storage area, and simultaneously confirming that the secure partition of the trusted execution environment is in a compliant operating state. Under the premise that the inherent physical characteristic data matches the standard characteristic data and the security partition compliance status meets the requirements, the access authorization of the hardware module is completed; the hardware module that fails the verification is automatically isolated by the monitoring terminal and does not participate in subsequent data collection and command execution.

[0030] Reference Figure 3 Specifically, step A1 completes the initial trusted access of the hardware module. Its execution entity is the trusted verification unit built into the Elec-Tech system. The verification process is completed within the secure partition of the trusted execution environment and does not occupy the business operation resources of the hardware module.

[0031] Inherent physical characteristic data refers to the set of physical quantities that reflect the underlying hardware characteristics of the hardware module after calibration at the factory stage. These include three categories: power supply ripple characteristics, analog-to-digital converter (AKC) reference offset characteristics, and communication interface impedance characteristics. Power supply ripple characteristics reflect the power output fluctuation pattern of the hardware module under rated power supply conditions and serve as a physical fingerprint for identifying the consistency of the module's power supply components. AKC reference offset characteristics reflect the reference drift of the internal AKC unit under standard excitation input and serve as the physical basis for identifying the uniqueness of the acquisition device. Communication interface impedance characteristics reflect the impedance response of the hardware module's external communication interface under fixed frequency excitation and serve as the physical basis for identifying the batch consistency of the interface devices. The above three types of characteristic data are stored in the secure storage area of ​​the Elec-Tech system based on the factory calibration value and cannot be read or tampered with by external programs.

[0032] After the terminal is powered on, the trusted verification unit collects the real-time values ​​of the three types of inherent physical characteristic data for each hardware module of the access terminal, and compares them one by one with the standard characteristic data of the corresponding module in the secure storage area to calculate the degree of matching between the real-time value and the standard value. At the same time, the trusted verification unit synchronously reads the current running status of the secure partition of the trusted execution environment to confirm that the partition access permission status is in compliance mode, the program running integrity status has passed the verification, and the data storage legality status is normal. Only under the dual premise that the inherent physical characteristic data and the standard characteristic data are completely matched and the three running statuses of the secure partition are all in compliance mode can the hardware module obtain access authorization and enter the subsequent operation stage.

[0033] Hardware modules that fail verification will be automatically isolated to an isolation partition by the terminal, and their data channels will be forcibly shut down. They will not participate in any data collection or instruction execution process. The initial trusted access design logic is based on the principle of physical non-cloning: unauthorized modules cannot replicate the inherent physical characteristics of compliant modules. Even if the module identification information is cracked, it is impossible to pass the comparison and verification of inherent physical characteristics. This solves the core defects of traditional solutions that rely on single identifier authentication and are easily forged and cracked from the hardware bottom layer.

[0034] A2: Generate trusted state quantification parameters, including verifying the matching degree between the running behavior data and the preset compliance rules, and verifying the consistency between the output data and the same source data of adjacent hardware modules. Based on the compliance level of the inherent physical characteristics of the hardware module, the compliance level of its operational behavior, the validity level of its output data, and the operational status of the trusted execution environment's secure partition, a trusted state quantification parameter is generated through weighted calculation of each dimension. When the operational status of a security partition does not meet compliance requirements, the calculation results of the three dimensions—the compliance level of inherent physical characteristics, the compliance level of operational behavior, and the validity level of output data—are not included in the generation of the trusted state quantification parameters.

[0035] Reference Figure 4 Specifically, step A2 continues to execute after access authorization is completed in step A1, generating a trusted state quantification parameter (denoted as T) that reflects the trustworthiness of the hardware module throughout its entire lifecycle. Its execution entity is the trusted computing unit of the Elec-Tech system, and its computing logic is solidified at the system's bottom layer and cannot be modified by external programs.

[0036] The generation of the trusted state quantization parameter T involves four types of input parameters. The first type is the matching coefficient of the inherent physical characteristics of the hardware module (denoted as...). This coefficient is determined by the matching degree between the inherent physical feature data collected in real time during the module's operation and the pre-stored standard feature data. The value range is [0,1], and the value is positively correlated with the matching degree, reflecting the identity and compliance status of the hardware module itself.

[0037] The second category is the compliance coefficient of hardware module operation behavior (denoted as...). This coefficient is determined by the matching degree between the module's real-time operational behavior data and the preset compliance rules. The operational behavior data includes the hardware module's sampling frequency switching behavior, gain adjustment behavior, and interface communication behavior. The preset compliance rules are the module's normal operation behavior guidelines preset by the Elec-Tech system, covering the entire process of module operation specifications. The numerical value is positively correlated with the degree of behavioral compliance; any operation in the module that exceeds the compliance rules will result in penalties. The value drops immediately, and behavioral anomalies that occur after module authentication can be captured in real time, solving the industry pain point of loss of control after traditional authentication solutions.

[0038] The third category is the validity coefficient of the hardware module output data (denoted as...). This coefficient is determined by the consistency verification result between the module's output data and the data of the same monitoring target collected by adjacent hardware modules of the same type at the same time node (data from the same source). The numerical value is positively correlated with the degree of data consistency, and is used to identify in real time situations where the module fails to collect data or the data is tampered with, so as to ensure the authenticity of the monitoring data output by the terminal.

[0039] The fourth category is the operational status coefficient of the trusted execution environment security partition (denoted as...). This coefficient reflects the overall compliance status of the trusted computing operating environment, and its value is either in compliant mode or non-compliant mode. When in compliance mode, , , Only the calculation results from the three dimensions will be incorporated into the overall credibility calculation, thus ensuring the foundation for the execution of trusted computing from the system's bottom layer.

[0040] If any unauthorized access, program tampering, or data anomaly occurs in the security partition, Immediately switch to non-compliant mode to directly block the generation of trusted state quantification parameters in the current cycle, thereby fundamentally avoiding the security risks caused by the tampering of the trusted computing environment.

[0041] The credible state quantization parameter T is obtained by weighting the above four types of parameters. , , The three dimensions correspond to weighted coefficients, the sum of which is fixed at 1. These coefficients can be adjusted based on module type and application importance: core control modules can increase the weighting of the compliance dimension, while data acquisition modules can increase the weighting of the data validity dimension, achieving differentiated and reliable management for different module types. The calculation expression for T is shown below: The value of T ranges from [0,1]. The value is positively correlated with the overall trustworthiness of the hardware module throughout its entire lifecycle. The higher the T value, the higher the overall trustworthiness of the module in the three dimensions of identity compliance, behavior compliance, and data validity. T is the core link connecting the initial trust access stage with the subsequent interference calculation, hardware adjustment, and data correction stages. Any change in the T value is transmitted to all subsequent stages in real time to ensure that the terminal's operating state is always adapted to the current trustworthiness state of the module.

[0042] In this embodiment, step S200 involves collecting various types of environmental physical quantities at the substation site, combining them with reliable state quantization parameters, and generating interference intensity quantization parameters that reflect the degree of coupling influence of multiple interference sources. This includes the following step B1: B1: Generate interference intensity quantification parameters, including collecting spatial electromagnetic interference data, power grid harmonic data, ambient temperature data and equipment vibration data at the substation site, converting various types of physical quantities into relative intensity parameters in a unified form, and eliminating the dimensional differences between different physical quantities; Based on the relative intensity parameters of each type of interference and their corresponding weighted proportions, and combined with the correction term for the coupling and superposition effect generated when multiple interference sources act simultaneously, the weighted calculation of the comprehensive impact of multi-source interference is completed. The weighted calculation results are corrected using the credible state quantization parameter to generate the interference intensity quantization parameter.

[0043] Furthermore, the coupling superposition effect correction term is calculated using a modal recognition method to capture the superposition amplification effect generated when multiple types of interference sources act simultaneously; The weighting percentages for each type of interference are set according to the installation location and anti-interference characteristics of the hardware modules: hardware modules installed in the high-voltage switch room are assigned a higher weighting percentage for electromagnetic interference, while hardware modules installed in the main transformer equipment are assigned a higher weighting percentage for vibration and temperature.

[0044] Reference Figure 5 Specifically, step B1 is executed after step A2 completes the generation of the credible state quantization parameter T. It quantifies the comprehensive impact of the T value on various types of physical field interference at the substation site, generating the interference intensity quantization parameter (denoted as...). Its execution entity is the interference calculation unit of the Dianhong system.

[0045] Substation sites simultaneously experience multiple types of physical field interference, including spatial electromagnetic interference, power grid harmonics, ambient temperature changes, and equipment vibration. Spatial electromagnetic interference data is collected by the electromagnetic sensing unit on the terminal, covering electromagnetic radiation and conducted interference generated by the operation of high-voltage equipment within the substation; power grid harmonic data is collected by the power grid monitoring unit on the terminal, covering voltage and current harmonic components during power grid operation; ambient temperature data is collected by the temperature sensing unit on the terminal, covering real-time ambient temperature values ​​at the terminal's installation location; and equipment vibration data is collected by the vibration sensing unit on the terminal, covering vibration intensity values ​​caused by substation equipment operation and the external environment.

[0046] The four types of original physical quantities mentioned above have different dimensions and significantly different magnitudes, making them unsuitable for direct unified calculation. Therefore, a standardized transformation logic is used to generate corresponding relative intensity parameters: the relative coefficient of spatial electromagnetic interference intensity (denoted as...). ), the relative coefficient of power grid harmonic distortion (denoted as ), ), the relative coefficient of ambient temperature fluctuation (denoted as ) ) and the relative coefficient of equipment vibration (denoted as Each relative coefficient is the ratio of the actual measured value to the rated tolerance threshold of the corresponding hardware module. The numerical range is uniform, and the higher the value, the more severe the impact of the corresponding type of interference. By unifying the dimensions, the dimensional differences between different physical quantities are eliminated, providing a unified basis for the coupled calculation of multiple types of interference.

[0047] In substations, four types of interference sources often coexist, and these sources can couple and superimpose. The overall impact is not simply the sum of the individual effects of each interference source, but rather exhibits an amplification effect. To accurately quantify this coupling and superposition effect, a multi-source modal coupling correction coefficient (denoted as ) is introduced. The modal identification method is used to analyze the superposition characteristics of vibration modes generated when multiple interference sources act simultaneously, and a correction coefficient reflecting the degree of coupling superposition is calculated. The numerical value is positively correlated with the degree of coupling, which makes up for the shortcomings of traditional schemes that only calculate the influence of a single disturbance and ignore the superposition effect of coupling, resulting in inaccurate quantization.

[0048] The sum of the weighting coefficients a, b, c, and d corresponding to each interference type is fixed at 1. The setting is tailored to the installation location and anti-interference characteristics of the hardware module: the module installed in the high-voltage switch room increases the proportion of a (electromagnetic interference weighting coefficient), b is the power grid harmonic weighting coefficient, and the module installed at the main transformer equipment increases the proportion of c (ambient temperature weighting coefficient) and d (equipment vibration weighting coefficient), so as to realize differentiated interference control of modules with different installation locations.

[0049] also, The calculation process uses the credible state quantization parameter T generated in step A2 as a correction input, forming a two-way linkage between the credible state and the impact of interference: the higher the T value, the better the protection integrity of the hardware module, and the smaller the actual impact on the module's operation under the same interference intensity. The interference intensity quantization parameter... The value of T narrows accordingly; the lower the T value, the narrower the value. The value is increased accordingly to reflect the weakening effect of decreased hardware reliability on the module's anti-interference capability, achieving a coordinated adaptation between reliability and anti-interference capability. The calculation expression for K is as follows: The value is a core intermediate parameter connecting the on-site environmental data acquisition stage with subsequent hardware adjustments and data correction stages. Any changes in the on-site interference environment are detected through this parameter. The value is transmitted in real time to subsequent execution stages to ensure that the terminal's hardware configuration and data correction are always adapted to the current interference environment.

[0050] In this embodiment, step S300 adjusts the operating configuration parameters of the hardware module based on the trusted state quantization parameter and the interference intensity quantization parameter, completes the dynamic resource reconstruction of the hardware module, performs correlation correction on the original data collected by the hardware module, and outputs the final monitoring data, including the following steps C1-C2: C1: Adjust the operating configuration parameters of the hardware module, including adjusting the sampling rate parameter, gain parameter, interface configuration parameter and redundancy parameter, and reconstruct the hardware module acquisition channel, communication channel and backup resources according to the adjusted operating configuration parameters. The reconstruction process does not interrupt the overall operation of the monitoring terminal. The raw data collected by the hardware module is correlated and corrected, including calculating the hardware resource correction coefficient related to the adjustment range of the running configuration and the error compensation coefficient related to the compensation range of the acquisition error, and applying the two correction coefficients simultaneously to the correction calculation of the raw data collected. The corresponding coefficients in the calculation are updated and corrected in real time based on the adjustment results of the running configuration parameters, and the data correction range is kept synchronized with the hardware configuration adjustment status throughout the process.

[0051] Reference Figure 6 Specifically, step C1 completes the interference intensity quantization parameter in step B1. Triggered immediately after generation, the parameter T is quantized with the trusted state and the interference intensity quantization parameter. As a dual-drive basis, the adaptive adjustment of hardware module operation configuration parameters and the correlation correction of raw data are completed simultaneously. The two execution actions are strictly synchronized and linked, with no execution gap.

[0052] Regarding the adaptive adjustment of runtime configuration parameters, the adjustment targets include four categories: sampling rate parameters, gain parameters, interface configuration parameters, and redundancy parameters. The sampling rate parameter controls the data acquisition frequency of the hardware module. The sampling rate is automatically increased when the value increases or the T value decreases to ensure real-time data acquisition. When the value decreases and the T value increases, the sampling rate is automatically reduced to optimize operating power consumption; the gain parameter controls the signal amplification factor of the hardware module. When the T value increases, the gain is increased to compensate for signal attenuation caused by interference; when the T value decreases, the gain is adjusted synchronously to counteract the impact of abnormal module status on signal quality. The interface configuration parameters control the operating mode of the hardware module's communication interface, and complete the adaptation and switching of the communication mode according to the current interference level and reliability status. The redundancy parameters control the activation status of the hardware module's backup resources. When the value increases or the T value decreases, the redundancy configuration is automatically increased to enhance operational reliability.

[0053] After the four types of operating configuration parameters are adjusted, the hardware scheduling unit of the Dianhong system will reconstruct the hardware module acquisition channel, communication channel and backup resources according to the adjusted parameter combination. The reconstruction process will not interrupt the overall operation of the monitoring terminal, and the reconstructed hardware configuration status information will be synchronously transmitted to the data correction execution stage.

[0054] Regarding the correlation correction of the original acquired data, the correction process involves two correlation correction coefficients. The hardware resource correlation correction coefficient (denoted as...) This reflects the impact of current hardware configuration adjustments on the collected data, calculated using T and K as dual inputs. A higher K value and a lower T value indicate a greater impact. The greater the deviation of the value from the standard value, the more the hardware module simultaneously improves the acquisition performance and redundancy configuration, and k1 is updated accordingly. The lower the value and the higher the T value, the better. As the value approaches the standard, the hardware module automatically optimizes its energy consumption configuration.

[0055] Data error compensation coefficient (denoted as) This reflects the compensation magnitude for acquisition errors caused by the current interference environment and the module's trustworthiness. It is also calculated using T and K as dual inputs. Integrating two major error sources—on-site interference and module reliability status—the higher the K value and the lower the T value, the better. The larger the compensation range, the better it is at effectively offsetting acquisition errors caused by interference and abnormal module states; the lower the K value and the higher the T value, the better. Approaching the standard value avoids data distortion caused by overcompensation.

[0056] Based on the two correction coefficients mentioned above, the raw data collected by the hardware module is correlated and corrected to output the final monitoring data (denoted as...). ).in, The AKC reference voltage for the hardware module is a fixed reference standard calibrated at the factory. Its value is not affected by the field environment and the operating status of the module, and provides a stable reference for the quantification of raw data. This is the raw voltage data directly output by the AKC hardware module, which includes acquisition errors caused by field interference and changes in module status. It needs to be processed... and The dual correction eliminates the influence of errors; The dimensions are consistent with the physical quantity of the target being collected, and the data accuracy is adapted to the application requirements of substation monitoring. It is the final output of the entire method and process, integrating all influencing factors such as the reliability of the integrated module, the on-site interference environment, and the hardware configuration status. The calculation expression is as follows: in, This is a hardware resource correlation correction coefficient. This coefficient is calculated based on both the full-cycle autonomous controllability and reliability coefficient and the interference impact coefficient. The coefficient value is directly related to the adjustment range of the hardware configuration. The higher the interference impact and the lower the module reliability, the smaller the coefficient value. The hardware module will simultaneously improve the acquisition performance and redundancy configuration. The lower the interference impact and the higher the module reliability, the closer the coefficient value is to the standard value. The hardware module will simultaneously optimize the operating energy consumption configuration. This coefficient is the core link connecting hardware parameter adjustment and data correction. The parameter adjustment of the hardware module is completely completed according to the value of this coefficient. At the same time, this coefficient also directly participates in the calculation process of data correction, ensuring that the adjustment of hardware configuration and the magnitude of data correction are completely matched, realizing the synchronous coordination of hardware adjustment and data correction, breaking the isolated operation mode of hardware adjustment and data correction in traditional solutions.

[0057] This is the data error compensation coefficient. It is calculated based on both the full-cycle autonomous controllability and the interference impact coefficient. The coefficient value is directly related to the magnitude of data correction. The higher the interference impact and the lower the module reliability, the larger the coefficient value, resulting in greater compensation for the original collected data. This effectively offsets the acquisition errors caused by interference and module status. Conversely, the lower the interference impact and the higher the module reliability, the closer the coefficient value is to the standard value, avoiding data distortion caused by overcompensation. This coefficient integrates two major error sources: on-site interference and module reliability status, enabling comprehensive and accurate compensation for acquisition errors. Compared to traditional solutions that only compensate for interference, this coefficient incorporates the influence of module reliability status, allowing for a simultaneous increase in compensation when module reliability declines, ensuring accurate monitoring data output even when module reliability is abnormal. The logical derivation of this calculation expression is based on the dual influencing factors of acquisition error. On-site interference and module reliability status are taken as the core sources of error. By correlating correction coefficients, hardware configuration and data correction are synchronously adapted. The benchmark parameters and original acquisition data are integrated to form the final accurate data. Relevant technicians can directly complete the data correction process according to the parameter definition and calculation logic. The calculation process can be implemented without the need to add additional data processing devices. The calculation logic can be adapted to different acquisition modules and application scenarios with different interference intensities. The stability of the corrected data is not affected by changes in module type and scenario.

[0058] After the configuration parameters are adjusted, the data correction calculation is complete. and The system updates synchronously based on the latest hardware configuration status. The update logic is embedded in the parameter linkage unit of the Dianhong system and cannot be modified by external programs. This ensures that the data correction range is synchronized with the hardware configuration adjustment status throughout the process, and the output monitoring data always perfectly matches the current hardware operating status.

[0059] C2: The generation of trusted state quantization parameters, the generation of interference intensity quantization parameters, the adjustment of running configuration parameters, and the correlation correction of raw collected data are executed cyclically according to a preset time period. The execution order within each period is fixed, and the execution result of each period covers the corresponding parameters of the previous period. Data interaction between hardware modules and between the monitoring terminal and the substation back-end system are all accomplished through a distributed soft bus. The hardware module is connected and removed through a distributed soft bus to achieve plug-and-play recognition. When connected, it automatically completes communication adaptation and data channel setup. When removed, it automatically closes the corresponding data channel and releases system resources.

[0060] Specifically: Step C2 specifies the cyclic scheduling mechanism and data interaction channel for all the above execution steps to ensure that the terminal is always in an operating mode adapted to the current state during long-term continuous operation.

[0061] The generation of the reliable state quantization parameter T, the generation of the interference intensity quantization parameter K, the adaptive adjustment of the operation configuration parameters, and the correlation correction of the original acquired data are executed cyclically according to a preset time period. The cycle duration is fixed in the timed scheduling unit of the Dianhong system to adapt to the real-time requirements of substation monitoring. The execution order in each cycle is strictly consistent with the initial execution order, that is, the order A2→B1→C1 cannot be changed. In each cycle, a T value update, a K value update, an operation configuration parameter adjustment, and an original acquired data correction are completed. The execution result of each cycle covers the corresponding parameters of the previous cycle, ensuring that the terminal always uses the latest state parameters to complete the operation control.

[0062] The cyclic execution process is synchronized with the data acquisition process of the hardware module, without occupying core control resources. The cyclic execution logic adapts to the continuous long-term operation of the terminal, without execution interruption or parameter corruption. Changes in the operating status of the hardware module and changes in parameters of the field environment can be fed back and adapted within the current execution cycle, ensuring the timeliness of the linkage closed loop response.

[0063] All data interaction between hardware modules within the terminal, as well as between the monitoring terminal and the substation's backend system, is accomplished through a distributed soft bus. This distributed soft bus is a unified interaction channel natively integrated into the Dianhong system, featuring encrypted data transmission and identity verification. All operational, status, and acquired data from the hardware modules are transmitted via the soft bus, ensuring data security without the need for additional encryption devices. The soft bus's transmission protocol is compatible with the communication standards of all domestically produced hardware modules, enabling seamless data interaction across different module types.

[0064] The operating status of the soft bus is linked to the trusted status of the terminal: when the trusted status of the terminal is abnormal, the soft bus automatically shuts down unnecessary data channels to ensure the security of core data transmission; the transmission bandwidth is dynamically adjusted according to the current data interaction needs, and the data transmission delay is adapted to the real-time requirements of substation monitoring.

[0065] The access and removal of hardware modules are both completed through plug-and-play identification via a distributed soft bus: when a module is accessed, the soft bus automatically identifies the module type and operating status, completes communication adaptation and data channel setup, and then triggers step A1 to complete the initial trusted access for the newly accessed module; when a module is removed, the soft bus automatically shuts down the corresponding data channel and releases system resources to ensure that the overall operation of the terminal is not affected.

[0066] The entire loop execution mechanism, together with the soft bus interaction system, forms a collaborative closed loop covering the entire operating cycle of the terminal. No matter how the hardware parameters are adjusted or how the on-site interference environment changes, the data correction calculation can complete the synchronous response, ensuring that the final monitoring data output by the terminal is always accurate.

[0067] Example 3 Reference Figure 2 This is the third embodiment of the present invention.

[0068] The above is an illustrative scheme of a method for the collaborative adaptation of a substation monitoring terminal hardware module with full-lifecycle reliability and multi-source interference. It should be noted that the technical solution of this system for the collaborative adaptation of a substation monitoring terminal hardware module with full-lifecycle reliability and multi-source interference is based on the same concept as the aforementioned method for the collaborative adaptation of a substation monitoring terminal hardware module with full-lifecycle reliability and multi-source interference. Details not described in detail in this embodiment can be found in the description of the aforementioned method for the collaborative adaptation of a substation monitoring terminal hardware module with full-lifecycle reliability and multi-source interference.

[0069] This embodiment also provides a full-cycle trusted and multi-source interference collaborative adaptation system for hardware modules of substation monitoring terminals, including: a trusted computing verification module, configured to collect inherent physical characteristic data of hardware modules accessing the substation monitoring terminal based on a trusted execution environment, complete the initial trusted access of the hardware modules, and generate trusted state quantification parameters; The interference calculation module is configured to collect various types of environmental physical quantities at the substation site, and combine them with reliable state quantification parameters to generate interference intensity quantification parameters. The hardware scheduling module is configured to adaptively adjust the operating configuration parameters of the hardware module based on the trusted state quantization parameter and the interference intensity quantization parameter. The data processing module is configured to correlate and correct the raw data collected by the hardware module based on the trusted state quantization parameter and the interference intensity quantization parameter, and output the final monitoring data.

[0070] This embodiment also provides an electronic device suitable for the full-cycle reliability and multi-source interference collaborative adaptation of the hardware module of a substation monitoring terminal, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the method for realizing the full-cycle reliability and multi-source interference collaborative adaptation of the hardware module of the substation monitoring terminal as proposed in the above embodiment.

[0071] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, it implements the method for full-cycle reliability and multi-source interference collaborative adaptation of the hardware module of the substation monitoring terminal as proposed in the above embodiment.

[0072] The storage medium proposed in this embodiment and the method for achieving full-cycle reliability and multi-source interference collaborative adaptation of the hardware module of the substation monitoring terminal proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0073] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0074] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for full-lifecycle reliable and multi-source interference collaborative adaptation of a substation monitoring terminal hardware module, characterized in that: This includes collecting the inherent physical characteristic data of the hardware modules connected to the substation monitoring terminal based on a trusted execution environment, and completing the initial trusted access of the hardware modules; Collect operational behavior data and output data of hardware modules to generate a quantitative parameter of trust status that reflects the trustworthiness of the hardware module throughout its entire lifecycle. Collect various types of environmental physical quantities at the substation site, and combine them with the reliable state quantification parameters to generate interference intensity quantification parameters that reflect the degree of coupling influence of multiple interference sources; Based on the quantization parameters of the trusted state and the quantization parameters of the interference intensity, the operating configuration parameters of the hardware module are adjusted to complete the dynamic reconstruction of the hardware module's resources, the original data collected by the hardware module is correlated and corrected, and the final monitoring data is output.

2. The method for full-cycle reliable and multi-source interference collaborative adaptation of a substation monitoring terminal hardware module as described in claim 1, characterized in that: The initial trusted access to the hardware module includes comparing the collected inherent physical feature data with the standard feature data pre-stored in the secure storage area, and simultaneously confirming that the secure partition of the trusted execution environment is in a compliant operating state. Under the premise that the inherent physical characteristic data matches the standard characteristic data and the security partition compliance status meets the requirements, the access authorization of the hardware module is completed; the hardware module that fails the verification is automatically isolated by the monitoring terminal and does not participate in subsequent data collection and command execution.

3. The method for full-cycle reliable and multi-source interference collaborative adaptation of a substation monitoring terminal hardware module as described in claim 2, characterized in that: The generation of trusted state quantification parameters includes: verifying the matching degree between the running behavior data and the preset compliance rules, and verifying the consistency between the output data and the same source data of adjacent hardware modules. Based on the compliance level of the inherent physical characteristics of the hardware module, the compliance level of its operational behavior, the validity level of its output data, and the operational status of the trusted execution environment's secure partition, the trusted state quantification parameters are generated through weighted calculations across various dimensions. When the operational status of a security partition does not meet compliance requirements, the calculation results of the three dimensions—the compliance level of inherent physical characteristics, the compliance level of operational behavior, and the validity level of output data—are not included in the generation of the trusted state quantification parameters.

4. The method for full-cycle reliable and multi-source interference collaborative adaptation of a substation monitoring terminal hardware module as described in claim 3, characterized in that: The generated interference intensity quantization parameter This includes collecting spatial electromagnetic interference data, power grid harmonic data, ambient temperature data, and equipment vibration data at the substation site, converting various types of physical quantities into relative intensity parameters in a unified form, and eliminating dimensional differences between different physical quantities; Based on the relative intensity parameters of each type of interference and their corresponding weighted proportions, and combined with the correction term for the coupling and superposition effect generated when multiple interference sources act simultaneously, the weighted calculation of the comprehensive impact of multi-source interference is completed. The weighted calculation results are corrected using the credible state quantization parameter to generate the interference intensity quantization parameter.

5. The method for full-cycle reliable and multi-source interference collaborative adaptation of a substation monitoring terminal hardware module as described in claim 4, characterized in that: The coupling superposition effect correction term is calculated by the modal recognition method to capture the superposition amplification effect generated when multiple types of interference sources act simultaneously. The weighting percentages for each type of interference are set according to the installation location and anti-interference characteristics of the hardware modules: hardware modules installed in the high-voltage switch room are assigned a higher weighting percentage for electromagnetic interference, while hardware modules installed in the main transformer equipment are assigned a higher weighting percentage for vibration and temperature.

6. The method for full-cycle reliable and multi-source interference collaborative adaptation of a substation monitoring terminal hardware module as described in claim 5, characterized in that: The adjustment of the hardware module's operating configuration parameters includes adjusting the sampling rate parameter, gain parameter, interface configuration parameter, and redundancy parameter, and reconstructing the hardware module's acquisition channel, communication channel, and backup resources based on the adjusted operating configuration parameters. The reconstruction process does not interrupt the overall operation of the monitoring terminal. The process of correlating and correcting the raw data collected by the hardware module includes calculating the hardware resource correction coefficient related to the adjustment range of the running configuration and the error compensation coefficient related to the compensation range of the acquisition error, and applying the two correction coefficients simultaneously to the correction calculation of the raw data collected. The corresponding coefficients in the calculation are updated and corrected based on the adjustment results of the running configuration parameters, and the data correction magnitude is kept synchronized with the hardware configuration adjustment status throughout the process.

7. The method for full-cycle reliable and multi-source interference collaborative adaptation of a substation monitoring terminal hardware module as described in claim 6, characterized in that: The generation of the trusted state quantization parameter, the generation of the interference intensity quantization parameter, the adjustment of the running configuration parameters, and the correlation correction of the original collected data are executed cyclically according to a preset time period. The execution order within each period is fixed, and the execution result of each period covers the corresponding parameter of the previous period. Data interaction between hardware modules and between the monitoring terminal and the substation back-end system are all accomplished through a distributed soft bus. The hardware module is connected and removed through a distributed soft bus to achieve plug-and-play identification. When connected, communication adaptation and data channel establishment are completed. When removed, the corresponding data channel is automatically closed and system resources are released.

8. A system for full-cycle reliability and multi-source interference collaborative adaptation of a substation monitoring terminal hardware module, based on the method for full-cycle reliability and multi-source interference collaborative adaptation of a substation monitoring terminal hardware module according to any one of claims 1 to 7, characterized in that: It also includes a trusted computing verification module, configured to collect inherent physical characteristic data of hardware modules connected to the substation monitoring terminal based on a trusted execution environment, complete the initial trusted access of the hardware modules, and generate trusted state quantification parameters. The interference calculation module is configured to collect various types of environmental physical quantities at the substation site and, in conjunction with the reliable state quantification parameters, generate interference intensity quantification parameters. The hardware scheduling module is configured to adaptively adjust the operating configuration parameters of the hardware module based on the trusted state quantization parameter and the interference intensity quantization parameter. The data processing module is configured to correlate and correct the raw data collected by the hardware module based on the trusted state quantization parameter and the interference intensity quantization parameter, and output the final monitoring data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the substation monitoring terminal hardware module full-cycle reliability and multi-source interference collaborative adaptation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the substation monitoring terminal hardware module full-cycle reliability and multi-source interference collaborative adaptation method as described in any one of claims 1 to 7.

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