A squeal detection apparatus and method

Abstract

This invention relates to the field of hardware circuit testing technology, and discloses an abnormal noise detection device and method. The device includes: a control device, a soundproof sealed cavity, and a moving device, an image acquisition device, and a sound pickup device disposed within the soundproof sealed cavity; the image acquisition device and the sound pickup device are disposed on the moving device; the control device is communicatively connected to the moving device, the image acquisition device, and the sound pickup device respectively; after the object to be tested is placed in the soundproof sealed cavity, the control device controls the image acquisition device to acquire a position image of the object to be tested, and divides the position image into regions to obtain several position regions to be tested of the object to be tested; the control device controls the moving device to move to each position region to be tested, and controls the sound pickup device to acquire the running sound of the object to be tested in each position region to be tested, and then determines the abnormal noise detection result of the object to be tested based on the running sound of the object to be tested in each position region to be tested, which can accurately identify and locate abnormal noise.

Description

Technical Field

[0001] This invention relates to the field of hardware circuit testing technology, specifically to an abnormal noise detection device and method. Background Technology

[0002] With the widespread application of automotive electrical components, these components play an increasingly important role in managing and monitoring various vehicle systems. However, in practical applications, some electrical components, due to component selection or circuit design, can generate abnormal noises during circuit operation due to the vibration of some components. For example, the vibration of inductors, transformers, or capacitors, if the vibration frequency is between 20Hz and 20kHz, can easily be heard as a "squeaking" noise. The most noticeable impact is on electrical components located in the cabin, which directly affect the overall NVH level of the vehicle (Noise, Vibration, and Harshness). Abnormal noises generated by electrical components may interfere with the driver's attention, affecting driving safety and increasing the risk of accidents; they can also cause discomfort to passengers, affecting the riding experience; if the abnormal noise persists for a long time, it may lead to malfunctions of controllers or related equipment, affecting the normal operation of the vehicle.

[0003] Therefore, identifying abnormal noises early in the testing and verification phase of electrical components is crucial. Currently, the conventional method for identifying circuit abnormal noises is through human hearing in a relatively quiet environment. However, this method may miss some abnormal noises due to differences in hearing perception among different testers; furthermore, the human ear's ability to locate sound is limited by biological structures and the nervous system, resulting in weak localization capabilities; and abnormal noise detection is easily affected by environmental interference, among other problems. Therefore, there is an urgent need for a fast and accurate abnormal noise detection and localization method for hardware testing of vehicle control systems, in order to identify problems early, improve corresponding issues, and further enhance the overall NVH (Noise, Vibration, and Harshness) level of the vehicle. Summary of the Invention

[0004] In view of this, the present invention provides an abnormal noise detection device and method to solve the problem that the existing detection methods mentioned in the above technical background are easily affected by human or environmental factors, which can easily lead to misjudgment and difficulty in locating abnormal noises, making it difficult to detect potential hardware defects in vehicles in a timely manner, and thus seriously affecting the NVH level of the whole vehicle.

[0005] In a first aspect, the present invention provides an abnormal noise detection device, the device comprising: a control device, a soundproof sealed cavity, and a moving device, an image acquisition device, and a sound pickup device disposed within the soundproof sealed cavity;

[0006] The image acquisition device and the sound pickup device are mounted on the mobile device;

[0007] The control device is communicatively connected to the mobile device, the image acquisition device, and the audio pickup device, respectively.

[0008] After the object to be tested is placed in the soundproof and sealed cavity, the control device controls the image acquisition device to acquire the position image of the object to be tested, and divides the position image into regions to obtain several position regions of the object to be tested.

[0009] The control device controls the mobile device to move to each detection location area, and controls the sound pickup device to collect the running sound of the object under test in each detection location area;

[0010] The control device determines the abnormal sound detection result of the object under test based on the running sound of the object under test in each detection location area.

[0011] This invention relates to an abnormal noise detection device comprising a control device, a soundproof sealed cavity, and a moving device, an image acquisition device, and a sound pickup device disposed within the soundproof sealed cavity. After the object to be detected is placed within the soundproof sealed cavity, the image acquisition device acquires a position image of the object to be detected to determine several detection position areas. At each detection position area, the sound pickup device collects the corresponding operating sound, and the presence of abnormal noise is determined based on the operating sound. This effectively avoids the influence of human and environmental factors on the identification of abnormal noise of the object to be detected, thereby achieving rapid and accurate abnormal noise detection and positioning. Applying this device to hardware testing for vehicle control helps to identify and improve problems in advance, greatly shortens the product development cycle, and thus improves the overall NVH level of the vehicle.

[0012] In one alternative embodiment, the moving device includes a slider and a coupling, with the image acquisition device and the sound pickup device respectively disposed at the bottom of the slider; wherein, the coupling is used to drive the slider to move within the soundproof and sealed cavity.

[0013] This invention integrates an image acquisition device and a sound pickup device at the bottom of a slider, and drives the slider to move within a soundproof and sealed cavity via a coupling. This enables spatiotemporal synchronous acquisition of visual and acoustic signals, providing a hardware foundation for accurate labeling of abnormal sound locations. In one optional embodiment, the coupling includes an X-axis coupling, a Y-axis coupling, and a Z-axis coupling; wherein the X-axis coupling is slidably connected to the Z-axis coupling, the Z-axis coupling is screw-connected to the Y-axis coupling, the Y-axis coupling is slidably connected to the slider, and a test platform is provided on the plane where the X-axis coupling is located.

[0014] This invention designs a coupling structure including X-axis, Y-axis and Z-axis, which can realize the precise movement of the slider in three-dimensional space, while ensuring the flexible decoupling of the slider's movement in each direction. This helps to balance the flexibility of movement and the accuracy of movement, thereby ensuring the accuracy and reliability of subsequent abnormal sound detection of the object to be tested.

[0015] In one alternative implementation, the image acquisition device is a structured light camera, and / or the sound pickup device is a condenser microphone.

[0016] In a second aspect, the present invention provides a method for detecting abnormal noise, applied to a control device in an abnormal noise detection device as described in the first aspect above or any corresponding embodiment thereof, the method comprising:

[0017] After the object to be tested is placed in the soundproof and sealed cavity, the image acquisition device is controlled to acquire the position image of the object to be tested, and the position image is divided into regions to obtain several position regions of the object to be tested.

[0018] The mobile device is controlled to move to each detection location area, and the sound pickup device is controlled to collect the running sound of the object under test in each detection location area;

[0019] The abnormal sound detection result of the object under test is determined based on the running sound of the object under test in each detection location area.

[0020] The abnormal noise detection method of the present invention involves placing the object to be tested in a soundproof sealed cavity, controlling an image acquisition device to acquire a position image of the object to be tested, and dividing the position image into regions to determine several detection position areas of the object to be tested; after controlling a moving device to move to each detection position area, a sound pickup device is used to acquire the running sound of the object to be tested accordingly, and the presence of abnormal noise is determined based on the running sound. This method can quickly and accurately identify the location and magnitude of abnormal noise generated by the object to be tested, effectively avoiding the influence of human and environmental factors on the identification of abnormal noise of the object to be tested, thereby achieving rapid and accurate abnormal noise detection and positioning. Applying this method to hardware testing of vehicle control helps to discover and improve problems in advance, not only shortening the product development cycle but also greatly improving the overall NVH level of the vehicle.

[0021] In one optional implementation, controlling the moving device to move to each detection location area includes:

[0022] Determine the starting region from each region to be detected;

[0023] The optimal motion trajectory is generated based on the positional relationship between the starting region and the other regions to be detected, and the moving device is controlled to move accordingly from the starting region along the optimal motion trajectory.

[0024] This invention automatically generates an optimal motion trajectory based on the positional relationship of each detection location area of ​​the object to be detected. This avoids invalid movements such as repeated back-and-forth or redundant paths, significantly reduces movement distance and time, thereby improving movement efficiency and maximizing resource utilization and optimizing task execution.

[0025] In one optional implementation, determining the abnormal sound detection result of the object to be detected based on the running sound of the object in each detection location region includes:

[0026] A power spectral density function is generated based on the running sound of each detection location area, and the power of the corresponding detection location area is calculated based on the power spectral density function.

[0027] Each power is superimposed onto the corresponding area to be detected to obtain the spectrogram of the object to be detected;

[0028] When the power in the spectrogram exceeds the preset power threshold, it is determined that the object to be detected has abnormal sound;

[0029] If the power in the spectrogram does not exceed the preset power threshold, it is determined that the object to be detected does not have abnormal noise.

[0030] This invention can accurately capture specific frequency components of sound by operating the power spectral density function of sound, thereby improving the accuracy of abnormal sound identification. Furthermore, by superimposing the power of each region to be detected to obtain a spectrogram, testers can quickly pinpoint the specific location of power anomalies. This not only achieves rapid identification and location of abnormal sounds, avoiding the subjectivity and ambiguity of traditional manual sound detection, but also improves the accuracy, efficiency, and automation level of abnormal sound detection.

[0031] In one optional implementation, when a power exceeding a preset power threshold exists in the spectrogram, the abnormal sound detection method further includes:

[0032] The corresponding detection area where the power exceeds the preset power threshold is marked to determine the location of the abnormal sound on the object to be detected.

[0033] This invention not only achieves accurate identification of abnormal sounds, but also designs a process for marking the corresponding detection area where abnormal sounds exist, which can intuitively and quickly locate the location of abnormal sounds in the object to be detected.

[0034] In an optional implementation, after the sound pickup device collects the operating sound of the object to be detected in each detection location area, the abnormal sound detection method further includes:

[0035] The slider in the control device is moved to the initial preset position of the soundproof and sealed cavity.

[0036] After the sound pickup device collects the sound of the object under test in each test location area, the present invention designs a corresponding repositioning operation of the moving device, that is, the slider in the moving device is moved to the initial preset position of the soundproof sealed cavity. Through the design of the consistency of the physical position of the slider, not only can the interference of position deviation on acoustic data be eliminated and the data repeatability be ensured, but it also facilitates the placement and removal of the object under test.

[0037] In an optional implementation, before the image acquisition device acquires a location image of the object to be detected, the abnormal sound detection method further includes:

[0038] Set the test parameters for the object to be tested, and verify whether the test parameters meet the preset test requirements;

[0039] When the parameters meet the preset test requirements, execute the step of controlling the image acquisition device to acquire the position image of the object to be detected.

[0040] The present invention provides a design and verification process for the test parameters of the object to be tested, which can ensure the accuracy and consistency of test conditions, avoid "false detection" or "missed detection" caused by parameter fluctuations, and thus improve the reliability of abnormal sound detection results.

[0041] In one optional implementation, after determining the abnormal sound detection result of the object to be detected based on the running sound of the object in each detection location region, the abnormal sound detection method further includes:

[0042] Display the abnormal sound detection results, and / or generate a corresponding detection report based on the abnormal sound detection results and spectrogram, and display and / or save the detection report.

[0043] This invention provides a visual display of abnormal sound detection results and generates corresponding detection reports, enabling an intuitive and comprehensive presentation of the abnormal sound detection results of the object under test.

[0044] This invention designs an abnormal noise detection device comprising a control device, a soundproof sealed cavity, and a moving device, an image acquisition device, and a sound pickup device disposed within the soundproof sealed cavity. The invention also designs a corresponding abnormal noise detection process for this device. After the object to be detected is placed within the soundproof sealed cavity, the image acquisition device acquires a position image of the object and divides the position image into regions to determine several detection areas. After the moving device moves to each detection area, the sound pickup device acquires the corresponding operating sound of the object and determines whether abnormal noise exists based on the operating sound. This effectively avoids the influence of human and environmental factors on abnormal noise identification, thus achieving rapid and accurate abnormal noise detection and localization. Applying this to hardware testing for vehicle control helps to identify and improve problems early, shortening the product development cycle and significantly improving the overall vehicle NVH level. Attached Figure Description

[0045] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0046] Figure 1 This is a structural block diagram of an abnormal noise detection device according to an embodiment of the present invention;

[0047] Figure 2 This is a structural block diagram of another abnormal sound detection device according to an embodiment of the present invention;

[0048] Figure 3 This is a structural diagram of the abnormal noise detection device;

[0049] Figure 4 This is a schematic diagram of the structure of a three-coordinate moving platform;

[0050] Figure 5 This is a structural diagram of the main equipment;

[0051] Figure 6 This is a flowchart illustrating the abnormal sound detection method according to an embodiment of the present invention;

[0052] Figure 7 This is a flowchart illustrating another abnormal sound detection method according to an embodiment of the present invention;

[0053] Figure 8 This is a flowchart of the abnormal sound detection process;

[0054] Figure 9 This is a diagram showing the division of regions. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] This embodiment provides an abnormal noise detection device. Figure 1 This is a structural block diagram of an abnormal noise detection device according to an embodiment of the present invention. Figure 1 As shown, the device includes: a control device 101, a soundproof sealed cavity 102, and a moving device 103, an image acquisition device 104, and a sound pickup device 105 disposed within the soundproof sealed cavity; wherein, the image acquisition device 104 and the sound pickup device 105 are disposed on the moving device 103; the control device 101 is communicatively connected to the moving device 103, the image acquisition device 104, and the sound pickup device 105 respectively; after the object to be detected is placed in the soundproof sealed cavity 102, the control device 101 controls the image acquisition device 104 to acquire a position image of the object to be detected, and divides the position image into regions to obtain several detection position regions of the object to be detected; the control device 101 controls the moving device 103 to move to each detection position region, and controls the sound pickup device 105 to acquire the running sound of the object to be detected in each detection position region respectively; the control device 101 determines the abnormal sound detection result of the object to be detected based on the running sound of the object to be detected in each detection position region.

[0057] It should be noted that the specific communication connection method between the control device 101 and the mobile device 103, image acquisition device 104, and microphone 105 in this embodiment is not limited and can be adapted according to actual needs. For example, the mobile device 103, image acquisition device 104, and microphone 105 can be connected to the control device 101 via wireless communication; or the control device 101 can be connected to the mobile device 103, image acquisition device 104, and microphone 105 via wired communication, such as by connecting cables. This is only an example.

[0058] In this embodiment, the specific type of the control device 101 can be determined according to actual needs. For example, the control device 101 may be a microcontroller, CPU, or other hardware device. This is only an example.

[0059] In this embodiment, the soundproof sealed cavity 102 is a sealed box, which is a closed space with high sound insulation and high sound absorption characteristics. It can isolate environmental noise and reduce the impact of abnormal sound reflection on the test results. Furthermore, according to the communication connection method set by the control device 101, if wired communication is used, a connector interface can be reserved in the box for power supply and data transmission between the internal devices and the control device 101. In addition, the soundproof box is also equipped with an openable and closable door, mainly used to take out the test sample, i.e., the object to be tested.

[0060] It should be noted that in this embodiment, the object to be tested refers to the circuitry or other similar objects of automotive electrical components with their casings removed. The specific details can be adjusted according to actual needs. It is important to note that the object to be tested needs to be powered on and in working condition during the testing process. Specifically, if the noise detection device of this embodiment is applied to noise detection in the field of vehicle controllers, the object to be tested is a controller that is close to the driver, such as a driver monitoring camera, display screen, or instrument panel. It can also be extended to other sound-sensitive areas, such as handheld terminals, based on actual testing needs; this is only an example. In one specific embodiment, the object to be tested is an automotive electrical component, specifically a PCBA (Printed Circuit Board Assembly) after the casing has been removed. This PCBA integrates various electronic components (such as chips, capacitors, resistors, connectors, sensors, etc.) and circuitry, responsible for key functions such as signal processing, control logic, and power management, and may participate in related control functions in a vehicle control system. It should be noted that even if the aforementioned automotive electrical components are located in a sealed central control area or are themselves sealed components, internal abnormal noises can still be transmitted into the cabin, making it difficult to locate the abnormal noises inside the vehicle.

[0061] In this embodiment, the specific details of the region division of the position image by the control device 101 can be adaptively adjusted according to actual needs. For example, the image can be divided into regular regions based on geometric shapes such as rectangles, circles, and polygons; or, the image can be divided into grids; or, the image can be automatically divided using relevant algorithms such as detection algorithms and template matching algorithms to obtain the corresponding detection position regions. This is only an example.

[0062] In this embodiment, the specific actions taken by the control device 101 to move the mobile device 103 to each detection location area can be adaptively adjusted according to actual needs. For example, the mobile device 103 may be controlled to move sequentially to the center position of each detection location area, or to any designated position, such as the vertex of the area. This is only an example.

[0063] It should be noted that in this embodiment, after the mobile device 103 moves to a detection location area, it controls the sound pickup device 105 to collect the operating sound of that area, repeating this process until the sound sampling of all detection location areas of the object to be detected is completed.

[0064] In this embodiment, the abnormal sound detection result of the object to be detected includes the presence of abnormal sound and the absence of abnormal sound. The specific content of the abnormal sound detection result of the object to be detected determined by the control device 101 based on the running sound is not limited here and can be adaptively adjusted according to actual needs. For example, the control device 101 preprocesses the running sound, such as removing environmental noise, such as background mechanical vibration and airflow sound, through bandpass filtering and adaptive noise cancellation; then it uses wavelet transform and short-time Fourier transform to capture transient abnormal sounds, such as intermittent abnormal noises; or, it uses an abnormal sound detection algorithm to obtain the corresponding detection result, such as template matching (i.e., pre-collecting normal sound samples of the object to be detected in each detection location area, generating feature templates, and then comparing the real-time sound signal with the feature templates through algorithms such as dynamic time warping and cosine similarity; if the difference exceeds a set threshold, the sound is determined to be an abnormal sound), which is only an example.

[0065] In summary, the abnormal noise detection device of this invention can, after the object to be tested is placed in a soundproof and sealed cavity, use an image acquisition device to acquire a position image of the object to be tested to determine several detection position areas. In each detection position area, a sound pickup device is used to collect the corresponding operating sound, and the abnormal noise of the object to be tested is determined based on the operating sound. This can effectively avoid the influence of human and environmental factors on the identification of abnormal noise of the object to be tested, thereby achieving fast and accurate abnormal noise detection and positioning. Applying it to the hardware testing of vehicle control can help to discover and improve problems in advance, greatly shorten the product development cycle, and thus improve the NVH level of the whole vehicle.

[0066] In this embodiment, Figure 2 This is a structural block diagram of another abnormal noise detection device according to an embodiment of the present invention. Figure 2As can be seen, the moving device includes a slider and a coupling, with an image acquisition device and a sound pickup device respectively located at the bottom of the slider; the coupling is used to drive the slider to move within the soundproof and sealed cavity; the image acquisition device is a structured light camera, and / or, the sound pickup device is a condenser microphone. It should be noted that the slider, as a component in mechanical transmission used to achieve linear motion, achieves smooth and efficient linear motion by reducing frictional resistance or changing the form of friction; the coupling is a mechanical component that connects two shafts and transmits torque. In this embodiment, the coupling includes an X-axis coupling, a Y-axis coupling, and a Z-axis coupling; wherein the X-axis coupling is slidably connected to the Z-axis coupling, the Z-axis coupling is screw-connected to the Y-axis coupling, the Y-axis coupling is slidably connected to the slider, and a test platform is provided on the plane where the X-axis coupling is located. Specifically, the aforementioned coupling structure enables the slider to move precisely in three-dimensional space while ensuring flexible decoupling of the slider's movement in all directions. This helps to balance motion flexibility and movement accuracy, thereby ensuring the accuracy and reliability of subsequent abnormal sound detection of the object under test.

[0067] It should be noted that the coupling structure including X, Y, and Z axes designed in this embodiment can drive the slider to move accordingly in the X, Y, and Z directions. Therefore, the coupling and slider including X, Y, and Z axes can also be called a three-coordinate moving platform. A test platform is set within this three-coordinate moving platform for placing the object to be inspected, and the test platform is installed in a fixed position. It is important to note that the object to be inspected in this embodiment is fixedly placed on the test platform, which can eliminate positioning deviations caused by object displacement (i.e., ensure zero positional offset during the inspection process, further ensuring the accuracy of image positioning and sound acquisition, providing reliable data for the subsequent accurate detection and positioning of abnormal sound sources). Especially for precision automotive electrical components, fixing them in place allows the sound pickup device to always be aligned with millisecond-level minute abnormal sound sources (such as loose components or poor soldering), thereby achieving high-precision positioning and effectively avoiding the missed detection of early minor defects.

[0068] It should be noted that structured light cameras often use invisible infrared lasers of a specific wavelength as a light source. The light emitted is transmitted onto the object to be detected after being encoded. The distortion of the returned encoded pattern is calculated by a corresponding algorithm to obtain the position and depth information of the object to be detected, and thus obtain three-dimensional image data. Capacitive microphones have the characteristics of high sensitivity, and this microphone is a directional microphone, which can only receive sound from a specific direction, which can effectively reduce the influence of sound from other directions on the sampled data.

[0069] It should be noted that in this embodiment, the image acquisition device and the sound pickup device are both located at the bottom of the slider, and the slider moves within the soundproof and sealed cavity via a coupling. This has the following advantages:

[0070] 1. Ensure spatial consistency of "location-sound" data.

[0071] In this embodiment, fixing the image acquisition device (such as a structured light camera) and the sound pickup device (such as a condenser microphone) to the same rigid structure at the bottom of the slider ensures that they maintain a fixed relative position in physical space. When the slider moves to a certain detection area, the coordinates of the image positioning (such as pixel coordinates) can be directly mapped to the actual detection position of the sound pickup device, avoiding misalignment of "position-sound" data caused by relative displacement of the devices, thereby achieving accurate localization of abnormal sound sources.

[0072] In practical applications, since abnormal noises from automotive electrical components may originate from multiple adjacent components, the precise spatial alignment design described above in this embodiment can avoid misjudgment and effectively eliminate interference from vibration noises from components in other locations.

[0073] 2. Reduce the interference of the device itself on the test results.

[0074] In this embodiment, the pickup device is installed close to the bottom of the slider, away from the drive mechanism, which aims to reduce the impact of device operating noise on acoustic signal acquisition through physical isolation.

[0075] 3. Efficiently utilize the space of the sealed cavity.

[0076] In this embodiment, both the image acquisition device and the sound pickup device are integrated into the bottom of the slider, forming a compact "detection probe," thereby effectively reducing the space it occupies within the cavity. In a specific embodiment, Figure 3 This is a structural diagram of an abnormal noise detection device. Figure 3 As can be seen, the equipment includes a soundproof box 1 (i.e., a soundproof sealed cavity), a three-coordinate moving platform 2 (i.e., a moving device), a structured light camera 3 (i.e., an image acquisition device), a microphone 4 (i.e., a sound pickup device), and a main device 5 (i.e., a control device). It should be explained that the soundproof box 1 is internally sealed and has reserved interfaces for communication (i.e., the various connecting lines in the diagram) and an openable door (for placing and removing the object 6 to be inspected).

[0077] In this embodiment, the three-coordinate moving platform 2 is fixed inside the soundproof box 1. Figure 4 This is a structural diagram of a three-coordinate moving platform. Figure 4 As can be seen, the three-coordinate moving platform 2 mainly includes a slider 21, couplings (i.e., the couplings corresponding to the three coordinate axes, namely the X-axis coupling 22, Y-axis coupling 23, and Z-axis coupling 24 shown in the figure), and a test table 25 (used to place the object to be tested 6). The slider 21 is driven by the couplings and can move along the X, Y, and Z directions; the three-coordinate moving platform 2 is driven and controlled by the main equipment 5 and is connected to the main equipment 5 through the connector of the soundproof box 1.

[0078] It should be noted that the above coupling structure is similar to the Cartesian coordinate system structure of a 3D printer. It is decoupled in the X, Y, and Z directions, so movement in one direction will not affect the other direction. Moreover, since it is a purely linear drive, its motion accuracy is relatively easy to control.

[0079] In this embodiment, the working principle and installation method of the X-axis coupling 22 are as follows: a guide rail is installed on both sides of the X-axis coupling 22; a stepper motor and a rubber drive wheel are installed at the bottom of the Z-axis coupling 24, wherein the rubber drive wheel is stuck on the guide rail, and the stepper motor drives the rubber wheel to rotate, so that the slider 21 can move precisely in the X direction.

[0080] In this embodiment, the working principle and installation method of the Y-axis coupling 23 are as follows: the Y-axis coupling 23 is a guide rail and a stepper motor and a rubber drive wheel are installed inside the slider 21. The rubber drive wheel is stuck on the guide rail, and the stepper motor drives the rubber wheel to rotate, which can realize the precise movement of the slider 21 in the Y direction.

[0081] In this embodiment, the working principle and installation method of the Z-axis coupling 24 are as follows: a lead screw motor is installed at the bottom of the Z-axis coupling 24, and the nut of the Y-axis coupling 23 is threaded onto the lead screw; when the lead screw motor rotates, the slider 21 on the Y-axis coupling 23 will move along the Z direction. It should be noted that since the lead screw motor is a stepper motor, the coupling structure described in this embodiment can precisely control the movement distance in the Z direction via electrical pulses.

[0082] In this embodiment, the structured light camera 3 is installed at the bottom of the slider 21 in the three-coordinate moving platform 2 and connected to the main device 5 through the connector of the soundproof box 1. It is used to collect the depth information of the object 6 to be tested inside the soundproof box 1. It should be noted that in order to eliminate the influence of the camera's background noise on the test results, the following two measures were taken in this embodiment: (1) a structured light camera with low background noise was selected; (2) the structured light camera was enclosed in a sealed structure.

[0083] In this embodiment, the microphone 4 is a capacitor type, installed at the bottom of the slider 21 in the three-coordinate moving platform 2, with the microphone 4's pickup hole facing the object to be tested 6. It is connected to the main device 5 via a connector in the soundproof enclosure 1, and is used to sample abnormal noises from the object to be tested 6 during operation. Specifically, the microphone 4 is a directional microphone, capable of receiving sound only from a specific direction, effectively reducing the impact of sound from other directions on the sampled data. During measurement, the slider 21 carrying the microphone 4 moves along a predetermined direction under the drive control of the main device 5, collecting sound signals at each grid point to be tested, then moving to the next grid point to collect sound signals, repeating this process until all grid points of the object to be tested 6 have been tested. During measurement, the microphone 4 only needs to maintain a certain distance from the object to be tested 6, without needing to contact it. If the object to be tested 6 produces abnormal noise, the capacitor diaphragm of the microphone 4 will deform due to sound wave vibration, outputting an analog electrical signal under the drive of the main device 5, which is then transmitted to the main device 5.

[0084] In one specific embodiment, Figure 5 This is a schematic diagram of the main device. As shown in the figure, the main device 5 includes a motor drive unit 51, an audio signal unit 52, a video signal unit 53, a computing unit 54, a storage unit 55, a display unit 56, a peripheral unit 57, and a power supply unit 58.

[0085] In this embodiment, the audio signal unit 52 provides drive for the microphone 4 and simultaneously receives analog signals from the microphone 4. Specifically, the received analog signal is first filtered to remove signals beyond 20Hz-20kHz that are inaudible to the human ear; then the analog signal is amplified, and finally the amplified analog audio signal is converted into a digital audio signal and sent to the computing unit 54.

[0086] In this embodiment, the video signal unit 53 provides a data transmission interface for accessing the structured light camera 3. By sending relevant instructions, the three-dimensional image data acquired by the structured light camera 3 can be read and then sent to the computing unit 54.

[0087] In this embodiment, the computing unit 54 is used for sound signal processing, 3D image data processing, and testing system operation. Specifically, during sound signal processing, it receives digital audio signals from the audio signal unit 52; it converts the digital audio signals into audio components of different frequencies using Fourier transform, and then calculates the power of the audio components of different frequencies to obtain a power spectral density function (this function can intuitively reflect the power distribution of the sound signal at different frequencies). In addition, the computing unit 54 receives 3D image data from the structured light camera 3 and extracts the 3D coordinates from the 3D image data. Furthermore, the computing unit 54 also provides support for functions related to the normal operation of the main device 5, such as driving the display, file system, parameter settings, and file management.

[0088] In this embodiment, the display unit 56 provides a human-computer interaction interface for the tester (i.e., the user of the abnormal sound detection device), mainly used for parameter setting and test data display. In addition, this unit also has touch functionality for controlling display zoom in / out, viewing specific values, parameter setting, file storage, and data export.

[0089] In this embodiment, the storage unit 55 is used to store test data, device firmware, and configuration files. The test data includes images, PDF files, and CSV files; and supports data import and export. The peripheral unit 57 includes USB and Ethernet interfaces for data transmission and networking. The power supply unit 58 provides power to the various functional units in the main device 5 and the microphone 4. Note that the abnormal sound detection device in this embodiment supports both battery and external power supply.

[0090] This invention also provides an embodiment of an abnormal sound detection method. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0091] This embodiment provides a method for detecting abnormal noise, which is applied to the control device in an abnormal noise detection device. Figure 6 This is a flowchart illustrating the abnormal sound detection method according to an embodiment of the present invention, as shown below. Figure 6 As shown, the process includes the following steps:

[0092] Step S601: After the object to be tested is placed in the soundproof and sealed cavity, the image acquisition device is controlled to acquire the position image of the object to be tested, and the position image is divided into regions to obtain several position regions of the object to be tested.

[0093] It should be noted that the specific content of the object to be detected and the specific method of dividing the location image into regions in this embodiment can be found in the relevant content above, and will not be repeated here.

[0094] Step S602: Control the mobile device to move to each detection location area, and control the sound pickup device to collect the running sound of the object to be detected in each detection location area.

[0095] It should be noted that in this embodiment, by dividing the location image into regions and collecting corresponding sound data for each region to be detected, the operating sound of multiple corresponding regions is obtained for subsequent determination of whether the object to be detected has abnormal noise. This design, through "image region division + regional sound acquisition," achieves a leap from "overall qualitative" to "local quantitative" abnormal noise detection. Its advantages are:

[0096] 1. Technical aspects: A closed loop of "spatial positioning → signal acquisition → intelligent analysis" has been established, which solves traditional problems such as fuzzy localization of different sound sources, superposition of multiple sound sources, and missed detection of complex structures.

[0097] In this embodiment, image-based region segmentation breaks down the object to be detected into several physical sub-regions (such as a PCBA integrating multiple electronic components at different locations), enabling the sound pickup device to collect sound from specific structural units (rather than the whole). For example, the "contact area" and "coil electromagnetic area" of an automotive relay can be detected separately through image positioning, avoiding misjudgment of different sound types caused by the mixing of two sound source signals (such as distinguishing between mechanical collision sounds and electromagnetic vibration sounds).

[0098] In this embodiment, the detection area generated by image analysis can cover all key parts of the object to be detected (including complex curved surfaces and hidden corners), and the mobile device can detect area by area according to a preset path, which can avoid missed detections caused by manual detection or random sampling. For example, for an irregularly shaped automotive sensor housing, the terminal area, housing weld seam area, chip packaging area, etc. can be automatically divided to ensure that every potential source of abnormal noise (such as vibration caused by loose solder joints) is covered.

[0099] 2. Engineering level: It supports automated and flexible inspection, adapts to the needs of multi-variety and large-scale production of automotive parts, and becomes a key technology bridge connecting visual inspection and acoustic inspection.

[0100] In this embodiment, there is no need to customize special fixtures or detection hardware for different objects to be detected. By simply adjusting the parameters of the image region segmentation algorithm (such as detection accuracy and region density), it is possible to adapt to the detection needs of everything from micro electronic components to large assemblies, which helps to significantly reduce the equipment investment cost of automotive parts production lines.

[0101] 3. Quality Aspect: Through fine-grained area inspection and data traceability, a feasible technical solution is provided for "zero-defect" manufacturing in automobiles, particularly aligning with the stringent requirements of new energy vehicles for "quiet cabins" and "highly reliable components." In this embodiment, the image and sound data and inspection results of each area to be inspected can be bound and archived with the component number to be inspected, forming a "location-defect-batch" associated database. For example, if the abnormal sound rate of a certain electronic component in the PCBA (sealed with various electronic components) corresponding to the central control unit of a certain batch of automobiles exceeds 1% for three consecutive days, the manufacturing process of that electronic component (such as component aging) can be quickly traced, enabling root cause analysis of the quality problem.

[0102] Step S603: Determine the abnormal sound detection result of the object to be detected based on the running sound of the object in each detection location area.

[0103] In this embodiment, the abnormal noise of the object to be detected refers to the noise that can be perceived by the human ear when certain electronic components (such as inductors, transformers, capacitors, etc.) on the object to be detected are operating at high frequencies. This noise typically manifests as a high-frequency buzzing, squeaking, or beeping sound, with a corresponding frequency range of 20Hz to 20kHz (within the range of human hearing), and is intermittent or continuous. In practical applications, for enclosed automotive electrical components (such as the PCBA corresponding to the automotive central control unit, which integrates various electronic components), the abnormal noise detection method described in this embodiment, namely "image region mapping + acoustic array pickup," can accurately locate the sound source of internal components of the PCBA within a certain area / volume of the enclosed space. This helps to expose design defects in advance, and then achieve rapid and accurate repair of defective components. Specifically, the abnormal noise detection method in this embodiment can not only detect and locate problems in advance during vehicle development, but also quickly resolve them, greatly reducing the project development cycle; at the same time, it can effectively prevent automotive electrical components with abnormal noise risks from reaching the user end, further reducing user complaints and improving the user experience.

[0104] It should be noted that the specific contents of steps S602 and S603 in this embodiment can be referred to the relevant contents above, and will not be repeated here.

[0105] The abnormal noise detection method of this invention involves placing the object to be tested into a soundproof sealed cavity, controlling an image acquisition device to acquire a position image of the object, and dividing the position image into regions to determine several detection position areas of the object. After controlling a moving device to move to each detection position area, a sound pickup device is used to acquire the running sound of the object, and the presence of abnormal noise is determined based on the running sound. This method can quickly and accurately identify the location and magnitude of abnormal noise generated by the object, effectively avoiding the influence of human and environmental factors on the identification of abnormal noise of the object. This achieves rapid and accurate abnormal noise detection and positioning. Applying this method to hardware testing of vehicle control helps to discover and improve problems in advance, shortening the product development cycle and greatly improving the overall NVH level of the vehicle.

[0106] This embodiment provides a method for detecting abnormal noise, which is applied to the control device in an abnormal noise detection device. Figure 7 This is a flowchart illustrating another abnormal sound detection method according to an embodiment of the present invention, as shown below. Figure 7 As shown, the process includes the following steps:

[0107] Step S701: After the object to be tested is placed in the soundproof and sealed cavity, the image acquisition device is controlled to acquire a position image of the object to be tested, and the position image is divided into regions to obtain several position regions of the object to be tested. For details, please refer to... Figure 6 Step S601 of the illustrated embodiment will not be described again here.

[0108] It should be noted that in this embodiment, the entire testing process for detecting abnormal sounds in the object to be tested can be implemented using dedicated testing software. Specifically, after interconnecting the abnormal sound detection device with the testing software, the abnormal sound identification and location of the object to be tested are achieved by setting corresponding parameters and testing procedures on the testing software. The setting and verification process of the test parameters for the object to be tested ensures the accuracy and consistency of the test conditions, avoids errors in results due to parameter fluctuations, and thus guarantees the authenticity and reliability of the abnormal sound detection results. Therefore, before controlling the image acquisition device to acquire the position image of the object to be tested, the abnormal sound detection method of this embodiment further includes:

[0109] Step A1: Set the test parameters for the object to be tested and verify whether the test parameters meet the preset test requirements.

[0110] In this embodiment, the specific content of the test parameters and preset test requirements can be set according to the actual test adaptability. For example, the test parameters may include the threshold corresponding to the sound abnormality. The test parameters can be verified by actual test data to see if they meet the corresponding numerical test requirements. This is only an example.

[0111] Step A2: When the parameters meet the preset test requirements, execute the step of controlling the image acquisition device to acquire the position image of the object to be detected.

[0112] In this embodiment of the invention, by designing the setting and verification process of test parameters, the "false detection" or "missed detection" caused by parameter fluctuations can be avoided, which greatly improves the reliability of abnormal sound detection.

[0113] Step S702: Control the mobile device to move to each detection location area, and control the sound pickup device to collect the running sound of the object to be detected in each detection location area.

[0114] Specifically, in step S702 above, controlling the moving device to move to each detection location area includes:

[0115] Step B1: Determine the starting region from each region to be detected.

[0116] In this embodiment, the specific method for determining the starting region can be adaptively adjusted according to actual needs, such as arbitrarily selecting a region to be detected as the starting region; or, determining the starting region based on the closest distance.

[0117] Step B2: Generate the optimal motion trajectory based on the positional relationship between the starting area and the other areas to be detected, and control the moving device to move accordingly from the starting area along the optimal motion trajectory.

[0118] In this embodiment, the specific method for generating the optimal motion trajectory is not limited in detail. For example, it can be automatically generated using relevant path planning algorithms such as dynamic programming, branch and bound, and genetic algorithms. This is only used as an example.

[0119] In this embodiment of the invention, the optimal motion trajectory is automatically generated based on the positional relationship of each detection location area of ​​the object to be detected, which can significantly reduce the distance and time of movement of the mobile device, thereby improving the movement efficiency and realizing the maximum utilization of resources and the optimal execution of tasks.

[0120] It should be explained that after the sound pickup device collects the operating sound of the object under test in each test location area, a corresponding repositioning operation of the moving device is designed. This involves moving the slider in the moving device to the initial preset position of the soundproof sealed cavity to ensure data repeatability and convenient operation of the object under test. Therefore, after controlling the sound pickup device to collect the operating sound of the object under test in each test location area, the abnormal sound detection method in this embodiment further includes: controlling the slider in the moving device to move to the initial preset position of the soundproof sealed cavity. It should be noted that the initial preset position can be adaptively adjusted according to actual needs, such as the highest point of the center of the soundproof sealed cavity (i.e., the soundproof box), to facilitate the placement and removal of the test sample.

[0121] Step S703: Determine the abnormal sound detection result of the object to be detected based on the running sound of the object in each detection location area.

[0122] Specifically, step S703 includes:

[0123] Step S7031: Generate a corresponding power spectral density function based on the running sound of each detection location area, and calculate the power of the corresponding detection location area based on the power spectral density function.

[0124] It should be noted that the power spectral density function describes the distribution of signal power with frequency. In this embodiment, the specific method of generating the power spectral density function is not limited and can be determined by referring to conventional implementations in the art. For example, after acquiring an audio signal, it is digitized, denoised using a relevant filter such as a low-pass filter, and then a fast Fourier transform is performed on the denoised data to obtain the power spectral density function; this is only an example. Furthermore, the power spectral density function can be integrated in the frequency domain to determine the corresponding power; that is, the area under the power spectral density function curve is the power of the corresponding frequency band.

[0125] Step S7032: Superimpose each power onto the corresponding area to be detected to obtain the spectrogram of the object to be detected.

[0126] It should be noted that a spectrogram, as a tool for visualizing the changes in frequency components of a sound signal over time, transforms abstract sound waves into intuitive two-dimensional or three-dimensional images by showing the relationship between time, frequency, and amplitude (energy) of sound. Here, time represents the duration of the sound signal; frequency represents the frequency components contained in the sound, such as low, mid, and high frequencies; and color / grayscale represents the signal amplitude (energy) at the corresponding time-frequency point. The darker the color or the higher the brightness, the stronger the energy.

[0127] Step S7033: When the power in the spectrogram exceeds the preset power threshold, it is determined that there is an abnormal sound in the object to be detected.

[0128] It should be noted that the specific value of the preset power threshold in this embodiment is not limited and can be adjusted adaptively according to actual needs. For example, the preset power threshold may be determined through offline calibration, or it may be determined based on the noise in the test environment. This is only an example.

[0129] In this embodiment, when it is determined that an abnormal sound exists on the object to be detected, the specific location of the abnormal sound is also determined to identify and locate the abnormal sound on the object to be detected. Therefore, when there is a power exceeding a preset power threshold in the spectrogram, the abnormal sound detection method in this embodiment further includes marking the corresponding detection location area where the power exceeds the preset power threshold to determine the location of the abnormal sound on the object to be detected. Specifically, this embodiment not only achieves accurate identification of abnormal sounds, but also allows for intuitive and rapid location of the abnormal sound on the object to be detected.

[0130] In one specific embodiment, the object to be inspected is taken as the PCBA (containing various electronic components sealed) corresponding to the central control unit of an automobile. In practical applications, traditional inspection methods require manual disassembly and investigation after abnormal noise is detected (taking approximately 15-20 minutes). The "abnormal noise detection + location" method in this embodiment can greatly reduce the investigation time and significantly improve the efficiency of component rework. Specifically, in this embodiment, by combining the image coordinate system and acoustic power distribution, a geographically marked "abnormal noise heat map" can be further generated (e.g., using different colors to mark areas with excessive power), realizing the visualization of defect locations and avoiding blind repairs based on "gut feeling".

[0131] Step S7034: If there is no power exceeding the preset power threshold in the spectrogram, it is determined that there is no abnormal sound in the object to be detected.

[0132] In this embodiment of the invention, by running the power spectral density function of sound, specific frequency components of sound can be accurately captured to improve the recognition accuracy of abnormal sounds. Furthermore, by superimposing the power of each region to be detected to obtain a spectrogram, testers can quickly locate the specific location of power anomalies, enabling rapid identification and localization of abnormal sounds. This avoids the subjectivity and ambiguity of traditional manual sound detection, greatly improving the accuracy, efficiency, and automation level of abnormal sound detection.

[0133] Step S704: Display the abnormal sound detection results, and / or generate a corresponding detection report based on the abnormal sound detection results and the spectrogram, and display and / or save the detection report.

[0134] In this embodiment of the invention, by visually displaying the abnormal sound detection results and generating a corresponding detection report, the abnormal sound detection results of the object to be detected can be presented intuitively and comprehensively.

[0135] In one specific embodiment, based on Figure 3 The diagram illustrates the structure of an abnormal noise detection device and provides a corresponding workflow for abnormal noise detection. Figure 8 This is a flowchart of the abnormal sound detection process. (By...) Figure 8 It can be seen that the specific workflow includes:

[0136] Step S801: Place the object to be tested on the test platform, set the test parameters, and identify the valid test area.

[0137] In this embodiment, the abnormal noise detection device is correctly connected and started. Simultaneously, the testing software in the main device is opened (i.e., dedicated testing software used to identify the 3D image of the object to be tested, generate moving coordinate points, drive the microphone to collect sound at each coordinate point, generate a power + frequency spectrogram, and determine the detection result based on the comparison of the sound power in the spectrogram with a set threshold, marking the points where the sound exceeds the standard, i.e., the coordinate points where abnormal noise exists). Note that after the device starts, the slider with the structured light camera and microphone in the soundproof box will automatically move to the position at coordinates (Xmid, Ymid, Zmax). This position is the highest point at the center of the soundproof box, facilitating the placement of the test object. Then, the object to be tested is placed within the testable area of ​​the three-coordinate moving platform in the soundproof box, and the soundproof box door is closed. Before testing in this embodiment, if the default parameters (such as grid size, noise threshold, etc.) cannot meet the testing requirements, it is necessary to set relevant parameters, such as grid size and noise exceeding the standard threshold, to meet the set testing requirements.

[0138] Step S802: Grid the valid test area map and generate motion trajectories.

[0139] In this embodiment, by clicking "Test Area Recognition" on the software interface, the main device will use a structured light camera to acquire three-dimensional images of the soundproof box. Then, it will automatically identify the border of the object to be detected from these images, calculate the size of the border, and output a valid test area map. Simultaneously, the valid test area map is divided into grids according to the grid values ​​set in the first step. Figure 9 This is a diagram illustrating the regional division. For example... Figure 9 As shown, the grid size in the diagram is related to the test density; that is, the smaller the grid, the higher the test density, and vice versa. This grid size also represents the distance the microphone moves each time during testing. Then, a vertex of the valid test area map is automatically selected as the origin of the coordinate system, and an optimal motion trajectory is automatically generated. The coordinates of this trajectory are derived from the 3D data of the object to be detected.

[0140] Step S803: Based on the grid points and motion trajectory, sample the sound data and generate the single-point power spectral density function for each sound data point.

[0141] In this embodiment, after the above-mentioned meshing steps are completed, click "Start Test" on the software interface. The main device controls the slider equipped with the microphone to move to the origin of the coordinate system (i.e., the initial coordinate point in the motion trajectory, which can be the center point coordinate of the grid, or the coordinate of any vertex, or any specified coordinate within the grid). The sound is sampled at the first coordinate point to obtain the power spectral density of the first coordinate point; then it moves to the second coordinate point to sample the sound to obtain the power spectral density of the second coordinate point; this process is repeated until all grid points are covered, and finally the power spectral density of all grid points is obtained.

[0142] It is important to note that due to the inherent noise of the slider during its movement, the main device will not sample the sound until it stops at the corresponding grid coordinate point. Throughout the process, the display unit will show the power spectral density of each grid point in real time; the display unit will also show the microphone's motion trajectory diagram in real time.

[0143] Step S804: Based on the grid point positions, superimpose the measured power spectral density onto the test area map to obtain the acoustic spectrum, and use it for abnormal sound detection.

[0144] In this embodiment, after all grid points have been tested, the slider will automatically move to its initial position at coordinates (Xmid, Ymid, Zmax). Simultaneously, the main device will extract the maximum power point and its corresponding frequency for each grid point, and plot a semi-transparent color map. The colors can be represented by different shades of red, yellow, and green; the higher the power, the closer the color is to red, and the lower the power, the closer the color is to green. Then, the semi-transparent color map and the effective test area map identified in the first step are superimposed on the gridded coordinates to generate a spectrogram. The spectrogram is used for abnormal noise detection; if the power measured at a grid point exceeds the noise threshold set in the first step, an abnormal noise is detected at that coordinate point, and the point will be marked and its maximum power displayed. Furthermore, the main device in this embodiment also supports automatic test report generation, which will display the synthesized spectrogram. The main device also supports local image saving, report and image data export, and other functions of the main device can be adaptively adjusted according to actual needs.

[0145] In summary, the noise detection device and method of this invention can quickly and accurately identify the location, frequency, and power of the noise generated by the object under test, and are unaffected by the testing environment. This solves the problems of misjudgment and difficulty in locating noises caused by human or environmental factors. Applying it to the hardware testing of vehicle controllers allows for early detection and improvement of problems, significantly shortening the product development cycle.

[0146] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. An abnormal noise detection device, characterized in that, The device includes: a control device, a soundproof and sealed cavity, and a moving device, an image acquisition device, and a sound pickup device disposed within the soundproof and sealed cavity; The image acquisition device and the sound pickup device are mounted on the mobile device; The control device is communicatively connected to the mobile device, the image acquisition device, and the sound pickup device, respectively. After the object to be tested is placed in the soundproof and sealed cavity, the control device controls the image acquisition device to acquire the position image of the object to be tested, and divides the position image into regions to obtain several position regions of the object to be tested. The control device controls the mobile device to move to each detection location area, and controls the sound pickup device to collect the running sound of the object to be detected in each detection location area; The control device determines the abnormal sound detection result of the object under test based on the running sound of the object under test in each detection location area.

2. The abnormal noise detection device according to claim 1, characterized in that, The moving device includes a slider and a coupling, with an image acquisition device and a sound pickup device respectively disposed at the bottom of the slider; wherein, the coupling is used to drive the slider to move within the soundproof and sealed cavity.

3. The abnormal noise detection device according to claim 2, characterized in that, The coupling includes an X-axis coupling, a Y-axis coupling, and a Z-axis coupling; wherein, the X-axis coupling is slidably connected to the Z-axis coupling, the Z-axis coupling is screw-connected to the Y-axis coupling, the Y-axis coupling is slidably connected to a slider, and a test platform is provided on the plane where the X-axis coupling is located.

4. The abnormal noise detection device according to claim 1, characterized in that, The image acquisition device is a structured light camera, and / or the sound pickup device is a condenser microphone.

5. A method for detecting abnormal sounds, characterized in that, The control device applied in the noise detection device as described in any one of claims 1 to 4, the method comprising: After the object to be tested is placed in the soundproof and sealed cavity, the image acquisition device is controlled to acquire the position image of the object to be tested, and the position image is divided into regions to obtain several position regions of the object to be tested. The mobile device is controlled to move to each detection location area, and the sound pickup device is controlled to collect the running sound of the object under test in each detection location area; The abnormal sound detection result of the object under test is determined based on the running sound of the object under test in each detection location area.

6. The abnormal sound detection method according to claim 5, characterized in that, The control and movement device moves to each detection location area, including: Determine the starting region from each region to be detected; An optimal motion trajectory is generated based on the positional relationship between the starting region and the other regions to be detected, and the moving device is controlled to move accordingly from the starting region along the optimal motion trajectory.

7. The abnormal sound detection method according to claim 5, characterized in that, The step of determining the abnormal sound detection result of the object under test based on the running sound of the object under test in each detection location area includes: A corresponding power spectral density function is generated based on the running sound of each detection location area, and the power of the corresponding detection location area is calculated based on the power spectral density function. Each power is superimposed onto the corresponding area to be detected to obtain the spectrogram of the object to be detected; When the power in the spectrogram exceeds a preset power threshold, it is determined that the object to be detected has abnormal sound; If no power exceeds a preset power threshold in the acoustic spectrogram, it is determined that the object to be detected does not have any abnormal sounds.

8. The abnormal sound detection method according to claim 7, characterized in that, When a power in the spectrogram exceeds a preset power threshold, the method further includes: The corresponding detection area where the power exceeds the preset power threshold is marked to determine the location of the abnormal sound on the object to be detected.

9. The abnormal sound detection method according to claim 5, characterized in that, After the control sound pickup device collects the running sound of the object to be detected in each detection location area, the method further includes: The slider in the control device is moved to the initial preset position of the soundproof and sealed cavity.

10. The abnormal sound detection method according to claim 5, characterized in that, Before the controlled image acquisition device acquires the position image of the object to be detected, the method further includes: Set the test parameters for the object to be tested, and verify whether the test parameters meet the preset test requirements; When the parameters meet the preset test requirements, the step of controlling the image acquisition device to acquire the position image of the object to be detected is executed.

11. The abnormal sound detection method according to claim 7, characterized in that, After determining the abnormal sound detection result of the object to be detected based on the running sound of the object in each detection location region, the method further includes: Display the abnormal sound detection results, and / or generate a corresponding detection report based on the abnormal sound detection results and the spectrogram, and display and / or save the detection report.

Images