Acoustic coded emission and deconvolution

Abstract

Coded emission (e.g., where a pulse sequence is transmitted corresponding to a specified code) can be used for respective acoustic transmission events for non- destructive testing. Enhanced A-scans can be assembled by convolving a specific finite-impulse-response filter profile with a time-domain representation of received acoustic echo data. Such an approach can be used to enhance dynamic range or signal-to-noise ratio, or to permit use of a lower analog gain to avoid saturation of a receive signal processing chain from features such as front wall echoes.

Description

ACOUSTIC CODED EMISSION AND DECONVOLUTIONCLAIM OF PRIORITY

[0001] This patent application claims the benefit of priority of Chi-Hang Kwan, U.S. Provisional Patent Application Number 63 / 520,509, titled “CODED EMISSION WITH FIR DECONVOLUTION,” filed on August 18, 2023 (Attorney Docket No. 6409.268PRV), which is hereby incorporated by reference herein in its entirety.FIELD OF THE DISCLOSURE

[0002] This document pertains generally, but not by way of limitation, to nondestructive evaluation, and more particularly, to apparatus and techniques for providing coded emission and corresponding detection techniques such as for acoustic imaging.BACKGROUND

[0003] Non-destructive testing (NDT) can refer to use of one or more different techniques to inspect regions on or within an object, such as to ascertain whether flaws or defects exist, or to otherwise characterize the object being inspected. Examples of non-destructive test approaches can include use of an eddy-current testing approach where electromagnetic energy is applied to the object and resulting induced currents on or within the object are detected, with the values of a detected current (or a related impedance) providing an indication of the structure of the object under test, such as to indicate a presence of a crack, void, porosity, or other inhomogeneity.

[0004] Another approach for NDT can include use of an acoustic inspection technique, such as where one or more electroacoustic transducers are used to insonify a region on or within the object under test, and acoustic energy that is scattered or reflected can be detected and processed. Such scattered or reflected energy can be referred to as an acoustic echo signal. Generally, such an acoustic inspection scheme involves use of acoustic frequencies in an ultrasonic range of frequencies, such as including pulses having energy in a specified range that can include value from, for example, a few hundred kilohertz, to tens of megahertz, as an illustrative example.SUMMARY OF THE DISCLOSURE

[0005] Acoustic testing, such as ultrasound-based inspection, can include use of individual transducers, or arrays of such transducers including providing focusing or beam-forming techniques to aid in construction of data plots or images representing a region of interest on or within a test specimen. Use of an array of ultrasound transducer elements can include use of a phased-array beamforming approach and can be referred to as Phased Array Ultrasound Testing (PAUT). For example, a delay-and- sum beamforming technique can be used such as including coherently summing timedomain representations of received acoustic signals from respective transducer elements or apertures. A Total Focusing Method (TFM) beamforming technique can use data acquired where or more elements in an array (or apertures defined by such elements) are used to transmit an acoustic pulse and other elements are used to receive scattered or reflected acoustic energy, and a matrix is constructed of time-series (e.g., A-Scan) representations corresponding to a sequence of transmit-receive cycles in which the transmissions are occurring from different elements (or corresponding apertures) in the array.

[0006] Such a matrix-capture acquisition scheme where A-scan data is obtained for each element in an array (or each defined aperture) can be referred to as a “full matrix capture” (FMC) technique. In a manner similar to TFM imaging, a phase-based approach can be used for one or more of acquisition, storage, or subsequent analysis. Such a phase-based approach can include coherent summation of normalized or quantized representations of A-Scan data corresponding to phase information. Such an approach can be referred to as a “phase coherence imaging” (PCI) beamforming technique. Other imaging approaches include plane-wave imaging (PWI), and the techniques described herein are generally applicable to various PAUT acquisition and beamforming techniques.

[0007] The present inventor has recognized, among other things, that one challenge presented by acoustic imaging techniques, is that a range of detectable amplitudes or “dynamic range” of received acoustic echo signals may make it difficult to suppress a strong front wall echo signal (or other strongly-reflecting feature) while still detecting weakly-reflected echo signals associated with flaws, defects, or other features of interest. In one approach, a transmit signal strength or receiver gain can be adjusted (e.g., increased) such as to detect weakly-reflecting features, but such increase cancreate a front wall echo signal that saturates the receive signal processing chain (in either the analog or the digital domain). Such saturation can mask features nearby the front wall echo or other strong reflector or scatterer. A reduction in transmission power or receive gain can help to suppress such saturation but might result in weakly- reflected echo signals being lost below the noise floor of the receive signal processing chain.

[0008] The present inventor has recognized, among other things, that a coded emission scheme (e.g., where a sequence of pulses corresponding to a specified code) can be used for respective transmit events such as to address one or more challenges mentioned above. Enhanced A-scans can be assembled by convolving a specific fmite-impulse-response filter profile with a time-domain representation of received acoustic echo data (or through a correlation-based detection approach using the original code sequence for evaluation). Use of coded emission can enhance dynamic range or signal-to-noise ratio (SNR) or permit use of a lower analog gain to avoid saturation of a receive signal processing chain by features such as front wall echoes, while still allowing weakly -reflecting features of interest to be resolved.

[0009] In an example, a machine-implemented method can be used for performing acoustic inspection or other acoustic evaluation, where the method comprises generating respective acoustic pulse transmissions using a specified pulse sequence corresponding to a specified code, and in response to the respective acoustic pulse transmissions, acquiring acoustic echo data indicative of scattered or reflected acoustic energy. The method can include applying a correlation-based detection approach or a deconvolution filter to provide filtered acoustic echo data. For example, the method can include filtering the acquired acoustic echo data using a finite impulse response (FIR) filter to provide filtered acoustic echo data. Imaging or beamforming can be performed, such as by coherently summing representations of the filtered acoustic echo data to provide a pixel or voxel element value in an image, where a series of such summations is used to form an image for storage or presentation.

[0010] In an example, a machine-implemented method can include establishing or evaluating candidate codes for use in a coded emission scheme for acoustic inspection, the machine-implemented method comprising establishing a code for use in an acoustic pulse transmission, the code defined by a specified pulse sequence that exhibits zero-valued autocorrelation sidelobes at odd-valued sample offsets, andestablishing a finite impulse response (FIR) filter for use in filtering acquired acoustic echo data received in response to the acoustic pulse transmission, the FIR filter providing deconvolution of the specified pulse sequence. For example, such as according to potential “pseudo-Barker” candidate codes, a second half of the specified pulse sequence after a mid-point of the specified pulse sequence comprises a mirror image of a first half of the specified pulse sequence but with alternating sign for each successive digit.

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

[0012] This summary is intended to provide an overview of subject matter of the present patent application. It is not intended to provide an exclusive or exhaustive explanation of the invention. The detailed description is included to provide further information about the present patent application.BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In the drawings, which are not necessarily drawn to scale, like numerals may describe similar components in different views. Like numerals having different letter suffixes may represent different instances of similar components. The drawings illustrate generally, by way of example, but not by way of limitation, various embodiments discussed in the present document.

[0014] FIG. 1 illustrates generally an example comprising an acoustic inspection system, such as can be used to perform at least a portion one or more techniques as shown and described herein.

[0015] FIG. 2 shows an illustrative example comprising an A-scan acquisition where saturation is occurring due to an acoustic echo from a front wall of an object under test.

[0016] FIG. 3A shows an illustrative example of a sequence of values corresponding to a 13-bit Barker Code that can be used as a pulse sequence for coded emission.

[0017] FIG. 3B shows an illustrative example of an autocorrelation functioncorresponding to the 13-bit Barker Code of FIG. 3A.

[0018] FIG. 4A shows an illustrative example comprising coefficients defining a Finite Impulse Response (FIR) filter, such as can be used for deconvolution of an acoustic echo signal elicited in response to an acoustic transmission generated using coded emission.

[0019] FIG. 4B shows an illustrative example of a deconvolved response resulting from filtering of an input time series using the FIR filter coefficients of FIG. 4A, where the input time series comprises the coded emission pulse sequence of FIG. 3 A.

[0020] FIG. 5 illustrates generally a relationship between noise averaging power and different code sequence lengths, along with an analytically-defined limit.

[0021] FIG. 6A shows an illustrative example of a 39-bit Pseudo-Barker Code that can be used as a pulse sequence for coded emission.

[0022] FIG. 6B shows an illustrative example of an autocorrelation function corresponding to the 39-bit code of FIG. 6A.

[0023] FIG. 6C shows an illustrative example of an FIR deconvolution filter that can be used for filtering an acoustic echo signal elicited in response to an acoustic transmission generated using a coded emission corresponding to the 39-bit code of FIG. 6A.

[0024] FIG. 6D shows an illustrative example of a deconvolved response resulting from filtering of an input time series using the FIR filter coefficients of FIG. 6C, where the input time series comprises the coded emission pulse sequence of FIG. 6A.

[0025] FIG. 7 illustrates generally a workflow that can be used to evaluate potential candidate codes (defining pulse sequences for transmission), along with a technique for selecting a code.

[0026] FIG. 8 illustrates generally a technique, such as a machine-implemented method that can be used for coded emission and associated detection in an acoustic inspection system.

[0027] FIG. 9A, FIG. 9B, and FIG. 9C shows various illustrative examples of images generated using TFM beamforming, with FIG. 9A showing TFM beamforming without use of coded emission, FIG. 9B showing TFM beamforming where coded emission is used and a correlation-based approach is used for detection, and FIG. 9C showing TFM beamforming where an FIR filter is used for performing deconvolution.

[0028] FIG. 10A, FIG. 10B, and FIG. 10C shows various illustrative examples ofimages generated using TFM beamforming, with FIG. 10A showing TFM beamforming performed in the presence of noise added to the input A-scan data, without use of coded emission, FIG. 10B showing TFM beamforming performed in the presence of noise, including averaging of 13 images where the noise signals added to underlying A-scan data are random and vary between trials, and FIG. IOC showing TFM beamforming where an FIR filter is used for performing deconvolution, where noise is added, but no averaging is performed.

[0029] FIG. 11 A, FIG. 11B, and FIG. 11C shows various examples of B-scan images, with FIG. 11 A showing an image acquisition where coded emission is not used, and a center frequency of 0.5 megahertz (MHz) is used, FIG. 11B showing an image acquisition where coded emission is not used, and a center frequency of 5.0 MHz is used, and FIG. 11C showing an image acquisition using coded emission, with a center frequency of 5.0 MHz, and an FIR filter used for deconvolution.

[0030] FIG. 12 illustrates a block diagram of an example comprising a machine upon which any one or more of the techniques (e.g., methodologies) discussed herein may be performed.DETAILED DESCRIPTION

[0031] Non-destructive testing of structures can be performed using an acoustic technique, such as involving ultrasonic inspection using a phased-array transducer architecture and associated processing (e.g., beamforming and imaging). As mentioned above, interpretation of acquired inspection data or associated images can present various challenges. Saturation of a receiver signal processing chain, such as due to strong front wall echoes associated with an object under test, can mask other more weakly -reflecting features of interest. In one approach, multiple acquisition and imaging operations can be performed, such as using different transmission power or receive gain settings. Use of multiple acquisitions in this manner can negatively impact inspection productivity, such as slowing down the inspection process, or even failing to detect weakly-reflecting features that are located nearby a strongly- reflecting feature. The approaches described in this document can be used such as to enhance one or more of a dynamic range of amplitude measurements in acoustic inspection, or an enhancement (e.g., increase) in signal -to-noise ratio (SNR), or both. Such enhancement can suppress saturation in A-scan data (e.g., suppressing clippingin the digital domain or saturation of an analog front end), or in resulting imaging formed using techniques such as Plane Wave Imaging (PWI) or Total Focusing Method (TFM) beamforming.

[0032] FIG. 1 illustrates generally an example comprising an acoustic inspection system 100, such as can be used to perform at least a portion one or more techniques as shown and described herein. The inspection system 100 can include a test instrument 140, such as a hand-held or portable assembly. The test instrument 140 can be electrically coupled to a probe assembly 150, such as using a multi -conductor interconnect 130. The probe assembly 150 can include one or more electroacoustic transducers, such as a transducer array 152 including respective transducers 154A through 154N. The transducers array can follow a linear or curved contour or can include an array of elements extending in two axes, such as providing a matrix of transducer elements. The elements need not be square in footprint or arranged along a straight-line axis. Element size and pitch can be varied according to the inspection application.

[0033] A modular probe assembly 150 configuration can be used, such as to allow a test instrument 140 to be used with various different probe assemblies. Generally, the transducer array 152 includes piezoelectric transducers, such as can be acoustically coupled to a target 158 (e.g., a test specimen or “object-under-test”) through a coupling medium 156. The coupling medium can include a fluid or gel or a solid membrane (e.g., an elastomer or other polymer material), or a combination of fluid, gel, or solid structures. For example, an acoustic transducer assembly can include a transducer array coupled to a wedge structure comprising a rigid thermoset polymer having known acoustic propagation characteristics (for example, Rexolite® available from C-Lec Plastics Inc.), and water can be injected between the wedge and the structure under test as a coupling medium 156 during testing, or testing can be conducted with an interface between the probe assembly 150 and the target 158 otherwise immersed in a coupling medium.

[0034] The test instrument 140 can include digital and analog circuitry, such as a front-end circuit 122 including one or more transmitter signal chains, receiver signal chains, or switching circuitry (e.g., transmit / receive switching circuitry). The transmitter signal chain can include amplifier and filter circuitry, such as to provide transmit pulses for delivery through an interconnect 130 to a probe assembly 150 forinsonifying the target 158, such as to image or otherwise detect a flaw 160 on or within the target 158 structure by receiving scattered or reflected acoustic energy elicited in response to the insonification.

[0035] While FIG. 1 shows a single probe assembly 150 and a single transducer array 152, other configurations can be used, such as multiple probe assemblies connected to a single test instrument 140, or multiple transducer arrays 152 used with a single probe assembly 150 or multiple probe assemblies for pitch / catch inspection modes. Similarly, a test protocol can be performed using coordination between multiple test instruments 140, such as in response to an overall test scheme established from a master test instrument 140 or established by another remote system such as a compute facility 108 or general-purpose computing device such as a laptop 132, tablet, smartphone, desktop computer, or the like. The test scheme may be established according to a published standard or regulatory requirement and may be performed upon initial fabrication or on a recurring basis for ongoing surveillance, as illustrative examples.

[0036] The receiver signal chain of the front-end circuit 122 can include one or more filters or amplifier circuits, along with an analog-to-digital conversion facility, such as to digitize echo signals received using the probe assembly 150. Digitization can be performed coherently, such as to provide multiple channels of digitized data aligned or referenced to each other in time or phase. The front-end circuit can be coupled to and controlled by one or more processor circuits, such as a processor circuit 102 included as a portion of the test instrument 140. The processor circuit can be coupled to a memory circuit 104, such as to execute instructions that cause the test instrument 140 to perform one or more of acoustic transmission, acoustic acquisition, processing, or storage of data relating to an acoustic inspection, or to otherwise perform techniques as shown and described herein. The test instrument 140 can be communicatively coupled to other portions of the system 100, such as using a wired or wireless communication interface 120.

[0037] For example, performance of one or more techniques as shown and described herein can be accomplished on-board the test instrument 140 or using other processing or storage facilities such as using a compute facility 108 or a general- purpose computing device such as a laptop 132, tablet, smart-phone, desktop computer, or the like. For example, processing tasks that would be undesirably slow if performed on-board the test instrument 140 or beyond the capabilities of the testinstrument 140 can be performed remotely (e.g., on a separate system), such as in response to a request from the test instrument 140. Similarly, storage of imaging data or intermediate data such as A-scan matrices of time-series data or other representations of such data, for example, can be accomplished using remote facilities communicatively coupled to the test instrument 140. The test instrument can include a display 110, such as for presentation of configuration information or results, and an input device 112 such as including one or more of a keyboard, trackball, function keys or soft keys, mouse-interface, touch-screen, stylus, or the like, for receiving operator commands, configuration information, or responses to queries.

[0038] Various acoustic inspection approaches may exhibit limitations in dynamic range or signal -to-noise ratio (SNR) for imaging of structures being inspected. For example, use of a Total Focusing Method (TFM) beamforming approach based on Full Matrix Capture (FMC) acquisition may present challenges in terms of SNR limitations. For example, TFM beamforming, where FMC acquisition is used, generally involves one transducer or one aperture transmitting with other transducers receive acoustic echo signals. Accordingly, such transmission may lack penetration power as compared to Plane Wave Imaging (PWI) due to the use of fewer transducer elements (or generally a single transducer element) per each transmission event. Such effects can also be exhibited when a sparse acquisition approach used. Sparse acquisition may involve performing less than a full matrix capture, where individual transmission events may again involve as few as a single element, with fewer transmit-receive acquisitions used for a beamforming summation. Generally, sparse acquisition may exhibit a lower signal-to-noise ratio as compared to full-aperture acquisition. In corrosion and composite inspections, the operator may need to increase an analog gain to see multiple reflections or to find a back wall echo for thick specimens. However, increasing the gain can make a front wall echo saturated, which can complicate processing and related imaging tasks. Techniques described herein may be used to enhance SNR or provide enhanced dynamic range (or both), such as in use cases or applications as mentioned above.

[0039] As an illustration, FIG. 2 shows an illustrative example comprising an A-scan acquisition 200 where saturation is occurring at 224 due to an acoustic echo from a front wall of an object under test. The present inventor has recognized that various challenges mentioned above may be addressed by increasing an SNR of acquired A-scan data without requiring an analog gain increase, which may also enhance dynamic range. Such dynamic range enhancement may allow detection of weak echo signals of interest while also suppressing saturation of the analog receive channel (or clipping in the digital domain).

[0040] The present inventor has recognized, among other things, that one approach for increasing SNR or dynamic range (or both) can include use of a coded emission pulse transmission and receiving scheme. For example, the Omniscan X3-64 (available from Evident Scientific, Inc., Waltham, MA, USA and Evident Canada, Inc., Quebec, QC, Canada) has a transmit pulse generator that can generate positivegoing and negative-going pulses, such as supporting at least three output states (positive amplitude, zero, and negative amplitude). Such states can be mapped to positive-sign, negative-sign and zero output values {+1, 0, -1}, and a code can be specified corresponding to a pulse sequence of such states, such that instead of a single transmit pulse envelope, a sequence of pulses can be transmitted having an envelope signs corresponding to a binary code (e.g., having two states comprising +1 or -1). A code can be selected to exhibit high self-correlation, such that the code exhibits an autocorrelation function peak corresponding to perfect time alignment with a representation of itself (e.g., no sample offset), and much lower (or even zero) correlation when correlation is evaluated with a delayed representation of itself offset by one or more samples in either direction (either leading or lagging). Such values in the autocorrelation function adjacent to the peak or main lobe can be referred to as “side lobes.”

[0041] Golay and Barker codes are binary-valued codes that can be used to provide coded emission. Golay code sets exhibit zero side lobes and generally involve two times (2x) the number of firing events as compared to non-coded excitation, therefore productivity (e.g., inverse of acquisition speed) is reduced by a factor of two. Barker codes are another family of codes exhibiting an autocorrelation function peak, where a maximum sidelobe-to-main lobe amplitude ratio is generally 1 / N, where N corresponds to a count of digits (e.g., a length in bits) of the code. The longest known Barker code has a length of 13. Consequently, a corresponding minimum sidelobe amplitude level is -22.3 dB.

[0042] FIG. 3A shows an illustrative example of a sequence of values corresponding to the 13-bit Barker Code mentioned above, that can be used as a pulse sequence forcoded emission, and FIG. 3B shows an illustrative example of an autocorrelation function corresponding to the 13-bit Barker Code of FIG. 3A, showing a strong main lobe (autocorrelation peak 334).

[0043] In the frequency domain, the convolution process for coded emission can be described as:

[0044] where Y (to) represents a coded emission response as a function of angular frequency, %(u>) represents an impulse response, and C(to) represents a code. The present inventor has recognized, among other things, that a deconvolution process can be used recover the impulse response, which can then be expressed as:

[0045] Deconvolution using a spectral technique can amplify noise in regions where | C (to) | approaches zero. However, for many binary codes, | C (to) | is generally never zero. In the time-domain the deconvolution process can be expressed as:

[0046] The time-domain impulse response function, h(t), can be implemented (e.g., approximated) as a Finite Impulse Response (FIR) filter. For example, FIG. 4A shows an illustrative example comprising coefficients defining an FIR filter, such as can be used for deconvolution of an acoustic echo signal elicited in response to an acoustic transmission generated using coded emission. The FIR filter shown illustratively in FIG. 4A corresponds to the 13-bit Barker code of FIG. 3 A. FIG. 4B shows an illustrative example of a deconvolved response (showing a strong peak 444) resulting from filtering of an input time series using the FIR filter coefficients of FIG. 4A, where the input time series comprises the coded emission pulse sequence of FIG. 3 A.

[0047] Because a deconvolution process can be applied for any binary code that has |C(u>) | that is never zero, metrics can be used to assess the suitability (e.g., optimality) of a candidate code and its corresponding FIR deconvolution filter. For practical application, the FIR deconvolution filter h(t) can be truncated to a limited number of taps (e.g., filter coefficients) for ease of implementation, such as by zeroing out or otherwise dropping coefficients below the specified amplitude threshold. A count of coefficients (e.g., number of taps) that could provide a reasonably accurate representation of h(t) can be expressed by the followingconstraint:EQN. 4

[0048] The constraint above implements an amplitude criterion, for use in evaluating a set of candidate impulse response filter coefficients corresponding to a candidate code. In the expressions above, a count Ntapcan be established corresponding to coefficients (e.g., taps) that have an amplitude greater than specified amplitude threshold (here corresponding to one percent of a maximum amplitude of (t)). Through empirical evaluation, and as an illustration, it is observed that a count of impulse response filter coefficients (Ntap) can be constrained to a specified multiple of a count of digits (Ncode) in the specified code, or fewer coefficients. For example, an tap / Code ratio under five (e.g., five FIR filter coefficients per digit of code) appears to generate useful results as shown illustratively below, though other ratios can be used based on empirical or numerical evaluation. As a numerical example, if a candidate code has a length of 20 digits, any candidate code with an associated deconvolution filter (t) that can be accurately represented by less than 100 taps meets the 5:1 criterion above.

[0049] Other constraints (e.g., metrics indicative of optimality or relative merit) can be applied to help evaluate candidate codes and associated deconvolution fdter coefficients. For example, use of coded emission can enhance the signal to noise ratio by suppressing non-coherent random noise. Accordingly, a quantitative metric can help in selection of a suitable code by comparing a noise suppression power of different codes. Assuming the random noise at each time sample are statistically independent, an effective noise averaging power for a binary code and its FIR deconvolution filter can be expressed as:

[0050] In EQN. 5 above, I represents a characteristic delay of the FIR filter (t). Because the SNR improvement is generally proportional to a square root of noise averaging power, it can be represented as:

[0051] As an illustration, FIG. 5 shows a relationship between noise averaging power and different code sequence lengths, along with an analytically-defined limitcorresponding to normalized autocorrelation. As discussed elsewhere herein, codes can be identified where a corresponding FIR deconvolution filter has a maximum of five coefficients per digit (per bit) of the code, and as shown in FIG. 5, the “pseudo” Barker codes established by the present inventor can provide performance that is comparable up to Barker codes up to 13-bit length, and for which codes have been identified up to 49 bits in length. A noise averaging power of non-ideal candidate codes and their associated deconvolution filters is below an analytically-defined limit (e.g., a theoretical maximum) of Ncode which can be achieved by normalized autocorrelation. (e.g., detection using correlation instead of using an FIR filter for deconvolution). Use of auto-correlation will always produce non-zero-valued sidelobes in the autocorrelation function.

[0052] While, ideally, a coded emission pulse sequence would have autocorrelation function sidelobes having zero amplitude, the present inventor has recognized, among other things, that the 13-bit Barker code exhibits sidelobes that alternate between nonzero and zero values, such as, referring to FIG. 3B, sample 1 at 336 being non-zero in FIG. 3B, and sample 2 at 338 being zero-valued in FIG. 3B. The present inventor has recognized that anew class of codes exist beyond 13 bits, having zero-valued autocorrelation sidelobes at odd-valued samples in the sequence. Codes meeting such a criterion are referred to herein as “pseudo-Barker” codes. For odd-length pseudoBarker codes (e.g., having an odd count of digits), all bits after the mid-point digit can be established deterministically, such as using an analytical expression (where z represents a digit number): code(i > nmid) = -l(l~nmM)code(2nnud- i); nmid=Nc°e+1EQN. 7

[0053] In EQN. 7, a second half of the specified pulse sequence after a mid-point of the specified pulse sequence (e.g., where i > nmid) comprises a mirror image of a first half of the specified pulse sequence (where i < nmid) but with alternating sign for each successive digit. Because pseudo-Barker codes are defined according to the expression above, an exhaustive search for a 49-bit pseudo-Barker code corresponds computationally to an exhaustive search among all possible 25-bit binary codes. The present inventor has also recognized, among other things, that suitable FIR deconvolution filter coefficients can be established, meeting the constraint of EQN. 4, above (e.g., having a suitably small number of taps comprising a specified multiple ofthe pseudo-Barker code length), while also providing acceptable noise averaging behavior according to EQN. 5, above.

[0054] FIG. 6A shows an illustrative example of a 39-bit Pseudo-Barker Code that can be used as a pulse sequence for coded emission. With a maximum allowable tap / code ratio of five, the optimal 39-bit code as shown in FIG. 6A is found to be [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 discussed above, a portion of the sequence 556 after the mid-point digit 554 (corresponding to sample 20) is a mirror image of the initial portion of the sequence, but with alternating sign between successive digits.

[0055] FIG. 6B shows an illustrative example of an autocorrelation function corresponding to the 39-bit code of FIG. 6A. A correlation peak (main lobe 534) is surrounded by side lobes where odd-numbers samples are zero-valued. FIG. 6C shows an illustrative example of an FIR deconvolution fdter that can be used for fdtering an acoustic echo signal elicited in response to an acoustic transmission generated using a coded emission corresponding to the 39-bit code of FIG. 6A. There are 157 non-zero filter coefficients shown in FIG. 6C (corresponding to 157 “taps”), providing a noise averaging power of 36, corresponding to an SNR improvement of 15.6 dB.

[0056] FIG. 6D shows an illustrative example of a deconvolved response resulting from filtering of an input time series using the FIR filter coefficients of FIG. 6C, where the input time series comprises the coded emission pulse sequence of FIG. 6A, showing the expected peak at 544 when the FIR deconvolution filter is aligned with a signal corresponding to the coded emission pulse sequence of FIG. 6A. In general, a sample count (e.g., length) of a convolved response can be represented as N+M-l, where N is length of the input signal (in this example, the code sequence), and M is the length of the filter. The input in the example of FIG. 6D (corresponding to the 39- bit code of FIG. 6A) case has length 39, and the FIR filter has a length of about 240 samples.

[0057] FIG. 7 illustrates generally a workflow 700 that can be used to evaluate potential candidate codes (defining pulse sequences for transmission), along with a technique for selecting a code, such as at run-time or when establishing software or firmware for imaging. At 705, during evaluation, a candidate or “trial” binary code 715 can be generated (either randomly or deterministically, such as using theexpression of EQN. 7 for evaluation of pseudo-Barker code candidates), and a corresponding FIR filter coefficient set can be determined at 720. At 725, a first constraint can be applied, such as corresponding to EQN. 4, above and an Ntap / Ncoderatio under five. At 730, a second constraint can be applied, such as to determine improvement in SNR due to noise averaging. At 735, results can be stored, such as in a table or other data structure. At 740, an optimal code for one or more code sequence bit lengths can be determined, such as using the table formed at 735.

[0058] During operation for A-scan acquisition or imaging, such as at run-time at 710, a code can be selected at 745, such as based either on user-selectable criteria (e.g., a gain or dynamic range selection) or based on other constraints such as selected for a particular measurement configuration, frequency, or application. At 750, a coded excitation can be generated, such as by generating acoustic pulses having an envelope defined by a specified code sequence. At 755, acoustic echo signals elicited in response to the transmission event at 750 can be deconvolved using an FIR filter. Alternatively, such acoustic echo signals could be detected using a correlation-based detection technique, though such a technique would likely introduce artifacts associated with side lobes in the autocorrelation function, as compared to deconvolution in the digital domain using an FIR filter. At 760, an A-scan output can be generated that is equivalent to a single-pulse transmission but having enhanced SNR. Such an A-scan output can be stored or presented to a user or can be used for other imaging applications such as PWI or TFM beamforming, as illustrative examples.

[0059] FIG. 8 illustrates generally a technique 800, such as a machine-implemented method that can be used for coded emission and associated detection in an acoustic inspection system. At 805, acoustic pulse transmissions can be generated (such as corresponding to transmit-receive acquisition as a portion of an FMC acquisition). The acoustic pulse transmissions can be defined by a pulse sequence corresponding to a specified code, such as a Barker code or pseudo-Barker code as discussed elsewhere herein. Generally, an acoustic pulser generates a pulse having a specified center frequency (e.g., in an ultrasonic range of frequencies), and for which the code defines an envelope of pulses in a sequence. At 810, acoustic echo data elicited 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 deconvolution based on the specified code used forgeneration of the acoustic pulse transmissions at 805. Alternatively, a correlationbased approach can be used for detection. At 820, an enhanced A-scan representation can be generated, such as having an improved SNR after deconvolution versus an A- scan acquired in the absence of coded emission and deconvolution. At 825, a group of enhanced A-scan representations can be coherently summed, such as for a delay-and- sum beamforming technique, such as to form a pixel or voxel value in an acoustic inspection image. A series of coded emission transmit events and corresponding receive events can be used to form a matrix of enhanced A-scans in this manner, such as for TFM or other beamforming and related imaging, as discussed below.

[0060] FIG. 9A, FIG. 9B, and FIG. 9C shows various illustrative examples of images generated using TFM beamforming, with FIG. 9A showing TFM beamforming without use of coded emission, FIG. 9B showing TFM beamforming where coded emission is used and a correlation-based approach is used for detection, and FIG. 9C showing TFM beamforming where an FIR fdter is used for performing deconvolution. For FIG. 9B and FIG. 9C, coded emission was simulated by convolving each A-scan in the FMC with a 13-bit Barker code (as shown in FIG. 3 A). The FMC data was then reconstructed using both auto-correlation (FIG. 9B) and FIR deconvolution (FIG. 9C). The reconstructed FMC (and resulting TFM image of FIG. 9C) using FIR deconvolution shows no change compared to the original (as represented by the TFM image of FIG. 9A), while the auto-correlation-reconstructed FMC (associated with the TFM image of FIG. 9B) has some artifacts such as shown in the region 346, due to non-zero sidelobes.

[0061] FIG. 10A, FIG. 10B, and FIG. 10C shows various illustrative examples of images generated using TFM beamforming, with FIG. 10A showing TFM beamforming performed in the presence of noise added to the input A-scan data, without use of coded emission, FIG. 10B showing TFM beamforming performed in the presence of noise, including averaging of 13 images where the noise signals added to underlying FMC A-scan data are random and vary between trials, and FIG. 10C showing TFM beamforming where an FIR fdter is used for performing deconvolution, where noise is added, but no averaging is performed. The simulation results of FIG. 9 A, FIG. 9B, FIG. 9C, FIG. 10A, FIG. 10B, and FIG. 10C suggest FIR deconvolution would not introduce sidelobes when SNR is high and would reduce the level ofrandom noise when SNR is low.

[0062] FIG. 11 A, FIG. 11B, and FIG. 11C shows various examples of B-scan images, with FIG. 11 A showing an image acquisition where coded emission is not used, and a center frequency of 0.5 megahertz (MHz) is used, FIG. 11B showing an image acquisition where coded emission is not used, and a center frequency of 5.0 MHz is used, and FIG. 11C showing an image acquisition using coded emission, with a center frequency of 5.0 MHz, and an FIR fdter used for deconvolution. Generally, use of coded emission as described in this document can increase penetration of a probe and hence a higher frequency probe can be used for highly attenuating materials such as composites, in the process enhancing the temporal resolution. In FIG. 11 A, a default inspection setup (using an 0.5 MHz probe) is shown, providing good penetration but relatively poor spatio-temporal resolution. By contrast, in FIG. 11B, a 5MHz probe without coded emission offers improved resolution versus FIG. 11 A, but the front wall region is highly saturated (due to high gain), and the deeper regions have low SNR. By contrast, using coded emission as shown in FIG. 11C, lower gain can be used which decreases saturation at the front wall in the region 1161. In addition, better SNR performance can be obtained in the deeper regions. Consequently, such higher dynamic range allows contemporaneous inspection of both the shallow and deep regions of the sample using a single acquisition and imaging operation.

[0063] FIG. 12 illustrates a block diagram of an example comprising a machine 1200 upon which any one or more of the techniques (e.g., methodologies) discussed herein may be performed. Machine 1200 (e.g., computer system) may include a hardware processor 1202 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a hardware processor core, or any combination thereof), a main memory 1204 and a static memory 1206, connected via an interlink 1230 (e.g., link or bus), as some or all of these components may constitute hardware for systems or related implementations discussed above.

[0064] Generally, the hardware processor 1202 may, for example, include at least one of 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 SpecificIntegrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Radio- Frequency Integrated Circuit (RFIC), a Neuromorphic Processor, a Quantum Processor, or any combination thereof. A processor circuit may further be a multi-core processor having two or more independent processors (sometimes referred to as "cores") that may execute instructions contemporaneously. Multi-core processors contain multiple computational cores on a single integrated circuit die, each of which can independently execute program instructions in parallel. Parallel processing on multi-core processors may be implemented via architectures like superscalar, VLIW, vector processing, or SIMD that allow each core to run separate instruction streams concurrently. A processor circuit may be emulated in software, running on a physical processor, as a virtual processor or virtual circuit. The virtual processor may behave like an independent processor but is implemented in software rather than hardware.

[0065] Specific examples of main memory 1204 include Random Access Memory (RAM), and semiconductor memory devices, which may include storage locations in semiconductors 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 disks; magneto-optical disks; RAM; or optical media such as CD-ROM and DVD-ROM disks.

[0066] The machine 1200 may further 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 an example, the display device 1210, input device 1212, and UI navigation device 1214 may be a touch-screen display. The machine 1200 may include a mass storage device 1208 (e.g., drive unit), a signal generation device 1218 (e.g., a speaker), a network interface device 1220, and one or more sensors 1216, such as a global positioning system (GPS) sensor, compass, accelerometer, or some other sensor. The machine 1200 may include an output controller 1228, such as a serial (e.g., universal serial bus (USB), parallel, or other wired or wireless (e.g., infrared (IR), near field communication (NFC), etc.) connection to communicate or control one or more peripheral devices (e.g., a printer, card reader, etc.).

[0067] The mass storage device 1208 may comprise a machine-readable medium 1222 on which is stored one or more sets of data structures or instructions 1224 (e.g.,software) embodying or utilized by any one or more of the techniques or functions described herein. The instructions 1224 may also reside, completely or at least partially, within the main memory 1204, within static memory 1206, or within the hardware processor 1202 during execution thereof by the machine 1200. In an example, one or any combination of the hardware processor 1202, the main memory 1204, the static memory 1206, or the mass storage device 1208 comprises a machine readable medium.

[0068] Specific examples of machine-readable media include, one or more of nonvolatile memory, such as semiconductor memory devices (e.g., EPROM or EEPROM) and flash memory devices; magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; RAM; or optical media such as CD-ROM and DVD-ROM disks. While the machine-readable medium is illustrated as a single medium, the term "machine readable medium" may include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) configured to store the one or more instructions 1224.

[0069] An apparatus of the machine 1200 includes one or more of a hardware processor 1202 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a hardware processor core, or any combination thereof), a main memory 1204 and a static memory 1206, sensors 1216, network interface device 1220, antennas, a display device 1210, an input device 1212, a UI navigation device 1214, a mass storage device 1208, instructions 1224, a signal generation device 1218, or an output controller 1228. The apparatus may be configured to perform one or more of the methods or operations disclosed herein.

[0070] The term “machine readable medium” includes, for example, any medium that is capable of storing, encoding, or carrying instructions for execution by the machine 1200 and that cause the machine 1200 to perform any one or more of the techniques of the present disclosure or causes another apparatus or system to perform any one or more of the techniques, or that is capable of storing, encoding or carrying data structures used by or associated with such instructions. Non-limiting machine- readable medium examples include solid-state memories, 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 disks; magneto-optical disks; Random Access Memory (RAM); or optical media such as CD-ROM and DVD-ROM disks. In some examples, machine readable media includes non-transitory machine-readable media. In some examples, machine readable media includes machine readable media that is not a transitory propagating signal.

[0071] The instructions 1224 may be transmitted or received, for example, over a communications network 1226 using a transmission medium via the network interface device 1220 utilizing any one of a number of transfer protocols (e.g., frame relay, internet protocol (IP), transmission control protocol (TCP), user datagram protocol (UDP), hypertext transfer protocol (HTTP), etc.). Example communication networks include a local area network (LAN), a wide area network (WAN), a packet data network (e.g., the Internet), mobile telephone networks (e.g., cellular networks), Plain Old Telephone (POTS) networks, and wireless data networks (e.g., Institute of Electrical and Electronics Engineers (IEEE) 802.11 family of standards known as WiFi®), IEEE 802.15.4 family of standards, a Long Term Evolution (LTE) 4G or 5G family of standards, a Universal Mobile Telecommunications System (UMTS) family of standards, peer-to-peer (P2P) networks, satellite communication networks, among others.

[0072] In an example, the network interface device 1220 includes one or more physical jacks (e.g., Ethernet, coaxial, or other interconnection) or one or more antennas to access the communications network 1226. In an example, the network interface device 1220 includes one or more antennas to wirelessly communicate using at least one of single-input multiple-output (SIMO), multiple-input multiple-output (MIMO), or multiple-input single-output (MISO) techniques. In some examples, the network interface device 1220 wirelessly communicates using Multiple User MIMO techniques. The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding or carrying instructions for execution by the machine 1200, and includes digital or analog communications signals or other intangible medium to facilitate communication of such software.Various Notes

[0073] Each of the non-limiting aspects in this document can stand on its own or canbe combined in various permutations or combinations with one or more of the other aspects or other subject matter described in this document.

[0074] The above detailed description includes references to the accompanying drawings, which form a part of the detailed description. The drawings show, by way of illustration, specific embodiments in which the invention can be practiced. These embodiments are also referred to generally as “examples.” Such examples can include elements in addition to those shown or described. However, the present inventor also contemplates examples in which only those elements shown or described are provided. Moreover, the present inventor also contemplates examples using any combination or permutation of those elements shown or described (or one or more aspects thereof), either with respect to a particular example (or one or more aspects thereof), or with respect to other examples (or one or more aspects thereof) shown or described herein.

[0075] In the event of inconsistent usages between this document and any documents so incorporated by reference, the usage in this document controls.

[0076] In this document, the terms “a” or “an” are used, as is common in patent documents, to include one or more than one, independent of any other instances or usages of “at least one” or “one or more.” In this document, the term “or” is used to refer to a nonexclusive or, such that “A or B” includes “A but not B,” “B but not A,” and “A and B,” unless otherwise indicated. In this document, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Also, in the following claims, the terms “including” and “comprising” are open-ended, that is, a system, device, article, composition, formulation, or process that includes elements in addition to those listed after such a term in a claim are still deemed to fall within the scope of that claim. Moreover, in the following claims, the terms “first,” “second,” and “third,” etc., are used merely as labels, and are not intended to impose numerical requirements on their objects.

[0077] Method examples described herein can be machine or computer-implemented at least in part. Some examples can include a computer-readable medium or machine- readable medium encoded with instructions operable to configure an electronic device to perform methods as described in the above examples. An implementation of such methods can include code, such as microcode, assembly language code, a higher-level language code, or the like. Such code can include computer readable instructions forperforming various methods. The code may form portions of computer program products. Such instructions can be read and executed by one or more processors to enable performance of operations comprising a method, for example. The instructions are in any suitable form, such as but not limited to source code, compiled code, interpreted code, executable code, static code, dynamic code, and the like.Further, in an example, the code can be tangibly stored on one or more volatile, non- transitory, or non-volatile tangible computer-readable media, such as during execution or at other times. Examples of these tangible computer-readable media can include, but are not limited to, hard disks, removable magnetic disks, removable optical disks (e.g., compact disks and digital video disks), magnetic cassettes, memory cards or sticks, random access memories (RAMs), read only memories (ROMs), and the like.

[0078] The above description is intended to be illustrative, and not restrictive. For example, the above-described examples (or one or more aspects thereof) may be used in combination with each other. Other embodiments can be used, such as by one of ordinary skill in the art upon reviewing the above description. The Abstract is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. Also, in the above Detailed Description, various features may be grouped together to streamline the disclosure. This should not be interpreted as intending that an unclaimed disclosed feature is essential to any claim. Rather, inventive subject matter may he in less than all features of a particular disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description as examples or embodiments, with each claim standing on its own as a separate embodiment, and it is contemplated that such embodiments can be combined with each other in various combinations or permutations. The scope of the invention should be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.

Claims

WHAT IS CLAIMED IS:

1. A machine-implemented method for performing acoustic inspection, the method comprising: generating respective acoustic pulse transmissions using a specified pulse sequence corresponding to a specified code; in response to the respective acoustic pulse transmissions, acquiring acoustic echo data indicative of scattered or reflected acoustic energy; filtering the acquired acoustic echo data using a finite impulse response (FIR) filter to provide filtered acoustic echo data; and coherently summing representations of the filtered acoustic echo data to provide a pixel or voxel element value.

2. The machine-implemented method of claim 1, wherein the specified pulse sequence comprises a code having an autocorrelation peak, corresponding to an autocorrelation main lobe, when aligned with a representation of itself having zero sample offset, and lower autocorrelation values, corresponding to autocorrelation sidelobes, when aligned with the representation of itself having a non-zero sample offset.

3. The machine-implemented method of any of claims 1 or 2, wherein the specified pulse sequence comprises a Barker code.

4. The machine-implemented method of any of claims 1 or 2, wherein the wherein the specified pulse sequence comprises a code having an odd count of digits.

5. The machine-implemented method of any of claims 1 through 4, wherein a second half of the specified pulse sequence after a mid-point of the specified pulse sequence comprises a mirror image of a first half of the specified pulse sequence but with alternating sign for each successive digit.

6. The machine-implemented method of any of claims 1 through 5, wherein the specified pulse sequence comprises a code, that when aligned with the representation of itself having a non-zero sample offset, exhibits zero-valued autocorrelationsidelobes at odd-valued sample offsets.

7. The machine-implemented method of any of claims 1 through 6, wherein the FIR fdter comprises coefficients established to provide deconvolution of the specified pulse 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 of claim 7, wherein applying the amplitude criterion includes determining a count of candidate impulse response filter coefficients corresponding to a candidate FIR filter having an amplitude greater than a specified amplitude threshold as a proportion of a filter coefficient having a maximum amplitude.

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

10. The machine-implemented method of any of claims 8 or 9, wherein the candidate FIR filter is truncated by dropping candidate impulse response filter coefficients below the specified amplitude threshold to provide the FIR filter used to provide deconvolution.

11. The machine-implemented method of any of claims 1 through 10, wherein the specified code or the FIR filter are established using a criterion that a count of impulse response filter coefficients is constrained to a specified multiple of a count of digits in the specified code.

12. The machine-implemented method of claim 11, wherein the specified multiple is five.

13. The machine-implemented method of any of claims 1 through 12, wherein the FIR filter is established by evaluating a noise averaging metric for a candidate FIR filter.

14. The machine-implemented method of any of claims 1 through 13, wherein the fdtered acoustic echo data comprises A-scan data.

15. The machine-implemented method of any of claims 1 through 14, wherein the coherently summing representations of the fdtered acoustic echo data comprises performing Total Focusing Method (TFM) beamforming, with the specified pulse sequence used for respective transmit-receive acquisitions in a matrix-capture acquisition scheme; and wherein the pixel or voxel element value comprises data for an image generated using the TFM beamforming.

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

17. A system for performing acoustic inspection, the system comprising: a pulse generator circuit; a receiver circuit; at least one processor circuit; and a memory circuit, the memory circuit comprising instructions that, when executed by the at least one processor circuit, cause the system to perform the machine-implemented method of any of claims 1 through 14.

18. A machine-implemented method for coded emission for acoustic inspection, the machine-implemented method comprising: establishing a code for use in an acoustic pulse transmission, the code defined by a specified pulse sequence that exhibits zero-valued autocorrelation sidelobes at odd-valued sample offsets; and establishing a finite impulse response (FIR) filter for use in filtering acquired acoustic echo data received in response to the acoustic pulse transmission, the FIRfilter providing deconvolution of the specified pulse sequence.

19. The machine-implemented method of claim 18, wherein a second half of the specified pulse sequence after a mid-point of the specified pulse sequence comprises a mirror image of a first half of the specified pulse sequence but with alternating sign for each successive digit.

20. The machine-implemented method of any 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 including determining a count of candidate impulse response filter coefficients corresponding to a candidate FIR filter having an amplitude greater than a specified amplitude threshold as a proportion of a filter coefficient having a maximum amplitude.

21. The machine-implemented method of claim 20, wherein the candidate FIR filter is truncated by dropping candidate impulse response filter coefficients below the specified amplitude threshold to provide the FIR filter used to provide deconvolution.

22. The machine-implemented method of any of claims 18 through 21, wherein the specified pulse sequence or the FIR filter are established using a criterion that a count of impulse response filter coefficients is constrained to a specified multiple of a count of digits in the specified pulse sequence.

23. The machine-implemented method of claim 22, wherein the specified multiple is five.

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

25. The machine-implemented method of any of claims 18 through 24, wherein the FIR fdter is established by evaluating a noise averaging metric for a candidate FIR fdter.

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