Abnormal noise source diagnosis system, method, medium, and product

Abstract

The application relates to the technical field of vehicle abnormal sound detection and diagnosis, in particular to an abnormal sound source diagnosis system and method, a medium and a product, wherein the system comprises: a phase module configured to collect at least one displacement signal of a target component of a vehicle; a vibration noise module configured to collect a vibration signal and an acoustic signal of the target component; and a processing unit configured to identify a plurality of phase windows in a displacement phase diagram according to the at least one displacement signal, determine the vibration signal and the acoustic signal in different phase windows, and diagnose an abnormal sound source of the target component according to the vibration signal and the acoustic signal in the different phase windows. Thus, the problems of strong subjectivity of experience judgment, fuzzy correlation between signal analysis results and actual mechanical states, and low diagnosis efficiency in the prior art are solved.

Description

Technical Field

[0001] This application relates to the field of vehicle abnormal noise detection and diagnosis technology, and in particular to an abnormal noise source diagnosis system, method, medium and product. Background Technology

[0002] Vehicle noise issues directly impact the quality of automotive noise, vibration, and acoustic roughness, as well as user experience, and are of significant engineering importance during vehicle development and validation. Therefore, the ability to quickly and accurately locate the source of noise and determine its specific mechanical condition under dynamic driving conditions is of significant engineering value.

[0003] Related technologies rely on engineers' experience to make judgments through real-vehicle road tests, which suffers from high subjectivity, poor repeatability, and difficulty in quantification. Alternatively, vibration sensors can be deployed and microphones can be used to collect vibration and acoustic signals for analysis to locate the abnormal noise component, but it is difficult to further determine the specific mechanical motion state in which the abnormal noise occurs. At the same time, for abnormal noises caused by dynamic gap changes, it is difficult to establish a stable correspondence between vibration and acoustic signals, resulting in unclear causal relationships and low diagnostic efficiency. Summary of the Invention

[0004] This application provides a diagnostic system, method, medium, and product for abnormal noise sources, in order to solve the problems of related technologies relying on experience-based judgment with strong subjectivity, unclear correlation between signal analysis results and actual mechanical conditions, and low diagnostic efficiency.

[0005] The first aspect of this application provides a diagnostic system for abnormal noise sources, including: a phase module for acquiring at least one displacement signal of a target component of a vehicle; a vibration and noise module for acquiring vibration signals and sound signals of the target component; and a processing unit for identifying multiple phase windows in the displacement phase diagram based on the displacement phase diagram of at least one displacement signal, determining the vibration signals and sound signals within different phase windows, and diagnosing the abnormal noise source of the target component based on the vibration signals and sound signals within different phase windows.

[0006] Optionally, in one embodiment of this application, the phase module includes at least one displacement sensor, one end of which is connected to the vehicle body and the other end of which is connected to the target component, for measuring the relative displacement between the target component and the vehicle body.

[0007] Optionally, in one embodiment of this application, the vibration noise module includes a vibration sensor and a microphone, which are arranged within a preset range of the target component. The vibration sensor collects the vibration signal of the target component, and the microphone collects the sound signal of the target component.

[0008] Optionally, in one embodiment of this application, the acquisition unit is connected to the phase module and the vibration noise module respectively, for synchronously acquiring displacement signals, vibration signals and sound signals.

[0009] A second aspect of this application provides a method for diagnosing abnormal noise sources. The method is applied to the processing unit of any of the above-described abnormal noise source diagnosis systems and includes the following steps: acquiring at least one displacement signal, vibration signal, and sound signal of a target component of a vehicle; identifying multiple phase windows in the displacement phase diagram based on the displacement phase diagram of at least one displacement signal, and acquiring vibration signals and sound signals within different phase windows; and diagnosing the abnormal noise source of the target component based on the vibration signals and sound signals within the phase windows.

[0010] Optionally, in one embodiment of this application, diagnosing the source of abnormal noise in a target component based on vibration and sound signals within a phase window includes: extracting vibration spectrum features of the vibration signal and acoustic features of the sound signal; and diagnosing the source of abnormal noise in the target component based on the vibration spectrum features and acoustic features.

[0011] Optionally, in one embodiment of this application, diagnosing the source of abnormal noise in a target component based on vibration spectrum characteristics and acoustic characteristics includes: identifying the phase window where the abnormal noise occurs based on vibration spectrum characteristics and acoustic characteristics; analyzing the mechanical characteristics corresponding to the phase window where the abnormal noise occurs based on the displacement phase diagram; determining the vibration direction based on the vibration spectrum characteristics corresponding to the phase window where the abnormal noise occurs; and diagnosing the source of abnormal noise in the target component based on the mechanical characteristics and vibration direction.

[0012] Optionally, in one embodiment of this application, acquiring vibration signals and sound signals within different phase windows includes: associating vibration signal and sound signal phase windows according to the acquisition time; and determining vibration signals and sound signals within different phase windows based on the associated data.

[0013] A third aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the abnormal noise source diagnosis method as described in the above embodiments.

[0014] A fifth aspect of this application provides a computer program that, when executed, is used to implement the abnormal noise source diagnosis method as described in the above embodiments.

[0015] Therefore, this application has the following beneficial effects: First, the phase module is used to acquire at least one displacement signal of the target component of the vehicle to obtain information on the dynamic relative displacement change of the target component during operation, thereby providing basic data support for subsequent mechanical state division. Using displacement signals as the basis, a physically meaningful motion representation is constructed, improving the observability of the target component's motion state. Second, the vibration and noise module is used to acquire vibration and sound signals of the target component to obtain information on the structural vibration response and acoustic response generated by the target component during movement, achieving synchronous acquisition of vibration and acoustic information and providing a multi-dimensional signal basis for abnormal noise characteristic analysis. Then, the processing unit constructs a displacement phase diagram based on at least one displacement signal and identifies multiple phase windows in the displacement phase diagram, thereby dividing the continuous displacement change process into different mechanical motion state intervals. Further, the corresponding vibration and sound signals within different phase windows are determined, and the abnormal noise source of the target component is diagnosed and analyzed based on the vibration and sound signals within different phase windows. By associating time-domain signals with mechanical phase windows, the correspondence between vibration, acoustic signals, and specific mechanical motion states is established, thereby improving the pertinence and accuracy of abnormal noise analysis. This solves the problems of reliance on experience-based judgment, strong subjectivity, unclear correlation between signal analysis results and actual mechanical conditions, and low diagnostic efficiency in related technologies.

[0016] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0017] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is an example diagram of an abnormal noise source diagnostic system according to an embodiment of this application; Figure 2 This is a diagram illustrating the overall architecture of the abnormal noise source diagnostic system according to an embodiment of this application. Figure 3 This is a flowchart of an abnormal noise source diagnosis method according to an embodiment of this application; Figure 4 This is a schematic diagram of a mechanical state window based on displacement phase division according to an embodiment of this application; Figure 5 This is a flowchart illustrating the specific steps of the abnormal noise source diagnosis method according to an embodiment of this application. Detailed Implementation

[0018] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0019] The following description, with reference to the accompanying drawings, describes an abnormal noise source diagnostic system, method, medium, and product according to embodiments of this application. Addressing the problems mentioned in the background art, this application provides an abnormal noise source diagnostic system. In this system, firstly, a phase module is used to acquire at least one displacement signal of a target component of a vehicle to obtain dynamic relative displacement change information of the target component during operation, thereby providing basic data support for subsequent mechanical state classification. The displacement signal is used as the basis to construct a physically meaningful motion representation, improving the observability of the target component's motion state. Secondly, a vibration and noise module is used to acquire vibration and sound signals of the target component to obtain structural vibration response and acoustic response information generated by the target component during movement, realizing the integration of vibration and acoustic information. Synchronous acquisition provides a multi-dimensional signal foundation for abnormal noise characteristic analysis. Then, the processing unit constructs a displacement phase map based on at least one displacement signal and identifies multiple phase windows within the map, thereby dividing the continuous displacement change process into different mechanical motion state intervals. Further, it determines the corresponding vibration and sound signals within different phase windows and performs diagnostic analysis on the abnormal noise source of the target component based on these signals. By correlating time-domain signals with mechanical phase windows, a correspondence between vibration, acoustic signals, and specific mechanical motion states is established, thus improving the targeting and accuracy of abnormal noise analysis. This solves the problems of related technologies relying on experience-based judgment with high subjectivity, unclear correlation between signal analysis results and actual mechanical states, and low diagnostic efficiency.

[0020] The abnormal noise source diagnostic system proposed according to an embodiment of this application is described with reference to the accompanying drawings.

[0021] Figure 1 This is a block diagram of an abnormal noise source diagnosis system according to an embodiment of this application.

[0022] like Figure 1 As shown, the abnormal noise source diagnostic system 10 includes: a phase module 100, a vibration and noise module 200, and a processing unit 300.

[0023] The phase module 100 is used to acquire at least one displacement signal of the target component of the vehicle; the vibration and noise module 200 is used to acquire vibration and sound signals of the target component; and the processing unit 300 is used to identify multiple phase windows in the displacement phase diagram based on the displacement phase diagram of at least one displacement signal, determine the vibration and sound signals in different phase windows, and diagnose the abnormal noise source of the target component based on the vibration and sound signals in different phase windows.

[0024] The phase module 100 is a functional module for acquiring displacement signals of the target component, and in this application represents a unit for acquiring basic data on the phase of mechanical motion. The vibration and noise module 200 is a functional module for acquiring vibration and sound signals of the target component, and in this application represents a unit for acquiring vibration and acoustic data related to abnormal noise. The processing unit 300 is a functional module for processing and analyzing the displacement signal, vibration signal, and sound signal, and in this application represents a core analysis unit for identifying phase windows and diagnosing abnormal noise sources. The displacement signal is a spatial position change signal acquired by a displacement sensor, and in this application represents the dynamic displacement information of the target component relative to a reference datum. The vibration signal is a signal acquired by a vibration sensor, and in this application represents the vibration characteristic information of the target component. The sound signal is a signal acquired by a microphone, and in this application represents the acoustic characteristic information generated by the target component.

[0025] It is understandable that by uniformly collecting and processing the displacement signal, vibration signal and sound signal of the target component, the mechanical motion state and abnormal noise phenomenon can be effectively correlated. In this application, the originally continuous and difficult-to-analyze dynamic process can be divided into phase windows with clear engineering significance, thereby significantly improving the accuracy and efficiency of abnormal noise source location.

[0026] In one embodiment of this application, the phase module 100 includes at least one displacement sensor, one end of which is connected to the vehicle body and the other end of which is connected to the target component, for measuring the relative displacement between the target component and the vehicle body.

[0027] In this application, a displacement sensor is a sensor used to measure changes in the position of an object, and in this application, it represents a detection element used to acquire the relative displacement between a target component and the vehicle body; a target component is a component in a vehicle that has relative motion, and in this application, it represents an object whose displacement is being measured and which may produce abnormal noise; relative displacement is the amount of position change between two objects, and in this application, it represents the dynamic displacement change of the target component relative to the vehicle body.

[0028] It is understandable that by connecting displacement sensors to the vehicle body and the target component respectively, the relative displacement signal between the two can be directly obtained, and the measurement results can be based on the vehicle body as a stable reference benchmark. This avoids the problem of uncertainty in the motion reference of a single component, improves the accuracy of displacement data, and provides reliable basic data support for subsequent mechanical motion phase division and phase window recognition.

[0029] The phase module 100 of this application embodiment includes at least one displacement sensor. One end of the displacement sensor is connected to the vehicle body, and the other end of the displacement sensor is connected to the target component. In this application, it is used to acquire the dynamic relative displacement signal of the target component relative to the vehicle body, thereby characterizing the position change state of the target component during the motion process, so that the relative displacement signal can be used as the basic data source for subsequent mechanical motion phase analysis.

[0030] In one embodiment of this application, the vibration noise module 200 includes a vibration sensor and a microphone, which are arranged within a preset range of the target component. The vibration sensor collects the vibration signal of the target component, and the microphone collects the sound signal of the target component.

[0031] Among them, the vibration sensor is a sensor used to detect the vibration state of an object, and in this application, it represents a detection element used to collect vibration signals of a target component; the preset range is a spatial area set according to the installation position of the target component and the propagation characteristics of abnormal noise, and in this application, it represents an arrangement area used to ensure effective collection of vibration and acoustic signals.

[0032] It is understandable that by synchronously arranging vibration sensors and microphones within a preset range of the target component, the structural vibration signal and the airborne sound signal can be acquired simultaneously. This allows for the simultaneous acquisition of structural response information and acoustic performance information of abnormal noises, improving the integrity and complementarity of abnormal noise characteristic information, enhancing the reliability of subsequent frequency domain analysis and feature recognition, and helping to more accurately distinguish the sources of different types of abnormal noises.

[0033] In one embodiment of this application, the vibration noise module 200 includes a vibration sensor and a microphone. The vibration sensor and microphone are used to acquire corresponding vibration and sound information when a target component moves or generates abnormal noise, thereby forming a multi-dimensional perception of the abnormal noise phenomenon. The vibration sensor is used to collect structural vibration signals of the target component to characterize its mechanical vibration characteristics; the microphone is used to collect sound signals generated by the target component to characterize the acoustic characteristics of the abnormal noise at the airborne propagation level. Through the above arrangement, this embodiment of the application enables the vibration and sound signals to be acquired synchronously near the target component, thereby providing basic data support for subsequent abnormal noise characteristic analysis and abnormal noise source diagnosis.

[0034] In one embodiment of this application, the acquisition unit is connected to the phase module 100 and the vibration noise module 200 respectively, and is used to synchronously acquire displacement signals, vibration signals and sound signals.

[0035] Synchronous acquisition refers to the process of simultaneously acquiring or time-aligning signals from different sources under a unified time reference. In this application, it represents an acquisition method that ensures consistent time correspondence between various types of signals.

[0036] Understandably, by synchronously acquiring displacement, vibration, and sound signals under a unified time reference through the acquisition unit, the strict alignment of multi-source signals in the time dimension is ensured. This guarantees the accurate and reliable correspondence between subsequent phase window division and vibration spectrum characteristics and acoustic characteristics, avoids misjudgment problems caused by time deviation, and improves the accuracy of correlation analysis between abnormal noise events and mechanical motion state.

[0037] In this application, the unit for synchronously acquiring and processing multi-source signals functions to collect and record displacement signals, vibration signals, and sound signals from different types of sensors under a unified time reference. This ensures the consistency of the correspondence between various signals in the time dimension, enabling effective correlation analysis between different signals. This synchronous acquisition method avoids data deviation problems caused by inconsistent sampling timing, making subsequent time-based segmented analysis and feature extraction more accurate and reliable, and providing a consistent data foundation for the correspondence analysis between abnormal noise phenomena and mechanical motion states.

[0038] Therefore, the overall architecture of the abnormal noise source diagnostic system 10 in this application embodiment is as follows: Figure 2 As shown, it includes the vehicle under test, phase module 100, auxiliary noise module, acquisition unit and processing unit 300.

[0039] The vehicle under test, as the test object, is used to generate operating status signals under target operating conditions. The phase module 100 is used to acquire at least one displacement signal from the target component of the vehicle under test. The auxiliary noise module is used to acquire vibration and sound signals from the target component, and includes a vibration sensor and a microphone. The acquisition unit is connected to both the phase module 100 and the auxiliary noise module to synchronously acquire and summarize various signals. The processing unit 300 is connected to the acquisition unit to receive multi-source signal data output by the acquisition unit, construct a displacement-phase diagram based on the displacement signals, identify multiple phase windows in the phase diagram, extract the corresponding vibration and sound signals within different phase windows, and perform abnormal noise diagnosis analysis based on the signals, thereby identifying the source of abnormal noise in the target component of the vehicle under test.

[0040] According to the abnormal noise source diagnostic system proposed in this application, firstly, a phase module is used to collect at least one displacement signal of the target component of the vehicle to obtain dynamic relative displacement change information of the target component during operation, thereby providing basic data support for subsequent mechanical state division. The displacement signal is used as the basis to construct a physically meaningful motion representation, improving the observability of the target component's motion state. Secondly, a vibration and noise module is used to collect vibration and sound signals of the target component to obtain structural vibration response and acoustic response information generated by the target component during movement, realizing the synchronous acquisition of vibration and acoustic information and providing a multi-dimensional signal basis for abnormal noise characteristic analysis. Then, the processing unit constructs a displacement phase diagram based on at least one displacement signal and identifies multiple phase windows in the displacement phase diagram, thereby dividing the continuous displacement change process into different mechanical motion state intervals. Further, the corresponding vibration and sound signals within different phase windows are determined, and the abnormal noise source of the target component is diagnosed and analyzed based on the vibration and sound signals within different phase windows. By associating the time-domain signal with the mechanical phase window, the correspondence between vibration, acoustic signals, and specific mechanical motion states is established, thereby improving the pertinence and accuracy of abnormal noise analysis. This solves the problems of reliance on experience-based judgment, strong subjectivity, unclear correlation between signal analysis results and actual mechanical conditions, and low diagnostic efficiency in related technologies.

[0041] Secondly Figure 3 This is a flowchart of a method for diagnosing abnormal noise sources provided in an embodiment of this application.

[0042] like Figure 3 As shown, the abnormal noise source diagnosis method includes the following steps: In step S101, at least one displacement signal, vibration signal, and sound signal of the target component of the vehicle are acquired.

[0043] Understandably, by acquiring displacement, vibration, and sound signals of the target component, multi-dimensional information on mechanical motion and abnormal noise phenomena can be acquired simultaneously. This provides a complete and relevant data foundation for subsequent phase construction, phase window division, and feature analysis, thereby ensuring that the abnormal noise source diagnosis process has sufficient data support and improving the accuracy and reliability of the analysis results.

[0044] In one embodiment of this application, acquiring at least one displacement signal, vibration signal, and sound signal of a target component of a vehicle includes planning and arranging corresponding sensors at measurement points of the target component. Specifically, for the chassis suspension system, this application uses displacement sensors to measure the vertical displacement of the wheel center or lower control arm position relative to the subframe or body, which is used to characterize motion states such as upward bounce, compression, downward bounce, and rebound. For the door or tailgate system, this application uses displacement sensors to measure its normal displacement relative to the door opening, which is used to characterize motion states such as being squeezed and being pulled open.

[0045] Meanwhile, in this embodiment, vibration sensors and microphones are arranged near the target component to obtain vibration and sound signals at the corresponding locations; and through dynamic road testing and data acquisition, the vehicle is put into a dynamic operating state during actual vehicle driving by simulating road conditions or abnormal noise test surfaces, and the displacement signal, vibration signal and sound signal full-time domain data are collected simultaneously, thereby providing basic data for subsequent time-related phase analysis and abnormal noise diagnosis.

[0046] In step S102, based on the displacement phase diagram of at least one displacement signal, multiple phase windows in the displacement phase diagram are identified, and vibration signals and sound signals within different phase windows are obtained.

[0047] Among them, the displacement phase diagram is a graphical representation of the motion state of the target component constructed based on the displacement signal and its change characteristics. In this application, it represents the data form reflecting the relationship between the mechanical motion phase and the change of time. The phase window is a time interval divided according to the displacement signal and its derivative change characteristics. In this application, it represents the analysis interval corresponding to a specific mechanical motion state.

[0048] Understandably, by identifying multiple phase windows based on displacement phase diagrams and extracting the corresponding vibration and sound signals within each phase window, continuous time-domain data is segmented and mapped according to mechanical motion states. This establishes a clear correspondence between abnormal noise phenomena and specific mechanical states, thereby effectively narrowing the analysis scope, highlighting key instantaneous features, improving the targeting and accuracy of feature extraction, and significantly enhancing the efficiency and reliability of abnormal noise source diagnosis.

[0049] In one embodiment of this application, acquiring vibration signals and sound signals within different phase windows includes: associating vibration signal and sound signal phase windows according to the acquisition time; and determining vibration signals and sound signals within different phase windows based on the associated data.

[0050] Among them, the acquisition time is the time identifier corresponding to various signals during the acquisition process; the association is the process of matching and aligning data from different sources based on the time identifier, which in this application represents the operation process of mapping vibration signals and sound signals to phase windows; the associated data is a set of multi-source signal data after time matching is completed, which in this application represents vibration signal and sound signal data with a unified time relationship established.

[0051] Understandably, by associating vibration and sound signals with phase windows based on acquisition time, precise alignment of multi-source signals in the time dimension can be achieved, ensuring a strict one-to-one correspondence between the data extracted within each phase window. This avoids feature mismatch issues caused by time deviations and improves the accuracy and consistency of data slicing.

[0052] This application embodiment analyzes the displacement signal and defines and marks multiple characteristic mechanical phase windows as the basis for subsequent signal correlation and data slicing. In this application embodiment, the identification of the characteristic mechanical phase windows is based on real-time or offline analysis of the raw displacement signal output by the wire-type displacement sensor. The raw displacement signal is a continuously changing numerical sequence over time, denoted as... This represents the dynamic displacement of a moving part relative to a reference datum. Through mathematical calculation, it can be derived from... Two physical quantities are derived from this: velocity and acceleration. Where velocity is... It reflects the rate and direction of displacement change; acceleration is This reflects the changing trend of the force. Based on the above three signals (displacement, velocity, and acceleration), different characteristic phase windows can be defined.

[0053]

[0054] For example, in one embodiment of this application, such as Figure 4 As shown, this application divides the motion process based on the changing trend of the displacement signal and its velocity characteristics in order to identify multiple key phase intervals.

[0055] Window A is the upward jump vertex window, and its identification condition is: displacement signal. The characteristic of reaching a local maximum, and the speed It changes from positive to negative and approaches zero; The specific algorithm is as follows: 1. Detect all local peak points of the displacement signal, satisfying:

[0056] 2. At this peak point, verify: ( (The speed threshold is close to zero) 3. Using this peak point as the center, extend forward and backward by a fixed time. (e.g., 0.05 seconds) to form a time window.

[0057] Window B is the bottom point window for the jump, and its identification condition is: displacement signal. Reaching a local minimum, and the speed It changes from negative to positive and approaches zero; The specific algorithm is as follows: 1. Detect all local valley points of the displacement signal, satisfying:

[0058] 2. At this valley point, verify:

[0059] 3. Using this valley point as the center, extend a fixed time forward and backward. This creates a time window.

[0060] Window C is the high-speed over-equilibrium point window, and its identification condition is: displacement signal. Passing through the zero point (equilibrium position), and the speed The absolute value is relatively large; The specific algorithm is as follows: 1. Detect the zero-crossing point of the displacement signal: satisfying... The moment ; 2. Near the zero point (e.g.) Calculate the average velocity within 0.01 seconds before and after the event. ； 3. If | |> ( If a preset high-speed threshold (e.g., 50 mm / s) is used, then the time interval in which the zero-crossing point is located is marked as window C. 4. Using this zero-crossing point as the center, extend forward and backward by a smaller time interval. This forms a window.

[0061] Window D is the displacement over-limit window, and its identification condition is: the absolute value of the displacement exceeds the preset engineering safety threshold; The specific algorithm is as follows: 1. Two preset thresholds: upper limit threshold and lower threshold (For example, the suspension system can be set to +15mm and -15mm). 2. Continuously scan the displacement signal and mark all signals that meet the requirements. or Time interval; 3. Each consecutive time period exceeding the limit constitutes an independent window D; 4. Optionally, a short buffer period can be added before and after the buffer period. (e.g., 0.01 seconds) to avoid the truncation effect.

[0062] After completing the phase window division and marking, this application associates the vibration signal and sound signal with the corresponding phase window based on the acquisition time of each signal, and extracts the vibration signal and sound signal in different phase windows accordingly, thereby realizing data segmentation and corresponding analysis based on mechanical motion state.

[0063] In step S103, the source of abnormal noise in the target component is diagnosed based on the vibration signal and sound signal within the phase window.

[0064] Understandably, by performing synchronous feature analysis on vibration and sound signals within a phase window, the abnormal noise diagnosis process is limited to a specific mechanical motion state, thereby reducing interference from unrelated operating condition signals and improving the separability of abnormal features. At the same time, by utilizing the differences between vibration spectrum features and acoustic features under different phase windows, the corresponding judgment of the abnormal noise occurrence conditions and triggering motion states can be realized, transforming the location of the abnormal noise source from an overall time domain judgment to a conditional judgment based on local mechanical states.

[0065] In one embodiment of this application, diagnosing the source of abnormal noise in a target component based on vibration and sound signals within a phase window includes: extracting vibration spectrum features of the vibration signal and acoustic features of the sound signal; and diagnosing the source of abnormal noise in the target component based on the vibration spectrum features and acoustic features.

[0066] Among them, vibration spectrum features are feature information obtained after frequency domain or time-frequency domain transformation of vibration signals, and in this application, they represent the vibration energy distribution and frequency composition characteristics of the target component under a specific mechanical state; acoustic features are feature information obtained by analyzing sound signals, and in this application, they represent the sound frequency composition and intensity distribution characteristics of the target component under a specific mechanical state; extraction in this application represents the operation process of obtaining frequency domain or time-frequency domain analysis results from vibration signals and sound signals.

[0067] It is understandable that by performing frequency domain or time-frequency domain processing on the vibration signal and sound signal within the phase window respectively, the corresponding vibration spectrum features and acoustic features can be extracted, and the original time domain signal can be converted into a comparable feature expression, thereby highlighting the differences in frequency distribution and energy structure of different abnormal noise types.

[0068] In this embodiment, the vibration and sound signals corresponding to each marked phase window are extracted. The vibration and sound signals are data acquired synchronously. Based on this, the vibration and sound signals are subjected to time-frequency analysis processing, such as fast Fourier transform or wavelet transform, to obtain the vibration spectrum features and acoustic features corresponding to each phase window, and to provide feature data support for subsequent abnormal noise source diagnosis based on vibration spectrum features and acoustic features.

[0069] In one embodiment of this application, diagnosing the source of abnormal noise in a target component based on vibration spectrum characteristics and acoustic characteristics includes: identifying the phase window where the abnormal noise occurs based on vibration spectrum characteristics and acoustic characteristics; analyzing the mechanical characteristics corresponding to the phase window where the abnormal noise occurs based on a displacement phase diagram; determining the vibration direction based on the vibration spectrum characteristics corresponding to the phase window where the abnormal noise occurs; and diagnosing the source of abnormal noise in the target component based on the mechanical characteristics and vibration direction.

[0070] Among them, mechanical features are the motion state information of the target component corresponding to the phase window, which in this application represents the specific motion form of the target component within the phase window; vibration direction is the main energy propagation direction of the vibration signal in the spatial coordinate system, which in this application represents the main force or vibration propagation direction when the target component makes abnormal noise; diagnosis in this application represents the analysis operation of determining the source of abnormal noise based on mechanical features and vibration direction.

[0071] It is understood that the embodiments of this application first identify the phase window where abnormal noise occurs based on vibration spectrum characteristics and acoustic characteristics, so as to accurately locate the time of occurrence of abnormal noise and mechanical motion state, thereby limiting the diagnostic range to specific phase conditions; further, the mechanical motion characteristics corresponding to the phase window are analyzed in combination with displacement phase diagram, so that the abnormal noise signal is associated with specific motion state (such as compression, rebound or high-speed zero-crossing motion); at the same time, the vibration direction information is determined based on the vibration spectrum characteristics within the phase window, thereby introducing the dimension of spatial force or vibration propagation direction; finally, by fusing mechanical characteristics and vibration direction information, the abnormal noise source is determined by the coordination of multi-dimensional information such as "time characteristics, motion state and spatial direction".

[0072] In one embodiment of this application, based on the vibration spectrum characteristics and acoustic characteristics within each phase window, different phase windows are compared and analyzed to identify the phase window where abnormal noise occurs, and the mechanical characteristics corresponding to the phase window are analyzed in conjunction with the displacement phase diagram.

[0073] Specifically, if abnormal high-frequency vibrations or impact-like acoustic features only appear significantly in the upper jump vertex window, it indicates that the abnormal noise may originate from interference or impact occurring in the target component under maximum compression. If friction-like acoustic features (such as a scream at a specific frequency) mainly appear in the high-speed over-equilibrium point window, it indicates that the abnormal noise may originate from frictional self-excitation of the target component during high-speed relative motion. If abnormal noises are detected in multiple phase windows but the corresponding vibration spectrum features and acoustic features are different, it indicates that there may be multiple sources of abnormal noise or complex coupling mechanisms.

[0074] Based on this, the vibration direction information is further determined according to the vibration spectrum characteristics within the phase window, and combined with mechanical characteristics, the abnormal noise source of the target component is comprehensively diagnosed, thereby achieving accurate determination of the location of the abnormal noise and its mechanism of action.

[0075] This application acquires displacement signals of target components using displacement sensors and constructs mechanical motion phases and phase windows based on these signals. This discretizes the continuous dynamic process into several mechanical state slices with clear engineering significance, transforming the analysis target from the overall time axis into local analysis within several key phase windows. Based on the phase windows, vibration and sound signals are correlated and analyzed to establish a one-to-one correspondence between abnormal noise phenomena and corresponding mechanical motion states. This enables rapid and accurate diagnosis of abnormal noise sources, effectively solving the problems of unclear causal relationships between abnormal noise phenomena and mechanical motion states, as well as low diagnostic efficiency in existing technologies.

[0076] The following example illustrates the situation where an electric vehicle experiences abnormal noises from its chassis when traversing a torsional road surface.

[0077] Regarding sensor arrangement, this application installs displacement sensors between the lower control arm on the right front and right rear of the vehicle and the vehicle body to measure the vertical relative displacement of the lower control arm relative to the vehicle body; at the same time, vibration sensors are arranged at the lower control arm, the upper suspension position of the shock absorber, and the spring position to collect vibration signals at the corresponding positions.

[0078] After data acquisition, the displacement signal is analyzed to construct the mechanical motion phase and identify the upper jump vertex window and the lower jump bottom point window. The upper jump vertex window corresponds to the stage when the suspension compresses to its extreme value when the vehicle crosses the bump, and the lower jump bottom point window corresponds to the stage when the vehicle rebounds to its extreme position after landing.

[0079] Further analysis of the vibration signals within each phase window revealed that the abnormal high-impact vibration spectrum characteristics only appeared in the bottom jump window. Combined with the displacement curve, it was found that the suspension exhibited obvious excessive rebound during this stage.

[0080] Based on the above analysis, it is determined that the abnormal noise does not occur during the compression process, but rather at the rebound limit position, corresponding to the motion state when the spring is stretched to its maximum stroke. Therefore, it can be concluded that the abnormal noise originates from a mismatch between the spring and the shock absorber, resulting in internal impact when the spring is stretched to its highest point and at a high speed, thus causing a knocking-like noise.

[0081] To address this issue, the matching relationship between the spring and the damper can be improved by adjusting the spring parameters, such as reducing the free length of the spring or optimizing the stiffness characteristics, thereby suppressing excessive rebound and eliminating abnormal noise.

[0082] In summary, the abnormal noise source diagnosis method of this application embodiment is as follows: Figure 5 As shown: In step S201, measurement point planning and sensor placement are performed. Specifically, displacement sensors are placed between the vehicle body and the moving part to be measured to acquire the dynamic relative displacement signal between them; at the same time, vibration sensors and acoustic sensors are placed in the suspected abnormal noise area to collect vibration signals and acoustic signals, thereby constructing a multi-source data acquisition system. In step S202, dynamic road testing and synchronous data acquisition are performed. The vehicle is run under preset test conditions, and displacement signals, vibration signals, and acoustic signals are acquired synchronously. The time alignment of each signal is achieved through a multi-channel synchronous acquisition device to obtain synchronous multi-source data. In step S203, the mechanical phase window is defined and marked. Displacement and velocity are calculated based on the displacement signal, and the mechanical phase window is divided according to the displacement extreme value, zero crossing and over-limit characteristics, including upper extreme value window, lower extreme value window, zero crossing high speed window and over-limit window; In step S204, data slicing and correlation analysis based on mechanical phase windows are performed. Vibration and acoustic signals are sliced ​​according to mechanical phase windows, and vibration and acoustic characteristic parameters within each window are extracted to achieve correlation analysis between phase and abnormal noise characteristics. In step S205, the root cause diagnosis of abnormal noise is performed. Based on the differences in vibration and acoustic characteristics within different mechanical phase windows, the mechanical motion state corresponding to the abnormal noise is determined, and the source component and generation mechanism of the abnormal noise are located by combining the characteristic information.

[0083] It should be noted that the foregoing explanation of the embodiment of the abnormal noise source diagnosis system also applies to the abnormal noise source diagnosis method of this embodiment, and will not be repeated here.

[0084] According to the abnormal noise source diagnosis method proposed in this application, firstly, at least one displacement signal, vibration signal, and sound signal of the target component of the vehicle are acquired to obtain displacement change information, structural vibration response information, and acoustic response information of the target component during operation, thereby providing multi-source basic data support for subsequent abnormal noise analysis and making the characterization of the target component's operating state more comprehensive; secondly, a displacement phase diagram is constructed based on the displacement signal, and multiple phase windows in the displacement phase diagram are identified. By dividing the continuous displacement change process into mechanical state intervals with clear physical meaning, a structured expression of the target component's motion process is realized, and the corresponding vibration and sound signals in different phase windows are further extracted, so that vibration and acoustic information can establish a correspondence with specific mechanical motion states; then, the vibration and sound signals in the phase windows are analyzed to diagnose and identify the abnormal noise source of the target component. By comparing and analyzing the vibration spectrum characteristics and acoustic characteristics under different mechanical phase conditions, the pertinence and accuracy of abnormal noise feature identification are improved, thereby enhancing the reliability of abnormal noise location and mechanism judgment. This enables multi-source signal correlation analysis and abnormal noise diagnosis based on mechanical phase, solving problems such as strong subjectivity due to reliance on experience-based judgment, ambiguous correlation between signal analysis results and actual mechanical state, and low diagnostic efficiency in related technologies.

[0085] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method for diagnosing abnormal noise sources.

[0086] This application also provides a computer program product, including a computer program or instructions, which, when executed by a processor, implements the above-described method for diagnosing abnormal noise sources.

[0087] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0088] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0089] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0090] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any of the following techniques known in the art, or a combination thereof: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (FPGAs), field-programmable gate arrays (FPGAs), etc.

[0091] Those skilled in the art will understand that all or part of the steps of the methods implementing the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0092] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A diagnostic system for abnormal noise sources, characterized in that, include: A phase module is used to acquire at least one displacement signal of a target component of the vehicle; A vibration and noise module is used to collect vibration and sound signals of the target component; The processing unit is configured to identify multiple phase windows in the displacement phase diagram based on at least one displacement signal displacement phase diagram, determine vibration signals and sound signals within different phase windows, and diagnose the source of abnormal noise of the target component based on the vibration signals and sound signals within different phase windows.

2. The abnormal noise source diagnostic system according to claim 1, characterized in that, The phase module includes at least one displacement sensor, one end of which is connected to the vehicle body and the other end of which is connected to the target component, for measuring the relative displacement between the target component and the vehicle body.

3. The abnormal noise source diagnostic system according to claim 1, characterized in that, The vibration noise module includes a vibration sensor and a microphone, which are arranged within a preset range of the target component. The vibration sensor collects the vibration signal of the target component, and the microphone collects the sound signal of the target component.

4. The abnormal noise source diagnostic system according to claim 1, characterized in that, Also includes; The acquisition unit is connected to the phase module and the vibration noise module respectively, and is used to synchronously acquire the displacement signal, the vibration signal and the sound signal.

5. A method for diagnosing abnormal noise sources, characterized in that, The method is applied to the processing unit of the abnormal noise source diagnostic system according to any one of claims 1-4. Acquire at least one displacement signal, vibration signal, and sound signal of the target component of the vehicle; Based on at least one displacement signal displacement phase diagram, identify multiple phase windows in the displacement phase diagram, and obtain vibration signals and sound signals within different phase windows; The source of abnormal noise in the target component is diagnosed based on the vibration and sound signals within the phase window.

6. The abnormal noise source diagnosis method according to claim 5, characterized in that, The method of diagnosing the source of abnormal noise in the target component based on the vibration signal and sound signal within the phase window includes: Extract the vibration spectrum features of the vibration signal and the acoustic features of the sound signal; The abnormal noise source of the target component is diagnosed based on the vibration spectrum characteristics and the acoustic characteristics.

7. The abnormal noise source diagnosis method according to claim 6, characterized in that, The method of diagnosing the abnormal noise source of the target component based on the vibration spectrum characteristics and the acoustic characteristics includes: The phase window in which the abnormal noise occurs is identified based on the vibration spectrum characteristics and the acoustic characteristics. The mechanical characteristics corresponding to the phase window where the abnormal noise occurs are analyzed based on the displacement phase diagram, and the vibration direction is determined based on the vibration spectrum characteristics corresponding to the phase window where the abnormal noise occurs. The source of abnormal noise in the target component is diagnosed based on the mechanical characteristics and the direction of vibration.

8. The method for diagnosing abnormal noise sources according to claim 5, characterized in that, The acquisition of vibration and sound signals within different phase windows includes: The phase window is associated with the vibration signal and the sound signal based on the acquisition time; Vibration and sound signals within different phase windows are determined based on the correlated data.

9. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed, they implement the abnormal noise source diagnosis method according to any one of claims 5-8.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed, they implement the abnormal noise source diagnosis method according to any one of claims 5-8.

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