118 results about "Acoustic array" patented technology

The invention provides an acoustic array adaptive calibration correction system applied to an underwater moving target, which relates to the technical field of marine equipment and comprises a multi-source excitation and environment perception module, an intelligent array perception and diagnosis module, an adaptive position inversion and uncertainty quantification module and a closed-loop calibration execution and self-learning optimization module. The multi-source excitation and environment perception module is responsible for providing reference signals required by calibration and establishing a correlation model of environment and formation distortion, and the intelligent array perception and diagnosis module realizes multi-modal data acquisition, array element health state monitoring and formation geometry self-perception. The adaptive position inversion and uncertainty quantization module completes signal processing, position estimation and error quantization propagation, and the closed-loop calibration execution and self-learning optimization module executes a compensation strategy, verifies a calibration effect and continuously optimizes system performance through online learning; the system solves the problem that a traditional method cannot process environment time varying, multi-sensor conflicts and uncertainty quantization.

The invention relates to the technical field of bag type dust collector filter bag abrasion detection, in particular to a filter bag damage non-contact detection method and system based on acoustic array positioning. The method comprises the following steps: arranging an acoustic sensor array in an air purification chamber of the dust remover, and collecting acoustic signals in real time; after band-pass filtering is carried out on the signals, feature vectors of the signals are extracted and matched with a pre-established acoustic fingerprint database, so that a filter bag damage event is recognized; after identification, based on the time difference of arrival of the signal to at least three sensors in the array, combining the coordinates of the sensors and the sound velocity, and utilizing a TDOA positioning algorithm to calculate the space coordinates of the damaged sound source; and finally, matching the coordinates with a pre-stored filter bag coordinate mapping table, determining the number of a specific damaged filter bag, and performing visual highlight marking on a pattern board plane layout of an application layer terminal. The online, real-time, automatic and accurate positioning of the damaged filter bag is realized, the problem that the prior art can only give an alarm but cannot position is solved, and the operation and maintenance efficiency and safety are improved.

The invention relates to the field of underwater sound signal processing, in particular to an underwater DOA (direction of arrival) estimation method based on graph nerves and a convolutional neural network, which comprises the following steps: 1, establishing a linear array, and enabling narrow-band signals to simultaneously reach an underwater sound array; 2, performing signal preprocessing to obtain a signal covariance matrix, and performing normalization processing; 3, extracting correlation between array elements and spatial features of array signals, and performing data supplementation on sparse linear array information; 4, forming a double-branch structure, enhancing the information aggregation capability, and extracting features from a space path and a time domain path; and 5, constructing an adjacent matrix, filling node features of damaged array elements, adopting a double-branch structure, extracting spatial features and time domain features, carrying out feature integration, and outputting a DOA estimation result. The spatial correlation between array elements is extracted and the array sparsity problem is processed by using the graph neural network, and the time domain features of the signals are extracted in combination with the convolutional neural network, so that more accurate and more robust DOA estimation can be realized under the conditions of low signal-to-noise ratio and array sparsity.

The invention provides a boiler heating surface pipe wall leakage detection method, and belongs to the technical field of industrial intelligent detection based on machine learning. According to the method, a heterogeneous sensing architecture combining adaptive signal decomposition optimized by an improved sparrow search algorithm and acoustic array positioning corrected by a physical field is adopted, and complementary features are extracted from time domain statistical features and a frequency domain energy spectrum through a specially designed double-flow space-time attention fusion neural network; therefore, the weak leakage signals in the strong noise environment can be captured and identified. Based on an identification result, a hearth three-dimensional temperature field distribution model is used for carrying out gridding correction on a sound wave propagation path, a nonlinear positioning equation set is constructed, and three-dimensional space sub-m-level accurate positioning of a leakage sound source is realized without manual intervention; the problems of false alarm and missing alarm caused by background noise interference and positioning deviation caused by temperature gradient in traditional acoustic monitoring are thoroughly solved.

Disclosed in the present invention are a wide-angle scanning imaging device, method and system. The device comprises a sonar probe and a device body. The sonar probe comprises an acoustic array and a transceiving processing module. The acoustic array comprises a transmitting array and a receiving array. The transmitting array comprises a group of transmitting transducers. Maximum response axes of the transmitting transducers are distributed in the vertical direction according to preset tilt angles, and a plurality of transmitted beams of the transmitting transducers form wide-angle coverage in the vertical direction. The receiving array performs resolution in the horizontal direction by means of beamforming, and vertical orientations of echoes are estimated by means of double-array output phase differences. The acoustic array performs rotational motion along the central axis of the device body. The transmitting array transmits broadband orthogonal pulses according to a preset period, the receiving array receives echo signals, and the transceiving processing module processes the echo signals according to the central frequency of the transmitted pulses of the transmitting array to obtain an underwater target imaging result. The present invention reduces the impact of underwater multipath interference and the like on phase estimation and improves the 3D imaging quality.

The invention discloses an audio-visual fusion unmanned aerial vehicle detection and positioning method, and belongs to the technical field of unmanned aerial vehicle detection and positioning, and the method comprises the steps: collecting sound signals of a detection region through a sound array, obtaining the local strongest direction of the sound signals, and forming an unmanned aerial vehicle candidate direction set; signals of candidate orientations of all unmanned aerial vehicles are directionally received, whether the unmanned aerial vehicles exist in the candidate orientations or not is judged through the unmanned aerial vehicle sound signal anomaly detector based on deep learning and the unmanned aerial vehicle image target detector based on deep learning, and an unmanned aerial vehicle orientation set is obtained; acquiring an image of a detection area through a binocular camera to obtain a depth image of a reference camera visual angle; uniquely corresponding the orientation of the unmanned aerial vehicle to the determined position of the depth image, and taking the depth value of the position as the distance of the unmanned aerial vehicle; and combining the unmanned aerial vehicle azimuth and the unmanned aerial vehicle distance to obtain three-dimensional coordinates of the unmanned aerial vehicle. The unmanned aerial vehicle can be identified and positioned by adopting an audio-visual fusion method.

The invention relates to the technical field of ocean engineering monitoring and underwater acoustic sensing, in particular to an underwater engineering structure anomaly detection and positioning method based on a subsurface buoy acoustic array. Comprising the following steps: establishing an equivalent coupling sound propagation model; a subsurface buoy system is arranged in a water body area above an underwater engineering structure, an acoustic receiving array is fixedly arranged on the subsurface buoy system, and time synchronization, array element space position calibration and channel gain calibration are carried out on the acoustic receiving array; when an abnormal acoustic event with a spatial consistent propagation characteristic is detected, the acoustic receiving array enters an enhanced working mode and outputs a multi-channel enhanced acoustic signal; and in the enhanced working mode, outputting a judgment result of whether an abnormal acoustic event occurs or not, and solving to obtain a position estimation value of the abnormal event in the axial direction of the structure and a corresponding positioning confidence interval. The method is suitable for online anomaly monitoring and accurate positioning of an underwater linear engineering structure with a known space trend in a complex marine environment.

The invention discloses a mural hollowing area intelligent detection method based on a sound wave array. The method comprises the following steps that the sound wave array is arranged to emit set sound waves, and signals are collected, calibrated and preprocessed; inputting a multi-branch convolution unit of the improved ConvTransform, and executing multi-scale convolution extraction and feature fusion; inputting a residual error convolution unit, and executing convolution transformation, residual error connection and channel weighting processing; inputting a time sequence perception self-attention module, and executing multi-head time sequence attention modeling under causal constraints; inputting the data into a multi-layer nonlinear mapping module, and executing full-connection operation, nonlinear mapping and normalization processing; calculating a classification probability, and determining a category index; and generating a spatial distribution diagram and outputting the spatial distribution diagram to a detection terminal by combining an array layout information mapping judgment result. The mural hollowing detection is realized by using the sound wave array and the improved ConvTransform, and the mural hollowing detection method has the advantages of high precision, accurate positioning and visual result.

An attachable endoscope assembly is disclosed herein. The attachable endoscope assembly can include an attachment component, an ultrasound assembly housing configured to selectively couple an ultrasound array to the attachable endoscope assembly, and a neck coupling the attachment component to the ultrasound assembly housing. The neck can include a guide configured to receive an instrument as it traverses out of an lumen of the endoscope and direct the instrument into a field-of-view of the ultrasound array when coupled to the ultrasound assembly housing, and a first pivot point including a first modulus of elasticity configured to move the ultrasound assembly housing between a relaxed position and a stressed position in response to a resultant force applied by the instrument when the instrument is received by the guide.

The invention proposes a novel steam pipeline leakage detection method based on the fusion of an acoustic array and a temperature measurement camera, and the method comprises the following steps: synchronously collecting an acoustic signal, a temperature image and a visible light image, carrying out the preprocessing and wave beam forming of the acoustic signal, obtaining an acoustic energy diagram, carrying out the thermal anomaly detection of the temperature image, and obtaining a detection result. Geometric registration is carried out on the acoustic energy diagram and the temperature image; beam forming is restrained by using the thermal anomaly mask; a sidelobe-restrained acoustic energy diagram is generated; multi-source evidence fusion is carried out on the sidelobe-restrained acoustic energy diagram and the thermal anomaly mask to obtain a leakage probability diagram; and finally, displaying a superposition result and receiving user interaction. According to the invention, through fusion of multiple devices such as the acoustic array and the temperature measurement camera, accurate detection and stable tracking of steam pipeline leakage are realized, and the method has important application prospects and technical significance.

The invention discloses a weak fault sound source monitoring and early warning method based on deep learning and an acoustic array, and belongs to the technical field of equipment state monitoring and fault diagnosis. In order to solve the problem of early fault detection caused by easy submergence of weak fault voiceprint signals, incomplete feature extraction and scarcity of fault samples in a strong noise environment, the method comprises the following steps: collecting multichannel signals through an acoustic array, establishing a dynamic noise baseline by adopting a Gaussian mixture model, and performing noise suppression in combination with a spectral subtraction method; extracting a composite feature vector containing time domain, frequency domain and time-frequency domain features; and carrying out fault identification by using the pre-trained and fine-tuned transfer learning model, and finally outputting an early warning according to an identification result. The method is suitable for online monitoring and early warning of early weak faults of industrial equipment.

The invention discloses a self-adaptive directional sound control method and system based on a multi-loudspeaker array. The method comprises the following steps: constructing an acoustic array by utilizing a plurality of loudspeakers distributed in different directions in the mobile terminal, performing single side band up-conversion processing on an audio signal, performing digital beam forming according to a target direction, and generating a plurality of paths of driving signals with phase difference and time delay difference, thereby forming a high-directivity sound field in a space. The system collects sound field feedback signals through a built-in microphone, and adopts a minimum mean square algorithm to adjust beam parameters in real time so as to compensate for terminal attitude, shielding and environmental noise changes and realize stable directional output of a sound field. The system further comprises a parameter library and sensor fusion module which supports adaptive calibration and multi-beam output of different devices. According to the invention, programmable directional sound transmission is realized without hardware modification, and the method has high privacy, low power consumption and strong robustness, and is suitable for private communication of an intelligent terminal and a multi-user audio partition playing scene.

The invention relates to a multi-source intelligent combined pose measurement method for a floating hydrophone array, and the method comprises the following steps: 1, obtaining the pose information of each node of the hydrophone array through a multi-source sensing module, and synchronously receiving sound signals and extracting the TDOA information of each node under the condition that the sound source position is known; step 2, constructing a measurement equation based on TDOA information, and performing inverse solution on the position of each node of the hydrophone array in combination with a hyperbolic positioning principle and a sound velocity model; according to the method, an inverse solution positioning mode of'known sound source position and inverse solution of receiving array node position 'is adopted, a flexible underwater acoustic array dynamic measurement scene under the traction of a floating platform is specially aimed at, the technical limitation that traditional TDOA and USBL positioning depends on a fixed geometric structure is broken through, the method does not need to arrange a plurality of reference receiver arrays, and the positioning accuracy is improved. And a high-precision synchronous clock system is not needed, and high-precision acoustic positioning can be realized only by depending on a single sound source and the distributed nodes, so that the system complexity and the field deployment cost are remarkably reduced.

The utility model discloses an acoustic array underwater automatic rotation device, which relates to the technical field of acoustic testing, and comprises an N-shaped support, a connecting plate, an electric control box, an operation panel and a transverse rolling force module, the N-shaped support is provided with a transverse rolling support, the connecting plate is provided with a stainless steel bearing, and the transverse rolling force module is provided with a transverse rolling force module. The connecting plate is rotatably connected with the transverse rolling support through a stainless steel bearing, an XY translation mechanism is arranged at the top of the N-shaped support, the XY translation mechanism is composed of two electric push rods arranged in the XY direction, and mounting plates are arranged at the extending ends of the two electric push rods. When the automatic rotation device is used, a product to be tested is only required to be clamped once, rotation actions of all angles to be tested of the acoustic array can be completed under the control of a system, the labor intensity of workers is reduced, the loading and unloading time of the product to be tested is saved, the test efficiency is improved, and the automatic rotation device is high in applicability, universal for various types of products and high in overall practicability.

According to the involute type multi-arm spiral sound array and the method, in the array, a center supporting piece is of a regular heptagonal plate-shaped structure, seven side edges of the center supporting piece are connected with seven base circle spiral arm connecting pieces in a welding mode respectively, the other end of each base circle spiral arm connecting piece is connected with an internal spiral arm structure, and the other end of each internal spiral arm structure is connected with an outer spiral arm structure; the other end of each internal spiral arm structure is connected with one middle spiral arm structure, and the other end of each middle spiral arm structure is connected with one external spiral arm structure; each external spiral arm structure is in welded connection with the middle spiral arm structure adjacent in the anticlockwise direction through an adjacent arm supporting rod; the bottom face of the center supporting piece is connected with the array connecting piece in a welded mode, and the array connecting piece is connected with the array supporting base structure in a fastened mode through bolts. The internal spiral arm structure, the middle spiral arm structure and the external spiral arm structure are provided with circular through holes used for installing microphones, and the circle centers of the through holes are located on an involute generated by the same base circle.

The application provides a device sound source position determination method based on a multi-sensor acoustic array imaging, and belongs to the technical field of sound field imaging, and comprises the following steps: S1, acquiring microphone sensor array experimental data; S2, data preprocessing and calculating sample covariance matrix; S3, performing characteristic decomposition and determining the number of sound sources; S4, preliminarily judging the sound source parameter range to determine the iteration initial value, and calculating the power parameter initial value corresponding to each sound source; S5, estimating noise variance S6, calculating the characteristic value and characteristic vector theoretical value of the sound source subspace; S7, solving S+1 dimensional nonlinear equation set to obtain the estimation result. The application can take the positions and powers of multiple sound sources as parameters to be estimated, model the sound pressure signal covariance matrix, then perform characteristic decomposition on the covariance matrix to obtain the characteristic value and characteristic vector theoretical value.

The invention provides an anti-pseudo peak frequency difference azimuth estimation method using sparse Bayesian learning, and relates to the technical field of underwater acoustic array signal processing. The method specifically comprises the steps of collecting signals, selecting processing frequency points, constructing a dictionary matrix and a joint spectrum matrix, quantifying the stability of signal intensity changing along with a reference high-frequency frequency point, optimizing the joint spectrum matrix according to the stability to eliminate false peaks, and obtaining an orientation estimation result. According to the technical scheme, false peaks can be effectively removed, the sidelobe height in the azimuth spectrum can be reduced, and the azimuth estimation accuracy of the target can be improved.

The present invention relates to a photoacoustic array probe comprising: a transducer array in which a plurality of transducer elements for detecting photoacoustic waves generated by light irradiated at a subject are arranged; an acoustic reflector arranged to face the transducer array so as to form a plurality of virtual detection points having a function of detecting the photoacoustic waves by reflecting ultrasonic waves generated from the plurality of transducer elements; and a driver for driving rotational motion of the acoustic reflector and / or linear motion of the transducer array and the acoustic reflector, wherein the formation range of the virtual detection points increases according to driving of the driver.

The present application relates to the technical field of UUV sound array platform, and especially relates to a UUV transverse low-resistance wing type multi-element sound array platform, a sound base array platform is installed on a UUV, and a wing line shape is designed to be contracted to a UUV cabin section surface at a front end, the present application guarantees better stability and follow-up performance when the platform moves in water, reduces flow noise, and a soft connection form is adopted between a base array frame and a sound array, so that the transmission sound signal is not distorted.

A spatial ultrasound modulator includes a signal line, an ultrasonic array, a pixel coder and an ultrasonic driver. The signal line includes a plurality of first conductive lines and a plurality of second conductive lines. The plurality of first conductive lines are arranged to be spaced apart from each other on a substrate. The plurality of second conductive lines are arranged to intersect the first conductive lines above the plurality of first conductive lines and to be spaced apart from each other. The ultrasonic array includes a plurality of ultrasonic generators. Each of the plurality of ultrasonic generators includes at least one capacitive micromachined ultrasonic transducer (CMUT) device. Each of the plurality of ultrasonic generators is superimposed on one of a plurality of pixels, which are intersection points of the plurality first conductive lines and the plurality of second conductive lines. Each of the plurality of ultrasonic generators generates a unit-ultrasonic wave. The pixel coder may be configured to generate the coding array by coding each of the plurality of pixels of the ultrasonic array so that an operation mode of each of the plurality of pixels may be a contrasting binary operation mode of the ultrasonic generator. The coding array includes active pixels and inactive pixels. The ultrasonic driver drives the coding array to generate amplitude-modulated ultrasonic waves of which a wavefront may be deformed. The amplitude-modulated ultrasonic waves are a synthesized plurality of unit-ultrasonic waves.

The application provides an acoustic array adaptive calibration correction system applied to an underwater moving target, relates to the technical field of marine equipment, and comprises a multi-source excitation and environment perception module, an intelligent array perception and diagnosis module, an adaptive position inversion and uncertainty quantification module and a closed-loop calibration execution and self-learning optimization module; the multi-source excitation and environment perception module is responsible for providing a reference signal required for calibration and establishing an association model of environment and array distortion, the intelligent array perception and diagnosis module realizes multi-modal data acquisition, array element health state monitoring and array geometry self-perception, the adaptive position inversion and uncertainty quantification module completes signal processing, position estimation and error quantification propagation, and the closed-loop calibration execution and self-learning optimization module executes a compensation strategy, verifies calibration effect and continuously optimizes system performance through online learning; the system solves the problems that cannot be handled by traditional methods, such as environment time variation, multi-sensor conflict and uncertainty quantification.

The application discloses a device and system for judging the fault of a supporting roller by combining an acoustic array and thermal imaging, comprising an inspection part, an acoustic array part, a thermal imaging part, a comprehensive processing part and a power supply. The application uses the acoustic array to collect the sound signals of the supporting roller bearing and completes preprocessing, then uses the MVDR algorithm to process the filtered signals, extracts the sound signal power of the supporting roller bearing, and uses the thermal imager to collect the thermal images of the conveying belt. After the preprocessing is completed, the edge detection and feature recognition are used to judge whether the temperature of the supporting roller is faulty. The comprehensive processing part uses the sound-temperature joint analysis algorithm to comprehensively analyze the acoustic array processing signals and the thermal imager processing signals, so as to quickly judge whether the supporting roller bearing is faulty, realizes the sound signal collection and processing of the fault of the supporting roller inner supporting bearing based on the combination of the acoustic array and the thermal imaging technology, and can greatly improve the fault detection accuracy through the analysis of the MVDR algorithm and the sound-temperature joint analysis algorithm.

A method of cavitation mapping in a region of interest is provided. Methods, systems and computer program products according to some embodiments include receiving ultrasound signals from a cavitation event with an ultrasound array; and localizing the cavitation event to determine a cavitation location. The method also includes mapping the cavitation location on an image; and providing information characterizing the cavitation event.

An ultrasound system includes an ultrasonic array having at least one ultrasonic element, wherein the ultrasonic array configured for transmitting analog ultrasound signals in ultra-high frequency above 25 MHz; an analog sampling recorder receiving the ultrasound signals in ultra-high frequency above 25 MHz and outputting an analog signal with a reduced frequency, wherein the analog sampling recorder will reduce the analog signal frequency; and an ultrasound subsystem coupled to the analog sampling recorder wherein the reduced frequency analog signal from the analog sampling recorder forms an analog front-end channel of the ultrasound subsystem.

The application discloses a three-node passive acoustic array ship positioning method based on a CNN-LSTM model, and relates to the technical field of underwater sound source positioning. The method comprises the following steps: step S1: collecting acoustic signals radiated by a target ship in real time through a three-node passive acoustic network arranged underwater; and pre-processing acoustic signals of each node to obtain interaural intensity difference features and interaural phase difference features; step S2: constructing a CNN-LSTM model, inputting combined feature maps of the interaural intensity difference features and the interaural phase difference features into a spatial feature extraction module of the CNN-LSTM model to perform spatial feature extraction, and outputting a spatial feature vector; step S3: inputting the spatial feature vector into a time sequence feature learning module of the CNN-LSTM model to perform time sequence feature extraction, and outputting a latent feature vector; and step S4: inputting the latent feature vector into an output layer of the CNN-LSTM model to complete regression prediction, and outputting a bearing angle and a distance value of a sound source.

The invention provides a power equipment state monitoring and fault diagnosis system based on multi-modal data, and relates to the field of data processing, and the system comprises a data collection module which comprises an acoustic array, an image collection device and an infrared thermal induction device, and the acoustic array comprises sound collection devices arranged at a plurality of positions of power equipment; the state monitoring module is used for determining abnormal sound coordinates according to the sound data acquired by the acoustic array; the data acquisition module is further used for controlling the image acquisition device to acquire images based on the abnormal sound coordinates and controlling the infrared thermal induction device to acquire infrared thermal induction data; and the fault diagnosis module is used for performing fault diagnosis based on the sound data acquired by the acoustic array, the image acquired by the image acquisition device and the infrared thermal induction data acquired by the infrared thermal induction device, and has the advantage of improving the efficiency and accuracy of state monitoring and fault diagnosis of the power equipment.

The invention discloses an urban environment noise source positioning, identification and classification method based on visual and acoustic information fusion. The method comprises the following steps: positioning a coordinate, an azimuth angle, a pitch angle and a distance of a noise source relative to an array center by using an acoustic array; adjusting the angle of the camera to align to the noise source position for video shooting; noise targets are classified by using a noise source target identification method based on fusion of acoustic data and video data, and the types of noise sources are determined; positioning the coordinate, azimuth angle, pitch angle and distance of the noise source relative to the camera by combining the visual data with the noise source classification result, and adjusting the result into the coordinate, azimuth angle, pitch angle and distance relative to the array center; and fusing the two groups of coordinates, azimuth angles, pitch angles and distances relative to the center of the array, and calculating a final result. Not only can the noise source target position be accurately positioned, but also the noise source target type can be accurately identified and classified.

The application discloses a manufacturing method of an anti-icing acoustic array module, and the module is manufactured by using an integrated forming process, and specifically comprises the following steps: S1, roughening treatment is performed on the inner and outer surfaces of a high-strength composite material layer to improve the surface bonding strength; S2, polyurea is sprayed on the front surface of the high-strength composite material layer, the thickness is uniform and controlled within the range of 0.5-2 mm; S3, an adhesive is coated on the back surface of the high-strength composite material layer, and a specific thickness of low-modulus polyurethane glue is poured after preheating; and S4, the anti-icing layer is completed by placing in an oven for heating and curing. The application has the advantages of simple process and uniform composite bonding of the anti-icing layer and the acoustic array main body, and can guarantee the acoustic performance of the acoustic array while obtaining the anti-icing capability.

The invention discloses a multi-mode fire early warning method and system, and relates to the technical field of industrial storage area fire early warning, the system collects temperature field distribution, particulate matter concentration and frequency spectrum signal data in real time by arranging a thermal infrared imager, a smoke sensor and an acoustic array microphone; performing time sequence frame difference and multi-frame mean filtering, calculating a thermal anomaly index and triggering smoke effect identification; adopting a sliding window difference and multi-point mean variance algorithm to extract smoke abnormal characteristics and trigger acoustic effect identification; based on the frequency spectrum signal, acoustic abnormal features are extracted, and cross-modal fusion judgment is triggered; and fusing the multi-modal abnormal indexes, calculating a fire comprehensive judgment index, and generating a corresponding early warning strategy according to a preset threshold value. According to the invention, efficient, accurate and real-time monitoring and response of the fire risk of the storage area are realized, the timeliness and reliability of fire early warning are improved, and a remarkable safety guarantee effect is achieved.

The invention relates to an ultrasonic array sensor (100) for detecting distances between a vehicle and objects in the surroundings of the vehicle, comprising at least one diaphragm component (110) having a vibrating diaphragm (111) and a cavity (113) in the interior of the diaphragm component (110); and at least two transducer elements (130), wherein each transducer element (130) is mechanically coupled to a diaphragm region (112), wherein the ultrasonic array sensor (100) has a support structure (120) which is arranged in the cavity (113) of the diaphragm component (110) and contacts a contact region of the diaphragm (111) on the inner side (118), as a result of which the diaphragm (111) is divided into at least two separate vibrating diaphragm regions (112), wherein the support structure (120) creates a natural frequency distance Δf eig between the different vibration modes of the diaphragm (111) of the ultrasonic array sensor (100) of less than or equal to 10% with respect to the operating frequency op of the ultrasonic array sensor (100).