Ultrasonic array based house leak location system

Abstract

The application discloses a housing leakage point positioning system based on an ultrasonic array and belongs to the technical field of ultrasonic detection. The system comprises an ultrasonic sensor array module, a plurality of groups of ultrasonic transmitter and receiver arrays arranged in a to-be-detected area and a signal processing unit, emits ultrasonic waves according to a preset time sequence and a frequency sequence and synchronously collects reflected echo signals; a data collection module, divides the echo signals into a plurality of subsegments according to time windows, and each subsegment corresponds to a transmission pulse; a matrix construction module, phase demodulates each subsegment to obtain a phase difference sequence and constructs a phase difference matrix; and a leakage positioning module, reconstructs the sound velocity distribution of the medium in the to-be-detected area by using the phase difference matrix through a phase inversion algorithm and positions the leakage point according to an abnormal area in the sound velocity distribution. The application realizes non-destructive accurate positioning of a housing leakage point, effectively overcomes the limitation that conventional detection methods are difficult to comprehensively cover hidden areas, and improves detection efficiency and positioning accuracy.

Description

Technical Field

[0001] This invention relates to the field of ultrasonic testing technology, specifically to a system for locating leaks in buildings based on ultrasonic arrays. Background Technology

[0002] For a long time, building leak detection has relied on manual observation, tapping and listening, and infrared thermal imaging. Manual observation can only detect surface seepage or obvious dampness, while tapping and listening depend on the operator's experience, resulting in poor consistency and difficulty in detecting hidden leaks. Infrared thermal imaging infers the leak area by detecting surface temperature differences caused by moisture evaporation, but it is significantly affected by ambient temperature and humidity. When the leak is located deep inside the wall or floor slab, the surface thermal difference is weak, making it easy to miss.

[0003] In ultrasonic testing, existing technologies mostly employ a single-frequency pulse-echo method, determining the presence of internal defects in materials by measuring changes in wave velocity or attenuation of echo amplitude. For locating leaks in buildings, moisture infiltration causes changes in acoustic impedance and sound velocity in localized areas. However, these changes are relatively small, and the echo amplitude or transit time of a single frequency is insensitive to minute changes in moisture content. This method is typically only effective for identifying larger-scale cavities or cracks, failing to effectively distinguish gradual changes in sound velocity caused by moisture content gradients. Furthermore, most existing ultrasonic location methods treat the received signal as an independent scalar result for each path, lacking the combined utilization of multi-frequency, multi-path phase information. This makes it difficult to reconstruct the spatial distribution of sound velocity in complex media, resulting in insufficient accuracy in leak location identification.

[0004] How to obtain sufficient detection information to distinguish minute differences in the moisture content of the medium, and to convert this information into a sound velocity image that can accurately reflect the location and extent of leakage, is an urgent problem to be solved. Summary of the Invention

[0005] This invention provides a house leak point location system based on an ultrasonic array, which extracts subtle changes in the sound velocity of the medium from multi-frequency phase information and reconstructs the spatial distribution of sound velocity reflecting the leakage state, thereby achieving precise location of the leak point.

[0006] To achieve the above objectives, the present invention provides the following technical solution: The present invention provides a building leak location system based on an ultrasonic array, comprising an ultrasonic sensor array module, a data acquisition module, a matrix construction module, and a leak location module. The ultrasonic sensor array module includes multiple sets of ultrasonic transmitter and receiver arrays arranged in the area to be tested, as well as a signal processing unit. The signal processing unit controls the multiple sets of ultrasonic transmitters to emit ultrasonic waves according to a preset time and frequency sequence, while simultaneously controlling the receiver array to synchronously acquire reflected echo signals. As a preferred arrangement, the transmitters and receivers are arranged in an equally spaced grid on multiple walls in the area to be tested. Each transmitter corresponds to a set of adjacent receivers to form a sub-array, and the coverage areas of each sub-array overlap, thereby forming high-density, multi-angle beam coverage of the area to be tested, improving the spatial resolution of leak anomalies.

[0007] In terms of the transmission control strategy, the preset timing and frequency sequence transmits single-frequency pulses sequentially in the order of low frequency first and high frequency later. The time interval between adjacent pulses is greater than the two-way propagation time of the maximum detection depth to avoid aliasing of echoes from different periods. The frequency values ​​are selected at equal attenuation intervals on the ultrasonic attenuation characteristic curve of the medium under test, so that the detection signals of each frequency band achieve a balance between penetration depth and signal-to-noise ratio, which is beneficial to obtaining more complete acoustic feature information inside the medium.

[0008] The data acquisition module divides the received echo signal into multiple segments according to time windows, with each segment corresponding to a transmission pulse. Preferably, the start time of each time window is determined by adding a fixed propagation delay to the transmission time of the corresponding transmission pulse, and the window length is equal to the sum of the duration of the transmission pulse and the maximum expected echo broadening. This allows for the precise extraction of echo components from the target depth range, suppressing clutter interference outside the detection blind zone.

[0009] The matrix construction module performs phase demodulation on each segment to obtain a phase difference sequence. Specifically, each segment is orthogonally demodulated with the reference waveform of the corresponding transmitted pulse to extract the in-phase and quadrature components. The instantaneous phase is obtained by calculating the arctangent of the in-phase and quadrature components, and the difference between the instantaneous phases of adjacent sampling points is then used to obtain the phase difference sequence. This demodulation method can effectively overcome the interference of echo amplitude fluctuations on phase extraction and stably restore the phase changes accumulated by the sound wave propagating in the medium. A phase difference matrix is ​​constructed based on the phase difference sequences of multiple segments. Preferably, the phase difference sequences of the same receiver under different transmitted pulses are arranged in chronological order as row vectors, and the phase difference sequences of different receivers under the same transmitted pulse are arranged in spatial order as column vectors, forming a two-dimensional complex matrix with the dimension of the number of receivers multiplied by the number of transmitted pulses. This integrates the spatiotemporal phase information of multiple frequencies and channels into a regular structure, providing a compact data foundation for subsequent inversion.

[0010] The leakage location module reconstructs the sound velocity distribution of the medium inside the test area using the phase difference matrix and a phase inversion algorithm. As a technical solution of this invention, the test area is discretized into multiple voxels, each assigned an initial sound velocity value. Based on the sound velocity values, the theoretical propagation time of each transmit-receive path is calculated, thus obtaining the theoretical phase difference. The sum of squared residuals between the theoretical and measured phase difference matrices is iteratively minimized. In each iteration, the sound velocity value of each voxel is corrected according to the residual gradient direction until the residual converges to a preset threshold. During iterative correction, the partial derivative of each voxel with respect to the theoretical phase difference of all paths is calculated, constructing a Jacobian matrix. Then, the product of the transpose of the Jacobian matrix and the residual vector is solved using the conjugate gradient method to obtain the sound velocity correction amount for each voxel, and the sound velocity value is updated with a fixed step size. This inversion process fully utilizes the path integral constraints contained in the phase difference matrix, enabling stable convergence to near the true value and exhibiting high sensitivity to slight local sound velocity decreases caused by leakage water infiltration.

[0011] After obtaining the sound velocity distribution, the leakage point is located based on the abnormal areas in the sound velocity distribution. First, regions with sound velocity values ​​lower than the normal background sound velocity value and a number of continuous voxels exceeding the minimum volume threshold are extracted from the reconstructed sound velocity distribution as candidate regions to filter out false anomalies caused by discrete noise fluctuations. The spatial gradient modulus of the sound velocity value in each candidate region is calculated, and the spatial coordinates of the voxel with the maximum modulus value are selected as the center point of the candidate region. The coordinate set of all center points is output as the location of the leakage point. The normal background sound velocity value is determined by performing histogram statistics on the sound velocity values ​​of all voxels in the reconstructed sound velocity distribution, and the sound velocity value corresponding to the peak value of the histogram is taken as the normal background sound velocity value; voxels with sound velocity values ​​lower than this peak value and a deviation exceeding a preset noise standard deviation multiple are judged as abnormal voxels. This statistical adaptive criterion does not require prior knowledge of the nominal sound velocity of the building materials and can automatically adapt to the background differences of different masonry, concrete, and other materials, accurately marking the areas of sound velocity decrease caused by water saturation or loose structure, ultimately achieving non-destructive, high-precision spatial location of leakage points.

[0012] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0013] The transmitter sequentially emits single-frequency pulses in a low-frequency to high-frequency order. The frequency values ​​are selected at equal attenuation intervals on the ultrasonic attenuation characteristic curve of the medium under test, and the time interval between adjacent pulses is greater than the two-way propagation time at the maximum detection depth. This frequency sequence design allows the ultrasonic waves to exhibit differentiated responses at different frequencies due to energy attenuation and phase delay caused by water leakage in the medium. The phase information carried by the echo signals of the same receiver under different transmitted pulses constitutes a set of multi-frequency characteristics. Orthogonal demodulation is performed on each segment to extract the in-phase and quadrature components, and the instantaneous phase and the phase difference between adjacent sampling points are calculated to obtain the phase difference sequence corresponding to each pulse. Then, the multi-frequency phase difference sequences of the same receiver are arranged in time, and the phase difference sequences of different receivers are arranged in space to form a two-dimensional complex phase difference matrix. This matrix integrates subtle phase changes in the frequency, spatial, and depth dimensions, and reflects the small local sound velocity shifts caused by water content more sensitively than the echo amplitude or transit time of a single frequency.

[0014] The sound velocity distribution within the test area is reconstructed using an iterative inversion algorithm based on the phase difference matrix. The area is discretized into voxels, and an initial sound velocity value is assigned to each voxel. The theoretical propagation time and theoretical phase difference for each transmit-receive path are calculated. The sum of squared residuals between the theoretical and measured phase difference matrices is used as the objective function. In each iteration, the sound velocity value of each voxel is corrected according to the residual gradient direction until the residuals converge. From the reconstructed sound velocity distribution, regions with sound velocity values ​​lower than the normal background sound velocity value and a number of consecutive voxels exceeding the minimum volume threshold are extracted as candidate leakage regions. The spatial gradient magnitude of the sound velocity values ​​within the candidate regions is calculated, and the spatial coordinates of the voxel with the maximum magnitude are output as the center of the leakage point. By reconstructing the sound velocity distribution through phase inversion, multi-frequency and multi-path phase information is directly converted into a spatial distribution image of the medium's physical parameters. The area of ​​sound velocity reduction caused by water leakage appears as a localizable anomaly on the image. In principle, this avoids the shortcomings of traditional amplitude attenuation methods that are sensitive to echo intensity fluctuations and coupling differences. It can provide continuous and accurate coordinate output for both hidden internal leakage points and areas with gradually changing water content. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0016] Figure 1 This is a schematic diagram of a house leak location system based on an ultrasonic array;

[0017] Figure 2 This is a schematic diagram of the ultrasonic transceiver array layout and signal processing flow.

[0018] Figure 3 This is a diagram showing the frequency characteristics of the ultrasonic attenuation coefficient of concrete walls and the selection of frequency points with equal attenuation intervals.

[0019] Figure 4 It reconstructs the sound velocity distribution histogram and anomaly detection threshold map. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] See Figure 1 This invention provides a building leak location system based on an ultrasonic array, comprising an ultrasonic sensor array module, a data acquisition module, a matrix construction module, and a leak location module. The ultrasonic sensor array module includes multiple sets of ultrasonic transmitters and receivers arranged in the area to be tested, as well as a signal processing unit. The signal processing unit controls the multiple ultrasonic transmitters to emit ultrasonic waves according to a preset time and frequency sequence, while simultaneously controlling the receiver array to synchronously acquire reflected echo signals. The data acquisition module divides the received echo signals into multiple segments according to a time window, with each segment corresponding to a transmitted pulse. The matrix construction module performs phase demodulation on each segment to obtain a phase difference sequence, and constructs a phase difference matrix based on the phase difference sequences of multiple segments. The leak location module uses the phase difference matrix to reconstruct the sound velocity distribution of the medium inside the area to be tested using a phase inversion algorithm, and locates the leak point based on abnormal areas in the sound velocity distribution.

[0022] Example 1

[0023] In specific implementation, please refer to Figure 2The arrangement of multiple ultrasonic transmitter and receiver arrays involves placing the transmitters and receivers in a grid with equal spacing on multiple walls within the test area. The grid spacing is set based on the wavelength corresponding to the center frequency of the transmitted ultrasonic waves, taking half of the center frequency wavelength. For each wall to be tested, the transmitters and receivers are arranged alternately and at equal intervals in the horizontal and vertical directions within the wall plane, forming a two-dimensional grid array. For each transmitter in the grid, multiple receivers directly adjacent to the transmitter's spatial position are selected to form a subarray, with the number of receivers in the subarray being four or eight. Using a subarray consisting of a single transmitter and a corresponding set of adjacent receivers as the basic transceiver unit, the spatial coverage areas of multiple subarrays on the test wall overlap, ensuring that any location within the test area is traversed by the transmission-reception paths of at least two subarrays.

[0024] The preset timing and frequency sequence is set to transmit single-frequency pulses sequentially, starting with low frequencies and then increasing to high frequencies. The transmission sequence begins with the preset lowest frequency and gradually increases the frequency value until the highest frequency, transmitting a single pulse of a fixed frequency each time. The time interval between adjacent pulses is set to be greater than the two-way propagation time of the maximum detection depth. The maximum detection depth is determined based on the vertical distance from the farthest wall surface in the test area to the mounting surface of the ultrasonic sensor array module. The two-way propagation time is obtained by dividing the maximum detection depth by the reference propagation speed of ultrasound in the test medium, and the calculated result is multiplied by a safety factor greater than 1 to obtain the time interval value. The frequency values ​​are selected at equal attenuation intervals on the ultrasonic attenuation characteristic curve of the test medium. First, samples are taken from the wall of the test area, and the curve of ultrasonic attenuation coefficient changing with frequency is measured. The maximum and minimum values ​​of the attenuation coefficient are obtained from the curve. Then, the attenuation coefficient interval is divided into the number of required frequency points minus 1, and the frequency value corresponding to each division point is selected as the transmission frequency to form a frequency sequence.

[0025] The signal processing unit generates transmission control commands based on the spatial positions of the multiple sets of transmitters and receivers, as well as the pre-set timing and frequency sequences. The signal processing unit sequentially drives each transmitter to generate a single-frequency pulse at its corresponding frequency value. Simultaneously with each transmission pulse, all receivers within the corresponding subarray of that transmitter are activated to synchronously acquire the reflected echo signals. The acquisition duration covers the entire reception window after the time interval elapsed since the transmission. The signal processing unit packages the echo signals acquired by each receiver according to the transmission pulse number and receiver number, and transmits them to the data acquisition module.

[0026] See Figure 3The figure shows the attenuation coefficient of ultrasound in the tested wall medium as a function of frequency. The horizontal axis represents frequency, ranging from approximately 20kHz to 200kHz (unit: kHz), and the vertical axis represents the attenuation coefficient (unit: dB / m). The curve generally shows a monotonically increasing trend with increasing frequency, with the attenuation coefficient gradually rising from near 0dB / m to approximately 36dB / m, demonstrating that the higher the frequency, the more significant the energy attenuation of ultrasound in the medium. The curve contains some random fluctuations, reflecting noise interference in the actual measurement.

[0027] The figure shows several discrete frequency points selected based on the principle of equal attenuation intervals, marked with red dots. These frequency points are evenly distributed within the range of attenuation coefficient values, with specific attenuation coefficients of approximately 0.3 dB / m, 9.3 dB / m, 18.5 dB / m, 27.5 dB / m, and 36.8 dB / m, respectively. As described in Example 1, these frequency points constitute a transmission frequency sequence, ensuring that the transmission frequencies are selected on the ultrasonic attenuation characteristic curve using equal intervals of attenuation coefficients, thereby balancing signal penetration capability and attenuation effects across different frequency bands.

[0028] Example 2

[0029] In practice, the data acquisition module receives echo signals from each receiver in the ultrasonic sensor array module and divides the echo signal on each receiving channel into multiple segments according to a time window. The echo signals are converted from analog to digital to form a discrete sampling sequence, with the sampling rate set to 8 times the highest frequency of the transmitted pulse. For each transmitted pulse, the data acquisition module extracts all sampling points within a time window from the echo signal sampling sequence, forming a segment, with each transmitted pulse corresponding to one segment.

[0030] For the m-th transmitted pulse, the start time of the time window is determined by adding a fixed propagation delay to the transmission time of the m-th transmitted pulse. The transmission time is obtained from the transmission timing record of the signal processing unit, and the fixed propagation delay is determined by the shortest sound path required for the ultrasonic wave to propagate from the transmitter surface to the surface of the nearest receiver adjacent to the transmitter. The fixed propagation delay is calculated by dividing the straight-line distance between the transmitter and the nearest receiver by the speed of sound in air. When both the transmitter and receiver are mounted on a wall, the fixed propagation delay also includes the propagation time of the ultrasonic wave in the coupling medium, which is measured using an offline calibration method.

[0031] The length of the m-th time window is equal to the sum of the duration of the m-th transmitted pulse and the maximum expected echo broadening. The duration of the transmitted pulse is determined by the pulse envelope width generated by the signal processing unit, and is set to an integer multiple of the period corresponding to the transmission frequency, with a value of 12 periods. The maximum expected echo broadening is determined based on the geometric dimensions of the area under test and the acoustic characteristics of the medium. The process of obtaining the maximum expected echo broadening is as follows: First, calculate the theoretical two-way propagation time corresponding to the maximum detection distance. The maximum detection distance is the straight-line distance from the farthest wall reflection point in the area under test to the plane where the receiver array is located. The theoretical two-way propagation time is equal to twice the maximum detection distance divided by the reference propagation speed of ultrasound in the medium under test; then multiply the theoretical two-way propagation time by a broadening factor. , broadening factor The value range is from 0.10 to 0.25, and the broadening factor is... The specific value is selected based on the degree of non-uniformity of the medium being tested. For concrete walls with a density of 2200 kg / m³ to 2400 kg / m³, the broadening factor... Take 0.18.

[0032] The start time of the m-th time window and end time The following relationship must be satisfied:

[0033]

[0034] in, Let represent the sum of the transmission time of the m-th transmitted pulse and the fixed propagation delay. Indicates the duration of the transmitted pulse. This indicates the maximum expected widening of the return.

[0035] The data acquisition module, based on the aforementioned time window parameters, extracts the echo signal belonging to the m-th transmitted pulse on each receiving channel, and uses the extracted sampling point sequence as the m-th sub-segment. For each receiver, sub-segments are extracted sequentially according to the time sequence number of the transmitted pulse, so that the echoes corresponding to different transmitted pulses on a receiving channel are separated into independent sub-segments that do not overlap in time. The data acquisition module groups all the separated sub-segments according to the receiver number and the transmitted pulse number, and outputs them to the matrix construction module.

[0036] Example 3

[0037] In practice, the matrix construction module performs phase demodulation on each sub-segment to obtain a phase difference sequence. The matrix construction module obtains a sub-segment from the data acquisition module; this sub-segment is a discrete-time sampling sequence, and the total number of sampling points in the sub-segment is... The sampling points are arranged in chronological order from 1 to... Numbering. At the same time, the matrix construction module obtains the reference waveform of the transmit pulse corresponding to the sub-segment. The reference waveform of the transmit pulse is a waveform sample synchronously acquired and stored from the transmit excitation end by the signal processing unit when the pulse is transmitted. The waveform sample has the same sampling rate as the sub-segment, and the starting sampling point of the waveform sample is aligned with the starting sampling point of the sub-segment on the time base.

[0038] The matrix construction module performs orthogonal demodulation on the sub-segments and the reference waveforms of the transmitted pulse. The orthogonal demodulation process is as follows: the sampled sequence of the sub-segment is multiplied by the in-phase reference signal generated from the reference waveform of the transmitted pulse to obtain an in-phase product sequence; the sampled sequence of the sub-segment is multiplied by the quadrature reference signal generated from the reference waveform of the transmitted pulse to obtain a quadrature product sequence. The in-phase reference signal is the reference waveform of the transmitted pulse itself, and the quadrature reference signal is the signal with a 90-degree phase shift obtained after Hilbert transform of the reference waveform of the transmitted pulse. The in-phase product sequence is passed through a low-pass filter with a cutoff frequency of 0.2 times the center frequency of the transmitted pulse. The filtered sequence is the in-phase component. The value of each sampling point is denoted as Passing the orthogonal product sequences through the same low-pass filter, the resulting sequence is the orthogonal component. The orthogonal component is the sequence of the first orthogonal product. The value of each sampling point is denoted as ,in The value range is 1 to .

[0039] The matrix construction module calculates the instantaneous phase from the in-phase and quadrature components. For each sampling point... Instantaneous phase Through in-phase components and orthogonal components The arctangent operation yields:

[0040]

[0041] in, Indicates the first The instantaneous phase of each sampling point, in radians, with a value range of [value missing]. ; Indicates the number of low-pass filters after the first pass. The in-phase component values ​​at each sampling point are dimensionless. Indicates the number of low-pass filters after the first pass. The orthogonal component values ​​of each sampling point are dimensionless. When it is zero, according to The positive and negative will Take respectively or The matrix construction module obtains all After obtaining the instantaneous phase of each sampling point, a phase difference sequence is constructed by taking the difference between the instantaneous phases of adjacent sampling points. For the sequence number... From 2 to The sampling points are used to calculate the phase difference. Phase difference equal minus The obtained phase difference is subjected to phase unwrapping processing. When the phase difference value between adjacent instants exceeds... At that time, the phase difference Add or subtract An integer multiple of , such that the phase difference is continuous and its absolute value is no greater than . The length of the unwrapped phase difference sequence is... , recorded as The matrix construction module uses the aforementioned phase difference sequence as the phase demodulation output of this sub-segment. For each sub-segment, the matrix construction module performs the same orthogonal demodulation, instantaneous phase calculation, and difference of instantaneous phase between adjacent sampling points to generate a phase difference sequence corresponding to each sub-segment. All phase difference sequences are stored according to the receiver number and transmit pulse number corresponding to the sub-segment for subsequent phase difference matrix construction.

[0042] Example 4

[0043] In practical implementation, the matrix construction module constructs a phase difference matrix based on the phase difference sequences of multiple sub-segments. The matrix construction module obtains the phase difference sequences corresponding to all sub-segments of all receivers under all transmitted pulses from the data acquisition module. Let the total number of receivers in the ultrasonic sensor array module be... The total number of pulses emitted by the signal processing unit in one complete scan cycle is For the first The receiver in the first For each segment acquired under the excitation of a transmit pulse, the matrix construction module has generated a corresponding phase difference sequence, which is denoted as [missing information]. ,in This represents the length of the phase difference sequence. The matrix construction module extracts a representative phase difference value from each phase difference sequence. The extraction of the representative phase difference value is based on: selecting an index within the phase difference sequence. The corresponding phase difference value is used as the representative phase difference value. ,index From the transmitter to the The theoretical two-way propagation time corresponding to the straight-line distance of each receiver is determined by the number of sampling points. The calculation method is to divide the theoretical two-way propagation time by the sampling period and then round down. The matrix construction module represents the phase difference. To construct a complex element for the argument, we substitute the argument into the complex exponential function. ,in This represents the imaginary unit. The matrix construction module arranges the complex elements constructed from the same receiver under different transmission pulses according to the transmission pulse timing, forming a row vector. The length of the row vector is equal to... The complex elements constructed from different receivers under the same transmitted pulse are arranged according to the spatial grid arrangement of the receivers in the ultrasonic sensing array module, forming a column vector. The length of the column vector is equal to... Following the above arrangement, the matrix construction module obtains a matrix with dimension [missing information]. take A two-dimensional complex matrix, denoted as the measured phase difference matrix. Measured phase difference matrix The Middle Line 1 Column elements That is, the receiver In transmitting pulse Complex elements.

[0044] It is understandable that the matrix construction module constructs the measured phase difference matrix. In some implementations, the dimensionality reduction of the phase difference sequence is not limited to taking a single representative value. In other implementations, principal component analysis can be performed on the phase difference sequence, and the coefficients corresponding to the first principal component can be taken to form complex elements to ensure information integrity and consistency of matrix dimension.

[0045] The leakage location module utilizes the measured phase difference matrix The sound velocity distribution of the medium inside the test area is reconstructed using a phase inversion algorithm. The leakage location module first discretizes the test area into multiple voxels. The test area is defined as the space enclosed by all the walls where the ultrasonic sensor array modules are arranged, with uniform step sizes in three mutually perpendicular directions. Divide and discretize into a total of Voxel number , Step length The frequency is set to one-quarter of the wavelength of the ultrasonic wave in the medium under test, corresponding to the highest frequency of all emitted pulses. Each voxel is assigned an initial velocity of sound. Initial speed of sound The initial sound velocity value is obtained from the preset material sound velocity table based on the material type of the wall in the area to be tested. For concrete walls, the initial sound velocity value is 4000 m / s; for brick walls, the initial sound velocity value is 3200 m / s.

[0046] The leakage location module calculates the theoretical propagation time and theoretical phase difference for each transmit-receive path based on the current sound velocity values ​​of each voxel. For the transmitted pulse... The corresponding transmitter and receiver The constructed transmit-receive path is determined by linear ray tracing to identify the propagation path of the ultrasonic beam in three-dimensional voxel space. The voxel traversal of this transmit-receive path is recorded. Path length When the path does not pass through a voxel At that time, path length It is zero. The sound speed distribution is... The theoretical propagation time of the transmit-receive path under given conditions. The following is obtained by summing the propagation time through each voxel:

[0047]

[0048] in, Indicates the first The transmitter corresponding to the first transmitted pulse... The theoretical propagation time between receivers, in seconds; Indicates the first The receiver and the first The straight-line propagation path between the transmitters corresponding to the first transmitted pulse passes through the first... The path length of an individual element, in meters; Indicates the first The current sound speed of the individual element, in meters per second. The leak location module is based on the theoretical propagation time. and transmit pulse angular frequency Calculate the theoretical phase difference The calculation relationship is as follows and normalize the results to the interval. Internally, the leakage location module then uses the theoretical phase difference... Generate theoretical complex elements The phase difference matrix between the theoretical and measured phase difference is composed of all theoretical complex elements. Theoretical phase difference matrix of the same dimension .

[0049] The leakage location module constructs an objective function, which is the theoretical phase difference matrix. Phase difference matrix with actual measurement Sum of squared residuals between Sum of Squared Residuals The expression is to make all The leakage location module is the sum of the squares of the moduli of the complex differences between the elements. It uses an iterative algorithm to minimize the sum of squared residuals. In each iteration, the leakage location module calculates the residual vector. residual vector The complex residuals corresponding to all transmit-receive paths The residual vector is formed by stacking columns in priority. The length is The leakage location module is for the first... sound velocity value of individual elements Calculate the residual vector The partial derivative of each element with respect to the speed of sound is specifically calculated by taking the real and imaginary parts of the complex residual with respect to the speed of sound. The partial derivatives are calculated for all voxels and all transmit-receive path combinations, and then assembled into a Jacobian matrix. Jacobian matrix The number of rows is The number of columns is Jacobian matrix The corresponding residual vector in the middle Individual components and voxels The elements are ,in Represents the residual vector The One portion, The leakage location module solves the normal equations using the conjugate gradient method. To obtain the sound speed correction vector Sound speed correction vector The length is , its first Each component Corresponding voxel The sound speed correction. The search direction used in the conjugate gradient method is initialized to the negative gradient direction. The maximum number of internal iterations is set to 30. The sound speed correction vector is then obtained. Then, the leakage location module proceeds in fixed steps. Update the speed of sound values ​​for all voxels: ,in Indicates the first After the second iteration, the voxel The speed of sound, This represents the updated speed of sound value, with a fixed step size. Set the value to 0.015. Fixed step size. The basis for choosing 0.015 is that, within the typical sound velocity range of 3000m / s to 5000m / s in concrete walls, the relative change in a single sound velocity update does not exceed 0.5%, which can effectively reduce the number of iterations and avoid sound velocity value oscillation.

[0050] The leakage location module recalculates the theoretical phase difference matrix after each update of the sound velocity value. and residual sum of squares When the sum of squared residuals Drop to preset threshold The relative change in the sum of squared residuals between the following or two consecutive iterations is less than Stop iteration when the threshold is reached. Take as The value was obtained by Monte Carlo simulation of the phase difference measurement uncertainty caused by background noise. In the simulation, a phase jitter of 0.02 radians was superimposed on the standard sound speed model, and the calculated average sum of squared residuals was used as the preset threshold. The reference values ​​are obtained. After the iteration, the leakage location module obtains the final sound velocity values ​​of each voxel, which constitute the sound velocity distribution of the medium inside the test area.

[0051] Example 5

[0052] In practical implementation, the leakage location module extracts the leakage point location from the sound velocity distribution obtained after the phase inversion algorithm iteration terminates. The sound velocity value corresponding to each individual element, the first The sound velocity value of an individual element is denoted as The leakage location module first determines the normal background sound velocity value. The process for determining the normal background sound velocity value is as follows: for all... Histogram analysis was performed on the sound velocity values ​​of individual units. The sound velocity values ​​were divided into several equally wide intervals from the minimum to the maximum value, with the interval width set to [value missing]. The number of voxels falling into each interval is counted to obtain a histogram distribution. On the histogram, the interval with the largest number of voxels is found, and the midpoint of the corresponding range of sound velocity values ​​is taken as the normal background sound velocity value, denoted as . When multiple intervals have the same maximum count, the average of the midpoint values ​​of these intervals is taken as the normal background sound velocity value.

[0053] Optionally, before histogram statistics, median filtering is applied to all voxel sound velocity values ​​in the sound velocity distribution, with a filter window size of [size missing]. Individual voxels are used to eliminate the impact of abrupt changes in the sound velocity values ​​of individual voxels on background estimation.

[0054] The leak location module then calculates the noise standard deviation. The noise standard deviation is calculated as follows: for each voxel... Calculate the speed of sound Compared to normal background sound velocity value absolute value of deviation The deviation sequence is obtained. The standard deviation of the deviation sequence is calculated and used as the noise standard deviation, denoted as . The preset noise standard deviation multiple is set to [value missing]. Multiples The basis is: under the assumption that the sound velocity in the wall medium follows a normal distribution, the sound velocity deviation exceeds... The probability is lower than This can be considered a significant anomaly caused by leakage.

[0055] The leakage location module identifies voxels with sound velocity values ​​below the normal background sound velocity and deviations exceeding a preset noise standard deviation multiple as abnormal voxels. The specific criteria are as follows: for voxels... At the same time satisfy and The voxels are marked as anomalous voxels.

[0056] The leakage location module extracts candidate regions from all anomalous voxels. The extraction method employs 3D connected component analysis, with a connectivity criterion of 26-neighbor connectivity; that is, two anomalous voxels are considered connected if they share a face, an edge, or a vertex. Connected components are labeled for all anomalous voxels, resulting in several connected components. For each connected component, the number of consecutive voxels it contains is counted. A minimum volume threshold is set. Individual elements. Minimum volume threshold is set to... The basis for individual elements is: when the discretization step size When the wavelength is one-quarter of the highest frequency, The volume of the cube enclosed by the individual units is approximately This volume is comparable to the minimum perceptible wet patch volume formed in the early stages of building leakage, and can filter out spurious candidate regions caused by isolated noise voxels. Connected regions with more than the minimum volume threshold are used as candidate regions, and each candidate region corresponds to the spatial range of a possible leakage point.

[0057] For each candidate region, the leak location module calculates the spatial gradient modulus of the sound velocity values ​​within that region. For any voxel within the candidate region, its spatial coordinates are indexed by integers in a three-dimensional discrete grid. The speed of sound is denoted as . Spatial gradient magnitude The calculation formula is:

[0058]

[0059] in, Voxel representation The spatial gradient modulus of the sound velocity at a given location, in units of ; Voxel representation exist The velocity of sound of the next adjacent voxel in the direction, in units of ; Voxel representation exist The velocity of sound of the adjacent voxel in the direction; direction and The meanings of directional symbols follow the same pattern; is the voxel discretization step size, in meters. For voxels on the candidate region boundary, when adjacent voxels are outside the candidate region, the gradient component in that direction is not included in the calculation, and the denominator remains the same. The sound velocity value of the missing adjacent voxel is replaced by the sound velocity value of the voxel itself in the molecule.

[0060] The leakage location module traverses all voxels within the candidate region, calculates the spatial gradient modulus of the sound velocity value for each voxel, and selects the voxel with the maximum modulus. The spatial coordinates of the voxel containing the maximum modulus are then determined. This serves as the center point of the candidate region. Spatial coordinates are based on the voxel grid index and step size. Converting to actual spatial coordinates, the conversion relationship is as follows: , , ,in The coordinates are the actual spatial coordinates of the discretization origin of the region to be measured. When multiple voxels within the same candidate region have the same maximum gradient magnitude, the average of these voxel spatial coordinates is taken as the center point coordinates.

[0061] The leakage location module performs the aforementioned center point location operation on all candidate areas, collecting the spatial coordinates of the center point output for each candidate area to form a coordinate set. The leakage location module outputs this coordinate set as the leakage point location set, where each element in the coordinate set represents the three-dimensional spatial location of a leakage point.

[0062] See Figure 4 The figure shows a statistical histogram of the reconstructed sound velocity distribution within the medium of the measured region. The horizontal axis of the histogram represents the sound velocity value in meters per second (m / s), and the vertical axis represents the number of voxels within the corresponding sound velocity range. The sound velocity range is divided into equal-width intervals, each 20 m / s wide. The histogram shows that the sound velocity values ​​are mainly concentrated in the range of 3800 m / s to 4300 m / s, with the voxel count reaching its peak near this interval, indicating that this range corresponds to the normal background sound velocity range. The normal background sound velocity values ​​are marked with a solid green line in the figure. The value is the midpoint of the interval with the most voxels in the histogram, approximately 4000 m / s, which matches the preset initial sound velocity value for concrete walls.

[0063] The anomaly detection threshold is represented by the red dashed line in the figure. The threshold is approximately 3500 m / s, which is three times the normal background sound velocity value minus the noise standard deviation. This threshold is used to identify anomalous voxels; voxels with sound velocities significantly lower than the normal background value and a deviation exceeding three times the noise standard deviation are marked as anomalous. The number of voxels with sound velocities below this threshold is relatively small, distributed between 2750 m / s and 3500 m / s, and is shown as the low-frequency region on the left side of the histogram in the figure. These voxels represent potential leakage anomalous voxels.

[0064] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes 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.

Claims

1. A house leak point location system based on ultrasonic array, characterized in that, include: An ultrasonic sensing array module comprises multiple ultrasonic transmitters and receiver arrays arranged in the area to be measured, as well as a signal processing unit. The signal processing unit controls the multiple ultrasonic transmitters to emit ultrasonic waves according to a preset time and frequency sequence, and simultaneously controls the receiver array to synchronously acquire reflected echo signals. The data acquisition module divides the received echo signal into multiple segments according to a time window, with each segment corresponding to a transmission pulse; The matrix construction module performs phase demodulation on each sub-segment to obtain a phase difference sequence, and constructs a phase difference matrix based on the phase difference sequences of multiple sub-segments; The leakage location module uses the phase difference matrix to reconstruct the sound velocity distribution of the medium inside the test area through a phase inversion algorithm, and locates the leakage point based on the abnormal area in the sound velocity distribution.

2. The house leakage point location system based on ultrasonic array according to claim 1, characterized in that, The array of multiple ultrasonic transmitters and receivers is arranged as follows: Transmitters and receivers are arranged in an equally spaced grid on multiple walls of the area to be tested. Each transmitter corresponds to a set of adjacent receivers to form a subarray, and the coverage areas of each subarray overlap.

3. The house leakage point location system based on ultrasonic array according to claim 1, characterized in that, The preset timing and frequency sequences are set as follows: Single-frequency pulses are emitted sequentially in the order of low frequency first and then high frequency. The time interval between adjacent pulses is greater than the two-way propagation time of the maximum detection depth, and the frequency values ​​are selected at equal attenuation intervals on the ultrasonic attenuation characteristic curve of the medium under test.

4. The house leakage point location system based on ultrasonic array according to claim 1, characterized in that, When the received echo signal is divided into multiple segments according to a time window, the start time of each time window is determined by the transmission time of the corresponding transmission pulse plus a fixed propagation delay, and the window length is equal to the sum of the duration of the transmission pulse and the maximum expected echo broadening.

5. The house leakage point location system based on ultrasonic array according to claim 1, characterized in that, The step of demodulating each sub-segment to obtain the phase difference sequence includes: Each segment is orthogonally demodulated with the reference waveform of the corresponding transmitted pulse to extract the in-phase component and the quadrature component; The instantaneous phase is obtained by calculating the arctangent of the in-phase component and the quadrature component; The phase difference sequence is obtained by taking the difference between the instantaneous phases of adjacent sampling points.

6. The house leakage point location system based on ultrasonic array according to claim 1, characterized in that, The construction of a phase difference matrix based on the phase difference sequence of multiple segments includes: Arrange the phase difference sequence of the same receiver under different transmitted pulses in chronological order as a row vector; The phase difference sequences of different receivers under the same transmitted pulse are arranged in spatial order as a column vector; It forms a two-dimensional complex matrix with the dimension being the number of receivers multiplied by the number of transmitted pulses.

7. The house leakage point location system based on ultrasonic array according to claim 1, characterized in that, The process of reconstructing the sound velocity distribution of the medium inside the region under test using the phase difference matrix and a phase inversion algorithm includes: The region to be measured is discretized into multiple voxels, and each voxel is assigned an initial sound velocity value. The theoretical propagation time for each transmit-receive path is calculated based on the speed of sound, and then the theoretical phase difference is calculated. The sum of squared residuals between the theoretical and measured phase difference matrices is minimized iteratively. In each iteration, the sound velocity value of each voxel is corrected according to the direction of the residual gradient until the residual converges to a preset threshold.

8. The house leakage point location system based on ultrasonic array according to claim 7, characterized in that, In each iteration, when correcting the sound velocity value of each voxel according to the residual gradient direction, the partial derivative of each voxel with respect to the theoretical phase difference of all paths is calculated to construct the Jacobian matrix. Then, the product of the transpose of the Jacobian matrix and the residual vector is solved by the conjugate gradient method to obtain the sound velocity correction amount of each voxel. The sound velocity value is then updated with a fixed step size.

9. The house leakage point location system based on ultrasonic array according to claim 1, characterized in that, The step of locating the leak point based on the abnormal area in the sound velocity distribution includes: Regions with sound velocity values ​​lower than the normal background sound velocity values ​​and a number of continuous voxels exceeding the minimum volume threshold are extracted from the reconstructed sound velocity distribution as candidate regions. Calculate the spatial gradient modulus of the sound velocity value in each candidate region, and select the spatial coordinates of the voxel where the maximum modulus value is located as the center point of the candidate region. Output the set of coordinates of all center points as the location of the leak.

10. The house leakage point location system based on ultrasonic array according to claim 9, characterized in that, The normal background sound velocity value is obtained by performing histogram statistics on the sound velocity values ​​of all voxels in the reconstructed sound velocity distribution, and taking the sound velocity value corresponding to the peak value of the histogram as the normal background sound velocity value. Voxels that are lower than the peak sound velocity value and whose deviation exceeds a preset noise standard deviation multiple are judged as abnormal voxels.

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