Novel acoustic signal characteristic frequency identification method based on discrete ultrasonic transducer array

Abstract

The invention discloses a novel acoustic signal characteristic frequency identification method based on a discrete ultrasonic transducer array, and the method comprises the steps: providing the discrete ultrasonic transducer array as a broadband receiver, and providing a sound source as an acoustic signal transmitter; the broadband receiver receives acoustic signals and extracts signal features to form a feature matrix; the feature matrix serves as a target mapping matrix to establish a fuzzy mapping relation with an acoustic signal with unknown feature frequency, and feature frequency identification results with different resolutions are achieved along with the number of the broadband receivers and the number of the multiple sets of sound sources. According to the method, the mapping matrix of the acoustic signal characteristic frequency is established based on the discrete ultrasonic transducer array, the operation is simple, and the method has the capability of identifying the acoustic signal characteristic frequency in a broadband range.

Description

Technical Field

[0001] The invention relates to the field of acoustics, and in particular to a novel acoustic signal characteristic frequency recognition method based on a discrete ultrasonic transducer array. Background Art

[0002] In the field of acoustics, target recognition refers to the detection, tracking, imaging, identification and classification of targets based on their characteristics through active or passive equipment supplemented by machine learning, sensitive sensor devices, visual image processing and other comprehensive approaches. It has important practical significance in many fields such as biological protection, economic development and people's livelihood.

[0003] With the rapid development of modern sensing technology, the research and application of technologies such as target recognition, target detection and target classification have become increasingly mature. Cheng Xiao et al. have realized the recognition and classification of underwater targets efficiently and accurately based on deep learning algorithms (CN116486177A); Zhao Xuchen et al. have provided a complete set of underwater devices and electronic equipment (CN115774849), which effectively solved the problem of target noise radiation interference and further improved the target recognition accuracy.

[0004] However, most of the existing research focuses on the positioning of targets, detecting the presence of targets, imaging and classification of targets. In contrast, research on the recognition of target characteristic frequencies is relatively scarce, and the existing technology and research have the following defects, including: the lack of an effective method for identifying targets based on the characteristic frequency of acoustic signals in the field of target recognition; the acoustic signal recognition and detection methods based on traditional hydrophones and ultrasonic transducers have the defects of a single detection range, a narrow operating frequency band, low device flexibility and a complex design process; target frequency recognition based on traditional methods relies on empirical judgment and cannot meet the needs of modern intelligent detection and identification equipment.

[0005] Therefore, it is of innovative significance to explore a new acoustic signal characteristic frequency identification method based on discrete ultrasonic transducer arrays. Summary of the invention

[0006] In order to improve the shortcomings and defects of the prior art, the present invention provides a novel acoustic signal characteristic frequency recognition method based on a discrete ultrasonic transducer array, comprising:

[0007] A discrete ultrasonic transducer array is provided as a wideband receiver; a plurality of groups of sound sources are provided as acoustic signal transmitters; a target mapping matrix is ​​established based on known acoustic signal characteristic information, wherein the known acoustic signal includes an operating frequency and an operating frequency band; a fuzzy mapping relationship is formed between the target mapping matrix and the unknown acoustic signal, and characteristic frequency recognition of acoustic signals in a wide frequency range is realized based on the fuzzy mapping relationship.

[0008] Discrete ultrasonic transducer arrays include but are not limited to broadband arrays composed of broadband ultrasonic transducer units based on a single type, and broadband arrays composed of multiple types of ultrasonic transducer units with progressive distribution of working frequency bands; discrete ultrasonic transducer arrays have broadband or multi-frequency working capabilities.

[0009] The discrete ultrasonic transducer units of the discrete ultrasonic transducer array are individually detachable and their positions are flexibly changeable.

[0010] The discrete ultrasonic transducer is a piezoelectric ultrasonic transducer, and the piezoelectric materials include piezoelectric ceramics PZT, aluminum nitride AlN, polyvinylidene fluoride PVDF, zinc oxide ZnO, piezoelectric crystals, and composite piezoelectric materials; the shapes of the prepared discrete ultrasonic transducers include cubes, cuboids, cylinders, and irregular geometric shapes.

[0011] The target mapping matrix is ​​a matrix based on the eigenvalues ​​of the acoustic signal, and the target mapping matrix includes a target mapping matrix based on a single eigenvalue and a target mapping matrix based on multiple eigenvalues.

[0012] The acoustic signal characteristic value includes at least one of the electrical signal oscillation attenuation period characteristic, the time domain electrical signal Fourier spectrum characteristic, the electrical signal pulse characteristic, the electrical signal energy and power characteristic, the electrical signal phase characteristic, and the electrical signal's own voltage and current characteristic.

[0013] The resolution of acoustic signal characteristic frequency identification is positively correlated with the number of discrete ultrasonic transducer arrays and multiple groups of sound sources.

[0014] Preferably, multiple groups of sound sources work separately, and the working frequencies of the sound sources do not overlap each other. The distribution of the working frequencies in a specific frequency band includes uniform distribution and non-uniform distribution. The sound sources are excited separately under the same conditions.

[0015] Preferably, the prepared discrete ultrasonic transducer captures acoustic signals emitted by multiple groups of sound sources, converts them through the piezoelectric effect, and finally outputs and stores them in the form of electrical signals.

[0016] Compared with the prior art, the novel acoustic signal characteristic frequency identification method based on discrete ultrasonic transducer array provided by the present invention has the following beneficial effects, including:

[0017] The method innovatively realizes accurate identification of characteristic frequencies of acoustic signals.

[0018] The method can achieve a broadband recognition effect equivalent to that of a continuous ultrasonic transducer array based on a discrete ultrasonic transducer array, reduce the device design dimension, and simplify the preparation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The specific embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings:

[0020] Figure 1 This is a recognition principle diagram of a novel acoustic signal characteristic frequency recognition method based on a discrete ultrasonic transducer array according to the present invention;

[0021] Figure 2 The figure is a schematic diagram of a discrete transducer unit structure listed in an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to illustrate the present invention in more detail, the technical solution of the present invention is further described below in conjunction with preferred embodiments and drawings. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0023] In the present invention, it is necessary to understand that the term "small amount" is to highlight the advantage that this embodiment only requires a small sample of ultrasonic transducers rather than an array; it is necessary to understand that the term "optimal" is to illustrate the output index of the deep learning algorithm in this embodiment; it is necessary to understand that the term "connection" includes electrical connection and mechanical connection; it can also be a direct connection or an indirect connection through an intermediate structure; it can be an integral connection or a partial connection. Therefore, the terms cannot be understood as limiting the present invention. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0024] Example:

[0025] Reference Figure 1 This embodiment provides a novel acoustic signal characteristic frequency recognition method based on a discrete ultrasonic transducer array. This method realizes the recognition of the characteristic frequency of acoustic signals in a wide frequency range by establishing a fuzzy correspondence between an unknown acoustic signal and a target mapping matrix.

[0026] This embodiment also includes:

[0027] A discrete ultrasonic transducer array consisting of a small number of discrete ultrasonic transducers is provided, wherein the prepared ultrasonic transducers are flexible in spatial position, artificially controllable and discrete from each other;

[0028] Acoustic signals emitted by multiple groups of sound sources with known working frequencies and working frequency bands are obtained through discrete ultrasonic transducers. The acoustic signals are output in the form of electrical signals through the piezoelectric effect, and features of the received electrical signals are extracted. In this embodiment, voltage amplitude features of the electrical signals are extracted. In addition, the acoustic signals listed in this embodiment are water acoustic signals.

[0029] Reference Figure 2 , is a discrete ultrasonic transducer unit prepared in this embodiment. This embodiment preferably uses PZT-5H, metal gold Au, conductive silver paste material and Si substrate material. The device preparation and test preparation process includes:

[0030] S1. PZT-5H is prepared into the required size by precision cutting and precision grinding. The device length in this embodiment is 12 mm, the aspect ratio is 6-30 times, and the thickness is 0.3 mm and 0.55 mm. In this embodiment, eight discrete block PZT-5H piezoelectric sheets (2) are prepared, respectively named P Ⅰ- P Ⅷ ;

[0031] S2, the P described in S1 Ⅰ -P Ⅷ Eight discrete block ultrasonic transducers are prepared by connecting them to the substrate (3) material through conductive silver glue, respectively, and are named U Ⅰ -U Ⅷ The U Ⅰ -U Ⅷ Fixed on a detachable mold, the position is flexible, manually controllable and separate from each other;

[0032] S3, through the coating process in S2 U Ⅰ -U Ⅷ A layer of metal electrode (1) is prepared on the top, and two wires are led out through the metal electrode (1) for signal transmission.

[0033] S4. Regarding the U described in S2 Ⅰ -U Ⅷ Perform self-transmitting and receiving tests, and analyze its working frequency band based on the echo signal. Ⅰ -U Ⅷ The combined operating frequency band is distributed in the range of 1MHz-7.5MHz.

[0034] The U Ⅰ -U Ⅷ In this embodiment, the process of sending and receiving acoustic signals includes the following steps:

[0035] T1. The sending and receiving process of acoustic signals takes place in a test tank filled with water;

[0036] T2. Preferably, ten groups of sound source probes are selected as acoustic signal transmitters, respectively named S Ⅰ -S X The S Ⅰ -S X The operating frequency is distributed in 0.5MHz-3.5MHz, the S Ⅰ -S X are excited by the same excitation source and emit ultrasonic signals;

[0037] T3, the U Ⅰ -U Ⅷ Sense and receive S described in T1 Ⅰ -SX The emitted ultrasonic signal is finally output in the form of a time-domain continuous electrical signal through the piezoelectric effect and stored in a storage unit.

[0038] In this embodiment, the process of identifying the characteristic frequency of the acoustic signal includes:

[0039] Feature extraction is performed on the stored electrical signal, and the eigenvalues ​​are stored again in the form of a feature matrix. The feature matrix is ​​used as a target mapping matrix after normalized data scaling transformation. When the unknown acoustic signal to be measured is received by the wideband receiver, the characteristic frequency of the acoustic signal to be measured can be effectively identified based on the fuzzy correspondence between the acoustic signal to be measured and the target mapping matrix. In this embodiment, recognition is carried out for acoustic signals with operating frequencies of 1.18MHz, 2.25MHz, and 2.90MHz, and recognition results with accuracy rates of 92.20%, 99.66%, and 97.69%, respectively, are obtained.

[0040] The embodiment receives the hydroacoustic signal through a wide-band array composed of eight discrete ultrasonic transducers, uses ten groups of sound sources to form a fuzzy mapping matrix in the range of 0.5MHz-3.5MHz, and successfully realizes accurate identification of the characteristic frequency of the hydroacoustic signal in a wide frequency range based on the fuzzy mapping matrix.

[0041] Finally, it should be explained that the above-described embodiments are only preferred examples for clearly illustrating the present invention, but this is not a limitation on the implementation scheme of the present invention. Ordinary technicians in the relevant field should understand that the technical features in the above schemes can be combined arbitrarily, and other different forms of modifications or equivalent replacements of some technical features can be made on the basis of the above specific implementation schemes. It is impossible to list all implementation schemes here. Therefore, all modifications, improvements, equivalent replacements, etc. derived from the technical schemes of the present invention within the spirit and principles of the present invention should be within the technical scope of the present invention.

Claims

1. A novel acoustic signal characteristic frequency recognition method based on discrete ultrasonic transducer array, characterized in that: include: providing an array of discrete ultrasonic transducers as a broadband receiver; Providing multiple groups of sound sources as acoustic signal transmitters; A target mapping matrix is ​​established based on known acoustic signal characteristic information, wherein the known acoustic signal includes a known operating frequency and an operating frequency band, and the target mapping matrix forms a fuzzy mapping relationship with the unknown acoustic signal, and the characteristic frequency recognition of the acoustic signal in a wide frequency range is realized based on the fuzzy mapping relationship.

2. According to claim 1, a novel acoustic signal characteristic frequency identification method based on discrete ultrasonic transducer array is characterized in that: The discrete ultrasonic transducer array includes but is not limited to an array composed of a single type of broadband ultrasonic transducer units and an array composed of multiple types of ultrasonic transducer units with progressive distribution of working frequency bands; the discrete ultrasonic transducer array has broadband or multi-frequency working capabilities.

3. The novel acoustic signal characteristic frequency identification method based on discrete ultrasonic transducer array according to claim 2 is characterized in that: The discrete ultrasonic transducer units of the discrete ultrasonic transducer array are individually detachable and their positions are flexible and changeable.

4. The novel acoustic signal characteristic frequency identification method based on discrete ultrasonic transducer array according to claim 1 is characterized in that: The discrete ultrasonic transducer is a piezoelectric ultrasonic transducer, and the piezoelectric material includes piezoelectric ceramic PZT, aluminum nitride AlN, polyvinylidene fluoride PVDF, zinc oxide ZnO, piezoelectric crystal, and composite piezoelectric material; the shape of the prepared discrete ultrasonic transducer includes a cube, a cuboid, a cylinder, and an irregular geometric body.

5. The novel acoustic signal characteristic frequency identification method based on discrete ultrasonic transducer array according to claim 1 is characterized in that: The target mapping matrix is ​​a matrix based on eigenvalues ​​of acoustic signals, and the target mapping matrix includes a target mapping matrix based on a single eigenvalue and a target mapping matrix based on multiple eigenvalues.

6. The novel acoustic signal characteristic frequency identification method based on discrete ultrasonic transducer array according to claim 5 is characterized in that: The acoustic signal characteristic value includes at least one of the electrical signal oscillation attenuation period characteristic, the time domain electrical signal Fourier spectrum characteristic, the electrical signal pulse characteristic, the electrical signal energy and power characteristic, the electrical signal phase characteristic, and the electrical signal's own voltage and current characteristic.

7. The novel acoustic signal characteristic frequency identification method based on discrete ultrasonic transducer array according to claim 1 is characterized in that: The resolution of the characteristic frequency identification of the acoustic signal is positively correlated with the number of the discrete ultrasonic transducer array and the plurality of groups of sound sources.

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