Acoustically coded transmission and deconvolution

Abstract

Coded transmissions (e.g., transmitting pulse sequences corresponding to specified codes) may be used for corresponding acoustic transmission events in non-destructive testing. An enhanced A scan may be constructed by convolving a specified finite impulse response filter profile with a time domain representation of received acoustic echo data. The method can be used for improving the dynamic range or the signal-to-noise ratio, or allowing lower analog gain to be used to avoid saturation of the received signal processing chain due to characteristics such as front wall echo.

Description

Cross-reference to related applications

[0001] This patent application claims the benefit of priority to U.S. Provisional Patent Application No. 63 / 520,509 (Attorney General’s Case No. 6409.268PRV), filed August 18, 2023, entitled “Encoded Emissions Using FIR Deconvolution,” which is hereby incorporated herein by reference. Technical Field

[0002] This document generally relates to (but is not limited to) nondestructive evaluation, and more specifically to apparatus and methods for providing coded emission and corresponding detection techniques (e.g., for acoustic imaging). Background Technology

[0003] Non-destructive testing (NDT) can refer to the use of one or more different techniques to inspect the surface or internal areas of an object, such as to determine the presence of defects or flaws, or to otherwise characterize the object being inspected. Examples of NDT methods may include eddy current testing, in which electromagnetic energy is applied to an object and the induced current generated on or inside the object is detected. The detected current (or associated impedance) value provides a structural indication of the object under test, such as indicating the presence of cracks, voids, pores, or other non-uniformities.

[0004] Another non-destructive testing method may involve employing acoustic testing techniques, such as using one or more electroacoustic transducers to acoustically irradiate the surface or internal region of the object under test, detecting and processing the scattered or reflected acoustic energy. This scattered or reflected energy can be referred to as an acoustic echo signal. Typically, such acoustic testing schemes involve using sound frequencies within the ultrasonic frequency range, such as pulses with energy within a specified range; as an illustrative example, this range may include values ​​from hundreds of kilohertz to tens of megahertz. Summary of the Invention

[0005] Acoustic testing (e.g., ultrasound-based testing) may include employing a single transducer or an array of such transducers, including providing focusing or beamforming techniques to aid in constructing a data map or image representing a region of interest on or within the surface of the sample under test. Using an array of ultrasonic transducer elements may include employing a phased array beamforming method, which may be referred to as Phased Array Ultrasonic Testing (PAUT). For example, delay-stack beamforming techniques may be employed, involving coherent summation of the time-domain representations of received acoustic signals from the respective transducer elements or apertures. Total Focusing Method (TFM) beamforming techniques utilize data acquired by one or more elements (or apertures defined by these elements) in an array to transmit acoustic pulses and utilize other elements to receive scattered or reflected acoustic energy, constructing a matrix represented by a time series (e.g., A-scan) corresponding to a transmit-receive periodic sequence, wherein the transmission is performed by different elements (or corresponding apertures) in the array.

[0006] This matrix-capture acquisition scheme, which acquires A-scan data for each element (or each defined aperture) in the array, can be called "full matrix acquisition" (FMC) technology. Similar to total focusing imaging, a phase-based approach can be used for one or more of the acquisition, storage, or subsequent analysis. This phase-based approach may include coherent summation of a normalized or quantized representation of the A-scan data corresponding to phase information. This approach can be called "phase-coherent imaging" (PCI) beamforming technology. Other imaging methods include plane-wave imaging (PWI), and the techniques described herein are generally applicable to various PAUT acquisition and beamforming techniques.

[0007] The inventors recognize that, among other things, one of the challenges facing acoustic imaging technology is that the detectable amplitude range or "dynamic range" of the received acoustic echo signal may make it difficult to suppress strong front wall echo signals (or other strong reflective features) while detecting weak reflected echo signals associated with defects, flaws, or other features of interest. In one approach, the transmitted signal strength or receiver gain can be adjusted (e.g., enhanced) to detect weak reflective features, but this enhancement can generate front wall echo signals that saturate the receiver signal processing chain (whether in the analog or digital domain). This saturation can mask features near the front wall echo or other strong reflectors or scatterers. Reducing the transmit power or receiver gain can help suppress this saturation, but may result in weak reflected echo signals being submerged under the noise floor of the receiver signal processing chain.

[0008] The inventors recognized that, among other things, coded transmission methods (e.g., pulse sequences corresponding to a specified code) can be used for the corresponding transmission events to address one or more of the aforementioned challenges. Enhanced A-scans can be constructed by convolving a specified finite impulse response filter profile with a temporal representation of the received acoustic echo data (or by a correlation-based detection method evaluated using the original coded sequence). Using coded transmission can improve dynamic range or signal-to-noise ratio (SNR), or allow the use of lower analog gain to avoid saturation of the receive signal processing chain due to features such as front wall echoes, while still being able to resolve weak reflection features of interest.

[0009] In one example, a machine-implemented method may be used to perform acoustic detection or other acoustic evaluation, wherein the method includes: generating a corresponding acoustic impulse transmission using a specified pulse sequence corresponding to a specified code, and acquiring acoustic echo data indicating scattered or reflected acoustic energy in response to the corresponding acoustic impulse transmission. The method may include applying a correlation-based detection method or a deconvolution filter to provide filtered acoustic echo data. For example, the method may include filtering the acquired acoustic echo data using a finite impulse response (FIR) filter to provide filtered acoustic echo data. Imaging or beamforming may be performed, for example, by coherently summing the representation of the filtered acoustic echo data to provide pixel or voxel element values ​​in an image, wherein a series of such sums is used to form an image for storage or display.

[0010] In one example, a machine-implemented method may include establishing or evaluating candidate codes for an coded emission scheme for acoustic detection. The machine-implemented method includes: establishing a code for acoustic impulse transmission defined by a specified impulse sequence that exhibits zero-valued autocorrelation sidelobes at odd-valued sample offsets; and establishing a finite impulse response (FIR) filter for filtering acquired acoustic echo data received in response to the acoustic impulse transmission, the FIR filter providing deconvolution of the specified impulse sequence. For example, according to a potential “pseudo-back” candidate code, a second half of the specified impulse sequence following the midpoint of the specified impulse sequence comprises a mirror image of the first half of the specified impulse sequence, but with alternating signs for each consecutive bit.

[0011] In one example, a system for performing acoustic detection or other acoustic evaluation includes a pulse generator circuit, a receiver circuit, at least one processor circuit, and a memory circuit that includes instructions that, when executed by the at least one processor circuit, cause the system to perform one or more machine-implemented methods shown and described herein, such as the methods discussed above.

[0012] This overview is intended to provide a general overview of the subject matter of this patent application and is not intended to provide an exclusive or exhaustive interpretation of the invention. Detailed description is provided to offer further information regarding this patent application. Attached Figure Description

[0013] In the accompanying drawings (which are not necessarily drawn to scale), the same reference numerals may denote similar components in different views. Similar reference numerals with different letter suffixes may denote different instances of similar components. The accompanying drawings illustrate, by way of example and not limitation, the various embodiments discussed herein.

[0014] Figure 1The overall illustration includes examples of acoustic detection systems, which may be used to perform at least a portion of one or more techniques shown and described herein.

[0015] Figure 2 An illustrative example is shown, including A-scan acquisition, where saturation occurs due to acoustic echoes from the front wall of the object under test.

[0016] Figure 3A An illustrative example of a numerical sequence corresponding to a 13-bit Barker code is shown, which can be used as a pulse sequence for encoded transmission.

[0017] Figure 3B It shows the corresponding Figure 3A An illustrative example of the autocorrelation function of a 13-bit Barker code.

[0018] Figure 4A An illustrative example is shown, including defining the coefficients of a finite impulse response (FIR) filter, which can be used, for example, to deconvolve an acoustic echo signal generated in response to an acoustic transmission produced using coded emission.

[0019] Figure 4B It shows the use of Figure 4A An illustrative example of the deconvolution response obtained after filtering an input time series using FIR filter coefficients, where the input time series includes... Figure 3A The encoded transmit pulse sequence in the middle.

[0020] Figure 5 The overall diagram illustrates the relationship between the average noise power and different coded sequence lengths, as well as the limits defined in the analysis.

[0021] Figure 6A An illustrative example of a 39-bit pseudo-Barker code that can be used to encode a sequence of transmitted pulses is shown.

[0022] Figure 6B It shows the corresponding Figure 6A An illustrative example of the autocorrelation function encoded in 39-bit NyQu.

[0023] Figure 6C An illustrative example of an FIR deconvolution filter is shown, which can be used to respond to... Figure 6A The acoustic echo signal generated by the acoustic transmission corresponding to the 39-bit code in the code is filtered.

[0024] Figure 6D It shows the use of Figure 6C An illustrative example of the deconvolution response obtained after filtering an input time series using FIR filter coefficients, where the input time series includes... Figure 6A The encoded transmit pulse sequence in the middle.

[0025] Figure 7 The overview illustrates the workflow that can be used to evaluate potential candidate codes (defining the transmission pulse sequence) and the techniques for selecting codes.

[0026] Figure 8 The overall presentation illustrates a technique, for example, a machine implementation method for coded emission and related detection in an acoustic detection system.

[0027] Figure 9A , Figure 9B and Figure 9C Several illustrative examples of images generated using TFM beamforming are shown: Figure 9A This demonstrates TFM beamforming without using coded transmission; Figure 9B TFM beamforming using coded transmission and detection employing a correlation-based method is illustrated. Figure 9C TFM beamforming using an FIR filter to perform deconvolution is shown.

[0028] Figure 10A , Figure 10B and Figure 10C Several illustrative examples of images generated using TFM beamforming are shown: Figure 10A This demonstrates TFM beamforming performed without coded transmission when noise is added to the input A-scan data; Figure 10B The TFM beamforming performed in the presence of noise is shown, including averaging of 13 images, where the noise signal added to the underlying A-scan data is random and varies between multiple trials; Figure 10C TFM beamforming with deconvolution performed using an FIR filter is shown, where noise is added but no averaging is performed.

[0029] Figure 11A , Figure 11B and Figure 11C Several examples of B-scan images are shown: Figure 11A The image acquisition is shown without coded transmission and with a center frequency of 0.5 MHz; Figure 11B The image acquisition is shown without coded transmission and with a center frequency of 5.0 MHz; Figure 11C Image acquisition using coded transmission is shown, with a center frequency of 5.0 MHz and deconvolution using an FIR filter.

[0030] Figure 12 A block diagram is shown that includes an example machine on which any one or more of the techniques (e.g., methods) described herein can be executed. Detailed Implementation

[0031] Nondestructive testing of structures can be performed using acoustic techniques, such as ultrasonic testing utilizing phased array transducer architectures and related processing (e.g., beamforming and imaging). As mentioned above, the interpretation of the acquired test data or related images can face various challenges. Saturation in the receiver signal processing chain (e.g., due to strong front wall echoes induced by the object under test) can mask other weak reflection features of interest. In one approach, multiple acquisition and imaging operations can be performed, for example, using different transmit power or receiver gain settings. Using multiple acquisitions in this way can negatively impact detection efficiency, such as slowing down the detection process or even causing weak reflection features located near strong reflection features to go undetected. The methods described in this document can be used to enhance one or more measurements of the dynamic range of amplitude measurements in acoustic testing, or to enhance (e.g., increase) the signal-to-noise ratio (SNR), or both. Such enhancement can suppress saturation in A-scan data (e.g., suppressing clipping in the digital domain or saturation in the analog front end), or saturation in generated images formed using techniques such as plane wave imaging (PWI) or total focusing (TFM) beamforming.

[0032] Figure 1 The overall illustration includes an example of an acoustic detection system 100, which may be used to perform at least a portion of one or more techniques shown and described herein. The detection system 100 may include a tester 140, such as a handheld or portable assembly. The tester 140 may be electrically coupled to a probe assembly 150 using, for example, a multi-conductor interconnect 130. The probe assembly 150 may include one or more electroacoustic transducers, such as a transducer array 152 including respective transducers 154A to 154N. The transducer array may follow a linear or curved profile, or may include an array of elements extending along two axes (e.g., a matrix providing transducer elements). The elements need not be in a square layout or arranged along a linear axis. Element size and spacing may vary depending on the detection application.

[0033] Modular probe assembly 150 can be configured, allowing tester 140 to be used with a variety of different probe assemblies. Typically, transducer array 152 includes piezoelectric transducers, for example, that can be acoustically coupled to a target 158 ​​(such as a test sample or "test object") via coupling medium 156. The coupling medium may include fluids, gels, or solid films (such as elastomers or other polymeric materials), or combinations of fluid, gel, or solid structures. For example, the acoustic transducer assembly may include a transducer array coupled to a wedge-shaped structure comprising a rigid thermosetting polymer (such as Rexolite® from C-Lec Plastics) with known acoustic propagation characteristics. During testing, water can be injected between the wedge-shaped structure and the test object as the coupling medium 156, or testing can be performed with the interface between probe assembly 150 and target 158 ​​immersed in the coupling medium.

[0034] The tester 140 may include digital and analog circuitry, such as front-end circuitry 122, which includes one or more transmitter signal chains, receiver signal chains, or switching circuitry (e.g., transmit / receive switch circuitry). The transmitter signal chain may include amplifier and filter circuitry to transmit transmission pulses to the probe assembly 150 via interconnection 130 to acoustically illuminate the target 158, thereby imaging or otherwise detecting defects 160 on or within the surface of the target 158 ​​structure by receiving acoustic energy scattered or reflected in response to the acoustic illumination.

[0035] Although Figure 1 A single probe assembly 150 and a single transducer array 152 are shown, but other configurations are also possible, such as connecting multiple probe assemblies to a single tester 140, or using multiple transducer arrays 152 in conjunction with a single probe assembly 150 or multiple probe assemblies for transmit / receive detection modes. Similarly, test protocols can be executed collaboratively by multiple testers 140, for example, in response to an overall test scheme established by a master tester 140, or a scheme established by other remote systems (e.g., computing facility 108 or general-purpose computing devices such as laptop 132, tablet, smartphone, desktop computer, etc.). This test scheme can be established according to publicly available standards or regulatory requirements and, as an illustrative example, can be implemented during the initial manufacturing phase or performed periodically for continuous monitoring.

[0036] The receiver signal chain of the front-end circuitry 122 may include one or more filter or amplifier circuits, and an analog-to-digital converter to digitize the echo signal received using the probe assembly 150. Digitization may be performed coherently to provide multi-channel digitized data that is time- or phase-aligned or referenced to each other. The front-end circuitry may be coupled to and controlled by one or more processor circuits, such as processor circuitry 102 included as part of the test instrument 140. The processor circuitry may be coupled to memory circuitry 104 to execute instructions causing the test instrument 140 to perform one or more operations related to acoustic transmission, acoustic acquisition, processing, or storage of data associated with acoustic testing, or to perform other techniques shown and described herein. The test instrument 140 may be communicatively coupled to other parts of the system 100, for example, using a wired or wireless communication interface 120.

[0037] For example, the execution of one or more of the techniques shown and described herein can be performed on test instrument 140 or using other processing or storage devices, such as computing facility 108 or general-purpose computing devices (e.g., laptop 132, tablet, smartphone, desktop computer, etc.). For example, processing tasks that would be inefficient or beyond the capabilities of test instrument 140 if performed on test instrument 140 can be performed remotely (e.g., on a stand-alone system), for example, in response to a request from test instrument 140. Similarly, storage of imaging data or intermediate data (e.g., an A-scan matrix of time-series data or other representations of such data) can be performed using a remote facility communicatively coupled to test instrument 140. The test instrument may include display 110 (e.g., for presenting configuration information or results) and input devices 112 (e.g., including one or more of a keyboard, trackball, function keys or soft keys, mouse interface, touchscreen, stylus, etc.) for receiving operator commands, configuration information, or responding to queries.

[0038] Many acoustic inspection methods may have limitations in dynamic range or signal-to-noise ratio (SNR) when imaging the structure under inspection. For example, total focusing (TFM) beamforming methods using full matrix acquisition (FMC) may face challenges in terms of SNR. For instance, TFM beamforming using FMC typically involves one transducer or one aperture for transmission, while other transducers receive the acoustic echo signal. Therefore, this transmission may lack penetration compared to plane wave imaging (PWI) because fewer transducer elements are used per transmission event (or typically a single transducer element). This effect may also occur when using sparse acquisition methods. Sparse acquisition may involve operations below those of full matrix acquisition, where a single transmission event may again involve only a single element, and fewer transmit-receive acquisitions are used for beamforming summation. Typically, sparse acquisition may exhibit a lower SNR compared to full aperture acquisition. In corrosion and composite material inspection, operators may need to increase the simulation gain to observe multiple reflections or search for back wall echoes in thick samples. However, increasing the gain can lead to front wall echo saturation, thereby complicating processing and related imaging tasks. The techniques described herein can be used to enhance the signal-to-noise ratio or provide enhanced dynamic range (or both), as in the use cases or applications mentioned above.

[0039] For example, Figure 2 An illustrative example is shown, including an A-scan acquisition 200, where saturation occurs at 224 due to acoustic echoes from the front wall of the object under test. The inventors recognized that several of the aforementioned challenges could be addressed by improving the signal-to-noise ratio of the acquired A-scan data without increasing the analog gain, which could also enhance the dynamic range. This enhanced dynamic range allows for the detection of weak echo signals of interest while suppressing saturation (or clipping in the digital domain) of the analog receiving channel.

[0040] The inventors recognize that, among other things, one method for improving signal-to-noise ratio or dynamic range (or both) may include employing an coded transmit pulse transmission and reception scheme. For example, the Omniscan X3-64 (supplied by Evident Scientific, Waltham, Massachusetts, USA, and Evident Canada, Quebec City, Quebec, Canada) has a transmit pulse generator capable of generating positive and negative pulses, supporting, for example, at least three output states (positive amplitude, zero, negative amplitude). These states can be mapped to positive, negative, and zero output values ​​{+1, 0, -1}, and the encoding of the pulse sequence corresponding to this state can be specified, such that instead of transmitting a single transmit pulse envelope, a pulse sequence with envelope symbols having corresponding binary codes (e.g., including both +1 and -1 states) is transmitted. A coding scheme with high autocorrelation can be selected such that the scheme exhibits a peak in the autocorrelation function when perfectly time-aligned with its own representation (e.g., without sample offset), but its correlation is significantly reduced (or even zero) when evaluated for correlation with its own delayed representation (offset by one or more sample points in either direction, whether forward or backward). These values ​​in the autocorrelation function that are adjacent to the peak or the main lobe can be referred to as "side lobes".

[0041] Gore codes and Barker codes are binary codes that can be used to provide coded transmissions. Gore codes have zero sidelobes and typically involve twice as many (2x) transmission events as uncoded excitations, thus halving their efficiency (e.g., the reciprocal of the acquisition rate). Barker codes are another type of code with a peak in the autocorrelation function, where the ratio of the maximum sidelobe amplitude to the main lobe amplitude is typically 1 / N, where N corresponds to the number of bits in the code (e.g., the bit length). The longest known Barker code is 13, therefore, the corresponding minimum sidelobe amplitude level is -22.3 dB.

[0042] Figure 3A An illustrative example of a numerical sequence corresponding to the aforementioned 13-bit Barker code is shown, which can be used as a pulse sequence for encoding transmission; Figure 3B It shows the corresponding Figure 3A An illustrative example of the autocorrelation function of the 13-bit Barker code, exhibiting a strong main lobe (autocorrelation peak 334).

[0043] In the frequency domain, the convolution process of the encoded emission can be described as follows:

[0044] Formula 1

[0045] in, This represents the encoded transmit response as a function of angular frequency. Indicates impulse response, The inventors recognize that, among other things, a deconvolution process can be used to recover the impulse response, which can be represented as:

[0046] Formula 2

[0047] Deconvolution using spectral techniques may be possible in | |Noise is amplified in regions approaching zero. However, for many binary codes, | | is usually not zero. In the time domain, the deconvolution process can be represented as:

[0048] Formula 3

[0049] Time-domain impulse response function This can be achieved (e.g., approximated) using a finite impulse response (FIR) filter. For example, Figure 4A An illustrative example is shown, including defining the coefficients of a finite impulse response (FIR) filter, which can be used, for example, to deconvolve an acoustic echo signal generated in response to an acoustic transmission produced using coded emission. Figure 4A The FIR filter shown corresponds to Figure 3A The 13-digit Buck code. Figure 4B It shows the use of Figure 4A This is an illustrative example of the deconvolution response (exhibiting a strong peak value of 444) obtained after filtering an input time series using finite impulse response filter coefficients, wherein the input time series includes... Figure 3A The encoded transmit pulse sequence in the middle.

[0050] Because deconvolution processing can be applied to any | The binary code is non-zero, therefore, metrics can be used to evaluate the suitability (e.g., optimality) of candidate codes and their corresponding FIR deconvolution filters. In practical applications, for ease of implementation, the FIR deconvolution filter can be... Truncating to a finite number of taps (e.g., filter coefficients), for example by setting coefficients below a specified amplitude threshold to zero or otherwise discarding them. This can provide... The number of coefficients (e.g., the number of taps) that can be reasonably and precisely represented can be expressed by the following constraint:

[0051] Formula 4

[0052] The above constraints implement an amplitude criterion for evaluating a set of candidate impulse response filter coefficients corresponding to a candidate 5-code. In the above expression, the number N can be determined. tap This quantity corresponds to an amplitude greater than a specified amplitude threshold (here, it corresponds to...). The coefficients (e.g., taps) are one percent of the maximum amplitude. Through empirical evaluation, and illustrated by examples, the number of impulse response filter coefficients (N) observed is... tap ) can be limited to the number of bits (N) in the specified encoding. code A coefficient that is a specified multiple or less of N. For example, as shown below, N tap / N code A ratio less than five (e.g., each bit of the code corresponds to five FIR filter coefficients) can produce useful results, but other ratios can be used based on empirical or numerical evaluation. As a numerical example, if the candidate code length is 20 bits, any associated deconvolution filter... Candidate codes that can be accurately represented by fewer than 100 taps all meet the above 5:1 standard.

[0053] Other constraints (e.g., indices indicating optimality or relative superiority) can be used to help evaluate candidate codes and their associated deconvolution filter coefficients. For example, using coded emission can improve the signal-to-noise ratio by suppressing incoherent random noise. Therefore, quantitative indices can assist in selecting a suitable code by comparing the noise suppression capabilities of different codes. Assuming that the random noise at each time sampling point is statistically independent, the effective noise average power of the binary code and its FIR deconvolution filter can be expressed as:

[0054] Formula 5

[0055] In formula 5 above, Represents the FIR filter The characteristic delay. Since the improvement in signal-to-noise ratio is generally proportional to the square root of the average noise power, it can be expressed as:

[0056] Formula 6

[0057] As an example, Figure 5 The relationship between average noise power and different coded sequence lengths is shown, along with the limits defined by the normalized autocorrelation analysis. As described elsewhere in this paper, codes can be identified where each bit of the code corresponds to a maximum of five coefficients for the FIR deconvolution filter. Figure 5 As shown, the "pseudo" Barker codes developed by the inventors offer performance comparable to Barker codes up to 13 bits long, and such codes up to 49 bits long have been identified. The noise-average power of the non-ideal candidate codes and their associated deconvolution filters is below the analytically defined limit (e.g., the theoretical maximum value) N achievable through normalized autocorrelation. code (For example, using correlation detection instead of FIR filters for deconvolution). Using autocorrelation will always produce non-zero sidelobes in the autocorrelation function.

[0058] While ideally the autocorrelation function sidelobes of the encoded transmit pulse sequence should have zero amplitude, the inventors have discovered, among other things, that the 13-bit Barker code exhibits sidelobes alternating between non-zero and zero values, for example, referring to... Figure 3B , Figure 3B Sample 1 at position 336 is non-zero, while sample 2 at position 338 is zero. The inventors have discovered a new coding class exceeding 13 bits, where the autocorrelation sidelobes at odd-numbered samples in the sequence are zero. Codes satisfying this criterion are referred to herein as "pseudo-Barker" codes. For pseudo-Barker codes of odd length (e.g., odd number of bits), all bits after the midpoint can be deterministically determined, for example, using an analytical expression (where i represents the number of bits):

[0059] Formula 7

[0060] In Formula 7, the second half of the specified pulse sequence after the midpoint 25 (e.g., where, ), including a mirror image of the first half of the specified pulse sequence (wherein, However, the sign of each consecutive bit alternates. Since the pseudo-Barker code is defined according to the above expression, an exhaustive search for the 49-bit pseudo-Barker code is computationally equivalent to an exhaustive search for all possible 25-bit binary codes. The inventors also recognize that, furthermore, suitable FIR deconvolution filter coefficients can be established that satisfy the constraints of Equation 4 above (e.g., the number of taps is a specified multiple of the pseudo-Barker code length and the number is sufficiently small), while providing acceptable noise averaging characteristics according to Equation 5 above.

[0061] Figure 6A An illustrative example of a 39-bit pseudo-Barker code that can be used to encode a sequence of transmitted pulses is shown. (The maximum allowed N...) tap / N code When the ratio is five, such as Figure 6A The optimal 39-bit encoding shown is: [1,1,1,1,1,-1,-1,1,-1,1,1,1,1,-1,-1,-1,-1,-1,-1,-1,-1,1,1,-1,-1,1,-1,1,-1,1,1,-1,1,1,-1,-1,1,-1,1,-1]. As mentioned above, the portion 556 after the midpoint 554 (corresponding to sample 20) of the sequence is a mirror image of the initial portion of the sequence, but the signs of consecutive digits alternate.

[0062] Figure 6B It shows the corresponding Figure 6AAn illustrative example of the autocorrelation function encoded in 39 bits. The correlation peak (main lobe 534) is surrounded by side lobes, where odd-numbered samples have a value of zero. Figure 6C An illustrative example of an FIR deconvolution filter is shown, which can be used to respond to the use of Figure 6A The acoustic echo signal generated by the acoustic transmission corresponding to the 39-bit code in the code is filtered. Figure 6C The diagram shows 157 non-zero filter coefficients (corresponding to 157 "tap"), providing an average noise power of 36, corresponding to a signal-to-noise ratio improvement of 15.6 dB.

[0063] Figure 6D It shows the use of Figure 6C The example illustrates how FIR filter coefficients are used to filter an input time series to obtain a deconvolution response, where the input time series includes... Figure 6A The encoded transmit pulse sequence in the image shows the effect of the FIR deconvolution filter with... Figure 6A When the signal is aligned to the encoded transmit pulse sequence, the expected peak appears at 544. Typically, the number of samples (e.g., length) of the convolutional response can be expressed as N+M-1, where N is the length of the input signal (the encoded sequence in this example) and M is the length of the filter. Figure 6D The input in the example (corresponding to) Figure 6A The 39-bit code has a length of 39, while the FIR filter has a length of approximately 240 samples.

[0064] Figure 7 The overall diagram illustrates a workflow 700 for evaluating potential candidate codes (defining the transmission pulse sequence), and techniques for selecting codes, such as during runtime or when building imaging software or firmware. At 705, during evaluation, candidate or "trial" binary codes 715 can be generated (generated in a random or deterministic manner, e.g., by evaluating pseudo-Barker code candidate schemes using the expression in Equation 7), and the corresponding FIR filter coefficient set can be determined at 720. At 725, a first constraint can be applied, such as corresponding to Equation 4 above and N... tap / N code The ratio is less than five. At 730, a second constraint can be applied, for example, to determine the signal-to-noise ratio improvement caused by noise averaging. At 735, the results can be stored, for example, in a table or other data structure. At 740, for example, using the table formed at 735, the optimal encoding for one or more encoded sequence bit lengths can be determined.

[0065] During A-scan acquisition or imaging operations, such as at 710, encoding can be selected at 745, for example, based on user-selectable criteria (such as gain or dynamic range selection) or other constraints, such as those specified by the measurement configuration, frequency, or application. At 750, coded excitation can be generated, for example, by generating acoustic pulses with envelopes defined by specified coded sequences. At 755, an FIR filter can be used to deconvolve the acoustic echo signal induced in response to the transmission event at 750. Alternatively, correlation-based detection techniques can be employed to detect such acoustic echo signals, although this technique may introduce sidelobe-related artifacts into the autocorrelation function compared to deconvolution using an FIR filter in the digital domain. At 760, an A-scan output equivalent to a single pulse transmission but with an enhanced signal-to-noise ratio can be generated. Such A-scan outputs can be stored or presented to the user, or used for other imaging applications, such as PWI or TFM beamforming, which are only illustrative examples here.

[0066] Figure 8 The overall illustration presents a technique 800, such as a machine-implemented method for coded emission and related detection in an acoustic detection system. At 805, an acoustic pulse transmission (e.g., a transmit-receive acquisition corresponding to a portion of the FMC acquisition) can be generated. The acoustic pulse transmission can be defined by a pulse sequence corresponding to a specified code, such as a Barker code or pseudo-Barker code as described elsewhere in this document. Typically, an acoustic pulse generator generates pulses with a specified center frequency (e.g., within the ultrasonic frequency range), and the code defines the envelope of the pulses in the sequence. At 810, acoustic echo data induced in response to the transmission at 805 can be acquired. At 815, the acoustic echo data can be filtered using an FIR filter to provide a deconvolution based on the specified code used to generate the acoustic pulse transmission at 805. Alternatively, a correlation-based method can be used for detection. At 820, an enhanced A-scan representation can be generated, for example, with an improved signal-to-noise ratio after deconvolution compared to an A-scan acquired without coded emission and deconvolution. At position 825, a set of enhanced A-scan representations can be coherently summed (e.g., using delayed superposition beamforming) to form pixel or voxel values ​​in the acoustically detected image. In this way, as described below, an enhanced A-scan matrix can be formed using a series of coded transmit events and corresponding receive events, for example, for TFM or other beamforming and related imaging.

[0067] Figure 9A , Figure 9B and Figure 9C Several illustrative examples of images generated using TFM beamforming are shown: Figure 9A This demonstrates TFM beamforming without using coded transmission; Figure 9B TFM beamforming using coded transmission and detection employing a correlation-based method is illustrated. Figure 9C TFM beamforming using an FIR filter to perform deconvolution is shown. For Figure 9B and Figure 9C By combining each A scan in the FMC with a 13-bit Barker code (such as...) Figure 3A Convolution (as shown) is performed to simulate encoded emission. Then autocorrelation (as shown) is used. Figure 9B ) and FIR deconvolution ( Figure 9C The FMC data is reconstructed using FIR deconvolution. The FMC reconstructed using FIR deconvolution (and the resulting...) Figure 9C TFM image) and original image (by Figure 9A The TFM image representation remains unchanged compared to the FMC image represented by autocorrelation reconstruction, while the FMC image represented by autocorrelation reconstruction remains unchanged. Figure 9B (Associated with the TFM image) Due to artifacts caused by non-zero side lobes, as shown in region 346.

[0068] Figure 10A , Figure 10B and Figure 10C Several illustrative examples of images generated using TFM beamforming are shown: Figure 10A This demonstrates TFM beamforming performed without coded transmission when noise is added to the input A-scan data; Figure 10B The TFM beamforming performed in the presence of noise is shown, including averaging of 13 images, where the noise signal added to the underlying FMC A-scan data is random and varies between multiple trials; Figure 10C TFM beamforming with deconvolution performed using an FIR filter is shown, where noise is added but no averaging is performed. Figure 9A , Figure 9B , Figure 9C , Figure 10A , Figure 10B and Figure 10C Simulation results show that when the signal-to-noise ratio is high, FIR deconvolution does not introduce sidelobes; while when the signal-to-noise ratio is low, FIR deconvolution reduces the level of random noise.

[0069] Figure 11A , Figure 11B and Figure 11C Several examples of B-scan images are shown: Figure 11A The image acquisition is shown without coded transmission and with a center frequency of 0.5 MHz; Figure 11B The image acquisition is shown without coded transmission and with a center frequency of 5.0 MHz; Figure 11CImage acquisition using coded transmission is illustrated, with a center frequency of 5.0 MHz and deconvolution performed using an FIR filter. Typically, the coded transmission described in this document enhances probe penetration, making high-frequency probes suitable for high-attenuation materials such as composite materials, thereby improving temporal resolution. Figure 11A The image shows the default detection settings (using a 0.5 MHz probe), which provide good penetration but relatively poor spatiotemporal resolution. In contrast, in... Figure 11B In the middle, the 5 MHz probe that did not use coded transmission was relatively... Figure 11A While resolution was improved, the front wall region was highly saturated (due to high gain), and the signal-to-noise ratio in deeper regions was low. In contrast, such as Figure 11C The coded emission shown allows for the use of lower gain, thereby reducing the saturation of the front wall in region 1161. Furthermore, better signal-to-noise ratio performance is achieved in deeper regions. Therefore, this higher dynamic range allows for simultaneous detection of both shallow and deep regions of the sample using a single acquisition and imaging operation.

[0070] Figure 12 A block diagram of an example including machine 1200 on which any one or more of the techniques (e.g., methods) described herein can be executed. Machine 1200 (e.g., a computer system) may include hardware processor 1202 (e.g., a central processing unit (CPU), graphics processing unit (GPU), hardware processor core, or any combination thereof), main memory 1204, and static memory 1206, connected via interconnect links 1230 (e.g., links or buses), as some or all of these components may constitute the hardware of the system or related implementation described above.

[0071] Typically, the hardware processor 1202 may include at least one of the following: a central processing unit (CPU), a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a graphics processing unit (GPU), a digital signal processor (DSP), a tensor processing unit (TPU), a neural processing unit (NPU), a vision processing unit (VPU), a machine learning accelerator, an artificial intelligence accelerator, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a radio frequency integrated circuit (RFIC), a neuromorphic processor, a quantum processor, or any combination thereof. The processor circuitry may also be a multi-core processor with two or more independent processors (sometimes referred to as "cores") capable of executing instructions simultaneously. A multi-core processor includes multiple computational cores on a single integrated circuit die, each core capable of independently and in parallel executing program instructions. Parallel processing on a multi-core processor can be implemented using architectures such as superscalar, very long instruction set (VLIW), vector processing, or single instruction multiple data (SIMD), enabling each core to run an independent stream of instructions in parallel. The processor circuitry can be simulated by software running on a physical processor as a virtual processor or virtual circuit. The virtual processor may appear as an independent processor but is implemented in software rather than hardware.

[0072] Specific examples of main memory 1204 include random access memory (RAM) and semiconductor memory devices, the latter of which may include semiconductor memory cells, such as registers. Specific examples of static memory 1206 include non-volatile memory, such as semiconductor memory devices (e.g., electrically programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM)) and flash memory devices; magnetic disks, such as internal hard disks and removable hard disks; magneto-optical disks; RAM; or optical media, such as CD-ROMs and DVD-ROMs.

[0073] Machine 1200 may also include a display device 1210, an input device 1212 (e.g., a keyboard), and a user interface (UI) navigation device 1214 (e.g., a mouse). In one example, the display device 1210, input device 1212, and UI navigation device 1214 may be a touchscreen display. Machine 1200 may include a mass storage device 1208 (e.g., a drive unit), a signal generation device 1218 (e.g., a speaker), a network interface device 1220, and one or more sensors 1216 (e.g., a Global Positioning System (GPS) sensor, a compass, an accelerometer, or other sensors). Machine 1200 may include an output controller 1228, such as a serial port (e.g., Universal Serial Bus (USB), a parallel interface, or other wired or wireless connectivity such as infrared (IR), near field communication (NFC), etc.), for communicating or controlling one or more peripheral devices (e.g., a printer, a card reader, etc.).

[0074] Mass storage device 1208 may include machine-readable medium 1222 on which one or more sets of data structures or instructions 1224 (e.g., software) are stored, which embody or apply any one or more of the technologies or functions described herein. Instructions 1224 may also reside wholly or partially in main memory 1204, static memory 1206, or hardware processor 1202 during execution by machine 1200. In one example, any or any combination of hardware processor 1202, main memory 1204, static memory 1206, or mass storage device 1208 may constitute a machine-readable medium.

[0075] Specific examples of machine-readable media include one or more of the following: non-volatile memory (such as semiconductor memory devices (e.g., EPROM or EEPROM) and flash memory devices); magnetic disks, such as internal hard disks and removable hard disks; magneto-optical disks; RAM; or optical media, such as CD-ROM and DVD-ROM discs. Although machine-readable media are shown as a single medium in the figure, the term "machine-readable medium" can include a single medium or multiple media configured to store one or more instructions 1224 (e.g., a centralized or distributed database, or associated caches and servers).

[0076] The apparatus of machine 1200 includes one or more of the following: a hardware processor 1202 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a hardware processor core, or any combination thereof), main memory 1204 and static memory 1206, a sensor 1216, a network interface device 1220, an antenna, a display device 1210, an input device 1212, a UI navigation device 1214, a mass storage device 1208, an instruction set 1224, a signal generation device 1218, or an output controller 1228. The apparatus can be configured to perform one or more methods or operations disclosed herein.

[0077] The term "machine-readable medium" includes, for example, any medium capable of storing, encoding, or carrying instructions executable by machine 1200, which may cause machine 1200 to perform one or more techniques described in this disclosure, or to cause other means or systems to perform any one or more techniques, or a medium capable of storing, encoding, or carrying data structures used by or associated with such instructions. Examples of non-limiting machine-readable media include solid-state memory, optical media, or magnetic media. Specific examples of machine-readable media include: non-volatile memory, such as semiconductor memory devices (e.g., electrically programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM)) and flash memory devices; magnetic disks, such as internal hard disks and removable hard disks; magneto-optical disks; random access memory (RAM); or optical media such as CD-ROMs and DVD-ROMs. In some examples, machine-readable media include non-transitory machine-readable media. In some examples, machine-readable media include machine-readable media that propagate non-transitory signals.

[0078] Instruction 1224 can be transmitted or received via communication network 1226, for example, through network interface device 1220 using any of a variety of transmission protocols (e.g., Frame Relay, Internet Protocol (IP), Transmission Control Protocol (TCP), User Datagram Protocol (UDP), Hypertext Transfer Protocol (HTTP), etc.) via a transmission medium. Examples of communication networks include: Local Area Networks (LANs), Wide Area Networks (WANs), Packet Data Networks (such as the Internet), Mobile Phone Networks (such as Cellular Networks), Ordinary Old-Style Telephone (POTS) networks and Wireless Data Networks (such as the IEEE 802.11 series of standards, i.e., Wi-Fi®), IEEE 802.15.4 series of standards, Long Term Evolution (LTE) 4G or 5G series of standards, Universal Mobile Telecommunications System (UMTS) series of standards, Point-to-Point (P2P) networks, satellite communication networks, etc.

[0079] In one example, network interface device 1220 includes one or more physical jacks (such as Ethernet, coaxial cable, or other interconnects) or one or more antennas for accessing communication network 1226. In one example, network interface device 1220 includes one or more antennas for wireless communication using at least one of single-input multiple-output (SIMO), multiple-input multiple-output (MIMO), or multiple-input single-output (MISO) technologies. In some examples, network interface device 1220 employs multi-user MIMO technology for wireless communication. The term "transmission medium" should be understood to include any intangible medium capable of storing, encoding, or carrying instructions executable by machine 1200, and includes digital or analog communication signals or other intangible media facilitating such software communication.

[0080] Various instructions

[0081] Each non-restrictive aspect of this document may exist independently or in combination with one or more other aspects or other topics described herein in various permutations or combinations.

[0082] The above detailed description includes references to the accompanying drawings, which form part of the detailed description. The drawings illustrate specific embodiments through which the invention may be practiced. These embodiments are generally also referred to as "examples." Such examples may include elements other than those shown or described. However, the inventors have also conceived of examples that provide only the shown or described elements. Furthermore, the inventors have conceived of examples employing any combination or arrangement of the shown or described elements (or one or more aspects thereof), whether for a specific example (or one or more aspects thereof) or for other examples shown or described herein (or one or more aspects thereof).

[0083] In the event of any inconsistency between the usage of this document and any other document incorporated herein by reference, the usage described herein shall prevail.

[0084] In this document, the use of singular terms is consistent with patent document conventions, encompassing one or more, and independent of any other instances or uses of "at least one" or "one or more." In this document, unless otherwise stated, the term "or" is used to refer to a non-exclusive "or," such that "A or B" includes "A but not B," "B but not A," and "A and B." In this document, the terms "comprising" and "wherein" are used as their common English equivalents to "comprising" and "wherein." Furthermore, in the following claims, the terms "comprising" and "including" are open-ended expressions, meaning that if a system, device, article, composition, formulation, or process in a claim includes elements beyond those listed following such terms, it is still considered to fall within the scope of that claim. Moreover, in the following claims, the terms "first," "second," "third," etc., are used only as identifiers and are not intended to impose a quantitative requirement on their contents.

[0085] The methods described herein can be implemented, at least in part, by a machine or computer. Some examples may include a computer-readable or machine-readable medium encoded with operable instructions for configuring an electronic device to perform the methods described in the examples above. Implementations of such methods may include code, such as microcode, assembly language code, high-level language code, etc. Such code may include computer-readable instructions for performing multiple methods and form part of a computer program product. For example, such instructions may be read and executed by one or more processors to perform operations containing the methods. These instructions may take any suitable form, including but not limited to source code, compiled code, interpreted code, executable code, static code, dynamic code, etc. Furthermore, in one example, the code may be tangibly stored on one or more volatile, non-transient, or non-volatile tangible computer-readable media, for example, during execution or at other times. Examples of such tangible computer-readable media include, but are not limited to, hard disks, removable disks, removable optical discs (such as CDs and DVDs), magnetic tapes, memory cards or memory sticks, random access memory (RAM), read-only memory (ROM), etc.

[0086] The foregoing description is intended to be illustrative and not limiting. For example, the examples (or one or more aspects thereof) described above may be used in combination with each other. Other embodiments may be used by those skilled in the art after reviewing the foregoing description. The abstract is provided to give the reader a quick understanding of the nature of the technical disclosure. It is understood that the abstract should not be used to interpret or limit the scope or meaning of the claims. Furthermore, in the detailed description above, multiple features may be combined together to simplify the disclosure. This should not be construed as meaning that a disclosed feature not covered by any claim is essential to any claim. Rather, the inventive subject matter may relate only to a subset of features of a specified disclosed embodiment. Therefore, the following claims are incorporated into the detailed description as examples or embodiments, each claim existing independently as a separate embodiment, and such embodiments may be combined with each other in various combinations or arrangements. The scope of the invention should be determined by reference to the appended claims and the full scope of their equivalents.

Claims

1. A machine-implemented method for performing acoustic detection, the method comprising: The corresponding acoustic pulse transmission is generated using a specified pulse sequence corresponding to a specified code; In response to the corresponding acoustic pulse transmission, acoustic echo data indicating scattered or reflected acoustic energy are acquired; The acquired acoustic echo data is filtered using a finite impulse response (FIR) filter to provide filtered acoustic echo data; as well as The filtered acoustic echo data is coherently summed to provide pixel or voxel element values.

2. The machine-implemented method according to claim 1, wherein, The specified pulse sequence includes an encoding that has an autocorrelation peak corresponding to the autocorrelation main lobe when aligned with a representation having a zero sample offset, and a lower autocorrelation value corresponding to the autocorrelation sidelobe when aligned with a representation having a non-zero sample offset.

3. The machine-implemented method according to any one of claims 1 or 2, wherein, The specified pulse sequence includes Barker codes.

4. The machine-implemented method according to any one of claims 1 or 2, wherein, The specified pulse sequence includes an encoding with an odd number of bits.

5. The machine-implemented method according to any one of claims 1-4, wherein, The second half of the specified pulse sequence following the midpoint of the specified pulse sequence is a mirror image of the first half of the specified pulse sequence, but the sign of each consecutive digit changes alternately.

6. The machine-implemented method according to any one of claims 1-5, wherein, The specified pulse sequence includes an encoding that, when aligned with a representation having a non-zero sample offset, exhibits zero-valued autocorrelation sidelobes at odd-valued sample offsets.

7. The machine-implemented method according to any one of claims 1-6, wherein, The FIR filter includes establishing coefficients to provide deconvolution of the specified impulse sequence, including establishing the coefficients by evaluating a set of candidate impulse response filter coefficients according to an amplitude criterion.

8. The machine-implemented method according to claim 7, wherein, Applying the amplitude criterion involves determining the number of coefficients in the candidate impulse response filter corresponding to the candidate FIR filter whose amplitude is greater than a specified amplitude threshold, as the proportion of filter coefficients with the maximum amplitude.

9. The machine-implemented method according to claim 8, wherein, The specified amplitude threshold is one percent of the maximum amplitude.

10. The machine-implemented method according to any one of claims 8 or 9, wherein, The candidate FIR filter is truncated by discarding candidate impulse response filter coefficients that are below the specified amplitude threshold to provide the FIR filter for providing deconvolution.

11. The machine-implemented method according to any one of claims 1-10, wherein, The specified encoding or the FIR filter is established using the following standard: the number of impulse response filter coefficients is constrained to a specified multiple of the number of bits in the specified encoding.

12. The machine-implemented method according to claim 11, wherein, The specified multiple is five.

13. The machine-implemented method according to any one of claims 1-12, wherein, The FIR filter is constructed by evaluating the noise average metric of the candidate FIR filters.

14. The machine-implemented method according to any one of claims 1-13, wherein, The filtered acoustic echo data includes A-scan data.

15. The machine-implemented method according to any one of claims 1-14, wherein, Coherent summation of the filtered acoustic echo data representation includes: performing total focusing (TFM) beamforming, wherein the specified pulse sequence is used for corresponding transmit-receive acquisition in a matrix acquisition scheme; and The pixel or voxel element values ​​include data from the image generated using the TM beamforming.

16. The machine-implemented method according to any one of claims 1-15, wherein, The specified pulse sequence is defined by a series of digits having values ​​selected from the set {1, -1}; and Wherein, the values ​​{1} and {-1} correspond to the specified positive and negative sign output amplitude values ​​from the pulse generator circuit used to generate the corresponding acoustic pulse transmission.

17. A system for performing acoustic detection, the system comprising: Pulse generator circuit; Receiver circuit; At least one processor circuit; as well as A memory circuit comprising instructions that, when executed by the at least one processor circuit, cause the system to perform a machine-implemented method according to any one of claims 1-14.

18. A machine-implemented method for coded emission in acoustic detection, the machine-implemented method comprising: An encoding for acoustic pulse transmission is established, the encoding being defined by a specified pulse sequence that exhibits zero-valued autocorrelation sidelobes at odd sample offsets; as well as A finite impulse response (FIR) filter is established to filter the acquired acoustic echo data received in response to the acoustic pulse transmission, the FIR filter providing deconvolution of the specified pulse sequence.

19. The machine-implemented method according to claim 18, wherein, The second half of the specified pulse sequence following the midpoint of the specified pulse sequence is a mirror image of the first half of the specified pulse sequence, but the sign of each consecutive digit changes alternately.

20. The machine-implemented method according to any one of claims 18 or 19, wherein, The FIR filter is established by evaluating a set of candidate impulse response filter coefficients according to an amplitude criterion, which includes determining the number of coefficients with amplitudes greater than a specified amplitude threshold among the coefficients of the candidate impulse response filters corresponding to the candidate FIR filter, as the proportion of filter coefficients with the maximum amplitude.

21. The machine-implemented method according to claim 20, wherein, The candidate FIR filter is truncated by discarding candidate impulse response filter coefficients that are below the specified amplitude threshold to provide the FIR filter for providing deconvolution.

22. The machine-implemented method according to any one of claims 18-21, wherein, The specified pulse sequence or the FIR filter is established using the following standard: the number of impulse response filter coefficients is constrained to a specified multiple of the number of bits in the specified pulse sequence.

23. The machine-implemented method according to claim 22, wherein, The specified multiple is five.

24. The machine-implemented method according to any one of claims 18-23, wherein, The specified pulse sequence is defined by a series of digits having values ​​selected from the set {1, -1}; and Wherein, the values ​​{1} and {-1} correspond to the specified positive and negative sign output amplitude values ​​from the pulse generator circuit used to generate the corresponding acoustic pulse transmission.

25. The machine-implemented method according to any one of claims 18-24, wherein, The FIR filter is constructed by evaluating the noise average metric of the candidate FIR filters.

Images