Transient signal sensing method and device based on multi-physics field coupling

Abstract

The invention provides a multi-physics field coupled transient signal sensing method and device, and the method comprises the steps: carrying out the measurement of an electric signal of a target multi-physics field through a plurality of preset sensors, and carrying out the amplification and digital processing of the electric signal obtained from the target multi-physics field, and obtaining an output signal; performing signal amplitude detection on the output signal, calculating current bias according to the deviation between the amplitude of the output signal and a target amplitude, and adjusting a bias magnetic field according to the current bias; performing time relative synchronization on the sensors to obtain time alignment data; and analyzing the characteristics of the output signal in real time, and carrying out global fault positioning, fault type judgment or transient process tracking on time data and the characteristics of the output signal through a preset analysis program. According to the invention, high-frequency transient signals can be captured; and high-precision monitoring, feature extraction and real-time analysis of transient signals on the low-voltage power distribution side are realized without depending on a synchronous calibration method of a high-precision time service module and relative time.

Description

Technical Field

[0001] The present invention relates to the field of transient signal sensing technology, and in particular to a multi-physical field coupled transient signal sensing method and device. Background Art

[0002] A distributed low-frequency magneto-electro-mechanical antenna transceiver system and design, for example, includes a signal amplifier, a power amplifier, a 1:N magneto-electro-electric power divider, and N communication channels arranged as distributed nodes. The 1:N magneto-electro-electric power divider is composed of a magneto-electro-composite material and a coil tightly wound around the outer surface of the magneto-electro-composite material. The two ends of the coil are connected to serve as power input ports. The magneto-electro-composite material is a symmetrical structure consisting of a piezoelectric layer and two magnetostrictive layers bonded to either side of the piezoelectric layer. The piezoelectric layer is cut into N sections along its length, each of which provides N independent power output ports. The N communication channels are composed of N magneto-electro-mechanical antennas and N correspondingly placed coils. The power output port of each 1:N magneto-electro-electric power divider is connected to the piezoelectric layer lead of each magneto-electro-mechanical antenna to provide a radiation excitation source. However, the sampling is fixed-frequency, resulting in a surge in data volume when sampling high-frequency signals, while details are easily lost when sampling low-frequency signals, resulting in high storage and transmission costs. The system does not rely on high-precision relative time synchronization with GPS and distributed collaborative analysis between devices. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and device for sensing transient signals coupled by multiple physical fields, so as to solve the technical problem of how to improve the sensing accuracy of transient signals coupled by multiple physical fields.

[0004] In one aspect, a method for sensing transient signals coupled with multiple physical fields is provided, comprising:

[0005] The electrical signals of the target multi-physical field are measured by a plurality of preset sensors, and the electrical signals obtained from the target multi-physical field are amplified and digitized to obtain output signals;

[0006] Performing signal amplitude detection on the output signal, calculating the current bias according to the deviation between the output signal amplitude and the target amplitude, and adjusting the bias magnetic field according to the current bias;

[0007] The sensors are synchronized relatively in time to obtain time-aligned data; the characteristics of the output signal are analyzed in real time, and the characteristics of the data and output signal are analyzed by a preset analysis program to perform global fault location, fault type identification or transient process tracking.

[0008] Preferably, the sensor includes at least an upper piezoelectric material layer, a magnetoelectric material layer and a lower piezoelectric material layer stacked in sequence, wherein the thickness ratio of the upper piezoelectric material layer, the magnetoelectric material layer and the lower piezoelectric material layer is set according to a preset ratio; the upper piezoelectric material layer is set to have a polarization direction perpendicular to the plane, so as to sense the stress field generated by voltage changes; the magnetoelectric material layer is magnetized along the length direction, so as to respond to changes in the magnetic field and generate magnetostrictive deformation; the lower piezoelectric material layer is set to have a polarization direction opposite to that of the upper piezoelectric material layer, so as to enhance the output charge signal.

[0009] Preferably, the amplifying and digitally processing the electrical signal obtained from the target multi-physical field includes amplifying and digitally processing the electrical signal through a preset signal converter.

[0010] Preferably, the signal converter sets the input impedance to be greater than a preset impedance threshold, sets the bandwidth to be a rated bandwidth, and sets the adjustable gain value to be a fixed gain range.

[0011] Preferably, adjusting the bias magnetic field according to the current bias includes:

[0012] Set the normal mode to the default operating state and set the sampling rate to the first fixed value;

[0013] determining whether a transient event exists according to the current bias value, and triggering entry into a low power consumption mode when there is no transient event within a preset time period, and setting the sampling rate to a second fixed value;

[0014] When the gradient threshold of the current bias value is greater than a preset judgment value, the high-precision mode is triggered and the sampling rate is set to a third fixed value.

[0015] Preferably, the relative time synchronization of the sensors includes:

[0016] The system connects to the sensors via Bluetooth and exchanges local time information with each other. The time difference and clock drift parameters are determined based on the exchanged local time information. The time synchronization of all sensors is uniformly adjusted based on the time difference and clock drift parameters to obtain time alignment data.

[0017] On the other hand, a multi-physical field coupled transient signal sensing device is provided, which is used to implement the multi-physical field coupled transient signal sensing method, comprising:

[0018] a sensing unit configured to measure electrical signals of a target multi-physical field using a plurality of preset sensors, amplify and digitize the electrical signals obtained from the target multi-physical field, and obtain an output signal; perform signal amplitude detection on the output signal, calculate a current bias based on a deviation between the output signal amplitude and a target amplitude, and adjust a bias magnetic field based on the current bias;

[0019] The control unit is used to synchronize the sensors relatively in time to obtain time-aligned data; analyze the characteristics of the output signal in real time, and perform global fault location, fault type identification or transient process tracking on the characteristics of its data and output signal through a preset analysis program.

[0020] In summary, the implementation of the embodiments of the present invention has the following beneficial effects:

[0021] The multi-physics field coupled transient signal sensing method and device provided by the present invention can capture high-frequency transient signals (such as nanosecond pulses), are less affected by electromagnetic interference and environmental noise, and extract waveform features more accurately; implement a dynamic sampling rate adjustment strategy; and use a relative time synchronization calibration method that does not rely on a high-precision timing module to calculate the trigger position of the transient waveform on the low-voltage side. This enables high-precision monitoring, feature extraction, and real-time analysis of transient signals on the low-voltage distribution side. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, without paying any creative work, other drawings obtained based on these drawings still fall within the scope of the present invention.

[0023] Figure 1 Schematic diagram of a transient signal sensing method for multi-physical field coupling in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be described in further detail below with reference to the accompanying drawings.

[0025] like Figure 1 FIG. 1 is a schematic diagram of an embodiment of a multi-physics field coupled transient signal sensing method provided by the present invention. In this embodiment, the method includes the following steps:

[0026] Step S1, measuring the electrical signal of the target multi-physical field through a plurality of preset sensors, and amplifying and digitizing the electrical signal obtained from the target multi-physical field to obtain an output signal; the sensor includes at least an upper piezoelectric material layer, a magnetoelectric material layer and a lower piezoelectric material layer stacked in sequence, wherein the thickness ratio of the upper piezoelectric material layer, the magnetoelectric material layer and the lower piezoelectric material layer is set according to a preset ratio; the upper piezoelectric material layer is set with a polarization direction perpendicular to the plane for sensing the stress field generated by voltage changes; the magnetoelectric material layer is set to be magnetized along the length direction for responding to magnetic field changes and generating magnetostrictive deformation; the lower piezoelectric material layer is set with a polarization direction opposite to that of the upper piezoelectric material layer for enhancing the output charge signal. The amplifying and digitizing the electrical signal obtained from the target multi-physical field includes amplifying and digitizing the electrical signal through a preset signal converter. The signal converter is set to have an input impedance greater than a preset impedance threshold, a bandwidth set to a rated bandwidth, and an adjustable gain value set to a fixed gain range.

[0027] Step S2, performing signal amplitude detection on the output signal, calculating the current bias based on the deviation between the output signal amplitude and the target amplitude, and adjusting the bias magnetic field based on the current bias; adjusting the bias magnetic field based on the current bias includes setting the normal mode to the default operating state and setting the sampling rate to a first fixed value; determining whether there is a transient event based on the current bias value, and when there is no transient event within a preset time period, triggering entry into a low power consumption mode, and setting the sampling rate to a second fixed value; when the gradient threshold of the current bias value is greater than a preset judgment value, triggering entry into a high-precision mode, and setting the sampling rate to a third fixed value.

[0028] Step S3: Perform relative time synchronization on the sensors to obtain time-aligned data; analyze the characteristics of the output signals in real time, and use a preset analysis program to perform global fault location, fault type identification, or transient process tracking on the data and output signal characteristics. Performing relative time synchronization on the sensors includes connecting with the sensors via Bluetooth, exchanging local time information, determining a time difference and clock drift parameters based on the exchanged local time information, and uniformly adjusting the time synchronization of all sensors based on the time difference and clock drift parameters to obtain time-aligned data.

[0029] A process logic of one embodiment of the present invention includes the following steps:

[0030] The sensor end uses a composite structure of piezoelectric materials (such as PZT) and magnetoelectric materials (such as Terfenol-D). Through the coupling effects of electric, magnetic, and stress fields, it achieves a wide bandwidth (0.1Hz-10MHz) and high sensitivity (μV-level signal detection). The composite structure is a stacked multi-physics field coupling structure, specifically a "PZT layer-Terfenol-D layer-PZT layer" sandwich structure. This structure achieves electric field-magnetic field-stress field coupling through mechanical stress transfer. The upper layer PZT: The polarization direction is perpendicular to the plane and is used to sense the stress field generated by voltage changes; the middle Terfenol-D: It is mainly responsible for the magnetostrictive effect, magnetized along the length direction, responding to changes in the magnetic field and producing magnetostrictive deformation; the lower layer PZT: The polarization direction is opposite to that of the upper layer, enhancing the output charge signal. In order to match the application scenario of transient abnormal waveform monitoring on the low-voltage side, the PZT layer thickness is 0.5mm (piezoelectric constant d33 ≥ 500pC / N), the Terfenol-D layer thickness is 1mm (magnetostriction coefficient λ ≥ 1500ppm), and the lateral dimensions are consistent (such as 10mm×10mm) to avoid uneven stress distribution.

[0031] Based on the design of the above materials, a wide-band, highly sensitive sensor can be obtained. The low-frequency band (0.1Hz to kHz) mainly relies on the magnetostrictive effect of Terfenol-D. When low-frequency magnetic field changes (such as industrial frequency 50 / 60Hz and its low-frequency harmonics, or geomagnetic field interference) or slower mechanical stress changes occur in the external environment, Terfenol-D will deform, and then transfer it to the PZT layer through the composite layer, and the PZT layer will generate a charge signal. The medium- and high-frequency bands (kHz to 10MHz) mainly rely on the piezoelectric effect of PZT. When there are medium- and high-frequency vibrations, shocks, or electric field coupling in the external environment, the PZT layer can directly generate a charge signal. At the same time, the high-frequency magnetostrictive effect of Terfenol-D will also contribute to a part of the response, further widening the overall frequency band.

[0032] In practical applications, by adjusting the thickness ratio of PZT and Terfenol-D, the prestress state, and the electrode layout, the resonant frequencies of the different materials can be partially overlapped or compensated, resulting in impedance matching and broadening of the resonant peak, achieving excellent sensitivity in the 0.1 Hz to 10 MHz range. Furthermore, the magnetostrictive coefficient of Terfenol-D multiplied by the piezoelectric coefficient of PZT produces a "magnetic-mechanical-electrical" multi-amplification effect. When a small external magnetic field change or mechanical stress occurs, the signal is further amplified and converted into a measurable potential difference through stress transfer and charge conversion between the material layers. This coupling effect can elevate weak signals, which are difficult to detect in a single material, to the μV level or even higher, enabling the sensor to achieve high sensitivity for extremely low energy or very small vibrations. Finally, a coordinated magnetic and electric field detection approach is employed, simultaneously collecting the PZT voltage output (reflecting electric field / stress changes) and the induced current of the Terfenol-D coil (reflecting magnetic field changes). Weighted fusion algorithms (such as PCA) are then used to extract the combined transient characteristics.

[0033] The sensor integrates a low-noise amplifier and analog-to-digital converter (ADC) to amplify and digitize the weak electrical signals received from the multi-physics coupling unit. A low-noise charge amplifier (input impedance >1 GΩ, DC-20 MHz bandwidth) with adjustable gain (1-1000 mV / pC) is designed for the PZT output. The Terfenol-D coil signal is amplified by an instrumentation amplifier before signal conditioning. A filter (1 kHz-10 MHz) is used to remove DC drift. Preliminary filtering and feature extraction are performed in real time within the embedded processor to improve the system's response to transient signals.

[0034] Furthermore, based on the above sensor settings, since the magnetoelectric conversion efficiency of Terfenol-D is nonlinearly related to the bias magnetic field strength, the operating point can be kept in the sensitivity peak area by adjusting the coil bias current in real time. The PZT output signal is subjected to signal amplitude detection, and the signal amplitude can be extracted using the envelope detection method. The PID control method is used to calculate the current bias based on the deviation between the output signal amplitude and the target amplitude, and finally an adjustable current of 0-100mA is output through the H-bridge circuit to quickly and dynamically adjust the bias magnetic field. The PID control formula is as follows:

[0035]

[0036] e(k)=A target -A PZT (k)

[0037] Embedded software is then used to analyze the characteristics of the sensor output signal (such as amplitude, frequency, and transient event probability) in real time, and a multi-mode sampling method is adopted to dynamically adjust the sampling rate to balance data accuracy and system resource consumption.

[0038] Example: In low power mode, a sampling rate of 1Khz is used. When there is no transient event for 20 consecutive seconds, the low power mode is triggered. In normal mode, a sampling rate of 100Khz is used, which is the default operating state. In high precision mode, a dynamic sampling rate of 1M-10MKhz is used, and the gradient threshold is set in the software. when When n is set according to the actual application scenario, or when the spectrum entropy suddenly increases, this mode is triggered and the sampling rate is dynamically adjusted according to the set threshold range.

[0039] In this way, under steady-state signals, low-power mode can reduce storage requirements by 90% and power consumption by more than 60%. High-precision mode is only activated when necessary, avoiding hardware heating and life loss caused by continuous high-speed sampling.

[0040] Furthermore, during data processing, the sensors are wirelessly synchronized via Bluetooth BLE to ensure that transient data collected by different nodes have a unified time base and reduce time errors. The establishment of time synchronization requires the following steps:

[0041] Connection phase: The devices that need time synchronization need to establish a Bluetooth connection, for example, the following connection network.

[0042] Calibration phase: Different devices have their own independent counters. Therefore, after establishing a connection, the Bluetooth master and slave should exchange local time information with each other (depending on the application scenario, this can be a one-way information transfer from master to slave or slave to master). Based on the other party's time information and the local time, parameters such as the time difference and clock drift between the Bluetooth master and slave can be derived.

[0043] Synchronization phase: After calibration, based on the application scenario, the master device will notify the Bluetooth slave device of the local time TA. The Bluetooth slave device can calculate the local time (TA_1, TA_2, ... TA_X) corresponding to the time TA based on the known time difference and clock drift. This (TA, TA_1, TA_2, ... TA_X) time is the final desired synchronization time, meaning that all devices can synchronize and perform a certain action at this specified time.

[0044] This method achieves data synchronization without requiring high-precision clock modules on each sensor node, such as GPS, Beidou, or IEEE 1588 (PTP). After achieving relative time synchronization, distributed collaborative analysis of transient data is possible. Sensor nodes upload processed key features or waveform data to edge computing nodes or the cloud. Higher-level analysis systems can use time-aligned data from different monitoring points to perform global fault location, fault type identification, and transient process tracking. On the edge side, real-time correlation analysis of monitoring data from multiple adjacent nodes can be performed to provide timely feedback on fault alerts or initiate protective actions.

[0045] Through the above process, the present invention can solve the following problems: Insufficient sensor performance: Conventional voltage / current sensors have limited bandwidth, making it difficult to capture high-frequency transient signals (such as nanosecond pulses), and their sensitivity is significantly affected by electromagnetic interference. Complex environmental noise affects waveform feature extraction, which is inaccurate. Existing sampling algorithms are mostly fixed-frequency modes, which leads to a surge in data volume when sampling high-frequency signals, while details are easily lost when sampling low-frequency signals, resulting in high storage and transmission costs. In complex electromagnetic environments, traditional filtering algorithms have difficulty distinguishing between noise and true transient features, resulting in an increased false alarm rate. Distributed monitoring nodes lack time synchronization and data association mechanisms, making it impossible to locate the location of transient events.

[0046] An embodiment of the present invention further provides a multi-physical field coupled transient signal sensing device, comprising:

[0047] a sensing unit configured to measure electrical signals of a target multi-physical field using a plurality of preset sensors, amplify and digitize the electrical signals obtained from the target multi-physical field, and obtain an output signal; perform signal amplitude detection on the output signal, calculate a current bias based on a deviation between the output signal amplitude and a target amplitude, and adjust a bias magnetic field based on the current bias;

[0048] The control unit is used to synchronize the sensors relatively in time to obtain time-aligned data; analyze the characteristics of the output signal in real time, and perform global fault location, fault type identification or transient process tracking on the characteristics of its data and output signal through a preset analysis program.

[0049] It should be noted that the device described in the above embodiment corresponds to the method described in the above embodiment. Therefore, the parts of the device described in the above embodiment that are not described in detail can be obtained by referring to the contents of the method described in the above embodiment, and will not be repeated here.

[0050] In summary, the implementation of the embodiments of the present invention has the following beneficial effects:

[0051] The multi-physical field coupled transient signal sensing method provided by the present invention can capture high-frequency transient signals (such as nanosecond pulses), is less affected by electromagnetic interference and environmental noise, and extracts waveform features more accurately; implements a dynamic sampling rate adjustment strategy; does not rely on a high-precision timing module, a relative time synchronization calibration method is used to calculate the trigger position of the low-voltage side transient waveform; and realizes high-precision monitoring, feature extraction and real-time analysis of transient signals on the low-voltage distribution side.

[0052] The above disclosure is merely a preferred embodiment of the present invention and certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A transient signal sensing method for multi-physical field coupling, characterized in that: include: The electrical signals of the target multi-physical field are measured by a plurality of preset sensors, and the electrical signals obtained from the target multi-physical field are amplified and digitized to obtain output signals; Performing signal amplitude detection on the output signal, calculating the current bias according to the deviation between the output signal amplitude and the target amplitude, and adjusting the bias magnetic field according to the current bias; Perform relative time synchronization on sensors to obtain time-aligned data; Analyze the characteristics of the output signal in real time, and use the preset analysis program to perform global fault location, fault type identification or transient process tracking on its data and output signal characteristics over time.

2. The method according to claim 1, wherein The sensor includes at least an upper piezoelectric material layer, a magnetoelectric material layer and a lower piezoelectric material layer stacked in sequence, wherein the thickness ratio of the upper piezoelectric material layer, the magnetoelectric material layer and the lower piezoelectric material layer is set according to a preset ratio; the upper piezoelectric material layer is set with a polarization direction perpendicular to the plane, so as to sense the stress field generated by voltage changes; the magnetoelectric material layer is magnetized along the length direction, so as to respond to changes in the magnetic field and generate magnetostrictive deformation; the lower piezoelectric material layer is set with a polarization direction opposite to that of the upper piezoelectric material layer, so as to enhance the output charge signal.

3. The method according to claim 2, wherein The amplifying and digitally processing the electrical signal obtained from the target multi-physical field includes amplifying and digitally processing the electrical signal through a preset signal converter.

4. The method according to claim 3, wherein The signal converter sets the input impedance to be greater than a preset impedance threshold, sets the bandwidth to be a rated bandwidth, and sets the adjustable gain value to be a fixed gain range.

5. The method according to claim 4, wherein The adjusting of the bias magnetic field according to the current bias comprises: Set the normal mode to the default operating state and set the sampling rate to the first fixed value; determining whether a transient event exists according to the current bias value, and triggering entry into a low power consumption mode when there is no transient event within a preset time period, and setting the sampling rate to a second fixed value; When the gradient threshold of the current bias value is greater than a preset judgment value, the high-precision mode is triggered and the sampling rate is set to a third fixed value.

6. The method according to claim 5, wherein The relative time synchronization of the sensors includes: The system connects to the sensors via Bluetooth and exchanges local time information with each other. The time difference and clock drift parameters are determined based on the exchanged local time information. The time synchronization of all sensors is uniformly adjusted based on the time difference and clock drift parameters to obtain time alignment data.

7. A multi-physics field coupled transient signal sensing device, used to implement the method according to any one of claims 1 to 6, characterized in that: include, A sensing unit is used to measure the electrical signals of the target multi-physical field through a plurality of preset sensors, and amplify and digitize the electrical signals obtained from the target multi-physical field to obtain output signals; Performing signal amplitude detection on the output signal, calculating the current bias according to the deviation between the output signal amplitude and the target amplitude, and adjusting the bias magnetic field according to the current bias; A control unit, used to synchronize the sensors relative to each other in time and obtain time-aligned data; Analyze the characteristics of the output signal in real time, and use the preset analysis program to perform global fault location, fault type identification or transient process tracking on its data and output signal characteristics over time.

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