WO2024009550A1 - Signal processing device and signal processing method - Google Patents

Signal processing device and signal processing method Download PDF

Info

Publication number
WO2024009550A1
WO2024009550A1 PCT/JP2023/006783 JP2023006783W WO2024009550A1 WO 2024009550 A1 WO2024009550 A1 WO 2024009550A1 JP 2023006783 W JP2023006783 W JP 2023006783W WO 2024009550 A1 WO2024009550 A1 WO 2024009550A1
Authority
WO
WIPO (PCT)
Prior art keywords
wave
signal processing
wave transmitting
plane
interface
Prior art date
Application number
PCT/JP2023/006783
Other languages
French (fr)
Japanese (ja)
Inventor
周 小林
泰郎 藤島
Original Assignee
三菱重工業株式会社
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 三菱重工業株式会社 filed Critical 三菱重工業株式会社
Publication of WO2024009550A1 publication Critical patent/WO2024009550A1/en

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/04—Analysing solids
    • G01N29/06—Visualisation of the interior, e.g. acoustic microscopy
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor

Definitions

  • the present disclosure relates to a signal processing device and a signal processing method.
  • Compressive sensing is used in various inspection technology fields, such as magnetic resonance imaging. Imaging methods using compressed sensing assume that the high intensity distribution in the visualization region is sparse, and use a small number of observation results to restore the entire image of the inspection target, or to image the inspection target with high resolution. (For example, see Patent Document 1).
  • the present disclosure has been made in view of the above, and aims to provide a signal processing device and a signal processing method that can accurately image an inspection target.
  • a plane wave transmitted from a plurality of wave transmitting/receiving elements in an oblique direction tilted with respect to a normal direction of an interface of an object to be inspected propagates inside the object to be inspected and is reflected at a focal point.
  • a plane wave transmitted from a plurality of wave transmitting/receiving elements in an oblique direction tilted with respect to a normal direction of an interface of an inspection object propagates inside the inspection object and is reflected at a focal point.
  • a propagation model loading step of loading a predetermined propagation model indicating a propagation path of the plane wave when reaching a wave transmitting/receiving element; and a case where a plurality of the wave transmitting/receiving elements transmit the plane wave in the oblique direction toward the inspection target.
  • an observation data acquisition step of acquiring observation data received by a plurality of said wave transmitting/receiving elements, and generating imaging data of said inspection target by compressed sensing based on said read propagation model and said acquired observation data. and an imaging data generation step.
  • FIG. 1 is a schematic diagram showing an example of a measurement system including a signal processing device according to this embodiment.
  • FIG. 2 is a flowchart illustrating an example of the signal processing method according to this embodiment.
  • FIG. 3 is a diagram schematically showing an example of a propagation path (outward path) of a transmitted wave in a propagation model.
  • FIG. 4 is a diagram schematically showing an example of a propagation path (return path) of a transmitted wave in a propagation model.
  • FIG. 5 is a flowchart illustrating an example of an algorithm in the compressed sensing processing step.
  • FIG. 6 is a diagram schematically showing an example of an imaging range by the measurement system.
  • FIG. 7 is a diagram schematically showing an example of monitoring acoustic images.
  • FIG. 8 is a diagram schematically showing the outline of imaging using a plurality of transmitted waves.
  • FIG. 9 is a diagram showing an example of a transmission level for each refraction angle of a transverse wave.
  • FIG. 1 is a schematic diagram showing an example of a measurement system SYS including a signal processing device 100 according to the present embodiment. As shown in FIG. 1, the measurement system SYS includes a sensor 10 and a signal processing device 100.
  • the sensor 10 has a plurality of wave transmitting/receiving elements 11 that output an emitted wave for exploration, receive reflected waves of the outputted emitted wave, and perform exploration of the inspection target 40.
  • the sensor 10 is arranged with a plurality of wave transmitting/receiving elements 11 arranged in an array.
  • the emitted wave is a plane wave, for example, an acoustic signal such as an ultrasonic wave.
  • PWI Plane Wave Imaging
  • the sensor 10 is a wedge-type sensor that makes the emitted wave enter in an oblique direction that is inclined with respect to the normal direction of the interface 41 of the inspection object 40 (the y direction in FIGS. 3 and 4).
  • the exploration is performed using ultrasonic waves, but radio waves or the like may also be used.
  • the signal processing device 100 is connected to the sensor 10 via a pulser receiver 50, for example.
  • the signal processing device 100 processes the signal received by the wave transmitting/receiving element 11 and detects the surroundings.
  • the signal processing device 100 includes a calculation section 20 and a storage section 30.
  • the calculation unit 20 is, for example, a CPU (Central Processing Unit).
  • the calculation unit 20 performs various calculations.
  • the storage unit 30 includes at least one of, for example, a RAM (Random Access Memory), a main storage unit such as a ROM (Read Only Memory), and an external storage unit such as an HDD (Hard Disk Drive).
  • the calculation unit 20 transmits and receives plane waves that are transmitted from the plurality of wave transmitting/receiving elements 11 in an oblique direction that is inclined with respect to the normal direction of the interface 41 of the test object 40, propagates inside the test object 40, is reflected at the focal point p, and is transmitted and received.
  • a predetermined propagation model indicating the propagation path of a plane wave when it reaches the wave element 11 is read.
  • the calculation unit 20 acquires observation data received by the plurality of wave transmitting/receiving elements 11 when the plurality of wave transmitting/receiving elements 11 transmit plane waves in the oblique direction to the inspection target 40 .
  • the calculation unit 20 generates imaging data of the inspection object 40 by compressed sensing based on the read propagation model and the acquired observation data.
  • the range of the interface 41 corresponding to the array aperture formed by the plurality of wave transmitting/receiving elements 11 is set inside the inspection object 40.
  • the calculation unit 20 invalidates plane waves that do not pass through the set range of the interface 41.
  • the calculation unit 20 executes each of the above-mentioned processes by reading and executing a program (software) from the storage unit 30.
  • the storage unit 30 stores various information such as calculation contents and programs of the calculation unit 20.
  • the storage unit 30 may store processing results detected by the sensor 10, that is, exploration results.
  • the calculation unit 20 optimizes the interface coordinates, which are the intersections of the interface 41 and the propagation path, in compressed sensing. In this case, the calculation unit 20 performs optimization so that the difference in the normal direction at the position of each wave transmitting/receiving element 11 becomes as small as possible for the reflected wave of the plane wave transmitted from each wave transmitting/receiving element 11. For example, optimization is performed so that the value is less than or equal to the value determined by the product of the speed of sound and the time corresponding to the pulse width of the plane wave.
  • the calculation unit 20 performs compressed sensing so that the number of effective plane waves arriving within a predetermined period corresponding to the pulse width of the plane wave is equal to or greater than a threshold value.
  • the threshold value is set so that the shorter the predetermined period, the smaller the value.
  • the calculation unit 20 performs optimization in compressed sensing, taking into account the sparsity of a plurality of clusters of high-intensity pixels that make up the imaging data.
  • the calculation unit 20 executes each of the above-mentioned processes by reading and executing a program (software) from the storage unit 30.
  • the storage unit 30 stores various information such as calculation contents and programs of the calculation unit 20.
  • the storage unit 30 may store processing results detected by the sensor 10, that is, exploration results.
  • the storage unit 30 stores plane waves emitted from the plurality of wave transmitting/receiving elements 11 in an oblique direction tilted with respect to the normal direction of the interface 41 of the test object 40 , which propagates inside the test object 40 and is reflected at a focal point to transmit and receive waves.
  • a signal processing program that causes a computer to execute a process of acquiring observation data received by the computer and a process of generating imaging data of the inspection target 40 by compressed sensing based on the read propagation model and the acquired observation data.
  • FIG. 2 is a flowchart illustrating an example of the signal processing method according to this embodiment.
  • the signal processing method according to the present embodiment includes a propagation model reading step S10, an observation data acquisition step S20, and an imaging data generation step S30.
  • the calculation unit 20 calculates that the plane waves transmitted from the plurality of wave transmitting/receiving elements 11 in an oblique direction inclined with respect to the normal direction of the interface 41 of the inspection object 40 propagate inside the inspection object 40.
  • a predetermined propagation model indicating the propagation path of a plane wave when it is reflected at the focal point and reaches the wave transmitting/receiving element 11 is read.
  • a transmitted wave i reaches an arbitrary focal position l from the transmission time, and a reflected wave from there returns to the k-th wave transmitting/receiving element 11 (k-th element).
  • the propagation time ⁇ ilk is required.
  • the propagation model read in the propagation model reading step S10 is one in which the propagation time ⁇ ilk for each focal position of the ultrasonic wave propagating through the wedge-shaped sensor 10 is calculated and recorded.
  • the propagation model is created offline in advance.
  • FIG. 3 is a diagram schematically showing an example of the propagation path (outward path) of the transmitted wave in the propagation model.
  • FIG. 3 shows a path from the transmitter of the sensor 10 to the focal point p.
  • FIG. 4 is a diagram schematically showing an example of a propagation path (return path) of a transmitted wave in a propagation model.
  • FIG. 4 shows a path from the focal point p to the receiving section of the sensor 10.
  • the propagation time ⁇ ilk can be calculated by dividing the outward propagation paths d (1) and d (2) shown in FIG. 3 and the return path propagation paths d (3) and d (4) shown in FIG. 4 by the speed of sound. It is possible to ask for it.
  • the propagation time ⁇ ilk is multiplied as follows.
  • the outward propagation paths d (1) and d (2) are the coordinates [x VIRT y VIRT ] T on the interface 41 of the propagation path, the intersection coordinates x b of the plane wave front with the interface 41 at the time of starting the emission, and the coordinates x b at the interface 41.
  • ⁇ W of the incident angle
  • the return propagation paths d (3) and d (4) are paths for the reflected wave to reach the position [x k y k ] T of the k-th element in the shortest time, and the coordinates on the interface 41 are optimized. is required. That is, the return propagation paths d (3) and d (4) are multiplied as follows using the optimized interface coordinates [x VIRT y VIRT ] T.
  • the coordinate x b on the interface 41 is scanned in the range 0 ⁇ x b ⁇ x w , and the coordinate where the difference ⁇ H k in the height direction between the propagation path shown in FIG. 4 and the target element is minimized is x VIRT. , k .
  • x VIRT,k 0, the above relationship holds true for the sensor 10 of any shape if optimization can be performed using the shortest time path.
  • the plane wave In a PWI that transmits a plane wave, the plane wave is formed only within a width range corresponding to the array aperture length of the sensor 10. Therefore, the range of interface coordinates shown in Figure 3 The plane wave does not reach the focal point that does not pass through the plane, and the above-mentioned propagation model does not hold. In this embodiment, since this condition is used as a modeling constraint, an invalid value is input for the propagation time of the focal point that does not pass through the above range. As a result, during compressed sensing, plane waves that do not pass through the set range of the interface 41 are invalidated.
  • the grid interval can be determined using ⁇ H k after optimization as an accuracy index.
  • Set the scanning grid interval to be .
  • v w is the speed of sound
  • T is the time equivalent to the pulse width of the ultrasonic wave
  • [Equation 6] is equivalent to the distance traveled in one pulse time.
  • an observation matrix A i (t) in compressed sensing is derived, and based on the derived observation matrix, an acoustic image Estimate.
  • the calculation unit 20 calculates the observation data received by the plurality of wave transmitting/receiving elements 11 when the plurality of wave transmitting/receiving elements 11 transmit plane waves in the oblique direction to the inspection object 40. get.
  • the calculation unit 20 generates imaging data of the inspection target 40 by compressed sensing based on the read propagation model and the acquired observation data.
  • FIG. 5 is a flowchart showing an example of an algorithm in compressed sensing processing step S30. Note that this embodiment is also effective in PWI that does not involve the wedge-type sensor 10.
  • the received signal ⁇ i k (t) of beam i and k-th element is calculated using the above ⁇ ilk It can be expressed as
  • Equation 8 a coefficient c ilk (t) is introduced into the equation shown in Equation 8 (step S501).
  • the coefficient c ilk (t) is , which limits the received signals to be processed.
  • the received signal can be spatially limited by applying the above condition for the pixel l where the plane wave does not arrive and the propagation time is an invalid value to "otherwise" in Equation 9.
  • Equation 9 the received signal is also limited on the propagation time axis as represented by T.
  • T is the time corresponding to the transmission pulse width
  • the coefficient c ilk (t) expresses the duration of the signal.
  • FIG. 6 is a diagram schematically showing an example of an imaging range by the measurement system.
  • FIG. 6 shows an example of the imaging range of the estimated value S i (t) of the pixel value at measurement time t, and an example of the imaging range of the entire imaging region S(t).
  • the received signal vector ⁇ i (t) of beam i is It can be written as
  • a il (t) is a vector representing the phase difference for each wave transmitting/receiving element 11, It can be defined as:
  • the observation matrix is the combination of these vectors into one matrix. (Step S505).
  • the pixel value s i (t) of the imaging range determined by beam i and time t is estimated by solving the optimization problem shown below.
  • an acoustic image is obtained (step S506).
  • the optimization index a known evaluation function such as LASSO, Sparse Group LASSO (SG-LASSO), etc. can be used.
  • Equation 15 can be solved using the observation matrix A i (t) described above.
  • ⁇ is a coefficient called a regularization parameter.
  • ⁇ G is a regularization parameter that determines the degree of sparsity of the chunk. Also, represents a portion of the vector S i (t). That is, It is.
  • FIG. 7 is a diagram schematically showing an example of monitoring acoustic images.
  • monitoring software that can visualize acoustic images for each setting and check visibility is useful for testing the test object 40.
  • FIG. 8 is a diagram schematically showing the outline of imaging using a plurality of transmitted waves.
  • plane waves are generally transmitted in multiple directions to cover the imaging range.
  • the acoustic image obtained as above is the imaging result for all beams. is assigned to the index of the entire imaging area and added (step S507). It is possible to obtain (step S508).
  • FIG. 9 is a diagram showing an example of a transmission level for each refraction angle of a transverse wave.
  • the horizontal axis in FIG. 9 indicates the refraction angle, and the vertical axis indicates the level.
  • the relationship shown in FIG. 9 is reflected and added to the coefficient k i of the equation shown in Equation 20 below.
  • the coefficient k i is a value corresponding to the vertical axis in FIG. 9 .
  • the overall image in the generated imaging data of the inspection object 40 is Optimized intensity range improves visibility.
  • the signal processing device is capable of transmitting plane waves emitted from the plurality of wave transmitting/receiving elements 11 in an inclined direction inclined with respect to the normal direction of the interface 41 of the inspection object 40.
  • the processing unit 20 includes a calculation unit 20 that performs a process of generating data.
  • the inspection object 40 is probed by a plane wave emitted from the wave transmitting/receiving element 11 in an inclined direction inclined with respect to the normal direction of the interface 41 of the inspection object 40, and imaging data is generated by compressed sensing. 40 can be imaged with high precision.
  • the signal processing device is the signal processing device according to the first aspect, in which in the propagation model, the range of the interface 41 corresponding to the array aperture formed by the plurality of wave transmitting/receiving elements 11 is set inside the inspection object 40, When performing compression sensing, the calculation unit 20 invalidates plane waves that do not pass through the set range of the interface 41. Therefore, since constraint conditions can be imposed on the propagation model, more accurate settings can be made in compressive sensing.
  • the calculation unit 20 optimizes the interface coordinates that are the intersections of the interface 41 and the propagation path in compressed sensing. , the calculation unit 20 calculates that the difference in the normal direction at the position of the plane wave reflected wave transmitted from each wave transceiver 11 is the product of the sound velocity and the time corresponding to the pulse width of the plane wave. Optimize so that the value is less than or equal to the required value. Therefore, the scanning range of the interface coordinates, which required adjustment by trial and error in the optimization algorithm, can be appropriately set.
  • the calculation unit 20 is configured such that the number of valid plane waves arriving within a predetermined period corresponding to the pulse width of the plane wave is equal to or greater than a threshold value. Compressed sensing is performed so that the threshold value becomes smaller as the predetermined period becomes shorter. Therefore, by limiting the observation data of plane waves, it is possible to speed up the processing of compressed sensing.
  • a signal processing device is the signal processing device according to any of the first to fourth aspects, in which the calculation unit 20 performs optimization for a plurality of clusters of pixels constituting imaging data in compressed sensing. .
  • the calculation unit 20 performs optimization for a plurality of clusters of pixels constituting imaging data in compressed sensing. .
  • the defect has a certain size. Therefore, by evaluating sparsity in units of a plurality of pixels, defects can be more easily visualized than in the case of evaluating sparsity in units of pixels.
  • a plane wave transmitted from a plurality of wave transmitting/receiving elements 11 in an inclined direction inclined with respect to a normal direction of an interface 41 of an inspection object 40 propagates inside the inspection object 40 and reaches a focal point.
  • a propagation model reading step S10 reads a predetermined propagation model indicating the propagation path of a plane wave when it is reflected and reaches the wave transmitting/receiving element 11, and a plane wave is transmitted in an oblique direction to the inspection object 40, and the received observation data is transmitted.
  • the process includes an observation data acquisition step S20, and an imaging data generation step S30, which generates imaging data of the inspection object 40 by compressed sensing based on the read propagation model and the acquired observation data.
  • the inspection object 40 is probed by a plane wave emitted from the wave transmitting/receiving element 11 in an inclined direction inclined with respect to the normal direction of the interface 41 of the inspection object 40, and imaging data is generated by compressed sensing. 40 can be imaged with high precision.

Landscapes

  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Pathology (AREA)
  • Immunology (AREA)
  • Biochemistry (AREA)
  • Engineering & Computer Science (AREA)
  • Signal Processing (AREA)
  • Acoustics & Sound (AREA)
  • Investigating Or Analyzing Materials By The Use Of Ultrasonic Waves (AREA)
  • Radar Systems Or Details Thereof (AREA)
  • Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)

Abstract

This signal processing device comprises a processing unit that performs: a process for reading a predetermined propagation model showing plane wave propagation paths when plane waves transmitted from a plurality of wave transmitter/receiver elements in an inclined direction at an angle to the normal direction to an interface of an object under examination propagate through the inside of the object under examination, are reflected at a focal point, and arrive at the wave transmitter/receiver elements; a process for acquiring observation data that is received by the plurality of wave transmitter/receiver elements when the plurality of wave transmitter/receiver elements transmit plane waves in the inclined direction to the object under examination; and a process for generating imaging data of the object under examination through compressed sensing on the basis of the read propagation model and the acquired observation data.

Description

信号処理装置及び信号処理方法Signal processing device and signal processing method
　本開示は、信号処理装置及び信号処理方法に関する。 The present disclosure relates to a signal processing device and a signal processing method.
　圧縮センシングは、例えば磁気共鳴イメージング等のような様々な検査技術の分野において使用されている。圧縮センシングを用いたイメージング手法においては、可視化領域において高い強度分布がスパースであると仮定し、少数の観測結果を用いて検査対象のイメージ全体を復元したり、高い分解能で検査対象のイメージングを行ったりすることが可能である（例えば、特許文献１参照）。 Compressive sensing is used in various inspection technology fields, such as magnetic resonance imaging. Imaging methods using compressed sensing assume that the high intensity distribution in the visualization region is sparse, and use a small number of observation results to restore the entire image of the inspection target, or to image the inspection target with high resolution. (For example, see Patent Document 1).
特許第６７３４２７０号公報Patent No. 6734270
　上記のような圧縮センシングを用いたイメージング手法においては、検査対象を精度よくイメージングすることが求められている。 In the imaging method using compressed sensing as described above, it is required to accurately image the inspection target.
　本開示は、上記に鑑みてなされたものであり、検査対象を精度よくイメージングすることが可能な信号処理装置及び信号処理方法を提供することを目的とする。 The present disclosure has been made in view of the above, and aims to provide a signal processing device and a signal processing method that can accurately image an inspection target.
　本開示に係る信号処理装置は、複数の送受波素子から検査対象の界面の法線方向に対して傾いた傾斜方向に発信される平面波が前記検査対象の内部を伝搬し焦点で反射して前記送受波素子に到達する場合の前記平面波の伝搬経路を示す所定の伝搬モデルを読み込む処理と、複数の前記送受波素子が前記検査対象に対して前記傾斜方向に前記平面波を発信した場合に複数の前記送受波素子で受信される観測データを取得する処理と、読み込んだ前記伝搬モデルと、取得した前記観測データとに基づいて、圧縮センシングにより前記検査対象のイメージングデータを生成する処理と、を行う処理部を備える。 In the signal processing device according to the present disclosure, a plane wave transmitted from a plurality of wave transmitting/receiving elements in an oblique direction tilted with respect to a normal direction of an interface of an object to be inspected propagates inside the object to be inspected and is reflected at a focal point. A process of reading a predetermined propagation model indicating a propagation path of the plane wave when it reaches a wave transmitting/receiving element, and a process of loading a predetermined propagation model indicating the propagation path of the plane wave when it reaches the wave transmitting/receiving element, and A process of acquiring observation data received by the wave transmitting/receiving element, and a process of generating imaging data of the inspection target by compressed sensing based on the read propagation model and the acquired observation data. It includes a processing section.
　本開示に係る信号処理方法は、複数の送受波素子から検査対象の界面の法線方向に対して傾いた傾斜方向に発信される平面波が前記検査対象の内部を伝搬し焦点で反射して前記送受波素子に到達する場合の前記平面波の伝搬経路を示す所定の伝搬モデルを読み込む伝搬モデル読み込みステップと、複数の前記送受波素子が前記検査対象に対して前記傾斜方向に前記平面波を発信した場合に複数の前記送受波素子で受信される観測データを取得する観測データ取得ステップと、読み込んだ前記伝搬モデルと、取得した前記観測データとに基づいて、圧縮センシングにより前記検査対象のイメージングデータを生成するイメージングデータ生成ステップとを含む。 In the signal processing method according to the present disclosure, a plane wave transmitted from a plurality of wave transmitting/receiving elements in an oblique direction tilted with respect to a normal direction of an interface of an inspection object propagates inside the inspection object and is reflected at a focal point. a propagation model loading step of loading a predetermined propagation model indicating a propagation path of the plane wave when reaching a wave transmitting/receiving element; and a case where a plurality of the wave transmitting/receiving elements transmit the plane wave in the oblique direction toward the inspection target. an observation data acquisition step of acquiring observation data received by a plurality of said wave transmitting/receiving elements, and generating imaging data of said inspection target by compressed sensing based on said read propagation model and said acquired observation data. and an imaging data generation step.
　本開示によれば、検査対象を精度よくイメージングすることが可能な信号処理装置及び信号処理方法を提供することができる。 According to the present disclosure, it is possible to provide a signal processing device and a signal processing method that can accurately image an inspection target.
図１は、本実施形態に係る信号処理装置を備える計測システムの一例を示す模式図である。FIG. 1 is a schematic diagram showing an example of a measurement system including a signal processing device according to this embodiment. 図２は、本実施形態に係る信号処理方法の一例を示すフローチャートである。FIG. 2 is a flowchart illustrating an example of the signal processing method according to this embodiment. 図３は、伝搬モデルにおける送信波の伝播経路（往路）の一例を模式的に示す図である。FIG. 3 is a diagram schematically showing an example of a propagation path (outward path) of a transmitted wave in a propagation model. 図４は、伝搬モデルにおける送信波の伝播経路（復路）の一例を模式的に示す図である。FIG. 4 is a diagram schematically showing an example of a propagation path (return path) of a transmitted wave in a propagation model. 図５は、圧縮センシング処理ステップにおけるアルゴリズムの一例を示すフローチャートである。FIG. 5 is a flowchart illustrating an example of an algorithm in the compressed sensing processing step. 図６は、計測システムによるイメージング範囲の一例を模式的に示す図である。FIG. 6 is a diagram schematically showing an example of an imaging range by the measurement system. 図７は、音響画像のモニタリングの一例を模式的に示す図である。FIG. 7 is a diagram schematically showing an example of monitoring acoustic images. 図８は、複数の送信波を用いたイメージングの概略を模式的に示す図である。FIG. 8 is a diagram schematically showing the outline of imaging using a plurality of transmitted waves. 図９は、横波の屈折角ごとの送信レベルの一例を示す図である。FIG. 9 is a diagram showing an example of a transmission level for each refraction angle of a transverse wave.
　以下、本開示に係る信号処理装置及び信号処理方法の実施形態を図面に基づいて説明する。なお、この実施形態によりこの発明が限定されるものではない。また、下記実施形態における構成要素には、当業者が置換可能かつ容易なもの、あるいは実質的に同一のものが含まれる。 Hereinafter, embodiments of a signal processing device and a signal processing method according to the present disclosure will be described based on the drawings. Note that the present invention is not limited to this embodiment. Furthermore, the constituent elements in the embodiments described below include those that can be easily replaced by those skilled in the art, or those that are substantially the same.
　図１は、本実施形態に係る信号処理装置１００を備える計測システムＳＹＳの一例を示す模式図である。図１に示すように、計測システムＳＹＳは、センサ１０と、信号処理装置１００とを備える。 FIG. 1 is a schematic diagram showing an example of a measurement system SYS including a signal processing device 100 according to the present embodiment. As shown in FIG. 1, the measurement system SYS includes a sensor 10 and a signal processing device 100.
　センサ１０は、探査用の発信波を出力し、出力した発信波の反射波を受信して、検査対象４０の探査を行う複数の送受波素子１１を有する。センサ１０は、複数の送受波素子１１がアレイ状に並んだ状態で配置される。本実施形態において、発信波は、平面波であり、例えば超音波等の音響信号である。本実施形態では、平面波によるＰＷＩ（Ｐｌａｎｅ　Ｗａｖｅ　Ｉｍａｇｉｎｇ）を行う場合を例に挙げて説明する。本実施形態において、センサ１０は、検査対象４０の界面４１の法線方向（図３、図４のｙ方向）に対して傾いた傾斜方向に発信波を入射させるウェッジ型のセンサである。なお、本実施形態では超音波を用いた探査としたが、電波等を用いてもよい。 The sensor 10 has a plurality of wave transmitting/receiving elements 11 that output an emitted wave for exploration, receive reflected waves of the outputted emitted wave, and perform exploration of the inspection target 40. The sensor 10 is arranged with a plurality of wave transmitting/receiving elements 11 arranged in an array. In this embodiment, the emitted wave is a plane wave, for example, an acoustic signal such as an ultrasonic wave. In this embodiment, a case where PWI (Plane Wave Imaging) using plane waves is performed will be described as an example. In this embodiment, the sensor 10 is a wedge-type sensor that makes the emitted wave enter in an oblique direction that is inclined with respect to the normal direction of the interface 41 of the inspection object 40 (the y direction in FIGS. 3 and 4). Note that in this embodiment, the exploration is performed using ultrasonic waves, but radio waves or the like may also be used.
　信号処理装置１００は、例えばパルサーレシーバー５０を介してセンサ１０に接続される。信号処理装置１００は、送受波素子１１で受信した信号を処理して、周囲を探知する。信号処理装置１００は、演算部２０と、記憶部３０とを有する。演算部２０は、例えばＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）である。演算部２０は、各種演算を行う。記憶部３０は、例えば、ＲＡＭ（Ｒａｎｄｏｍ　Ａｃｃｅｓｓ　Ｍｅｍｏｒｙ）と、ＲＯＭ（Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）のような主記憶部と、ＨＤＤ（Ｈａｒｄ　Ｄｉｓｋ　Ｄｒｉｖｅ）などの外部記憶部とのうち、少なくとも１つ含む。 The signal processing device 100 is connected to the sensor 10 via a pulser receiver 50, for example. The signal processing device 100 processes the signal received by the wave transmitting/receiving element 11 and detects the surroundings. The signal processing device 100 includes a calculation section 20 and a storage section 30. The calculation unit 20 is, for example, a CPU (Central Processing Unit). The calculation unit 20 performs various calculations. The storage unit 30 includes at least one of, for example, a RAM (Random Access Memory), a main storage unit such as a ROM (Read Only Memory), and an external storage unit such as an HDD (Hard Disk Drive).
　演算部２０は、複数の送受波素子１１から検査対象４０の界面４１の法線方向に対して傾いた傾斜方向に発信される平面波が検査対象４０の内部を伝搬し焦点ｐで反射して送受波素子１１に到達する場合の平面波の伝搬経路を示す所定の伝搬モデルを読み込む。演算部２０は、複数の送受波素子１１が検査対象４０に対して傾斜方向に平面波を発信した場合に複数の送受波素子１１で受信される観測データを取得する。演算部２０は、読み込んだ伝搬モデルと、取得した観測データとに基づいて、圧縮センシングにより検査対象４０のイメージングデータを生成する。 The calculation unit 20 transmits and receives plane waves that are transmitted from the plurality of wave transmitting/receiving elements 11 in an oblique direction that is inclined with respect to the normal direction of the interface 41 of the test object 40, propagates inside the test object 40, is reflected at the focal point p, and is transmitted and received. A predetermined propagation model indicating the propagation path of a plane wave when it reaches the wave element 11 is read. The calculation unit 20 acquires observation data received by the plurality of wave transmitting/receiving elements 11 when the plurality of wave transmitting/receiving elements 11 transmit plane waves in the oblique direction to the inspection target 40 . The calculation unit 20 generates imaging data of the inspection object 40 by compressed sensing based on the read propagation model and the acquired observation data.
　伝搬モデルにおいて、複数の送受波素子１１によるアレイ開口に対応する界面４１の範囲が検査対象４０の内部に設定される。この場合、演算部２０は、圧縮センシングを行う際、設定された界面４１の範囲を経由しない平面波については無効とする。 In the propagation model, the range of the interface 41 corresponding to the array aperture formed by the plurality of wave transmitting/receiving elements 11 is set inside the inspection object 40. In this case, when performing compressed sensing, the calculation unit 20 invalidates plane waves that do not pass through the set range of the interface 41.
　演算部２０は、記憶部３０からプログラム（ソフトウェア）を読み出して実行することで、上記の各処理を実行する。記憶部３０は、演算部２０の演算内容やプログラムなどの各種情報を記憶する。記憶部３０は、センサ１０で検出した処理結果、つまり探査の結果を記憶してもよい。 The calculation unit 20 executes each of the above-mentioned processes by reading and executing a program (software) from the storage unit 30. The storage unit 30 stores various information such as calculation contents and programs of the calculation unit 20. The storage unit 30 may store processing results detected by the sensor 10, that is, exploration results.
　演算部２０は、圧縮センシングにおいて、界面４１と伝搬経路との交点である界面座標の最適化を行う。この場合、演算部２０は、それぞれの送受波素子１１から発信される平面波の反射波について当該送受波素子１１の位置における法線方向の差分が限りなく小さくなるように最適化を行う。例えば、音速と平面波のパルス幅に対応する時間との積で求められる値以下となるように最適化を行う。 The calculation unit 20 optimizes the interface coordinates, which are the intersections of the interface 41 and the propagation path, in compressed sensing. In this case, the calculation unit 20 performs optimization so that the difference in the normal direction at the position of each wave transmitting/receiving element 11 becomes as small as possible for the reflected wave of the plane wave transmitted from each wave transmitting/receiving element 11. For example, optimization is performed so that the value is less than or equal to the value determined by the product of the speed of sound and the time corresponding to the pulse width of the plane wave.
　演算部２０は、平面波のパルス幅に対応する所定期間内に到達する有効な平面波の数が閾値以上となるように圧縮センシングを行う。この場合、閾値は、所定期間が短いほど小さい値となるように設定される。 The calculation unit 20 performs compressed sensing so that the number of effective plane waves arriving within a predetermined period corresponding to the pulse width of the plane wave is equal to or greater than a threshold value. In this case, the threshold value is set so that the shorter the predetermined period, the smaller the value.
　演算部２０は、圧縮センシングにおいて、イメージングデータを構成する複数の高強度の画素の塊のスパース性を考慮して最適化を行う。 The calculation unit 20 performs optimization in compressed sensing, taking into account the sparsity of a plurality of clusters of high-intensity pixels that make up the imaging data.
　演算部２０は、記憶部３０からプログラム（ソフトウェア）を読み出して実行することで、上記の各処理を実行する。記憶部３０は、演算部２０の演算内容やプログラムなどの各種情報を記憶する。記憶部３０は、センサ１０で検出した処理結果、つまり探査の結果を記憶してもよい。 The calculation unit 20 executes each of the above-mentioned processes by reading and executing a program (software) from the storage unit 30. The storage unit 30 stores various information such as calculation contents and programs of the calculation unit 20. The storage unit 30 may store processing results detected by the sensor 10, that is, exploration results.
　記憶部３０は、複数の送受波素子１１から検査対象４０の界面４１の法線方向に対して傾いた傾斜方向に発信される平面波が検査対象４０の内部を伝搬し焦点で反射して送受波素子１１に到達する場合の平面波の伝搬経路を示す所定の伝搬モデルを読み込む処理と、複数の送受波素子１１が検査対象４０に対して傾斜方向に平面波を発信した場合に複数の送受波素子１１で受信される観測データを取得する処理と、読み込んだ伝搬モデルと、取得した観測データとに基づいて、圧縮センシングにより検査対象４０のイメージングデータを生成する処理とをコンピュータに実行させる信号処理プログラムを記憶する。 The storage unit 30 stores plane waves emitted from the plurality of wave transmitting/receiving elements 11 in an oblique direction tilted with respect to the normal direction of the interface 41 of the test object 40 , which propagates inside the test object 40 and is reflected at a focal point to transmit and receive waves. The process of reading a predetermined propagation model indicating the propagation path of a plane wave when it reaches the element 11, and the process of loading a predetermined propagation model that indicates the propagation path of a plane wave when it reaches the element 11, and the process of reading a predetermined propagation model that indicates the propagation path of a plane wave when it reaches the element 11, and the process of reading a predetermined propagation model that indicates the propagation path of a plane wave when it reaches the element 11. A signal processing program that causes a computer to execute a process of acquiring observation data received by the computer and a process of generating imaging data of the inspection target 40 by compressed sensing based on the read propagation model and the acquired observation data. Remember.
　以下、本実施形態に係る測定システムの計測処理について説明する。図２は、本実施形態に係る信号処理方法の一例を示すフローチャートである。図２に示すように、本実施形態に係る信号処理方法は、伝搬モデル読み込みステップＳ１０と、観測データ取得ステップＳ２０と、イメージングデータ生成ステップＳ３０とを含む。 Hereinafter, the measurement processing of the measurement system according to this embodiment will be explained. FIG. 2 is a flowchart illustrating an example of the signal processing method according to this embodiment. As shown in FIG. 2, the signal processing method according to the present embodiment includes a propagation model reading step S10, an observation data acquisition step S20, and an imaging data generation step S30.
　伝搬モデル読み込みステップＳ１０において、演算部２０は、複数の送受波素子１１から検査対象４０の界面４１の法線方向に対して傾いた傾斜方向に発信される平面波が検査対象４０の内部を伝搬し焦点で反射して送受波素子１１に到達する場合の平面波の伝搬経路を示す所定の伝搬モデルを読み込む。 In the propagation model reading step S10, the calculation unit 20 calculates that the plane waves transmitted from the plurality of wave transmitting/receiving elements 11 in an oblique direction inclined with respect to the normal direction of the interface 41 of the inspection object 40 propagate inside the inspection object 40. A predetermined propagation model indicating the propagation path of a plane wave when it is reflected at the focal point and reaches the wave transmitting/receiving element 11 is read.
　本実施形態に係る測定システムの計測処理では、送信時刻から任意の焦点位置ｌに送信波ｉが到達し、そこからの反射波がｋ番目の送受波素子１１（第ｋ素子）に返ってくるまでの伝搬時間τｉｌｋが必要になる。伝搬モデル読み込みステップＳ１０において読み込まれる伝搬モデルは、ウェッジ型のセンサ１０を介して伝搬する超音波の焦点位置ごとの伝搬時間τｉｌｋを計算し、記録したものである。伝搬モデルは、オフラインで事前に作成されるものである。 In the measurement process of the measurement system according to this embodiment, a transmitted wave i reaches an arbitrary focal position l from the transmission time, and a reflected wave from there returns to the k-th wave transmitting/receiving element 11 (k-th element). The propagation time τ ilk is required. The propagation model read in the propagation model reading step S10 is one in which the propagation time τ ilk for each focal position of the ultrasonic wave propagating through the wedge-shaped sensor 10 is calculated and recorded. The propagation model is created offline in advance.
　図３は、伝搬モデルにおける送信波の伝播経路（往路）の一例を模式的に示す図である。図３では、センサ１０の送信部から焦点ｐまでの経路を示す。図４は、伝搬モデルにおける送信波の伝播経路（復路）の一例を模式的に示す図である。図４では、焦点ｐからセンサ１０の受信部までの経路を示す。 FIG. 3 is a diagram schematically showing an example of the propagation path (outward path) of the transmitted wave in the propagation model. FIG. 3 shows a path from the transmitter of the sensor 10 to the focal point p. FIG. 4 is a diagram schematically showing an example of a propagation path (return path) of a transmitted wave in a propagation model. FIG. 4 shows a path from the focal point p to the receiving section of the sensor 10.
　伝搬時間τｉｌｋは、図３に示す往路の伝搬経路ｄ（１）、ｄ（２）、及び、図４に示す復路の伝搬経路ｄ（３）、ｄ（４）を音速で除算することで求めることが可能である。センサ１０内の音速をｖｗ、検査対象４０内の音速をｖｓとすると、伝搬時間τｉｌｋは、以下のようにかける。
Figure JPOXMLDOC01-appb-M000001
 The propagation time τ ilk can be calculated by dividing the outward propagation paths d (1) and d (2) shown in FIG. 3 and the return path propagation paths d (3) and d (4) shown in FIG. 4 by the speed of sound. It is possible to ask for it. When the sound speed inside the sensor 10 is v w and the sound speed inside the inspection object 40 is v s , the propagation time τ ilk is multiplied as follows.
Figure JPOXMLDOC01-appb-M000001
　往路の伝搬経路ｄ（１）、ｄ（２）は、伝搬経路の界面４１上の座標［ｘＶＩＲＴ　ｙＶＩＲＴ］Ｔ、出射開始時点の平面波面の界面４１との交点座標ｘｂ、界面４１での入射角θＷを用いて、以下のようにかける。
Figure JPOXMLDOC01-appb-M000002
 The outward propagation paths d (1) and d (2) are the coordinates [x VIRT y VIRT ] T on the interface 41 of the propagation path, the intersection coordinates x b of the plane wave front with the interface 41 at the time of starting the emission, and the coordinates x b at the interface 41. Using the incident angle θ W of , it is multiplied as follows.
Figure JPOXMLDOC01-appb-M000002
　復路の伝搬経路ｄ（３）、ｄ（４）は、反射波が第ｋ素子の位置［ｘｋ　ｙｋ］Ｔに最短時間で到達する経路であり、界面４１上の座標を最適化することで求められる。すなわち、復路の伝搬経路ｄ（３）、ｄ（４）は、最適化した界面座標［ｘＶＩＲＴ　ｙＶＩＲＴ］Ｔを用いて以下のようにかける。
Figure JPOXMLDOC01-appb-M000003
 The return propagation paths d (3) and d (4) are paths for the reflected wave to reach the position [x k y k ] T of the k-th element in the shortest time, and the coordinates on the interface 41 are optimized. is required. That is, the return propagation paths d (3) and d (4) are multiplied as follows using the optimized interface coordinates [x VIRT y VIRT ] T.
Figure JPOXMLDOC01-appb-M000003
　界面４１上の座標ｘｂを０＜ｘｂ≦ｘｗの範囲で走査し、図４に示す伝搬経路と対象とする素子の高さ方向の差分△Ｈｋが最小化となる座標をｘＶＩＲＴ，ｋとして最適化を行う。なお、図３及び図４では、ｘＶＩＲＴ，ｋ＝０となる例を示しているが、最短時間経路で最適化できれば、任意形状のセンサ１０において上記の関係は成立する。
Figure JPOXMLDOC01-appb-M000004
 The coordinate x b on the interface 41 is scanned in the range 0<x b ≦ x w , and the coordinate where the difference ΔH k in the height direction between the propagation path shown in FIG. 4 and the target element is minimized is x VIRT. , k . Note that although FIGS. 3 and 4 show an example in which x VIRT,k = 0, the above relationship holds true for the sensor 10 of any shape if optimization can be performed using the shortest time path.
Figure JPOXMLDOC01-appb-M000004
　平面波を送信するＰＷＩでは、センサ１０のアレイ開口長に相当する幅の範囲内でのみ平面波が形成される。そのため、図３に示す界面座標の範囲
Figure JPOXMLDOC01-appb-M000005
 　を経由しない焦点に対しては平面波が到達せず、上述の伝搬モデルが成立しない。本実施形態では、この条件をモデリングの拘束条件とするため、上記範囲を経由しない焦点の伝搬時間は無効値を入力する。これにより、圧縮センシングの際、設定された界面４１の範囲を経由しない平面波については無効となる。 In a PWI that transmits a plane wave, the plane wave is formed only within a width range corresponding to the array aperture length of the sensor 10. Therefore, the range of interface coordinates shown in Figure 3
Figure JPOXMLDOC01-appb-M000005
 The plane wave does not reach the focal point that does not pass through the plane, and the above-mentioned propagation model does not hold. In this embodiment, since this condition is used as a modeling constraint, an invalid value is input for the propagation time of the focal point that does not pass through the above range. As a result, during compressed sensing, plane waves that do not pass through the set range of the interface 41 are invalidated.
　上記の最適化アルゴリズムでは、ｘｂの走査グリッドを定義する。そのため、グリッド間隔を細かくとることでモデルの精度が向上する一方、計算時間が増加する。現実的な計算時間で精度を担保するため、本実施形態では、最適化後の△Ｈｋを精度の指標とし、グリッド間隔を決定することができる。具体的には、
Figure JPOXMLDOC01-appb-M000006
 　となる走査グリッド間隔となるよう設定する。ここで、ｖｗは音速、Ｔは超音波のパルス幅に相当する時間であり、［数６］は、１パルスの時間で進む距離に相当する。これにより、最適化アルゴリズムにおけるトライアンドエラーによる調整が必要であった界面座標の走査範囲を適切に設定できる。なお、この考え方は、送信モードｆｕｌｌ　ｍａｔｒｉｘ　ｃａｐｔｕｒｅにおいて、往路の伝搬モデルの計算でも有効である。 In the above optimization algorithm, we define a scan grid of x b . Therefore, while finer grid spacing improves model accuracy, it also increases calculation time. In order to ensure accuracy with a realistic calculation time, in this embodiment, the grid interval can be determined using ΔH k after optimization as an accuracy index. in particular,
Figure JPOXMLDOC01-appb-M000006
 Set the scanning grid interval to be . Here, v w is the speed of sound, T is the time equivalent to the pulse width of the ultrasonic wave, and [Equation 6] is equivalent to the distance traveled in one pulse time. This makes it possible to appropriately set the scanning range of the interface coordinates, which previously required adjustment by trial and error in the optimization algorithm. Note that this idea is also effective in calculating the outward path propagation model in the full matrix capture transmission mode.
　上記のように導出した伝搬モデル（音波が伝搬する際の時間τｉｌｋ）に基づいて、圧縮センシングにおける観測行列Ａｉ（ｔ）を導出し、導出した観測行列に基づいて、音響画像
Figure JPOXMLDOC01-appb-M000007
 　を推定する。 Based on the propagation model derived as described above (the time τ ilk when a sound wave propagates), an observation matrix A i (t) in compressed sensing is derived, and based on the derived observation matrix, an acoustic image
Figure JPOXMLDOC01-appb-M000007
 Estimate.
　次に、観測データ取得ステップＳ２０において、演算部２０は、複数の送受波素子１１が検査対象４０に対して傾斜方向に平面波を発信した場合に複数の送受波素子１１で受信される観測データを取得する。 Next, in observation data acquisition step S20, the calculation unit 20 calculates the observation data received by the plurality of wave transmitting/receiving elements 11 when the plurality of wave transmitting/receiving elements 11 transmit plane waves in the oblique direction to the inspection object 40. get.
　次に、圧縮センシング処理ステップＳ３０において、演算部２０は、読み込んだ伝搬モデルと、取得した観測データとに基づいて、圧縮センシングにより検査対象４０のイメージングデータを生成する。 Next, in compressed sensing processing step S30, the calculation unit 20 generates imaging data of the inspection target 40 by compressed sensing based on the read propagation model and the acquired observation data.
　図５は、圧縮センシング処理ステップＳ３０におけるアルゴリズムの一例を示すフローチャートである。なお、本実施例は、ウェッジ型のセンサ１０を介さないＰＷＩにおいても有効である。 FIG. 5 is a flowchart showing an example of an algorithm in compressed sensing processing step S30. Note that this embodiment is also effective in PWI that does not involve the wedge-type sensor 10.
　ビームｉ、第ｋ素子の受信信号ηｉ ｋ（ｔ）は、上記のτｉｌｋを用いて
Figure JPOXMLDOC01-appb-M000008
 　と表現できる。 The received signal η i k (t) of beam i and k-th element is calculated using the above τ ilk
Figure JPOXMLDOC01-appb-M000008
 It can be expressed as
　本実施形態では、数８で示される式において、係数ｃｉｌｋ（ｔ）を導入する（ステップＳ５０１）。 In this embodiment, a coefficient c ilk (t) is introduced into the equation shown in Equation 8 (step S501).
　係数ｃｉｌｋ（ｔ）は、
Figure JPOXMLDOC01-appb-M000009
 　で表され、処理する受信信号を限定する。 The coefficient c ilk (t) is
Figure JPOXMLDOC01-appb-M000009
 , which limits the received signals to be processed.
　数９の「otherwise」に対して、上記で平面波が到達せず伝搬時間を無効値とした画素ｌの条件を当てはめることで、空間的に受信信号を限定することができる。 The received signal can be spatially limited by applying the above condition for the pixel l where the plane wave does not arrive and the propagation time is an invalid value to "otherwise" in Equation 9.
　数９では、Ｔで表されるように伝搬時間軸でも受信信号を限定する。Ｔは送信パルス幅に相当する時間であり、係数ｃｉｌｋ（ｔ）はその信号の持続を表現している。 In Equation 9, the received signal is also limited on the propagation time axis as represented by T. T is the time corresponding to the transmission pulse width, and the coefficient c ilk (t) expresses the duration of the signal.
　この係数ｃｉｌｋ（ｔ）により，時刻ｔにおいて画素値ｓｌを求められるかどうかの判定が可能になる。具体的には、ｋ＝１，２，…，ＭのＭ個の係数ｃｉｌｋ（ｔ）の大半が０であれば、時刻ｔの計測値では画素値ｓｌを計算することができない。一方、Ｍ個の係数ｃｉｌｋ（ｔ）の中で一定数以上の値が１であれば、ｓｌを計算できる。 This coefficient c ilk (t) makes it possible to determine whether the pixel value s l can be calculated at time t. Specifically, if most of the M coefficients c ilk (t) of k=1, 2, . . . , M are 0, the pixel value s l cannot be calculated using the measured value at time t. On the other hand, if more than a certain number of values among the M coefficients c ilk (t) are 1, s l can be calculated.
　そこで、画素値計算可否を判定する閾値
Figure JPOXMLDOC01-appb-M000010
 　を導入し、時刻ｔにおいて、
Figure JPOXMLDOC01-appb-M000011
 　となるインデクスｌの集合Ｓｉ（ｔ）を求め（ステップＳ５０２、ステップＳ５０３）、その集合を構成するインデクスの数をＬｉ（ｔ）とおく。
　数７で示す式の送信パルス幅Ｔが短いと、数１１で示す式の左辺は小さくなる傾向となり、判定が厳しくなるため、ｃ０を小さく設定する。そして、上記の過程を経て選定した画素に対応する座標を記録する（ステップＳ５０４）。図６は、計測システムによるイメージング範囲の一例を模式的に示す図である。図６では、計測時刻ｔにおける画素値の推定値Ｓｉ（ｔ）のイメージング範囲の例と、イメージング領域全体Ｓ（ｔ）のイメージング範囲の例とが示されている。 Therefore, the threshold value for determining whether or not pixel value calculation is possible is
Figure JPOXMLDOC01-appb-M000010
 is introduced, and at time t,
Figure JPOXMLDOC01-appb-M000011
 A set S i (t) of indexes l is determined (steps S502 and S503), and the number of indexes composing the set is set as L i (t).
If the transmission pulse width T of the equation shown in Equation 7 is short, the left side of the equation shown in Equation 11 tends to become small, making the judgment difficult, so c0 is set small. Then, the coordinates corresponding to the pixels selected through the above process are recorded (step S504). FIG. 6 is a diagram schematically showing an example of an imaging range by the measurement system. FIG. 6 shows an example of the imaging range of the estimated value S i (t) of the pixel value at measurement time t, and an example of the imaging range of the entire imaging region S(t).
　ビームｉの受信信号ベクトルηｉ（ｔ）は、
Figure JPOXMLDOC01-appb-M000012
 　と書ける。ここでａｉｌ（ｔ）は送受波素子１１毎の位相差を表すベクトルであり、
Figure JPOXMLDOC01-appb-M000013
 　のように定義することができる。また、これらのベクトルを一つの行列にまとめたものが観測行列
Figure JPOXMLDOC01-appb-M000014
 　である（ステップＳ５０５）。 The received signal vector η i (t) of beam i is
Figure JPOXMLDOC01-appb-M000012
 It can be written as Here, a il (t) is a vector representing the phase difference for each wave transmitting/receiving element 11,
Figure JPOXMLDOC01-appb-M000013
 It can be defined as: Also, the observation matrix is the combination of these vectors into one matrix.
Figure JPOXMLDOC01-appb-M000014
 (Step S505).
　上記のように求めた観測行列Ａｉ（ｔ）を用いて、ビームｉ、時刻ｔで決まるイメージング範囲の画素値ｓｉ（ｔ）を、以下で示す最適化問題を解くことで推定する、つまり、音響画像を求める（ステップＳ５０６）。最適化指標については、例えばＬＡＳＳＯ、Ｓｐａｒｓｅ　Ｇｒｏｕｐ　ＬＡＳＳＯ（ＳＧ－ＬＡＳＳＯ）等のような公知の評価関数を用いることができる。 Using the observation matrix A i (t) obtained as above, the pixel value s i (t) of the imaging range determined by beam i and time t is estimated by solving the optimization problem shown below. , an acoustic image is obtained (step S506). As the optimization index, a known evaluation function such as LASSO, Sparse Group LASSO (SG-LASSO), etc. can be used.
　上記の評価関数のうち、例えばＳＧ－ＬＡＳＳＯは、画素単位のスパース性と同時に複数の画素で塊となって構成される強度分布のスパース性も評価することを狙って、
Figure JPOXMLDOC01-appb-M000015
 　で示される最適化指標である。数１５で示される式は、上記した観測行列Ａｉ（ｔ）を用いて解くことが可能となる。ここで、λは正則化パラメータと呼ばれる係数である。λの値を大きくすることで、よりスパースな結果を得ることができる。λＧは塊のスパース性の度合を決める正則化パラメータである。また、
Figure JPOXMLDOC01-appb-M000016
 　は、ベクトルＳｉ（ｔ）の一部を表す。すなわち、
Figure JPOXMLDOC01-appb-M000017
 　である。 Among the above evaluation functions, for example, SG-LASSO aims to evaluate the sparsity of the intensity distribution composed of multiple pixels as well as the sparsity of each pixel.
Figure JPOXMLDOC01-appb-M000015
 is the optimization index shown by . The equation shown in Equation 15 can be solved using the observation matrix A i (t) described above. Here, λ is a coefficient called a regularization parameter. By increasing the value of λ, sparser results can be obtained. λ G is a regularization parameter that determines the degree of sparsity of the chunk. Also,
Figure JPOXMLDOC01-appb-M000016
 represents a portion of the vector S i (t). That is,
Figure JPOXMLDOC01-appb-M000017
 It is.
　上記の圧縮センシングの特性を考慮すると、評価関数、パラメータを自由に選択することが可能である。図７は、音響画像のモニタリングの一例を模式的に示す図である。このような場合、図７に示すように、設定ごとに音響画像を可視化し、視認性を確認できるモニタリングソフトが検査対象４０の検査で有用となる。 Considering the characteristics of compressed sensing described above, it is possible to freely select the evaluation function and parameters. FIG. 7 is a diagram schematically showing an example of monitoring acoustic images. In such a case, as shown in FIG. 7, monitoring software that can visualize acoustic images for each setting and check visibility is useful for testing the test object 40.
　図８は、複数の送信波を用いたイメージングの概略を模式的に示す図である。図８に示すように、本実施形態のようなＰＷＩでは、一般的にイメージング範囲を網羅するように複数の方向に平面波を送信する。例えば、上記のように得られる音響画像については、全ビームに対するイメージング結果である
Figure JPOXMLDOC01-appb-M000018
 　を、イメージング領域全体のインデクスに割り付けて加算する（ステップＳ５０７）ことで、広範囲の
Figure JPOXMLDOC01-appb-M000019
 　を得ることが可能である（ステップＳ５０８）。 FIG. 8 is a diagram schematically showing the outline of imaging using a plurality of transmitted waves. As shown in FIG. 8, in PWI like this embodiment, plane waves are generally transmitted in multiple directions to cover the imaging range. For example, the acoustic image obtained as above is the imaging result for all beams.
Figure JPOXMLDOC01-appb-M000018
 is assigned to the index of the entire imaging area and added (step S507).
Figure JPOXMLDOC01-appb-M000019
 It is possible to obtain (step S508).
　図９は、横波の屈折角ごとの送信レベルの一例を示す図である。図９の横軸が屈折角を示し、縦軸がレベルを示す。図９に示す関係を、以下の数２０で示す式の係数ｋｉに反映して加算する。係数ｋｉは、図９の縦軸に対応する値である。
Figure JPOXMLDOC01-appb-M000020
 FIG. 9 is a diagram showing an example of a transmission level for each refraction angle of a transverse wave. The horizontal axis in FIG. 9 indicates the refraction angle, and the vertical axis indicates the level. The relationship shown in FIG. 9 is reflected and added to the coefficient k i of the equation shown in Equation 20 below. The coefficient k i is a value corresponding to the vertical axis in FIG. 9 .
Figure JPOXMLDOC01-appb-M000020
　さらに、複数の送信波の伝搬経路が重なったイメージング範囲において、推定画素値を比較し、各音響画像の強度レベルを調整することで、生成される検査対象４０のイメージングデータにおいて、全体の画像の強度レンジが最適化され、視認性が向上する。 Furthermore, by comparing the estimated pixel values and adjusting the intensity level of each acoustic image in the imaging range where the propagation paths of multiple transmitted waves overlap, the overall image in the generated imaging data of the inspection object 40 is Optimized intensity range improves visibility.
　以上説明したように、本開示において、第１態様に係る信号処理装置は、複数の送受波素子１１から検査対象４０の界面４１の法線方向に対して傾いた傾斜方向に発信される平面波が検査対象４０の内部を伝搬し焦点で反射して送受波素子１１に到達する場合の平面波の伝搬経路を示す所定の伝搬モデルを読み込む処理と、複数の送受波素子１１が検査対象４０に対して傾斜方向に平面波を発信した場合に複数の送受波素子１１で受信される観測データを取得する処理と、読み込んだ伝搬モデルと、取得した観測データとに基づいて、圧縮センシングにより検査対象４０のイメージングデータを生成する処理と、を行う演算部２０を備える。 As described above, in the present disclosure, the signal processing device according to the first aspect is capable of transmitting plane waves emitted from the plurality of wave transmitting/receiving elements 11 in an inclined direction inclined with respect to the normal direction of the interface 41 of the inspection object 40. A process of reading a predetermined propagation model indicating the propagation path of a plane wave when it propagates inside the inspection object 40 and reaches the wave transmission/reception element 11 after being reflected at the focal point, and a process in which the plurality of wave transmission/reception elements 11 are connected to the inspection object 40. A process of acquiring observation data received by a plurality of wave transmitting/receiving elements 11 when a plane wave is transmitted in an inclined direction, and imaging of the inspection target 40 by compressed sensing based on the read propagation model and the acquired observation data. The processing unit 20 includes a calculation unit 20 that performs a process of generating data.
　したがって、送受波素子１１から検査対象４０の界面４１の法線方向に対して傾いた傾斜方向に発信される平面波により検査対象４０の探査を行い、圧縮センシングによりイメージングデータを生成するため、検査対象４０を精度よくイメージングすることが可能となる。 Therefore, the inspection object 40 is probed by a plane wave emitted from the wave transmitting/receiving element 11 in an inclined direction inclined with respect to the normal direction of the interface 41 of the inspection object 40, and imaging data is generated by compressed sensing. 40 can be imaged with high precision.
　第２態様に係る信号処理装置は、第１態様に係る信号処理装置において、伝搬モデルにおいて、複数の送受波素子１１によるアレイ開口に対応する界面４１の範囲が検査対象４０の内部に設定され、演算部２０は、圧縮センシングを行う際、設定された界面４１の範囲を経由しない平面波については無効とする。したがって、伝搬モデルに拘束条件を課すことができるため、圧縮センシングにおいて、より高精度の設定が可能となる。 The signal processing device according to the second aspect is the signal processing device according to the first aspect, in which in the propagation model, the range of the interface 41 corresponding to the array aperture formed by the plurality of wave transmitting/receiving elements 11 is set inside the inspection object 40, When performing compression sensing, the calculation unit 20 invalidates plane waves that do not pass through the set range of the interface 41. Therefore, since constraint conditions can be imposed on the propagation model, more accurate settings can be made in compressive sensing.
　第３態様に係る信号処理装置は、第１態様及び第２態様に係る信号処理装置において、演算部２０は、圧縮センシングにおいて、界面４１と伝搬経路との交点である界面座標の最適化を行い、演算部２０は、それぞれの送受波素子１１から発信される平面波の反射波について当該送受波素子１１の位置における法線方向の差分が、音速と平面波のパルス幅に対応する時間との積で求められる値以下となるように最適化を行う。したがって、最適化アルゴリズムにおけるトライアンドエラーによる調整が必要であった界面座標の走査範囲を適切に設定できる。 In the signal processing device according to the third aspect, in the signal processing device according to the first aspect and the second aspect, the calculation unit 20 optimizes the interface coordinates that are the intersections of the interface 41 and the propagation path in compressed sensing. , the calculation unit 20 calculates that the difference in the normal direction at the position of the plane wave reflected wave transmitted from each wave transceiver 11 is the product of the sound velocity and the time corresponding to the pulse width of the plane wave. Optimize so that the value is less than or equal to the required value. Therefore, the scanning range of the interface coordinates, which required adjustment by trial and error in the optimization algorithm, can be appropriately set.
　第４態様に係る信号処理装置は、第１態様から第３態様に係る信号処理装置において、演算部２０は、平面波のパルス幅に対応する所定期間内に到達する有効な平面波の数が閾値以上となるように圧縮センシングを行い、閾値は、所定期間が短いほど小さい値となるように設定される。したがって、平面波の観測データを限定することで、圧縮センシングの処理を高速化することができる。 In the signal processing device according to the fourth aspect, in the signal processing device according to the first to third aspects, the calculation unit 20 is configured such that the number of valid plane waves arriving within a predetermined period corresponding to the pulse width of the plane wave is equal to or greater than a threshold value. Compressed sensing is performed so that the threshold value becomes smaller as the predetermined period becomes shorter. Therefore, by limiting the observation data of plane waves, it is possible to speed up the processing of compressed sensing.
　第５態様に係る信号処理装置は、第１態様から第４態様に係る信号処理装置において、演算部２０は、圧縮センシングにおいて、イメージングデータを構成する複数の画素の塊に対して最適化を行う。イメージングデータの欠陥の大きさを推定する場合、欠陥はある程度の大きさを有しているという前提がある。このため、複数の画素の塊を単位としてスパース性を評価することで、画素単位のスパース性を評価する場合に比べて欠陥を可視化しやすくなる。 A signal processing device according to a fifth aspect is the signal processing device according to any of the first to fourth aspects, in which the calculation unit 20 performs optimization for a plurality of clusters of pixels constituting imaging data in compressed sensing. . When estimating the size of a defect in imaging data, it is assumed that the defect has a certain size. Therefore, by evaluating sparsity in units of a plurality of pixels, defects can be more easily visualized than in the case of evaluating sparsity in units of pixels.
　第６態様に係る信号処理方法は、複数の送受波素子１１から検査対象４０の界面４１の法線方向に対して傾いた傾斜方向に発信される平面波が検査対象４０の内部を伝搬し焦点で反射して送受波素子１１に到達する場合の平面波の伝搬経路を示す所定の伝搬モデルを読み込む伝搬モデル読み込みステップＳ１０と、検査対象４０に対して傾斜方向に平面波を発信し、受信した観測データを取得する観測データ取得ステップＳ２０と、読み込んだ伝搬モデルと、取得した観測データとに基づいて、圧縮センシングにより検査対象４０のイメージングデータを生成するイメージングデータ生成ステップＳ３０とを含む。 In the signal processing method according to the sixth aspect, a plane wave transmitted from a plurality of wave transmitting/receiving elements 11 in an inclined direction inclined with respect to a normal direction of an interface 41 of an inspection object 40 propagates inside the inspection object 40 and reaches a focal point. A propagation model reading step S10 reads a predetermined propagation model indicating the propagation path of a plane wave when it is reflected and reaches the wave transmitting/receiving element 11, and a plane wave is transmitted in an oblique direction to the inspection object 40, and the received observation data is transmitted. The process includes an observation data acquisition step S20, and an imaging data generation step S30, which generates imaging data of the inspection object 40 by compressed sensing based on the read propagation model and the acquired observation data.
　したがって、送受波素子１１から検査対象４０の界面４１の法線方向に対して傾いた傾斜方向に発信される平面波により検査対象４０の探査を行い、圧縮センシングによりイメージングデータを生成するため、検査対象４０を精度よくイメージングすることが可能となる。 Therefore, the inspection object 40 is probed by a plane wave emitted from the wave transmitting/receiving element 11 in an inclined direction inclined with respect to the normal direction of the interface 41 of the inspection object 40, and imaging data is generated by compressed sensing. 40 can be imaged with high precision.
１０　センサ
１１　送受波素子
２０　演算部
３０　記憶部
４０　検査対象
４１　界面
５０　パルサーレシーバー
１００　信号処理装置
ＳＹＳ　計測システム 10 Sensor 11 Wave transmitting/receiving element 20 Arithmetic unit 30 Storage unit 40 Inspection object 41 Interface 50 Pulsar receiver 100 Signal processing device SYS Measurement system

Claims (6)

  1. 　複数の送受波素子から検査対象の界面の法線方向に対して傾いた傾斜方向に発信される平面波が前記検査対象の内部を伝搬し焦点で反射して前記送受波素子に到達する場合の前記平面波の伝搬経路を示す所定の伝搬モデルを読み込む処理と、
    　複数の前記送受波素子が前記検査対象に対して前記傾斜方向に前記平面波を発信した場合に複数の前記送受波素子で受信される観測データを取得する処理と、
    　読み込んだ前記伝搬モデルと、取得した前記観測データとに基づいて、圧縮センシングにより前記検査対象のイメージングデータを生成する処理と、を行う処理部を備える
    　信号処理装置。     The above case where a plane wave emitted from a plurality of wave transmitting/receiving elements in an inclined direction tilted with respect to the normal direction of the interface of the object to be inspected propagates inside the object to be inspected, is reflected at a focal point, and reaches the wave transmitting/receiving element. A process of loading a predetermined propagation model indicating a propagation path of a plane wave;
    a process of acquiring observation data received by the plurality of wave transmitting and receiving elements when the plurality of wave transmitting and receiving elements transmit the plane waves in the oblique direction to the inspection target;
    A signal processing device comprising: a processing unit that performs a process of generating imaging data of the inspection target by compressed sensing based on the read propagation model and the acquired observation data.
  2. 　前記伝搬モデルにおいて、複数の前記送受波素子によるアレイ開口に対応する前記界面の範囲が前記検査対象の内部に設定され、
    　前記処理部は、前記圧縮センシングを行う際、設定された前記界面の範囲を経由しない前記平面波については無効とする
    　請求項１に記載の信号処理装置。     In the propagation model, a range of the interface corresponding to an array aperture formed by the plurality of wave transmitting/receiving elements is set inside the inspection target,
    The signal processing device according to claim 1, wherein the processing unit invalidates the plane wave that does not pass through the set range of the interface when performing the compressed sensing.
  3. 　前記処理部は、前記圧縮センシングにおいて、前記界面と前記伝搬経路との交点である界面座標の最適化を行い、
    　前記処理部は、それぞれの前記送受波素子から発信される前記平面波の反射波について当該送受波素子の位置における前記法線方向の差分が、音速と前記平面波のパルス幅に対応する時間との積で求められる値以下となるように前記最適化を行う
    　請求項１に記載の信号処理装置。     The processing unit optimizes interface coordinates that are intersections between the interface and the propagation path in the compressed sensing,
    The processing unit is configured to determine that the difference in the normal direction at the position of the wave transmitting/receiving element with respect to the reflected wave of the plane wave transmitted from each of the wave transmitting/receiving elements is the product of the speed of sound and the time corresponding to the pulse width of the plane wave. The signal processing device according to claim 1 , wherein the optimization is performed so that the value is less than or equal to a value determined by .
  4. 　前記処理部は、前記平面波のパルス幅に対応する所定期間内に到達する有効な前記平面波の数が閾値以上となるように前記圧縮センシングを行い、
    　前記閾値は、前記所定期間が短いほど小さい値となるように設定される
    　請求項１に記載の信号処理装置。     The processing unit performs the compressed sensing such that the number of effective plane waves arriving within a predetermined period corresponding to the pulse width of the plane wave is equal to or greater than a threshold;
    The signal processing device according to claim 1, wherein the threshold value is set to a smaller value as the predetermined period is shorter.
  5. 　前記処理部は、前記圧縮センシングにおいて、前記イメージングデータを構成する複数の画素の塊に対して最適化を行う
    　請求項１に記載の信号処理装置。     The signal processing device according to claim 1, wherein the processing unit performs optimization on a plurality of pixel blocks forming the imaging data in the compressed sensing.
  6. 　複数の送受波素子から検査対象の界面の法線方向に対して傾いた傾斜方向に発信される平面波が前記検査対象の内部を伝搬し焦点で反射して前記送受波素子に到達する場合の前記平面波の伝搬経路を示す所定の伝搬モデルを読み込む伝搬モデル読み込みステップと、
    　複数の前記送受波素子が前記検査対象に対して前記傾斜方向に前記平面波を発信した場合に複数の前記送受波素子で受信される観測データを取得する観測データ取得ステップと、
    　読み込んだ前記伝搬モデルと、取得した前記観測データとに基づいて、圧縮センシングにより前記検査対象のイメージングデータを生成するイメージングデータ生成ステップと
    　を含む信号処理方法。     The above case where a plane wave emitted from a plurality of wave transmitting/receiving elements in an inclined direction tilted with respect to the normal direction of the interface of the object to be inspected propagates inside the object to be inspected, is reflected at a focal point, and reaches the wave transmitting/receiving element. a propagation model loading step of loading a predetermined propagation model indicating a propagation path of a plane wave;
    an observation data acquisition step of acquiring observation data received by the plurality of wave transmitting/receiving elements when the plurality of wave transmitting/receiving elements transmit the plane waves in the oblique direction to the inspection target;
    A signal processing method comprising: an imaging data generation step of generating imaging data of the inspection target by compressed sensing based on the read propagation model and the acquired observation data.
PCT/JP2023/006783 2022-07-07 2023-02-24 Signal processing device and signal processing method WO2024009550A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2022-109883 2022-07-07
JP2022109883A JP2024008204A (en) 2022-07-07 2022-07-07 Signal processing device and signal processing method

Publications (1)

Publication Number Publication Date
WO2024009550A1 true WO2024009550A1 (en) 2024-01-11

Family

ID=89452936

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2023/006783 WO2024009550A1 (en) 2022-07-07 2023-02-24 Signal processing device and signal processing method

Country Status (2)

Country Link
JP (1) JP2024008204A (en)
WO (1) WO2024009550A1 (en)

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2020091129A (en) * 2018-12-03 2020-06-11 三菱重工業株式会社 Aperture synthetic processing device, aperture synthetic processing method and program of the same

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2020091129A (en) * 2018-12-03 2020-06-11 三菱重工業株式会社 Aperture synthetic processing device, aperture synthetic processing method and program of the same

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
BAI ZHILIANG, CHEN SHILI, JIA LECHENG, ZENG ZHOUMO: "Ultrasonic Phased Array Compressive Imaging in Time and Frequency Domain: Simulation, Experimental Verification and Real Application", SENSORS, MDPI, CH, vol. 18, no. 5, CH , pages 1460, XP093126801, ISSN: 1424-8220, DOI: 10.3390/s18051460 *
GUEDDARI L. EL; CIUCIU P.; CHOUZENOUX E.; VIGNAUD A.; PESQUET J.-C.: "Calibrationless Oscar-Based Image Reconstruction in Compressed Sensing Parallel MRI", 2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019), IEEE, 8 April 2019 (2019-04-08), pages 1532 - 1536, XP033576523, DOI: 10.1109/ISBI.2019.8759393 *

Also Published As

Publication number Publication date
JP2024008204A (en) 2024-01-19

Similar Documents

Publication Publication Date Title
Zhang et al. The use of ultrasonic arrays to characterize crack-like defects
Sy et al. Development of the specular echoes estimator to predict relevant modes for Total Focusing Method imaging
Zhang et al. Effects of array transducer inconsistencies on total focusing method imaging performance
TWI503542B (en) Ultrasonic measurement methods and apparatus
CN110840488B (en) Imaging method, system and device based on shear wave
CN109875606B (en) Ultrasonic CT sound velocity imaging method based on prior reflection imaging
US11041831B2 (en) Ultrasonic probe, ultrasonic flaw detection apparatus and method
JP5127573B2 (en) Ultrasonic flaw detection apparatus and method
Budyn et al. Characterisation of small embedded two-dimensional defects using multi-view Total Focusing Method imaging algorithm
Sac et al. 2D high-frequency forward-looking sonar simulator based on continuous surfaces approach.
JP7233646B2 (en) ULTRASOUND INSPECTION METHOD, ULTRASOUND INSPECTION APPARATUS AND PROGRAM
CN113504306A (en) Steel rail defect detection method based on ultrasonic phased array low-rank matrix recovery
US10386335B2 (en) Method for processing signals from an ultrasound probe acquisition, corresponding computer program and ultrasound probe device
JP5910641B2 (en) Ultrasonic imaging method and ultrasonic imaging apparatus
US20240013044A1 (en) Method for characterizing a part through non-destructive inspection
CN113552571B (en) Underwater laser induced acoustic SAFT imaging method based on PSM algorithm
WO2024009550A1 (en) Signal processing device and signal processing method
Malatesta et al. Double-stage DMAS with fresnel zone filtering in guided waves damage imaging
Shi et al. Waveform-based geometrical inversion of obstacles
US11054398B2 (en) Ultrasonic inspection method, ultrasonic inspection device, and computer-readable storage medium
CN111399038B (en) Slope parameter extraction method and device and computer readable storage medium
US20100104132A1 (en) Computer image processing system and method for ndt/ndi testing devices
CA3040331A1 (en) Method and device for detecting and characterizing a reflecting element in an object
JP2024055507A (en) Signal processing device and signal processing method
JP2017500553A (en) How to rebuild the surface of a fragment

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 23835091

Country of ref document: EP

Kind code of ref document: A1