A power frequency interference adaptive suppression method and system for a transient electromagnetic instrument

Abstract

The application belongs to the technical field of geophysical exploration instruments, and specifically discloses a power frequency interference adaptive suppression method and system for a transient electromagnetic instrument. The method estimates the frequency coefficient of the power frequency signal based on the voltage discrete signal, constructs a recursive model based on the frequency coefficient, and generates the base function of the fundamental frequency and each order harmonic step by step. The normalized least mean square criterion is used to adaptively estimate the amplitude and phase parameters of the power frequency and harmonic interference, the power frequency interference signal is reconstructed and offset from the original voltage signal, so that the transient electromagnetic secondary field signal after suppressing the power frequency interference is obtained. The method does not require an external reference signal, can effectively suppress the power frequency and harmonic interference under the condition of power frequency fluctuation and strong noise, reduce the influence of power frequency interference on the transient electromagnetic response signal, and improve the signal-to-noise ratio and stability of the transient electromagnetic measurement data.

Description

Technical Field

[0001] This application pertains to the field of instruments in geophysical exploration, and more specifically, relates to an adaptive suppression method and system for power frequency interference in transient electromagnetic instruments. Background Technology

[0002] In transient electromagnetic exploration, especially in urban or industrial areas, 50 / 60Hz power frequency interference and its harmonics generated by power lines are the main noise sources affecting data quality. This interference signal is usually non-stationary, and its frequency, amplitude, and phase change dynamically over time. It can severely contaminate or even drown out weak TEM secondary field signals, especially in late traces that reflect deep information, and may lead to incorrect geological conclusions in subsequent inversion interpretations.

[0003] Traditional interference suppression methods have many limitations. In the data acquisition phase, bipolar synchronous sampling is typically used, alternating the transmission of positive and negative polarities of current, followed by superposition and subtraction of the positive and negative signals during data processing. Theoretically, this method can eliminate power frequency interference when the transmission period is an even multiple of the power frequency period. However, in real-world field environments, this method often only suppresses a portion of the interference, failing to meet the requirements for high-quality data inversion. Other methods, such as swapping the transmitter and receiver positions to avoid power lines, are only suitable for areas with simple power line distribution and flat terrain. At the data processing level, fixed-frequency digital notch filters are commonly used. However, when the power frequency drifts, narrowband notch filters cannot completely filter out interference due to frequency mismatch, while wideband notch filters inevitably damage effective signal components with frequencies close to the interference, resulting in information loss. More importantly, when processing transient signals like TEM, the inherent transient response of these recursive filters causes severe distortion in the early part of the signal. This problem is related to various factors such as the filter's initial conditions and notch bandwidth, making it difficult to solve simply and effectively. Other software-based post-processing methods, while potentially more algorithmically advanced, suffer from non-real-time nature, preventing on-site personnel from assessing data quality promptly and increasing exploration uncertainty and operational risks. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the purpose of this application is to provide an adaptive power frequency interference suppression method and system for transient electromagnetic instruments, aiming to solve the problems of traditional interference suppression methods being non-real-time, non-adaptive, and prone to damaging effective signals.

[0005] The first aspect of this application relates to an adaptive suppression method for power frequency interference in a transient electromagnetic instrument, comprising the following steps:

[0006] The continuous voltage signal output by the transient electromagnetic instrument is discretized to obtain the discrete voltage signal;

[0007] Based on the frequency coefficients of the fundamental frequency signal obtained through voltage discrete signals, the fundamental frequency basis and harmonic basis functions of the power frequency signal are constructed using recursive relations.

[0008] Using the fundamental frequency basis function and the basis functions of each harmonic as reference input signals, under the constraint of the minimum mean square error criterion, the weight parameters of the reference input signals are iteratively updated by the normalized minimum mean square adaptive algorithm, so that the weighted interference estimation signal gradually approaches and fits the power frequency interference component in the voltage discrete signal, thereby obtaining the amplitude and phase of the fundamental frequency interference signal and the harmonic interference signals.

[0009] The power frequency interference signal is obtained by summing the fundamental frequency interference signal and harmonic interference signal. The power frequency interference signal is then subtracted from the voltage continuous signal output by the transient electromagnetic instrument to obtain the secondary field signal without power frequency interference.

[0010] In some embodiments, an adaptive suppression method for power frequency interference in a transient electromagnetic instrument further includes: performing data preprocessing on the discrete voltage signal and then obtaining the frequency coefficient of the fundamental frequency signal through an inverse cosine function; the data preprocessing method is: converting the discrete voltage signal into a fixed-point number format, then filtering it through a bandpass filter, and outputting a discrete voltage signal containing the fundamental frequency.

[0011] In some implementations, the frequency coefficients of the fundamental frequency signal are obtained as follows:

[0012] The frequency coefficients are updated using an inverse cosine function on a discrete voltage signal containing the fundamental frequency. If the change in the frequency coefficients obtained in two consecutive tests is less than a set threshold, a fundamental frequency locking signal is generated, the fundamental frequency estimation converges, and the frequency coefficients of the fundamental frequency signal are obtained.

[0013] In some implementations, the expressions for the fundamental frequency basis and the harmonic basis are as follows:

[0014] ;

[0015] ;

[0016] ;

[0017] ;

[0018] ;

[0019] When acquiring the fundamental frequency base station ;

[0020] When obtaining the harmonic basis of each order. ;

[0021] in, The frequency coefficients of the fundamental frequency signal are used to characterize the instantaneous frequency characteristics of the power frequency signal in the discrete time domain. For the first The frequency coefficients corresponding to the first harmonic are used to characterize the frequency position of the first harmonic under discrete sampling conditions; It is set to a constant and used as the initial condition for the recursive calculation of harmonic frequency coefficients; The frequency coefficient corresponding to the power frequency fundamental frequency is determined by the fundamental frequency angular frequency and reflects the discrete frequency characteristics of the power frequency fundamental frequency at the current sampling time. and They represent the first First harmonic and second harmonic The frequency coefficients corresponding to the first harmonic; For the first The sinusoidal basis function corresponding to the first harmonic; For the first The amplitude coefficients of the first-order sinusoidal basis functions; This refers to the fundamental angular frequency corresponding to the power frequency signal. For the first The initial phase of the first harmonic sinusoidal basis function; For the first The cosine basis function corresponding to the first harmonic; For the first The magnitude coefficients of the cosine basis functions; These are harmonic orders.

[0022] In some implementations, the amplitude and phase of the fundamental frequency interference signal and harmonic interference signal are determined as follows:

[0023] ;

[0024] ;

[0025] in, for The first-order power frequency harmonic interference signal is at the first The estimated value at each sampling time is used to characterize the instantaneous amplitude of the corresponding harmonic interference component; and They are respectively with the first Orthogonal basis of first harmonics (the two are orthogonal); The forgetting factor has a range of values ​​of 100. This is used to adjust the weight ratio between historical and current sampled data in the adaptive update process; and These are the cumulative energy values ​​of the fundamental frequency orthogonal basis signal and the harmonic orthogonal basis, respectively, used as normalization factors to perform energy normalization processing on the adaptive weight update process, thereby improving the numerical stability of the algorithm. Let be the error signal, representing the difference between the discrete voltage signal and the signal reconstructed from the basis functions at the current time. The difference between the estimated signals for first harmonic interference.

[0026] The second aspect of this application relates to an adaptive power frequency interference suppression system for a transient electromagnetic instrument, comprising:

[0027] The data acquisition module is used to receive the continuous voltage signal output by the transient electromagnetic instrument and perform discretization processing to obtain the discrete voltage signal;

[0028] The fundamental frequency estimation module is used to obtain the frequency coefficients of the fundamental frequency signal based on the discrete voltage signal;

[0029] The harmonic basis recursive generation module is used to construct the fundamental frequency basis and harmonic basis functions of the power frequency signal based on the frequency coefficients of the fundamental frequency signal using recursive relationships.

[0030] The harmonic adaptive cancellation module is used to take the fundamental frequency basis and the basis functions of each order of harmonics as reference input signals. Under the constraint of the minimum mean square error criterion, it iteratively updates the weight parameters of the reference input signals through the normalized minimum mean square adaptive algorithm, so that the weighted interference estimation signal gradually approaches and fits the power frequency interference component in the voltage discrete signal, thereby obtaining the amplitude and phase of the fundamental frequency interference signal and the harmonic interference signals of each order.

[0031] The interference reconstruction module is used to sum the fundamental frequency interference signal and harmonic interference signal to obtain the power frequency interference signal, and subtract the power frequency interference signal from the voltage continuous signal output by the transient electromagnetic instrument to obtain the secondary field signal without power frequency interference.

[0032] In some implementations, the power frequency interference adaptive suppression system further includes a data preprocessing module, comprising: a fixed-point format conversion unit and a front-end bandpass filter unit;

[0033] The fixed-point format conversion unit is used to convert discrete voltage signals into a unified fixed-point number representation;

[0034] The pre-stage bandpass filter unit is used to perform bandpass filtering on fixed-point data and output a discrete voltage signal containing the fundamental frequency.

[0035] In some implementations, the fundamental frequency estimation module includes a frequency coefficient update unit and a stability decision unit;

[0036] The frequency coefficient update unit is used to update the frequency coefficients of a discrete voltage signal containing the fundamental frequency using an inverse cosine function;

[0037] The stability decision unit is used to generate a base frequency lock signal if the change in the frequency coefficient obtained in two consecutive acquisitions is less than a set threshold, thus converging the base frequency estimation and obtaining the frequency coefficient of the power frequency signal.

[0038] In some implementations, the expressions for the fundamental frequency basis and each order harmonic basis in the harmonic basis recursive generation module are as follows:

[0039] ;

[0040] ;

[0041] ;

[0042] ;

[0043] ;

[0044] When acquiring the fundamental frequency base station ;

[0045] When obtaining the harmonic basis of each order. ;

[0046] in, The frequency coefficients of the fundamental frequency signal are used to characterize the instantaneous frequency characteristics of the power frequency signal in the discrete time domain. For the first The frequency coefficients corresponding to the first harmonic are used to characterize the frequency position of the first harmonic under discrete sampling conditions; It is set to a constant and used as the initial condition for the recursive calculation of harmonic frequency coefficients; The frequency coefficient corresponding to the power frequency fundamental frequency is determined by the fundamental frequency angular frequency and reflects the discrete frequency characteristics of the power frequency fundamental frequency at the current sampling time. For the first The sinusoidal basis function corresponding to the first harmonic; For the first The amplitude coefficients of the first-order sinusoidal basis functions; This refers to the fundamental angular frequency corresponding to the power frequency signal. For the first The initial phase of the first harmonic sinusoidal basis function; For the first The cosine basis function corresponding to the first harmonic; For the first The magnitude coefficients of the cosine basis functions; These are harmonic orders.

[0047] In some implementations, the amplitude and phase of the fundamental frequency interference signal and harmonic interference signal in the harmonic adaptive cancellation module are determined as follows:

[0048] ;

[0049] ;

[0050] in, for The first-order power frequency harmonic interference signal is at the first The estimated value at each sampling time is used to characterize the instantaneous amplitude of the corresponding harmonic interference component; and They are respectively with the first Orthogonal basis of first harmonics (the two are orthogonal); The forgetting factor has a range of values ​​of 100. This is used to adjust the weight ratio between historical and current sampled data in the adaptive update process; and These are the energy accumulations of the corresponding fundamental frequency orthogonal basis signals and harmonic orthogonal basis signals, respectively, used as normalization factors to perform energy normalization processing on the adaptive weight update process, thereby improving the numerical stability of the algorithm. Let be the error signal, representing the difference between the discrete voltage signal and the signal reconstructed from the basis functions at the current time. The difference between the estimated signals for first harmonic interference.

[0051] Thirdly, this application provides an FPGA for performing the method described in the first aspect or any possible implementation thereof.

[0052] Fourthly, this application provides an electronic device, comprising: at least one memory for storing a program; and at least one processor for executing the program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to execute the method described in the first aspect or any possible implementation thereof.

[0053] Fifthly, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0054] In a sixth aspect, this application provides a computer program product that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0055] It is understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0056] Overall, the technical solutions conceived in this application have the following beneficial effects compared with the prior art:

[0057] This application presents a power frequency interference suppression method fully integrated into a transient electromagnetic instrument. It proposes a complete adaptive estimation-reconstruction-subtraction method, overcoming the shortcomings of traditional methods in terms of real-time performance, adaptability, and signal fidelity. Through an innovative two-stage processing mode of learning followed by cancellation, this method not only achieves real-time, adaptive elimination of dynamic power frequency interference but also significantly saves computational resources and reduces instrument power consumption by switching to a low-power steady-state cancellation mode after parameter stabilization. It also avoids repetitive learning of stable background noise. This method requires no external reference signal or complex software post-processing, enabling real-time, automatic tracking and elimination of dynamically changing fundamental frequencies and their harmonic interference at the data acquisition site. Simultaneously, it maximizes the preservation of the effective components of transient electromagnetic signals, significantly improving the instrument's detection performance and operational efficiency in complex electromagnetic interference environments. Attached Figure Description

[0058] Figure 1 This is a flowchart illustrating the adaptive suppression method for power frequency interference of a transient electromagnetic instrument provided in an embodiment of this application.

[0059] Figure 2 This is a time-domain comparison diagram of the signals before and after the adaptive suppression method for power frequency interference based on transient electromagnetic instruments provided in the embodiments of this application. Detailed Implementation

[0060] 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.

[0061] In this application, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A existing alone, A and B existing simultaneously, and B existing alone. In this application, the symbol " / " indicates that the related objects are in an "or" relationship, for example, A / B means A or B.

[0062] In this application, the terms “first” and “second” are used to distinguish different objects, rather than to describe a specific order of objects.

[0063] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0064] In the description of the embodiments in this application, unless otherwise stated, "multiple" means two or more.

[0065] The embodiments of this application are described below with reference to the accompanying drawings.

[0066] The adaptive power frequency interference suppression method for transient electromagnetic instruments provided in this application does not directly filter the signal in the frequency domain. Instead, it first accurately estimates the real-time parameters of the power frequency interference and all its harmonic components mixed in the signal. Based on these parameters, a complete copy of the interference signal is reconstructed inside the transient electromagnetic instrument. Finally, this copy is subtracted from the original acquired data to obtain a pure TEM (transient electromagnetic response) signal. This method does not require any external reference signal and can independently eliminate interference.

[0067] The entire solution is designed as a highly efficient multi-stage pipeline operation and implemented on an FPGA (Field-Programmable Gate Array) hardware platform. The first stage is fundamental frequency estimation, which uses a fundamental frequency estimation module to accurately lock and track the dynamic changes of the power frequency fundamental frequency in real time. The second stage is harmonic reconstruction, which uses a set of computationally efficient digital oscillators to generate reference waveforms for each harmonic based on the calculated power frequency signal frequency, and combines an improved normalized least mean square algorithm to quickly and adaptively estimate the real-time amplitude and phase of each harmonic. This method avoids the complex calculations that are costly to implement in hardware, making it particularly suitable for implementation on an FPGA. Through this hardware-based real-time processing, this application solves the delay and adaptability problems of traditional methods, and can stably achieve deep suppression of interference signals under various signal-to-noise ratio conditions and power frequency drift conditions, while maximizing the protection of the integrity of the original transient electromagnetic signal.

[0068] Example 1

[0069] like Figure 1 As shown, this application provides an adaptive elimination method for power frequency harmonic interference in transient electromagnetic instruments, specifically including the following steps:

[0070] Step S1: Discretize the continuous voltage signal output by the transient electromagnetic instrument to obtain a discrete voltage signal;

[0071] The ADC of a transient electromagnetic instrument discretizes the received continuous voltage signal to form a discrete voltage signal. The model is:

[0072] ;

[0073] in, It is the sum of the pure secondary field signal and the non-power frequency noise signal; It is the sum of the fundamental frequency interference signal and the harmonic interference signal (power frequency interference signal). It is an integer; It is a set of integers;

[0074] Among them, the sum of fundamental frequency interference signal and harmonic interference signal This can be expressed as the sum of each harmonic and the fundamental frequency interference signal:

[0075] ;

[0076] in, k For harmonic order; M This represents the total harmonic order; The amplitudes of each harmonic interference signal and the fundamental frequency interference signal; The frequencies of each harmonic interference signal and the fundamental frequency interference signal; The phase of each harmonic interference signal and the fundamental frequency interference signal; It is a harmonic signal or a power frequency signal;

[0077] Step S2: Data preprocessing module: Converts the discrete voltage signal into Q format, then filters it through a bandpass filter to output a discrete voltage signal containing the power frequency base frequency;

[0078] The data preprocessing module includes an analog-to-digital converter (ADC) input interface, an input buffer interface, a fixed-point format conversion unit, and a pre-stage bandpass filter unit. The ADC input interface converts the discrete voltage signal output from the transient electromagnetic instrument into a fixed-point format. This signal is then filtered by the pre-stage bandpass filter unit (BPF) to output a discrete voltage signal containing the power frequency.

[0079] ;

[0080] in, It is a discrete voltage signal containing the power frequency fundamental frequency; Indicates to Perform bandpass filtering;

[0081] Among them, the filtering multiplication operations involved in the front-end bandpass filter unit are completed by a unified DSP (Digital Signal Processor) pool, and the multi-cycle pipeline structure significantly reduces resource consumption.

[0082] More specifically, the front-end bandpass filter unit adopts a fixed-point IIR (Infinite Impulse Response) digital filter structure. The filter coefficients are stored in the FPGA in constant form. All multiplication operations are completed in a time-division multiplexing manner through a unified DSP pool multiplier resource in a multi-cycle pipeline to reduce logic resource consumption and power consumption.

[0083] Step S3: Fundamental frequency estimation module: The voltage discrete signal is passed through an inverse cosine frequency to obtain the frequency coefficient of the fundamental frequency signal;

[0084] Preprocessed signal The signal is fed into the fundamental frequency estimation module, which is implemented using a multi-cycle finite state machine and utilizes the inverse cosine frequency calculation function. The output is shared by the DSP (Digital Signal Processing) pool for multiplication. When the frequency continuously changes to less than a set threshold, a fundamental frequency lock signal is generated, indicating that the fundamental frequency estimation has converged. The frequency coefficients of the fundamental frequency signal of the power frequency signal are used to characterize the instantaneous frequency characteristics of the power frequency signal in the discrete time domain.

[0085] More specifically, the fundamental frequency estimation module uses 64-bit fixed-point parameters to update intermediate variables sample by sample, adjacent... When the absolute value of the difference is continuously lower than the threshold and the number of continuous samples reaches the set value, the base frequency is determined to be locked, and a lock flag signal is output.

[0086] Step S4: Harmonic basis recursive generation module: Based on the frequency coefficients of the fundamental frequency signal, construct the fundamental frequency basis and harmonic basis functions of each order in the power frequency signal using recursive relationships;

[0087] Output of the module based on harmonic basis recursion The FPGA uses a recursive relationship to generate the fundamental frequency base and harmonic bases of each order;

[0088] ;

[0089] ;

[0090] ;

[0091] ;

[0092] ;

[0093] When acquiring the fundamental frequency base station ;

[0094] When obtaining the harmonic basis of each order. ;

[0095] in, For the first The sinusoidal basis function corresponding to the first harmonic; For the first The amplitude coefficients of the first-order sinusoidal basis functions; This refers to the fundamental angular frequency corresponding to the power frequency signal. For the first The initial phase of the first harmonic sinusoidal basis function; For the first The cosine basis function corresponding to the first harmonic; For the first The magnitude coefficients of the cosine basis functions; Harmonic order; This is the frequency coefficient constant corresponding to the zeroth harmonic, used as the initial condition for the recursive calculation of the harmonic frequency coefficient. The frequency coefficient corresponding to the fundamental frequency is determined by the cosine value of the fundamental frequency angular frequency of the power frequency. It is used to characterize the fundamental frequency characteristics of the power frequency signal in the discrete time domain and serves as the basic parameter for the recursive generation of the frequency coefficients of each order of harmonics. For the first The frequency coefficients corresponding to the first harmonic are used to characterize the second harmonic. Frequency position of the first harmonic under discrete sampling conditions;

[0096] Step S5: Harmonic Adaptive Cancellation Module: Summing the fundamental frequency basis functions to construct the fundamental frequency interference signal, summing the harmonic basis functions of each order to construct the harmonic interference signal; combining the voltage discrete signal, the fundamental frequency interference signal, and the harmonic interference signal, the amplitude and phase of the fundamental frequency interference signal and the harmonic interference signal are obtained through the normalized least mean square algorithm.

[0097] Modeling method for each harmonic:

[0098] ;

[0099] Will The amplitude and phase of the fundamental frequency and harmonic interference signals are determined and stored using the normalized least mean square algorithm.

[0100] ;

[0101] ;

[0102] in, for The first-order power frequency harmonic interference signal is at the first The estimated value at each sampling time is used to characterize the instantaneous amplitude of the corresponding harmonic interference component; and They are respectively with the first Orthogonal basis of first harmonics (the two are orthogonal); The forgetting factor has a range of values ​​of 100. This is used to adjust the weight ratio between historical and current sampled data in the adaptive update process; and These are the energy accumulation amounts of the corresponding orthogonal basis signals, used as normalization factors to perform energy normalization processing on the adaptive weight update process, thereby improving the numerical stability of the algorithm. Let be the error signal, representing the difference between the discrete voltage signal and the signal reconstructed from the basis functions at the current time. The difference between the estimated first harmonic interference signals;

[0103] The formula is updated for adaptive learning. During this process, the DSP pool sequentially processes the amplitude and phase updates of the fundamental frequency and each order of harmonic interference signals until the normalized minimum mean square algorithm converges.

[0104] Step S6: The interference reconstruction module sums the fundamental frequency interference signal and harmonic interference signal to obtain the power frequency interference signal, and subtracts the power frequency interference signal from the voltage continuous signal output by the transient electromagnetic instrument to obtain the secondary field signal without power frequency interference signal.

[0105] More specifically, upon entering steady-state mode, all updates cease, retaining only the rebuild pipeline:

[0106] ;

[0107] Final output:

[0108] ;

[0109] The pipeline delay is fixed and can be fully aligned with the ADC timing, enabling pure hardware real-time cancellation.

[0110] More specifically, the switching between the adaptive learning phase and the steady-state cancellation phase is controlled by the FPGA master control state machine. The adaptive learning phase allows the harmonic basis recursive generation module and the harmonic adaptive cancellation module to update parameters, while the steady-state cancellation phase prohibits parameter updates and only uses the interference reconstruction module and the harmonic adaptive cancellation module to complete real-time interference suppression.

[0111] Example 2

[0112] This application provides a power frequency interference adaptive suppression system for a transient electromagnetic instrument, integrated into the receiver of the transient electromagnetic instrument, comprising:

[0113] The data acquisition module is equipped with an ADC interface and an input buffer interface, which are used to receive and buffer the continuous voltage signal output by the transient electromagnetic receiving coil, and to perform discretization processing to obtain the discrete voltage signal.

[0114] The data preprocessing module includes a fixed-point format conversion unit and a pre-bandpass filtering unit;

[0115] Fixed-point format conversion unit, used to convert discrete voltage signals into a unified Q-format fixed-point representation;

[0116] The pre-stage bandpass filter unit is used to perform bandpass filtering on fixed-point data, highlighting the power frequency and its harmonic components, and outputting a discrete voltage signal containing the power frequency fundamental frequency.

[0117] The fundamental frequency estimation module is used to estimate the frequency parameters of the fundamental frequency based on the discrete voltage signal output from the preceding bandpass filter unit. and output a lock flag;

[0118] The harmonic basis recursive generation module is used to generate harmonic basis recursion. After locking, an orthogonal basis for generating harmonics from the 1st to the Mth order is generated. , ;

[0119] The harmonic adaptive cancellation module is used to receive discrete voltage signals and form orthogonal bases of harmonics from the 1st to the Mth order, and adaptively estimate the amplitude and phase of each order harmonic using the normalized least mean square algorithm.

[0120] The coefficient storage module is used to store the coefficients after convergence. The amplitude and phase of fundamental frequency interference signals and harmonic interference signals;

[0121] The interference reconstruction module is used to reconstruct power frequency and harmonic interference estimates based on the coefficient storage module and the harmonic basis recursion module during the steady-state phase. The output signal is obtained by subtracting the discrete voltage signal from the output signal. ;

[0122] The DSP multiplier pool is used to provide contribution multiplication operation resources for the front-end bandpass filter module, fundamental frequency estimation module, harmonic basis recursive generation module and harmonic adaptive cancellation module.

[0123] In some specific implementations, the fundamental frequency estimation module includes a multiplication unit, an addition / subtraction unit, a state register group, and a comparison unit. These functional units work collaboratively under unified timing control to perform the defined inverse cosine operation on the power frequency coefficients of the discrete voltage signal and output the power frequency coefficients. The multiplication unit is provided uniformly by the DSP multiplier pool and serves the fundamental frequency estimation module in turn according to a predetermined timing sequence. It performs the multiplication operations involved in the inverse cosine frequency calculation, including the product calculation between the current sampled signal and historical state variables. This is achieved through a shared DSP. Multiplication resources reduce the logic resource consumption required for overall hardware implementation; the addition and subtraction unit is used to perform addition or subtraction on the intermediate results output by the multiplication unit to realize the accumulation and difference operations required in the recursive update of the base frequency, thereby gradually updating the frequency estimation state quantity corresponding to the current sampling time; the state register group is used to store the intermediate state variables and historical calculation results in the base frequency estimation process, including the frequency estimation state information of the previous sampling time and several previous sampling times, to support the recursive update operation based on historical states; the state register group is synchronously updated according to the calculation results in each sampling period; the comparison unit is used to compare the frequency estimation results obtained in consecutive sampling times. When the change between two adjacent frequency estimation results is less than the preset threshold and the set number of sampling points is continuously met, it is determined that the base frequency estimation result has converged, and the base frequency lock flag signal is output; through the coordinated work of the above functional units, the base frequency estimation module can perform real-time frequency estimation of the power frequency component contained in the voltage discrete signal without relying on the external reference signal, and provide stable and reliable frequency coefficient input for the subsequent harmonic basis recursive generation module and harmonic adaptive cancellation module;

[0124] More specifically, the hardware structure of the baseband estimation module includes a delay register, a subtractor, a recursive calculation unit, a parameter update unit, a division unit, and a stability decision unit.

[0125] The discrete input voltage signal is first processed by a delay register and a subtractor to form a differential signal between adjacent sampling times. This signal is used to highlight the periodic variation characteristics of the power frequency interference signal, thereby suppressing the influence of non-periodic components in the transient electromagnetic signal.

[0126] The recursive calculation unit is used to calculate intermediate state quantities based on the current differential signal and historical state information. It is updated in real time; the intermediate state variable is used to characterize the phase change trend of the power frequency interference signal at the current sampling time. It is the core state variable in the frequency calculation process, and its value evolves recursively with the sampling time.

[0127] Within the parameter update unit, separate statistical update channels are set up to recursively calculate statistics related to frequency estimation; among them, the statistics... A statistic used to describe the cumulative correlation between intermediate state quantities and differential signals. It is used to describe the cumulative characteristics of the energy or amplitude changes of intermediate state quantities; statistics are used to improve the stability and robustness of frequency estimation results in noisy environments by accumulating and updating information from multiple sampling times.

[0128] By using the division unit, the ratio of the above statistics is calculated to obtain the frequency coefficient corresponding to the power frequency interference signal, which is used to characterize the instantaneous frequency characteristics of the power frequency signal under the current sampling conditions.

[0129] Finally, in the stability decision unit, the frequency coefficient changes obtained at multiple consecutive sampling times are compared and judged. When the frequency coefficient change is within the preset threshold range and the set number of sampling points is continuously met, it is determined that the fundamental frequency estimation result has converged, and the fundamental frequency estimation result and the corresponding frequency lock flag signal are output.

[0130] In some specific implementations, the harmonic basis recursion generation module includes multiple harmonic recursion units, each containing a multiplier, an adder / subtractor, and a register, used for... Generate a function of a specified order based on the recurrence relation for the input. , The harmonic order M can be set during the FPGA configuration phase;

[0131] In some specific implementations, the harmonic adaptive cancellation module includes a harmonic reference register group, an interference estimation calculation unit, an error calculation unit, and a weight update unit. Its specific operation process is as follows:

[0132] First, at each sampling moment, the harmonic reference register group outputs the fundamental frequency basis function and the orthogonal basis functions corresponding to each harmonic, generated by the digital oscillator recursive model, according to the current sampling sequence number. The basis functions are synchronized with the discrete voltage signal at the current sampling moment and are used to characterize the reference waveforms of the power frequency fundamental frequency and its harmonics. Subsequently, in the interference estimation calculation unit, for each harmonic, the corresponding orthogonal basis function is multiplied by its adaptive amplitude and phase weights, and the product is added to obtain the estimation result of the harmonic interference component. By superimposing the fundamental frequency interference estimation result and the harmonic interference estimation results, a copy of the overall power frequency interference estimation signal is formed. Then, in the error calculation unit, the overall power frequency interference estimation signal is subtracted from the original discrete voltage signal to obtain the error signal. The error signal is used to characterize the residual difference between the interference estimation result at the current moment and the actual discrete voltage signal. Then, in the weight update unit, using the error signal as feedback, and under the constraint of a preset step size parameter, the amplitude and phase weights corresponding to each harmonic are adaptively updated according to the normalized minimum mean square criterion. This allows the power frequency interference estimation signal reconstructed in subsequent sampling moments to gradually approximate the actual power frequency and harmonic interference components in the discrete voltage signal under the meaning of minimum mean square error. Finally, the error signal is used as the output signal after the power frequency interference is suppressed, thereby obtaining the transient electromagnetic response signal after canceling the power frequency and harmonic interference.

[0133] In some specific implementations, the coefficient storage module adopts a dual-port RAM or register file structure, with one end being written to the updated value by the harmonic basis recursive generation module during the adaptive learning phase. The amplitude and phase of the power frequency interference signal are determined at one end, while at the other end, fixed parameters are read by the interference reconstruction module and the harmonic basis recursive generation module during the steady-state cancellation phase.

[0134] In some specific implementations, the DSP multiplier consists of multiple FPGA internal multiplier arrays. Through time-division multiplexing and multi-cycle pipeline scheduling methods, it provides shared computing resources for the front-end bandpass filter unit, harmonic basis recursive generation module and fundamental frequency estimation module, and controls the overall resource usage and power consumption while supporting configurable harmonic suppression of orders 1 to N.

[0135] This application provides a real-time power frequency interference processing method fully integrated into a transient electromagnetic instrument. By implementing a complete adaptive estimation-reconstruction-subtraction algorithm on FPGA hardware, it overcomes the shortcomings of traditional methods in terms of real-time performance, adaptability, and signal fidelity. This method, through an innovative two-stage processing mode of learning followed by cancellation, not only achieves real-time and adaptive elimination of dynamic power frequency interference, but also significantly saves FPGA hardware computing resources and reduces instrument power consumption by switching to a low-power steady-state cancellation mode after parameter stabilization, avoiding repetitive learning work on stable background noise. This method requires no external reference signal or complex software post-processing, and can automatically track and eliminate dynamically changing fundamental frequencies and their harmonic interference in real time at the data acquisition site, while maximizing the preservation of the effective components of transient electromagnetic signals. This significantly improves the instrument's detection performance and operational efficiency in complex electromagnetic interference environments. Figure 2 As shown.

[0136] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An adaptive suppression method for power frequency interference in a transient electromagnetic instrument, characterized in that, Includes the following steps: The continuous voltage signal output by the transient electromagnetic instrument is discretized to obtain the discrete voltage signal; Based on the frequency coefficients of the fundamental frequency signal obtained through voltage discrete signals, the fundamental frequency basis and harmonic basis functions in the power frequency signal are constructed using recursive relations. Using the fundamental frequency basis function and the basis functions of each harmonic as reference input signals, under the constraint of the minimum mean square error criterion, the weight parameters of the reference input signals are iteratively updated by the normalized minimum mean square adaptive algorithm, so that the weighted interference estimation signal gradually approaches and fits the power frequency interference component in the voltage discrete signal, thereby obtaining the amplitude and phase of the fundamental frequency interference signal and the harmonic interference signals. The power frequency interference signal is obtained by summing the fundamental frequency interference signal and harmonic interference signal. The power frequency interference signal is then subtracted from the voltage continuous signal output by the transient electromagnetic instrument to obtain the secondary field signal without power frequency interference.

2. The method of claim 1, wherein, After preprocessing the discrete voltage signal, the frequency coefficients of the fundamental frequency signal are obtained by using an inverse cosine function. The data preprocessing method is as follows: the discrete voltage signal is converted into a fixed-point number format, and then filtered by a bandpass filter to output a discrete voltage signal containing the fundamental frequency.

3. The method of claim 2, wherein the step of determining the power level of the power frequency interference signal is performed by a power frequency interference detector. The method for obtaining the frequency coefficients of the fundamental frequency signal is as follows: The frequency coefficients are updated using a discrete voltage signal containing the power frequency baseband through an inverse cosine function. If the change in the frequency coefficients obtained in two consecutive acquisitions is less than a set threshold, a baseband frequency locking signal is generated, the baseband estimation converges, and the frequency coefficients of the baseband signal are obtained.

4. The adaptive power frequency interference suppression method according to claim 3, characterized in that, The expressions for the fundamental frequency basis and the harmonic basis are as follows: ； ； ； ； ； When the fundamental base is acquired, ; When the harmonic bases of each order are acquired, ; in, The frequency coefficient of the fundamental frequency signal is used to characterize the instantaneous frequency characteristics of the power frequency signal in the discrete time domain. For the first The frequency coefficients corresponding to the first harmonic are used to characterize the second harmonic. Frequency position of the first harmonic under discrete sampling conditions; It is set to a constant and used as the initial condition for the recursive calculation of harmonic frequency coefficients; The frequency coefficient corresponding to the fundamental frequency; and They represent the first First harmonic and second harmonic The frequency coefficients corresponding to the first harmonic; For the first The sinusoidal basis function corresponding to the first harmonic; For the first The amplitude coefficients of the first-order sinusoidal basis functions; This refers to the fundamental angular frequency corresponding to the power frequency signal. For the first The initial phase of the first harmonic sinusoidal basis function; For the first The cosine basis function corresponding to the first harmonic; For the first The magnitude coefficients of the cosine basis functions; These are harmonic orders.

5. The adaptive power frequency interference suppression method according to claim 4, characterized in that, The methods for determining the amplitude and phase of fundamental frequency interference signals and harmonic interference signals are as follows: ； ； in, for The first-order power frequency harmonic interference signal is at the first The estimated value at each sampling time is used to characterize the instantaneous amplitude of the corresponding harmonic interference component; and They are respectively with the first Orthogonal basis of first harmonics; Forgetting factor; and These represent the cumulative energy of the fundamental frequency orthogonal basis signal and the harmonic orthogonal basis, respectively. This is the error signal.

6. A power frequency interference adaptive suppression system for a transient electromagnetic instrument, characterized in that, include: The data acquisition module is used to receive the continuous voltage signal output by the transient electromagnetic instrument and perform discretization processing to obtain the discrete voltage signal; The fundamental frequency estimation module is used to obtain the frequency coefficients of the fundamental frequency signal based on the discrete voltage signal; The harmonic basis recursive generation module is used to construct the fundamental frequency basis and harmonic basis functions of the power frequency signal based on the frequency coefficients of the fundamental frequency signal using recursive relationships. The harmonic adaptive cancellation module is used to take the fundamental frequency basis and the basis functions of each order of harmonics as reference input signals. Under the constraint of the minimum mean square error criterion, it iteratively updates the weight parameters of the reference input signals through the normalized minimum mean square adaptive algorithm, so that the weighted interference estimation signal gradually approaches and fits the power frequency interference component in the voltage discrete signal, thereby obtaining the amplitude and phase of the fundamental frequency interference signal and the harmonic interference signals of each order. The interference reconstruction module is used to sum the fundamental frequency interference signal and harmonic interference signal to obtain the power frequency interference signal, and subtract the power frequency interference signal from the voltage continuous signal output by the transient electromagnetic instrument to obtain the secondary field signal without power frequency interference.

7. The power frequency interference adaptive suppression system according to claim 6, characterized in that, It also includes a data preprocessing module, comprising: a fixed-point format conversion unit and a pre-stage bandpass filter unit; The fixed-point format conversion unit is used to convert discrete voltage signals into a unified fixed-point number representation; The pre-stage bandpass filter unit is used to perform bandpass filtering on fixed-point data and output a discrete voltage signal containing the fundamental frequency.

8. The power frequency interference adaptive suppression system of claim 7, wherein, The fundamental frequency estimation module includes a frequency coefficient update unit and a stability decision unit; The frequency coefficient update unit is used to update the frequency coefficients of a discrete voltage signal containing the fundamental frequency using an inverse cosine function; The stability decision unit is used to generate a base frequency lock signal if the change in the frequency coefficient obtained in two consecutive acquisitions is less than a set threshold, thus converging the base frequency estimation and obtaining the frequency coefficient of the power frequency signal.

9. The power frequency interference adaptive suppression system of claim 8, wherein, The expressions for the fundamental frequency basis and the harmonic basis of each order in the harmonic basis recursive generation module are as follows: ； ； ； ； ； When the fundamental base is acquired, ; When the harmonic bases of each order are acquired, ; in, The frequency coefficients of the fundamental frequency signal are used to characterize the instantaneous frequency characteristics of the power frequency signal in the discrete time domain. For the first The frequency coefficients corresponding to the first harmonic are used to characterize the frequency position of the first harmonic under discrete sampling conditions; It is set to a constant and used as the initial condition for the recursive calculation of harmonic frequency coefficients; The frequency coefficient corresponding to the power frequency fundamental frequency is determined by the fundamental frequency angular frequency and reflects the discrete frequency characteristics of the fundamental frequency at the current sampling time; and They represent the first First harmonic and second harmonic The frequency coefficients corresponding to the first harmonic; For the first The sinusoidal basis function corresponding to the first harmonic; For the first The amplitude coefficients of the first-order sinusoidal basis functions; This refers to the fundamental angular frequency corresponding to the power frequency signal. For the first The initial phase of the first harmonic sinusoidal basis function; For the first The cosine basis function corresponding to the first harmonic; For the first The magnitude coefficients of the cosine basis functions; These are harmonic orders.

10. The power frequency interference adaptive suppression system of claim 9, wherein, The method for determining the amplitude and phase of the fundamental frequency interference signal and harmonic interference signal in the harmonic adaptive cancellation module is as follows: ； ； in, for The first-order power frequency harmonic interference signal is at the first The estimated value at each sampling time is used to characterize the instantaneous amplitude of the corresponding harmonic interference component; and They are respectively with the first Orthogonal basis of first harmonics; Forgetting factor; and These represent the cumulative energy of the fundamental frequency orthogonal basis signal and the harmonic orthogonal basis, respectively. This is the error signal.

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