Interference suppression method, system, device and controller for a contactless voltage sensor

Abstract

The application relates to an interference suppression method, system, device and controller of a non-contact voltage sensor. The method comprises the following steps: monitoring high-energy particle radiation of an environment where the voltage sensor is located to obtain radiation intensity information of the high-energy particles; if the radiation intensity information of the high-energy particles represents that a first anti-interference condition is met, cutting off a signal input channel of the voltage sensor, and collecting a first output signal of an internal reference source of the sensor; wherein the first anti-interference condition comprises a transient high-energy particle interference event; determining a transient interference deviation amount of a current signal processing channel based on the first output signal; and if the voltage sensor resumes normal measurement, performing offset correction according to the transient interference deviation amount. The application can improve the stability and reliability of the sensor in a complex radiation environment.

Description

Technical Field

[0001] This application relates to the field of sensor measurement technology, and in particular to an interference suppression method, system, device and controller for a non-contact voltage sensor. Background Technology

[0002] In the field of non-contact electrical measurement, non-contact large-range voltage sensors have become key components for voltage sensing in smart grids and industrial automation due to their advantages of high safety, simple insulation, and flexible deployment. However, their high-sensitivity signal processing circuits are susceptible to the influence of high-energy charged particles such as cosmic rays and atmospheric neutrons, which can cause transient pulses or logic errors, leading to sudden distortion of the measurement signal. Their reliability faces fundamental challenges in environments with strong radiation, such as high altitudes.

[0003] To suppress such interference, relevant technologies mainly employ post-processing solutions involving physical shielding and signal filtering. However, physical shielding has limited effectiveness and high cost when pursuing miniaturization; traditional filtering lacks the ability to identify random and transient interference caused by particles, which may affect dynamic response. All related solutions are passive defenses and cannot achieve source identification and active compensation for interference.

[0004] Therefore, the relevant technologies still struggle to meet the high reliability requirements of non-contact sensors in high-energy particle-dense environments. Summary of the Invention

[0005] Therefore, it is necessary to provide an interference suppression method, system, device, and controller for a non-contact voltage sensor that can improve the anti-interference reliability of non-contact sensors, addressing the aforementioned technical problems.

[0006] In a first aspect, this application provides an interference suppression method for a non-contact voltage sensor, the method comprising:

[0007] The high-energy particle radiation in the environment where the voltage sensor is located is monitored to obtain information on the radiation intensity of high-energy particles;

[0008] If the radiation intensity information of high-energy particles satisfies the first anti-interference condition, the signal input path of the voltage sensor is cut off, and the first output signal of the sensor's internal reference source is acquired; wherein, the first anti-interference condition includes the occurrence of a transient high-energy particle interference event.

[0009] Based on the first output signal, determine the instantaneous interference deviation of the current signal processing channel;

[0010] If the voltage sensor resumes normal measurement, offset correction is performed based on the instantaneous interference deviation.

[0011] In one embodiment, the method further includes:

[0012] If the voltage sensor meets the second anti-interference condition, the signal input path of the voltage sensor is switched to the internal reference source, and the second output signal of the internal reference source is acquired. The second anti-interference condition includes the conditions of periodic triggering or event triggering calibration and drift compensation mechanism.

[0013] Based on the second output signal, determine the cumulative interference deviation of the current signal processing channel;

[0014] If the voltage sensor resumes normal measurement, offset correction is performed based on the accumulated interference deviation.

[0015] In one embodiment, if the radiation intensity information characterization of high-energy particles satisfies the first anti-interference condition, the method further includes:

[0016] In the event of an abnormal operation of the voltage sensor controller, a hardware reset of the controller is performed.

[0017] In one embodiment, determining the current interference deviation of the current signal processing channel includes:

[0018] Sample the current output signal;

[0019] The current interference deviation is calculated based on the current output signal using an adaptive filtering algorithm.

[0020] When the current interference deviation is the instantaneous interference deviation, the current output signal is the first output signal; when the current interference deviation is the cumulative interference deviation, the current output signal is the second output signal.

[0021] In one embodiment, the adaptive filtering algorithm includes the Kalman filtering algorithm.

[0022] In one embodiment, offset correction is performed based on the current interference deviation, including:

[0023] Determine the normal measurement signal after resuming normal measurement;

[0024] The target measurement signal is determined based on the degree of difference between the normal measurement signal and the current interference deviation. Wherein, when the first anti-interference condition is met, the current interference deviation is the instantaneous interference deviation, and when the second anti-interference condition is met, the current interference deviation is the cumulative interference deviation.

[0025] Based on the target measurement signal, the voltage sensor is used for measurement and control.

[0026] In one embodiment, the measurement control of the voltage sensor based on the target measurement signal further includes:

[0027] Perform data verification on the target measurement signal;

[0028] If the target measurement signal data verification fails, the current output signal will be re-acquired until the data verification passes.

[0029] In one embodiment, the radiation intensity information includes the pulse count rate of high-energy particles; the first anti-interference condition includes the pulse count rate being greater than or equal to a preset count rate threshold.

[0030] In one embodiment, the second anti-interference condition includes:

[0031] Reaching the preset periodic calibration time; and / or,

[0032] Based on the radiation intensity information, the calculated cumulative flux of high-energy particles exceeds the second preset threshold.

[0033] Secondly, this application also provides a non-contact voltage sensor system for implementing the method described above, the system comprising:

[0034] A voltage sensing unit is used for non-contact sensing of the voltage being measured and generating a sensing signal.

[0035] The particle monitoring unit is used to monitor high-energy particle radiation in the environment and generate radiation intensity information.

[0036] The processing control unit, which is connected to the voltage sensing unit and the particle monitoring unit respectively, is configured to perform the steps of the above method.

[0037] In one embodiment, the particle monitoring unit includes:

[0038] Particle detectors are used to respond to high-energy particles and output corresponding electrical signals.

[0039] The signal processing circuit, connected to the particle detector and the processing control unit respectively, is used to condition and shape the electrical signal and generate radiation intensity information.

[0040] In one embodiment, the processing control unit includes:

[0041] The microcontroller executes the steps of the above method;

[0042] The watchdog timer circuit is connected to the microcontroller. When the watchdog timer times out and is not refreshed, it triggers a system hardware reset of the microcontroller.

[0043] Thirdly, this application also provides an interference suppression device for a non-contact voltage sensor, the device comprising:

[0044] The monitoring module is used to monitor the high-energy particle radiation in the environment where the voltage sensor is located, and obtain the radiation intensity information of the high-energy particles.

[0045] If the radiation intensity information of high-energy particles satisfies the first anti-interference condition, the first anti-interference module cuts off the signal input path of the voltage sensor and acquires the first output signal of the sensor's internal reference source; wherein, the first anti-interference condition includes the occurrence of a transient high-energy particle interference event.

[0046] The deviation determination module is used to determine the instantaneous interference deviation of the current signal processing channel based on the first output signal;

[0047] The offset correction module is used to perform offset correction based on the instantaneous interference deviation if the voltage sensor resumes normal measurement.

[0048] Fourthly, this application also provides a controller, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method.

[0049] Fifthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0050] The interference suppression method, system, device, and controller for the non-contact voltage sensor provided in this application monitor the high-energy particle radiation in the environment where the voltage sensor is located to obtain the radiation intensity information of high-energy particles, enabling real-time and quantitative sensing of high-energy particle radiation. If the radiation intensity information of high-energy particles meets the first anti-interference condition, the signal input path of the voltage sensor is cut off, and the first output signal of the sensor's internal reference source is acquired, which can improve the reliability of the voltage sensor under extreme transient interference. Based on the first output signal, the instantaneous interference deviation of the current signal processing channel is determined, which can transform the random and abstract interference effect into a specific and compensable system error parameter, achieving accurate calibration of the interference effect. If the voltage sensor resumes normal measurement, offset correction is performed based on the instantaneous interference deviation, which can actively eliminate the influence of interference on the measurement results, thereby restoring the accuracy of the measurement. Compared with related technologies, this application effectively suppresses the impact of transient high-energy particle interference on the measurement accuracy of non-contact voltage sensors by real-time monitoring of high-energy particle radiation and responding to interference events, cutting off the signal input path to avoid interference propagation, and calculating the instantaneous deviation by combining the signal collected by the internal reference source and automatically correcting it after recovery. This can improve the stability and reliability of the sensor in complex radiation environments. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 A flowchart illustrating an interference suppression method for a non-contact voltage sensor provided in an embodiment of this application;

[0053] Figure 2 A schematic diagram illustrating the interference suppression process of another non-contact voltage sensor provided in this application embodiment;

[0054] Figure 3 A flowchart illustrating an offset correction step based on interference quantity provided in an embodiment of this application;

[0055] Figure 4 This is a schematic diagram of a non-contact voltage sensor system provided in an embodiment of this application;

[0056] Figure 5 This is a schematic diagram of the overall structure of a non-contact voltage sensor system provided in an embodiment of this application;

[0057] Figure 6 A schematic flowchart illustrating a method for suppressing interference in a non-contact voltage sensor provided in this application embodiment;

[0058] Figure 7 A schematic diagram illustrating the working process of a particle detection circuit provided in an embodiment of this application;

[0059] Figure 8 This is a schematic diagram of the structure of an interference suppression device for a non-contact voltage sensor provided in an embodiment of this application;

[0060] Figure 9 This is a schematic diagram of the internal structure of a controller provided in an embodiment of this application. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0062] Non-contact, large-range voltage sensors offer high safety and flexibility due to their elimination of direct contact with the measured object, making them widely used in power systems, industrial automation, and other fields. However, high-energy particles (such as cosmic rays and medium-energy protons) can interfere with the sensor's signal acquisition and processing circuitry, leading to measurement errors or signal distortion. Current technologies typically suppress interference through physical shielding and signal filtering, but the effectiveness is limited, especially in environments with high-energy particle density.

[0063] In one exemplary embodiment, Figure 1 This is a flowchart illustrating an interference suppression method for a non-contact voltage sensor provided in an embodiment of this application, as shown below. Figure 1 As shown, a method for interference suppression of a non-contact voltage sensor is provided. This method is illustrated using a controller as an example. It is understood that this method can also be applied to a server, or to a system including both a controller and a server, and is implemented through the interaction between the controller and the server. The controller can be, but is not limited to, various microcontrollers, DSPs (Digital Signal Processors), or computers. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. In this embodiment, the method includes the following steps S101 to S104: Wherein:

[0064] S101. Monitor the high-energy particle radiation in the environment where the voltage sensor is located to obtain the radiation intensity information of the high-energy particles.

[0065] High-energy particle radiation refers to a stream of microscopic particles from outer space or ground-based radiation sources, possessing sufficient energy to penetrate matter and potentially induce various effects in semiconductor devices. This can include protons, neutrons, alpha particles, and heavy ions. The environment in which the voltage sensor is located refers to the physical space where the sensor is actually deployed and operates; its radiation background may vary depending on geographical location, altitude, and shielding conditions. Monitoring refers to the continuous or periodic measurement and recording of the flux or fluence rate of high-energy particles in the environment using specialized detection equipment. Radiation intensity information refers to quantitative data characterizing the activity level of high-energy particles in the environment, such as instantaneous pulse count rate and particle fluence per unit time.

[0066] For example, a separate radiation monitoring unit can be integrated onto the printed circuit board (PCB) of a non-contact voltage sensor to detect high-energy particles penetrating the sensor housing and internal shielding structure in real time. This radiation monitoring unit can convert particle events into electrical signals, process them to generate digitized radiation intensity information, and transmit it to the controller for real-time analysis.

[0067] As an example, a silicon PIN photodiode can be reverse-biased as the particle-sensitive region, and combined with a charge-sensitive preamplifier (CSA) and shaping circuitry, the current pulses generated by the particles passing through can be shaped into countable quasi-Gaussian pulses. Finally, the instantaneous count rate is measured by the timer / counter of the MCU (Microcontroller Unit) as radiation intensity information.

[0068] In practical applications, by monitoring radiation intensity information in real time, the system can shift from passively enduring interference to actively sensing environmental threats, providing a data foundation for subsequent intelligent decision-making and tiered response.

[0069] S102. If the radiation intensity information of high-energy particles satisfies the first anti-interference condition, the signal input path of the voltage sensor is cut off, and the first output signal of the internal reference source of the sensor is acquired; wherein, the first anti-interference condition includes the occurrence of a transient high-energy particle interference event.

[0070] The first anti-interference condition refers to the criteria for triggering the highest level of emergency protection mechanism. Cutting off the signal input path refers to physically disconnecting the sensing electrode from the subsequent precision amplifier using hardware circuitry such as analog switches to prevent strong transient interference currents from directly impacting the core circuitry. The internal reference source refers to a known, stable voltage or short-circuit reference point within the sensor, such as a precision grounding resistor or the output of a voltage reference chip. The first output signal refers to the actual voltage value output by the signal processing channel, including amplifiers and ADCs (Analog-to-Digital Converters), after the signal path is cut off and switched to the internal reference source.

[0071] For example, the controller can continuously monitor radiation intensity information (such as pulse count rate). When this radiation intensity information exceeds a preset radiation intensity threshold (e.g., determined to be a strong transient high-energy particle shower event), a hardware interrupt can be triggered. In the interrupt service routine, the controller can drive the GPIO (General Purpose Input / Output) to control the analog switch action, switching the ADC input from the external signal channel to the internal reference voltage, and initiating one or more high-speed ADC samplings to obtain the output reading of the reference source at this time, i.e., the first output signal.

[0072] As an example, when the timer of the MCU (Microcontroller Unit) measures an instantaneous count rate exceeding a preset threshold, the External Interrupt Pin (EXTI) can immediately generate a hardware interrupt. In the Interrupt Service Routine (ISR), the MCU can use the GPIO control switch to cut off the sensor input and start the ADC to perform 32 rapid continuous samples of the internal reference voltage to obtain the first output signal dataset.

[0073] This allows for "hard isolation" and signal calibration of transient strong interference. By quickly cutting off the input path, it effectively prevents transient current pulses caused by high-energy particles from impacting and flooding vulnerable front-end circuits, protecting hardware safety. Simultaneously, by using an internal reference source flowing through the interfered signal chain, it is possible to accurately capture the instantaneous disturbance caused by this event to the system gain and offset, providing direct experimental data for subsequent software compensation. This can serve as a protective measure to ensure the system remains undistorted and undamaged under sudden interference, while maintaining data traceability.

[0074] S103. Based on the first output signal, determine the instantaneous interference deviation of the current signal processing channel.

[0075] The instantaneous interference deviation refers to the signal path error introduced by a single or short-duration high-intensity particle radiation event (such as a single-particle transient), which has instantaneous or rapidly decaying characteristics. The current signal processing channel refers to all signal conditioning and conversion circuitry from the sensor analog front-end (after the switch) to the controller ADC input pin. The determination step refers to extracting the value characterizing the channel deviation from the first output signal through calculation or estimation algorithms.

[0076] For example, the controller can perform digital signal processing on the first output signal (i.e., the output under the reference source) and extract or estimate the system deviation value introduced by the transient interference at the current moment through a preset specific algorithm, and record the system deviation value as the transient interference deviation amount.

[0077] As an example, a moving average filter can be performed on the first output signal data obtained through rapid sampling to suppress random noise. The filtered value is then fed into a simplified Kalman filter to estimate the current system deviation V. drift The V drift This is the instantaneous disturbance deviation, which is stored in a global variable for subsequent compensation.

[0078] In practical applications, by accurately calculating the instantaneous interference deviation, the random and abstract physical disturbances caused by high-energy particles can be transformed into specific and quantifiable system error parameters. This allows for precise assessment of the interference's impact, enabling the system to clearly understand its state shift after the interference, rather than continuing to use a contaminated signal baseline. This fundamentally eliminates the direct influence of instantaneous interference on single or short-cycle measurement results, thereby improving the instantaneous accuracy of non-contact voltage sensor measurements.

[0079] S104. If the voltage sensor resumes normal measurement, offset correction shall be performed based on the instantaneous interference deviation.

[0080] "Restoring normal measurement" refers to the controller switching the signal input path back to the sensing electrode after the interference event subsides (e.g., radiation intensity drops below a safe threshold), allowing the sensor to continue performing normal voltage sensing functions. "Offset correction" refers to subtracting the previously calculated instantaneous interference deviation from the original measurement value before outputting the final measurement result, in order to eliminate the fixed offset caused by interference within the system itself.

[0081] For example, after confirming that the external environment is safe, the controller can control the analog switch to switch to the measurement channel. And after switching to the normal measurement channel, each raw voltage value obtained by the ADC sampling can be subjected to a deviation compensation operation before being used for calculation or output: the stored instantaneous interference deviation is subtracted from the measured raw voltage value to obtain the corrected accurate measurement value.

[0082] As an example, after a non-contact voltage sensor measurement system resumes normal measurement, each normal voltage sampling value V... raw The value is determined immediately based on the expression before output: V corrected =V raw -V drift Among them, V drift V is the instantaneous disturbance deviation estimated in step S103. corrected This is the final accurate measurement after drift compensation.

[0083] Thus, by automatically performing offset correction after an interference event, the residual effects of transient interference on the measurement reference can be quickly eliminated, allowing the system output to rapidly recover to an accurate state. This ensures the continuity and validity of the measurement data, thereby achieving a seamless transition from interference suppression to accurate measurement recovery.

[0084] In this embodiment, by actively and in real-time sensing the external high-energy particle radiation environment, the uncontrollable threat of high-energy particle radiation is transformed into quantifiable internal data. Based on the sensed data, protection is triggered, namely, hardware isolation and rapid deviation estimation are performed for sudden strong interference, protecting hardware safety and locking in instantaneous errors. Furthermore, after normal measurement is restored, the estimated interference deviation can be used to perform real-time and accurate measurement compensation on the measurement signal, which can reduce the impact of interference on the final output accuracy, thereby achieving high reliability of non-contact sensor anti-interference.

[0085] In one exemplary embodiment, Figure 2 A schematic diagram illustrating the interference suppression process of another non-contact voltage sensor provided in this application embodiment is shown below. Figure 2 As shown, the method also includes:

[0086] S201. If the voltage sensor meets the second anti-interference condition, the signal input path of the voltage sensor is switched to the internal reference source, and the second output signal of the internal reference source is acquired.

[0087] S202. Based on the second output signal, determine the cumulative interference deviation of the current signal processing channel.

[0088] S203. If the voltage sensor resumes normal measurement, offset correction shall be performed based on the accumulated interference deviation.

[0089] The second anti-interference condition can refer to the conditions of the calibration and drift compensation mechanism that is periodically triggered or event-triggered. The cumulative interference deviation can refer to the slow drift of semiconductor device parameters caused by effects such as total ionizing dose (TID) due to long-term radiation exposure; this drift can be gradual and cumulative over a long period. The second output signal can refer to the output value acquired after the signal processing path switches to the internal reference source during periodic calibration.

[0090] For example, the controller can automatically trigger the calibration process based on a preset time period or when the cumulative flux count counted by the particle monitoring unit reaches a certain threshold. The controller can switch the signal input path to an internal reference source for sampling and analyze the long-term trend of the sampled value and the ideal reference value using a preset algorithm to calculate the cumulative interference deviation.

[0091] As an example, the system can be timed by a high-precision hardware timer, triggering a calibration every fixed period T1 (e.g., 10 seconds). The MCU can control an analog switch to switch the front-end input to the internal precision short-circuit reference point. After stabilization, the internal reference output is sampled 256 times consecutively to obtain sampled data. This sampled data is then averaged and recursively calculated using an adaptive Kalman filter. The final optimal estimate is the cumulative interference deviation, and the global variables are updated accordingly.

[0092] In this embodiment, through a periodic or conditionally triggered self-calibration mechanism, the circuit performance slow drift (i.e., cumulative damage) caused by long-term radiation exposure can be monitored and compensated online and in real time, which can address the problem of long-term accuracy degradation, thereby ensuring the measurement accuracy and stability of the sensor when working in harsh environments for a long time.

[0093] In an exemplary embodiment, if the characterization of the radiation intensity information of high-energy particles satisfies the first anti-interference condition, the method further includes:

[0094] In the event of an abnormal operation of the voltage sensor controller, a hardware reset of the controller is performed.

[0095] Among these, controller malfunction refers to serious faults such as single-event latch-up (SEL) or program crashes caused by strong interference, resulting in the controller losing responsiveness or making logical errors. Hardware reset refers to forcibly restoring all registers and the program counter of the controller to their initial state through external circuitry, which can be used as a cold start.

[0096] For example, when the controller enters the protection process corresponding to the first anti-interference condition, an independent hardware watchdog timer can be enabled simultaneously. If the controller fails to "feed" the watchdog normally (i.e. refresh the watchdog) within a preset time, the watchdog circuit will output a reset signal, forcing the controller to restart.

[0097] As an example, after the protection process is triggered, either an independent watchdog timer within the MCU or an external discrete watchdog chip can be enabled. If strong interference causes the MCU program to crash and prevents the normal watchdog feeding operation from being performed, the watchdog timer will force a hardware reset signal after a timeout, causing the entire system to restart from its initial state.

[0098] In this embodiment, a hardware watchdog is used as the final safety barrier to recover from severe controller deadlock or fault states, thereby improving the system's self-healing ability and task continuity. It can avoid the risk of permanent paralysis of the entire sensor system due to a single point of failure and can meet the reliability requirements of high non-contact voltage sensors.

[0099] In one exemplary embodiment, determining the current interference deviation of the current signal processing channel includes:

[0100] Sample the current output signal;

[0101] The current interference deviation is calculated based on the current output signal using an adaptive filtering algorithm.

[0102] When the current interference deviation is the instantaneous interference deviation, the current output signal is the first output signal; when the current interference deviation is the cumulative interference deviation, the current output signal is the second output signal.

[0103] Adaptive filtering algorithms refer to algorithms that can automatically adjust parameters based on the statistical characteristics of the input signal to optimally estimate the desired signal. Adaptive filtering algorithms can be used to extract slowly changing or abruptly changing trend signals from noise.

[0104] For example, the system can employ the same adaptive filtering-based calculation method to address both transient disturbances and cumulative drift. This method can perform smoothing preprocessing on the sampled data and dynamically estimate the optimal value representing the system deviation (i.e., the amount of disturbance deviation) using an adaptive filter.

[0105] As an example, the system can employ the Kalman filter algorithm as an adaptive filtering algorithm. This algorithm can recursively calculate the optimal estimate of the system state (in this case, the disturbance deviation) online by setting parameters such as process noise covariance Q and measurement noise covariance R, and it has good tracking and filtering capabilities for both sudden changes (instantaneous disturbances) and gradual changes (cumulative drift).

[0106] In this embodiment, a unified adaptive filtering framework can be used to handle the two types of interference deviations, which can simplify system design, thereby improving code reusability. It can distinguish between real deviations and random noise in the signal, thus more accurately and robustly estimating the impact of interference, providing an algorithmic foundation for subsequent high-precision compensation.

[0107] In one exemplary embodiment, the adaptive filtering algorithm includes the Kalman filtering algorithm.

[0108] The Kalman filter algorithm can be considered an optimal recursive state estimation algorithm. It can perform real-time, progressive state estimation of a noisy linear dynamic system using a system model composed of state equations and observation equations. In this application, the "state" in the Kalman filter algorithm refers to the current disturbance deviation (including instantaneous or cumulative disturbance deviation) that needs to be estimated in real time, and the "observation" refers to the current output signal (first or second output signal) obtained after sampling the internal reference source. This algorithm can integrate prior knowledge of the system with new observation data, and provide an optimal estimate of the system state based on the minimum mean square error criterion.

[0109] For example, a Kalman filter algorithm can be implemented in the program of a processing control unit (such as a microcontroller). This algorithm models the drift process of the signal processing channel as a dynamic system, recursively updating the optimal estimate of the system bias (i.e., the amount of interference bias) using reference source output data acquired during each periodic calibration or emergency event trigger. The algorithm automatically balances the confidence levels of historical estimates with the reliability of the latest observations, thereby robustly extracting slowly changing cumulative drift trends or sudden instantaneous shifts from noise.

[0110] As an example, during the initialization phase, the process noise covariance Q, measurement noise covariance R, and initial estimation error covariance P are set. Each time calibration or event compensation is triggered, the reference sample value, preprocessed with a moving average, can be used as the input filter for the current measurement value. Subsequently, the algorithm recursively executes two steps: prediction and update. The prediction step predicts the current state and its error covariance based on the state estimate and process model from the previous time step. The update step corrects the prediction using the new measurement value, calculates the Kalman gain, and finally obtains the optimal estimate of the disturbance bias at the current time step and the updated error covariance. This optimal estimate is then assigned as a global variable for subsequent real-time compensation.

[0111] In this embodiment, by employing the Kalman filter algorithm, high-precision and robust online estimation of interference deviations can be achieved. The introduction of the Kalman filter algorithm enables intelligent and accurate algorithmic compensation, thereby ensuring the accuracy and reliability of the measurement at the algorithmic level.

[0112] In one exemplary embodiment, Figure 3 A flowchart illustrating an offset correction step based on interference quantity is provided for an embodiment of this application, as shown below. Figure 3 As shown, offset correction is performed based on the current interference deviation, including:

[0113] S301. Determine the normal measurement signal after resuming normal measurement;

[0114] S302. Determine the target measurement signal based on the degree of difference between the normal measurement signal and the current interference deviation; wherein, when the first anti-interference condition is met, the current interference deviation is the instantaneous interference deviation, and when the second anti-interference condition is met, the current interference deviation is the cumulative interference deviation.

[0115] S303. Based on the target measurement signal, perform measurement control of the voltage sensor.

[0116] In this context, the normal measurement signal can refer to the raw voltage value directly sampled by the ADC after the sensor input is switched back to the sensing electrode. The degree of difference refers to the elimination of interference bias through mathematical operations (such as subtraction). The target measurement signal can refer to the final result obtained after offset correction, which is considered to be closer to the actual measured voltage.

[0117] For example, during the compensation phase, the system's controller can read the currently stored disturbance deviation (which may be instantaneous or cumulative) and subtract it from each newly acquired normal measurement signal. The resulting difference is the target measurement signal. This target measurement signal can be used for display, uploading, or closed-loop control.

[0118] As an example, this step can be implemented using the following expression:

[0119] ;

[0120] Regardless of V drift Whether the disturbance originates from a transient event or a periodic calibration, the compensation operation can be the same, ensuring the consistency and simplicity of the compensation logic.

[0121] In this embodiment, a pre-defined subtraction compensation model transforms complex hardware anti-interference and software algorithm results into simple and effective corrections to the output data. This allows the high reliability of anti-interference capabilities to be directly reflected in the final measurement accuracy, thus achieving a complete closed loop from internal state perception to external output optimization. This, in turn, improves the reliability of non-contact sensor anti-interference and enhances measurement accuracy.

[0122] In one exemplary embodiment, the measurement control of the voltage sensor based on the target measurement signal further includes:

[0123] Perform data verification on the target measurement signal;

[0124] If the target measurement signal data verification fails, the current output signal will be re-acquired until the data verification passes.

[0125] Data verification refers to a mechanism for detecting errors in digital data during transmission or storage, used to detect bit errors caused by single event upsets (SEUs).

[0126] For example, after obtaining the target measurement signal (usually a digital quantity), before using the target measurement signal for critical control or sending it to the host computer, it can be verified by a checksum (such as CRC check). If the verification fails, it indicates that the data may have been corrupted during generation or transmission. The system will discard the data and trigger a new measurement sampling to obtain the correct data.

[0127] As an example, many high-precision ADCs append a CRC code to the SPI data frame. The MCU recalculates the CRC and compares it after receiving the data. If the check fails, the MCU logs the error and immediately re-initiates a complete ADC read operation, replacing the erroneous data with the new, correct data. This enables checks such as bit-flip correction.

[0128] In this embodiment, by adding verification and retransmission steps at the data link layer, transient data errors caused by single-event upsets can be effectively suppressed, preventing individual erroneous data points from affecting the overall measurement results or causing miscontrols. This further improves the reliability of the entire system from the perspective of information transmission reliability, thereby ensuring the authenticity and validity of the output data.

[0129] In one exemplary embodiment, the radiation intensity information includes the pulse count rate of high-energy particles; the first anti-interference condition includes a pulse count rate greater than or equal to a preset count rate threshold.

[0130] The pulse count rate refers to the number of effective pulses output by the particle detector per unit time, reflecting the frequency of high-energy particle incidence. The preset count rate threshold is a pre-set threshold value based on the sensor circuit's tolerance and application requirements.

[0131] For example, the particle monitoring unit can convert each detected valid particle event into a digital pulse, and the microcontroller can measure the number of pulses per second using a timer / counter. When the real-time calculated count rate exceeds a threshold set in the software, a strong interference event is determined to have occurred.

[0132] As an example, a count rate threshold can be set in the MCU. When the instantaneous count rate measured by the timer exceeds this threshold, the EXTI pin connected to the output pulse of the shaping circuit immediately generates a hardware interrupt, quickly triggering the protection process of the first anti-interference condition.

[0133] In this embodiment, the radiation intensity is quantified into an intuitive pulse count rate, and a clear hardware interrupt threshold is set, which enables the system to respond to interference events extremely quickly and definitively, avoiding the delay caused by software polling, and providing the possibility of achieving rapid emergency protection, thereby improving the real-time performance of the system in dealing with sudden interference.

[0134] In one exemplary embodiment, the second anti-interference condition includes:

[0135] Reaching the preset periodic calibration time; and / or,

[0136] Based on the radiation intensity information, the calculated cumulative flux of high-energy particles exceeds the second preset threshold.

[0137] The preset periodic calibration time can be a fixed time interval, such as triggering calibration every 10 seconds or every minute. Cumulative fluence refers to the total number of high-energy particles passing through a unit area over a period of time; it is an indicator of cumulative radiation dose. The second preset threshold is a threshold value set for cumulative radiation damage.

[0138] For example, the system can manage periodic calibration triggers via a separate real-time clock (RTC). Simultaneously, the microcontroller continuously increments the counts reported by the particle monitoring unit and estimates the cumulative fluence based on the detector's sensitive area. When either condition is met, a calibration process designed to compensate for accumulated drift is triggered.

[0139] As an example, after the system is running, timing can be achieved using a high-precision hardware timer or the RTC inside the MCU. Whenever time interval T1 is reached, the timer generates an interrupt, triggering the calibration sequence. This is a typical method for triggering periodic calibration.

[0140] In this embodiment, a triggering mechanism combining time-driven and event-driven (cumulative injection) approaches ensures that drift compensation maintains a regular rhythm while adaptively adjusting based on the actual radiation intensity received. This triggering strategy guarantees the timeliness and effectiveness of compensation, optimizing system power consumption and resource usage while maintaining accuracy.

[0141] In one exemplary embodiment, Figure 4 This is a schematic diagram of a non-contact voltage sensor system provided in an embodiment of this application, as shown below. Figure 4 As shown, this non-contact voltage sensor system is used to implement the method described above. The system may include: a voltage sensing unit 410, a particle monitoring unit 420, and a processing control unit 430, wherein:

[0142] Voltage sensing unit 410 is used for non-contact sensing of the voltage to be measured and generating a sensing signal;

[0143] Particle monitoring unit 420 is used to monitor high-energy particle radiation in the environment and generate radiation intensity information;

[0144] The processing control unit 430, which is connected to the voltage sensing unit 410 and the particle monitoring unit 420 respectively, is configured to perform the steps of the above method.

[0145] The voltage sensing unit 410 may include sensing electrodes, a high-impedance preamplifier, etc., and can convert changes in the spatial electric field into a weak electrical signal. The particle monitoring unit 420 can refer to an independent radiation detection subsystem. The processing and control unit 430 can be based on a microcontroller and is responsible for executing all monitoring, judgment, control, and algorithms.

[0146] For example, the voltage sensing unit 410, particle monitoring unit 420, and processing control unit 430 can be physically integrated into the same PCB or the same package. The outputs of the voltage sensing unit 410 and the particle monitoring unit 420 are both connected to the analog / digital input port of the processing control unit 430. The processing control unit 430 coordinates the entire anti-interference suppression process according to its internally programmed logic.

[0147] As an example, the system can constitute a complete protection system. The voltage sensing unit 410 includes electrodes and front-end circuitry; the particle monitoring unit 420 can be a particle detection subsystem; and the processing control unit 430 can be a signal processing and control system with an MCU as the processing circuit.

[0148] In this embodiment, by transforming the method implementation into a specific system implementation, the hardware configuration in the actual product is clarified. This provides a physical foundation for comprehensive and coordinated anti-interference from the physical layer to the information layer, enabling the highly reliable anti-interference method to be implemented in manufacturable and applicable sensor products.

[0149] In one exemplary embodiment, the particle monitoring unit includes:

[0150] Particle detectors are used to respond to high-energy particles and output corresponding electrical signals.

[0151] The signal processing circuit, connected to the particle detector and the processing control unit respectively, is used to condition and shape the electrical signal and generate radiation intensity information.

[0152] Among them, particle detectors are radiation-sensitive devices, such as PIN diodes and radiation-sensitive FETs. Signal processing circuits typically include analog circuits such as preamplifiers, shapers, and discriminators, used to amplify and shape the weak and irregularly shaped charge signals output by the detector into standardized digital pulses.

[0153] For example, a high-energy particle strikes the sensitive volume of the detector, generating electron-hole pairs and forming a transient current pulse. The signal processing circuit first integrates the charge into a voltage pulse through a charge-sensitive preamplifier, then optimizes the signal-to-noise ratio and pulse shape through a shaping circuit, and finally compares it with a threshold through a comparator, outputting a regular TTL or CMOS level pulse to the processing control unit for counting.

[0154] As an example, a silicon PIN photodiode can be used as the particle detector. The signal processing circuitry includes a charge-sensitive preamplifier (CSA) composed of operational amplifiers and a CR-(RC) amplifier. 4 The circuitry includes a shaping circuit and a voltage comparator. The final output counting pulse is fed into the MCU's timer / counter for measurement.

[0155] In this embodiment, the particle monitoring unit enables the "visualization" of high-energy particle interference. It converts invisible radiation fields into precisely measurable electrical signals, providing environmental awareness for the entire system. The independence and specialization of this particle monitoring unit ensure the accuracy and reliability of radiation monitoring.

[0156] In one exemplary embodiment, the processing control unit includes:

[0157] The microcontroller executes the steps of the above method;

[0158] The watchdog timer circuit is connected to the microcontroller. When the watchdog timer times out and is not refreshed, it triggers a system hardware reset of the microcontroller.

[0159] The microcontroller is a single-chip microcomputer that integrates multiple functions such as CPU, memory, timer, ADC, and communication interface. The watchdog timer circuit (WDT) can be an independent timer that requires the microcontroller to periodically send a "feed the dog" signal to reset the timer. If no signal is received within the timeout period, the system is considered to be malfunctioning.

[0160] For example, the microcontroller can act as the main control chip, running firmware programs to implement all logic such as S101-S104. A watchdog timer circuit (which can be an independent watchdog IWDG built into the MCU or an external discrete chip) is connected to a GPIO pin of the microcontroller. During normal program loops, this pin is periodically operated on to "feed the watchdog." If the program crashes, the watchdog feeding stops, and a reset is triggered after the watchdog times out.

[0161] As an example, an independent watchdog timer (or an external discrete watchdog chip) can be enabled within the MCU. If strong interference causes the MCU program to crash and fail to feed the watchdog, the WDT will force a hardware reset after a timeout, causing the entire system to restart.

[0162] In this embodiment, by configuring a watchdog circuit, even if a severe software failure or hardware latch-up causes the microcontroller to crash, the system can be restarted through a forced reset. This adds a layer of fault tolerance to the processing control unit itself, ensuring the high reliability of the control unit as the core of the system. This allows the entire sensor system to withstand extremely harsh interference environments, thereby improving the anti-interference reliability and measurement accuracy of the non-contact voltage sensor.

[0163] In some specific embodiments, the interference suppression method and system for the non-contact voltage sensor provided in this application may specifically include:

[0164] The non-contact voltage sensor system employs a physical protection layer: through materials science and hardware selection, it physically attenuates and resists particle bombardment, serving as the "first line of defense." The system detection layer, using dedicated detectors and scheduling strategies, senses the radiation environment in real time and responds intelligently, acting as an "early warning and decision-making center." The signal processing layer, through algorithms and redundancy design, corrects and compensates for any interference that slips through the network at the software level. These three layers work together to form a comprehensive protection solution, from the outside in and from hardware to software.

[0165] Figure 5 This is a schematic diagram of the overall structure of a non-contact voltage sensor system provided in an embodiment of this application. This non-contact voltage sensor system can be a high-energy particle interference suppression system. As shown in the figure, the electrode substrate is made of high-purity alumina ceramic, a highly stable dielectric material with high radiation resistance, effectively reducing the degradation of the dielectric properties caused by radiation. The connection from the electrode to the preamplifier uses a double-shielded cable; the inner layer is a differential signal line, and the outer layer is a drive shielding layer, driven by the operational amplifier output to cancel parasitic capacitance. The outermost metal shielding mesh needs to be properly grounded at multiple points.

[0166] like Figure 5 As shown, the protected area is the cavity shield for the signal processing circuit. A U-shaped shield made of aluminum (such as Al 6061) is used to enclose the entire PCB board, with the opening facing the mounting direction of the sensing electrodes. A dense aluminum oxide film is generated on the inner wall of the aluminum shield through anodizing, followed by a tantalum (Ta) or tungsten (W) coating approximately 100 μm thick using plasma spraying. This layer is mainly used to absorb high-energy particles and block the transient γ / X-rays they generate.

[0167] The second layer is the system detection layer. Figure 6 This is a schematic flowchart illustrating a method for suppressing interference in a non-contact voltage sensor, as provided in an embodiment of this application. Figure 6As shown, the specific system flow can be the integration of a particle detection subsystem. A simple radiation monitoring unit is integrated on the PCB to quantify the high-energy particle fluence at the current location in real time.

[0168] Alternatively, a silicon PIN photodiode can be used. When reverse-biased, its depletion layer serves as the particle-sensitive region. High-energy particles passing through it generate electron-hole pairs, forming current pulses. The diode should be mounted in a blank area of ​​the PCB, as close as possible to the front-end analog circuitry while avoiding excessively long leads, and away from the thick metal area of ​​the shielding to ensure effective particle reception.

[0169] Design a charge-sensitive preamplifier (CSA) consisting of an operational amplifier, a feedback capacitor, and a reset resistor. The CSA output is connected to a CR-(RC) converter. 4 The shaping circuit shapes the current pulse into a quasi-Gaussian pulse with an amplitude proportional to the particle energy. The shaped pulse is then fed into a voltage comparator and compared with an adjustable threshold voltage (set by the MCU's DAC for noise suppression), outputting a standard TTL (Transistor-Transistor Logic) counting pulse. This counting pulse can be fed into the input capture channel of a high-speed timer / counter (such as STM32's TIMx) on the MCU. Simultaneously, this pulse signal is also connected to an external interrupt pin (EXTI) on the MCU. A count rate threshold can be set in the MCU software. When the instantaneous count rate measured by the timer exceeds this threshold, the EXTI pin immediately generates a hardware interrupt, triggering a protection procedure.

[0170] Figure 7 This is a schematic diagram of the working process of a particle detection circuit provided in an embodiment of this application, as shown below. Figure 7 As shown, the real-time data from the particle detection circuit can be used to dynamically adjust the system's operating state via MCU software, and to execute a controlled recovery sequence during severe interference. Specifically, this can include:

[0171] The MCU can jump to the interrupt service routine (ISR) and control the switch via GPIO to cut off the sensor input.

[0172] The MCU can achieve fast self-calibration, which can specifically include: enabling the ADC to perform 32 rapid continuous samplings of the reference voltage.

[0173] The MCU implements the filtering calculation, which may specifically include: performing a moving average on the sampled values, then inputting the sampled values ​​into a simplified Kalman filter to estimate the current system deviation V. drift .

[0174] The MCU can update the state, specifically by: changing the V... driftThe value is stored in a global variable shared by all measurement functions, which enables the independent watchdog timer inside the MCU (or an external discrete watchdog chip). If the MCU program crashes due to strong interference and fails to feed the watchdog, the WDT (Watchdog Timer) will force a hardware reset after the timeout, causing the entire system to restart.

[0175] The third part is the signal processing layer, which includes:

[0176] Initialization and parameter settings: After the system powers on, relevant variables can be initialized in the MCU software. For example, setting the calibration period: `const int T1=10`; initializing the global drift variable: `float V`. drift =0.0.

[0177] Initialize the adaptive Kalman filter parameters: Set the process noise covariance Q, measurement noise covariance R, and initial estimation error covariance P. According to the principle of the adaptive Kalman filter, the filter will converge quickly within a few iterations and automatically reduce it to a reasonable value.

[0178] Triggering the calibration sequence: After the system starts running, a high-precision hardware timer or the real-time clock (RTC) inside the MCU will keep track of time. Whenever the time interval T1 is reached, the timer will generate an interrupt to trigger the calibration sequence.

[0179] Hardware switching and sampling: The MCU's GPIO pin outputs a control level to drive an analog switch, switching the differential input of the front-end amplifier from one channel (CH1) to another channel (CH2). CH1 is the signal path for measurement, and CH2 is connected to an internal precision short-circuit reference point (i.e., a ground resistor or a known precision bias voltage).

[0180] After the switching is complete, the MCU can wait for a short settling time (e.g., 100μs) to allow the amplifier and ADC signals to stabilize. The MCU then controls the ADC to sample the output value at this time N times (e.g., N=256), obtaining a raw sampled dataset S. raw[i] , where i = 0, 1, 2, ..., N-1.

[0181] The following expression can be obtained through moving average filtering:

[0182] (1);

[0183] in, This represents the average output voltage obtained after the moving average filter. It can be the target result of this calculation, representing the initial stable estimate after removing random noise. N represents the total number of sampling points participating in the averaging, i.e., the size of the moving window. The value of N determines the trade-off between the smoothness of the filter and real-time performance. This represents the i-th original sample value, where the index i is an integer ranging from 0 to N. 1 represents a set of discrete voltage data points collected in chronological order. This represents the summation operation, for values ​​from i=0 to i=N. All of 1 Accumulate.

[0184] Add the N consecutively collected raw sample values ​​together, then divide by N to obtain the arithmetic mean of these N data points. This operation effectively suppresses high-frequency random noise (such as white noise), providing a reliable initial observation for subsequent accurate estimation algorithms such as Kalman filtering.

[0185] This step is mainly used to suppress random white noise and obtain a preliminary stable estimate. Z, the measured value of the Kalman filter in this study k The standard recursive equation for Kalman filtering is executed. The optimal estimate X obtained in each calculation is then used. k Assigned to a global variable .

[0186] Resume measurement and real-time compensation: The MCU controls the analog switch to switch back to CH1 (connecting the sensing electrode).

[0187] The system resumed normal voltage measurement mode, and thereafter, each normal voltage sample value... The following expression (2) can be executed immediately before output:

[0188] (2);

[0189] This is the final accurate measurement value after drift compensation, which is sent to the host computer or used for subsequent control.

[0190] The next step can be bit-flip error correction, a mechanism designed to prevent transient outliers and data transmission errors caused by single-event upsets (SEUs). Currently, many high-precision ADCs automatically append a CRC checksum to the data frame when transmitting data via the SPI interface. After receiving a complete data frame, the MCU recalculates the checksum for the received data bits using the same CRC algorithm. The calculated CRC is then compared with the CRC sent by the ADC. If the CRC check passes, the data transmission is considered error-free, and the data is stored in a buffer. If the CRC check fails, it means a bit flip may have occurred during SPI transmission.

[0191] The MCU immediately logs an error (e.g., "SEU Error detected") and re-initiates a complete ADC read operation, replacing the erroneous data with the new, correct data. The error log can be used for system health monitoring and predictive maintenance.

[0192] In practical applications, this application provides a comprehensive solution to the measurement interference problem of non-contact voltage sensors in high-energy particle environments. By combining a three-layer collaborative protection mechanism—physical protection through partitioned shielding, intelligent scheduling based on real-time monitoring, and precise compensation through adaptive Kalman filtering—a leap from passive defense to active sensing and intelligent suppression is achieved. This application effectively overcomes the limitations of traditional methods that cannot simultaneously address measurement and protection, or cope with unknown radiation environments, significantly improving the measurement accuracy, reliability, and long-term stability of sensors in special scenarios, and possesses broad application value.

[0193] In some exemplary embodiments, this application provides a comprehensive multi-level protection system that significantly enhances anti-interference capabilities. Through a double-layer shielding structure, effective physical protection is provided for subsequent precision signal processing circuits without affecting the electric field induction in the probe area. By selecting high-precision anti-interference front-end components, the fault tolerance of the core circuit to ionizing radiation and single-event effects is improved, ensuring the stability of basic signal conditioning in harsh environments. Intelligent compensation for transient interference and cumulative drift is achieved, ensuring long-term accuracy. Real-time perception and early warning of the radiation environment are realized through the particle detection subsystem, providing a basis for intelligent decision-making by the system. Furthermore, through a self-calibration / drift compensation algorithm, utilizing an internal reference and Kalman filtering, slow drift caused by the TID effect can be estimated and subtracted online and in real-time, minimizing the accuracy degradation caused by radiation. Redundant sampling and bit-flip error correction effectively suppress transient outliers and data errors caused by SEU, ensuring the validity and reliability of each output data. The system's adaptability and robustness are enhanced, ensuring high reliability. Through adaptive power consumption scheduling, the system can dynamically adjust its operating strategy based on radiation intensity, reducing the risk of failure and optimizing energy consumption. A controlled and robust recovery process is constructed through a software-hardware collaborative anomaly recovery sequence. Combined with a hardware watchdog, this ensures that the system can automatically recover from severe particle interference events, greatly improving the system's self-healing ability and task continuity, and avoiding issues such as system crashes or the need for manual restarts.

[0194] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0195] The interference suppression device for a non-contact voltage sensor provided in the embodiments of this application will be described below. The interference suppression device for a non-contact voltage sensor has the same inventive concept as the interference suppression method for a non-contact voltage sensor described above. The solution to the problem provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the interference suppression device for a non-contact voltage sensor provided below can be found in the limitations of the interference suppression method for a non-contact voltage sensor described above. The interference suppression device for a non-contact voltage sensor described below and the interference suppression method for a non-contact voltage sensor described above can be referred to each other, and will not be repeated here.

[0196] In one exemplary embodiment, Figure 8 This is a schematic diagram of the structure of an interference suppression device for a non-contact voltage sensor provided in an embodiment of this application, as shown below. Figure 8 As shown, the interference suppression device 80 of the non-contact voltage sensor includes: a monitoring module 810, a first anti-interference module 820, a deviation determination module 830, and an offset correction module 840, wherein:

[0197] The monitoring module 810 is used to monitor the high-energy particle radiation in the environment where the voltage sensor is located, and to obtain the radiation intensity information of the high-energy particles.

[0198] The first anti-interference module 820, if the radiation intensity information of high-energy particles meets the first anti-interference condition, cuts off the signal input path of the voltage sensor and acquires the first output signal of the sensor's internal reference source; wherein, the first anti-interference condition includes the occurrence of a transient high-energy particle interference event.

[0199] The deviation determination module 830 is used to determine the instantaneous interference deviation of the current signal processing channel based on the first output signal.

[0200] The offset correction module 840 is used to perform offset correction based on the instantaneous interference deviation if the voltage sensor resumes normal measurement.

[0201] In an exemplary embodiment, the device further includes a first anti-interference module; the first anti-interference module is configured to switch the signal input path of the voltage sensor to an internal reference source and acquire the second output signal of the internal reference source if the voltage sensor meets the second anti-interference condition; determine the cumulative interference deviation of the current signal processing channel based on the second output signal; and perform offset correction based on the cumulative interference deviation if the voltage sensor resumes normal measurement.

[0202] In one exemplary embodiment, the first anti-interference module 820 is used to perform a hardware reset of the controller in the event of an abnormal operation of the controller of the voltage sensor.

[0203] In an exemplary embodiment, the deviation determination module 830 is used to sample the current output signal; and calculate the current interference deviation based on the current output signal using an adaptive filtering algorithm; wherein, when the current interference deviation is an instantaneous interference deviation, the current output signal is a first output signal; and when the current interference deviation is a cumulative interference deviation, the current output signal is a second output signal.

[0204] In one exemplary embodiment, the adaptive filtering algorithm includes the Kalman filtering algorithm.

[0205] In an exemplary embodiment, the offset correction module 840 is used to determine the normal measurement signal after normal measurement is restored; and to determine the target measurement signal based on the degree of difference between the normal measurement signal and the current interference deviation; wherein, when the first anti-interference condition is met, the current interference deviation is the instantaneous interference deviation, and when the second anti-interference condition is met, the current interference deviation is the cumulative interference deviation; and to perform measurement control of the voltage sensor based on the target measurement signal.

[0206] In an exemplary embodiment, the offset correction module 840 is used to perform data verification on the target measurement signal; if the target measurement signal data verification fails, the current output signal is re-acquired until the data verification passes.

[0207] In one exemplary embodiment, the radiation intensity information includes the pulse count rate of high-energy particles; the first anti-interference condition includes a pulse count rate greater than or equal to a preset count rate threshold.

[0208] In one exemplary embodiment, the second anti-interference condition includes: reaching a preset periodic calibration time; and / or, based on radiation intensity information, the calculated cumulative flux of high-energy particles exceeds a second preset threshold.

[0209] Each module in the interference suppression device of the aforementioned non-contact voltage sensor can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the controller in hardware form or independent of it, or stored in the memory of the controller in software form, so that the processor can call and execute the corresponding operations of each module.

[0210] In one exemplary embodiment, this application also provides a controller, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the interference suppression method for any of the non-contact voltage sensors described in the above embodiments.

[0211] In one exemplary embodiment, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the interference suppression method for any of the non-contact voltage sensors described above.

[0212] In one exemplary embodiment, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the interference suppression method for any of the non-contact voltage sensors described in the above embodiments.

[0213] Indicatively, such as Figure 9 As shown, Figure 9 This is a schematic diagram of the internal structure of a controller 900 provided in an embodiment of this application. The controller 900 can be provided as a server. (Refer to...) Figure 9 The controller 900 includes a processor 902, which further includes one or more processors, and memory resources represented by memory 901 for storing instructions executable by the processor 902, such as a computer program. The computer program stored in memory 901 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processor 902 is configured to execute instructions to perform the interference suppression method for the non-contact voltage sensor of any of the above embodiments. The controller 900 may operate on an operating system stored in memory 901, such as Windows Server™, Mac OS X™, Unix™, Linux™, Free BSD™, or similar.

[0214] The controller 900 may also include a power supply component 903 configured to perform power management of the controller 900, a wired or wireless network interface 904 configured to connect the controller 900 to a network, and an input / output (I / O) interface 905. Wireless operation can be achieved via Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by a processor, the computer program implements an interference suppression method for a contactless voltage sensor.

[0215] Those skilled in the art will understand that Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the controller to which the present application is applied. A specific controller may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0216] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0217] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0218] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0219] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for suppressing interference in a non-contact voltage sensor, characterized in that, The method includes: The high-energy particle radiation in the environment where the voltage sensor is located is monitored to obtain the radiation intensity information of the high-energy particles; If the radiation intensity information of the high-energy particles satisfies the first anti-interference condition, the signal input path of the voltage sensor is cut off, and the input is switched to the internal reference source of the sensor to collect the first output signal of the internal reference source of the sensor; wherein, the first anti-interference condition includes the occurrence of a transient high-energy particle interference event; Based on the first output signal, determine the instantaneous interference deviation of the current signal processing channel; If the voltage sensor resumes normal measurement, offset correction is performed based on the instantaneous interference deviation. The method further includes: If the voltage sensor meets the second anti-interference condition, the signal input path of the voltage sensor is switched to the internal reference source, and the second output signal of the internal reference source is acquired. The second anti-interference condition includes the conditions of periodic triggering or event triggering calibration and drift compensation mechanism. Based on the second output signal, determine the cumulative interference deviation of the current signal processing channel; If the voltage sensor resumes normal measurement, offset correction is performed based on the accumulated interference deviation. The second anti-interference condition includes: Reaching the preset periodic calibration time; and / or, Based on the radiation intensity information, the calculated cumulative flux of high-energy particles exceeds a second preset threshold.

2. The method according to claim 1, characterized in that, If the radiation intensity information characterization of the high-energy particles satisfies the first anti-interference condition, the method further includes: In the event of an abnormal operation of the controller of the voltage sensor, a hardware reset of the controller shall be performed.

3. The method according to claim 1, characterized in that, Determine the current interference deviation of the current signal processing channel, including: Sample the current output signal; The current interference deviation is calculated based on the current output signal using an adaptive filtering algorithm. Wherein, when the current interference deviation is an instantaneous interference deviation, the current output signal is a first output signal; when the current interference deviation is a cumulative interference deviation, the current output signal is a second output signal.

4. The method according to claim 3, characterized in that, The adaptive filtering algorithm includes the Kalman filtering algorithm.

5. The method according to claim 1, characterized in that, Offset correction is performed based on the current interference deviation, including: Determine the normal measurement signal after resuming normal measurement; The target measurement signal is determined based on the degree of difference between the normal measurement signal and the current interference deviation; wherein, when the first anti-interference condition is met, the current interference deviation is the instantaneous interference deviation, and when the second anti-interference condition is met, the current interference deviation is the cumulative interference deviation. Based on the target measurement signal, the voltage sensor is controlled for measurement.

6. The method according to claim 5, characterized in that, The measurement control of the voltage sensor based on the target measurement signal further includes: Perform data verification on the target measurement signal; If the target measurement signal data verification fails, the current output signal will be re-acquired until the data verification passes.

7. The method according to claim 1, characterized in that, The radiation intensity information includes the pulse count rate of high-energy particles; the first anti-interference condition includes the pulse count rate being greater than or equal to a preset count rate threshold.

8. A non-contact voltage sensor system, characterized in that, The system for implementing the method as described in any one of claims 1-7 comprises: A voltage sensing unit is used for non-contact sensing of the voltage being measured and generating a sensing signal. A particle monitoring unit is used to monitor high-energy particle radiation in the environment and generate the radiation intensity information. The processing control unit, connected to the voltage sensing unit and the particle monitoring unit respectively, is configured to perform the steps of the method according to any one of claims 1-7.

9. The system according to claim 8, characterized in that, The particle monitoring unit includes: Particle detectors are used to respond to high-energy particles and output corresponding electrical signals. The signal processing circuit is connected to the particle detector and the processing control unit, respectively, and is used to condition and shape the electrical signal and generate the radiation intensity information.

10. The system according to claim 9, characterized in that, The processing control unit includes: microcontroller; A watchdog timer circuit is connected to the microcontroller and triggers a system hardware reset of the microcontroller when the watchdog timer times out and is not refreshed.

11. An interference suppression device for a non-contact voltage sensor, characterized in that, The device includes: The monitoring module is used to monitor the high-energy particle radiation in the environment where the voltage sensor is located, and to obtain the radiation intensity information of the high-energy particles; If the radiation intensity information of the high-energy particles satisfies the first anti-interference condition, the first anti-interference module cuts off the signal input path of the voltage sensor and switches the input to the internal reference source of the sensor to collect the first output signal of the internal reference source of the sensor; wherein, the first anti-interference condition includes the occurrence of a transient high-energy particle interference event; The deviation determination module is used to determine the instantaneous interference deviation of the current signal processing channel based on the first output signal; An offset correction module is used to perform offset correction based on the instantaneous interference deviation if the voltage sensor resumes normal measurement. The first anti-interference module is also used to switch the signal input path of the voltage sensor to the internal reference source if the voltage sensor meets the second anti-interference condition, and to acquire the second output signal of the internal reference source; based on the second output signal, determine the cumulative interference deviation of the current signal processing channel; if the voltage sensor resumes normal measurement, perform offset correction according to the cumulative interference deviation. The second anti-interference condition includes: Reaching the preset periodic calibration time; and / or, Based on the radiation intensity information, the calculated cumulative flux of high-energy particles exceeds a second preset threshold.

12. A controller comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

Images