Broken wire detection method and device for automobile inhaul cable

Abstract

The invention relates to the technical field of inhaul cable detection, and provides a broken wire detection method and device for an automobile inhaul cable, and the method comprises the steps: judging whether a broken wire exists or not based on the difference information between the vibration feature information of a steel wire in an automobile inhaul cable sheath within a preset time period and preset standard vibration feature information; if yes, obtaining state parameter information of the inhaul cable and the time difference of stress wave receiving of stress wave sensors at the two ends of the sheath; correcting the length of the inhaul cable and the propagation velocity of the stress wave based on the state parameter information of the inhaul cable to obtain the corrected length of the inhaul cable and the corrected propagation velocity of the stress wave; and based on the time difference, the corrected inhaul cable length and the corrected stress wave propagation velocity, determining a wire breaking position. According to the method, nondestructive testing on the broken steel wire in the inhaul cable in the automobile running process is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of cable detection, and in particular to a method and device for detecting broken wires in automobile cables. Background Art

[0002] Automotive cables are crucial components in key systems like steering and braking. They consist primarily of an outer sheath and an inner steel wire. During vehicle operation, the steel wires within the cables are subjected to cyclical tensile and bending loads. Long-term use can lead to fatigue fractures. Because the sheath encases the wires, wire breaks cannot be directly observed from the outside, posing challenges to safe vehicle operation and maintenance.

[0003] Currently, the commonly used method for detecting broken wires in cables mainly relies on regular manual inspection or disassembly inspection. This method not only requires stopping the vehicle for inspection, but may also damage the sheath structure during the disassembly and assembly process. Summary of the Invention

[0004] The present application provides a method and device for detecting broken wires in automobile cables to solve the problems raised in the above-mentioned background technology.

[0005] In a first aspect, the present application provides a method for detecting broken wires in automobile cables, comprising: Acquire the vibration signal of the steel wire in the sheath of the automobile cable in real time, and filter and reduce noise on the vibration signal to obtain a preprocessed vibration signal; Performing time-frequency domain analysis on the preprocessed vibration signal to obtain vibration characteristic information of the cable; Calculating a component-by-component deviation rate between the vibration characteristic information and the standard vibration characteristic information, and determining whether a broken wire exists based on a preset deviation rate threshold and the calculation result of the component-by-component deviation rate; When the wire breakage determination result is a wire breakage, obtaining the cable state parameter information and the time difference between the stress wave sensors at both ends of the sheath receiving the stress wave; Correcting the cable length and the stress wave propagation velocity based on the cable state parameter information to obtain a corrected cable length and a corrected stress wave propagation velocity; The broken wire position is determined based on the time difference, the corrected cable length, and the corrected stress wave propagation velocity.

[0006] In one possible implementation, the real-time acquisition of the vibration signal of the steel wire in the sheath of the automobile cable and the filtering and noise reduction processing of the vibration signal to obtain the preprocessed vibration signal include: Vibration signals are collected by a vibration sensor installed on the outer wall of the sheath; Filtering the vibration signal through a digital bandpass filter to obtain a first filtered signal; performing adaptive filtering on the first filtered signal to obtain a second filtered signal; The second filtered signal is smoothed to obtain the preprocessed vibration signal.

[0007] In a possible implementation, performing time-frequency domain analysis on the preprocessed vibration signal to obtain vibration characteristic information of the cable includes: Performing frame processing on the pre-processed vibration signal through a Hamming window to obtain a time window signal; Performing short-time Fourier transform processing on the time window signal to obtain a spectrum distribution signal; Extracting frequency domain feature parameters, time domain feature parameters and time-frequency joint feature parameters from the spectrum distribution signal; Perform sliding window averaging processing on the frequency domain characteristic parameters, the time domain characteristic parameters and the time-frequency joint characteristic parameters to obtain the vibration characteristic information.

[0008] In one possible implementation, calculating the component-by-component deviation rate of the vibration characteristic information and the standard vibration characteristic information, and determining whether a broken wire exists based on a preset deviation rate threshold and the component-by-component deviation rate calculation result, includes: For each component of the vibration characteristic information, calculating a deviation rate between a first value and a second value of the component; wherein the first value is a value corresponding to the component in the vibration characteristic information, and the second value is a value corresponding to the component in the standard vibration characteristic information; Determine the over-limit parameter corresponding to each component based on the deviation rate corresponding to each component and the preset deviation rate threshold corresponding to each component; Performing weighted summation on the out-of-limit parameters corresponding to each of the components to obtain an anomaly score; Determining whether the abnormality score is greater than a preset score; If it is greater than the preset score, the abnormality score is continuously calculated based on the preset time step within a preset time period after the current moment, and when the abnormality score calculated each time is greater than the preset score, it is determined that a broken wire occurs at the current moment.

[0009] In a possible implementation, the correcting the cable length and the stress wave propagation velocity based on the cable state parameter information to obtain the corrected cable length and the corrected stress wave propagation velocity includes: The cable length is corrected based on the cable bending angle and a preset equivalent path calculation formula to obtain a corrected cable length.

[0010] The stress wave propagation velocity is tension-corrected based on the cable tension to obtain a tension-corrected stress wave propagation velocity.

[0011] The stress wave propagation velocity after tension correction is corrected based on the cable temperature to obtain the corrected stress wave propagation velocity.

[0012] In a second aspect, the present application provides a broken wire detection device for an automobile cable, comprising: A signal processing module is used to obtain the vibration signal of the steel wire in the sheath of the automobile cable in real time, and filter and reduce noise on the vibration signal to obtain a preprocessed vibration signal; A time-frequency domain analysis module, configured to perform time-frequency domain analysis on the preprocessed vibration signal to obtain vibration characteristic information of the cable; a determination module, configured to calculate a component-by-component deviation rate between the vibration characteristic information and the standard vibration characteristic information, and determine whether a broken wire exists based on a preset deviation rate threshold and the calculation result of the component-by-component deviation rate; An acquisition module, configured to acquire the cable state parameter information and the time difference between the stress wave sensors at both ends of the sheath receiving the stress wave when the broken wire determination result is a broken wire; a correction module, configured to correct the cable length and the stress wave propagation velocity based on the cable state parameter information to obtain a corrected cable length and a corrected stress wave propagation velocity; A position determination module is used to determine the position of the broken wire based on the time difference, the corrected cable length and the corrected stress wave propagation speed.

[0013] The present application provides a method and device for detecting broken wires in automobile cables. The method comprises: acquiring a vibration signal of a steel wire in a sheath of the automobile cable in real time, filtering and noise reduction processing the vibration signal to obtain a preprocessed vibration signal; performing time-frequency domain analysis on the preprocessed vibration signal to obtain vibration characteristic information of the cable; calculating a component-by-component deviation rate between the vibration characteristic information and standard vibration characteristic information, and determining whether a broken wire exists based on a preset deviation rate threshold and the component-by-component deviation rate calculation result; when the broken wire is determined to be a broken wire, acquiring cable state parameter information and a time difference between stress waves received by stress wave sensors at both ends of the sheath; and correcting the cable length and stress wave propagation velocity based on the cable state parameter information to obtain a corrected cable length and a corrected stress wave propagation velocity. The location of the broken wire is determined based on the time difference, the corrected cable length, and the corrected stress wave propagation velocity. This method, on the one hand, achieves non-destructive detection of broken wires within the cable while the vehicle is in motion by installing a non-contact vibration sensor on the outer wall of the sheath and using a multi-stage filtering strategy to process the vibration signal, avoiding damage to the sheath structure caused by traditional disassembly testing. On the other hand, by establishing a joint determination mechanism of multi-dimensional characteristic parameters and a time continuity verification mechanism, the accuracy of determining when a broken wire has occurred is improved. Furthermore, by correcting the cable length and stress wave propagation velocity based on the cable state parameter information to obtain the corrected cable length and stress wave propagation velocity, the broken wire is precisely located, providing accurate location information for subsequent maintenance and improving maintenance efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0015] Figure 1 A schematic flow chart of a method for detecting broken wires in an automobile cable provided in an embodiment of the present application; Figure 2 A schematic block diagram of the structure of a broken wire detection device for an automobile cable provided in an embodiment of the present application; Figure 3 A schematic block diagram of the structure of a terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0017] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, combined, or partially merged, so the actual execution order may change based on actual circumstances.

[0018] It should also be understood that the terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0019] It should be further understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0020] The following describes some embodiments of the present application in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0021] See also Figure 1 , Figure 1 A schematic flow chart of a method for detecting broken wires in a car cable provided in an embodiment of the present application is shown as follows: Figure 1 As shown, the method for detecting broken wires in automobile cables provided in the embodiment of the present application includes steps S1 to S4.

[0022] Step S1: determining whether a wire breakage exists based on difference information between vibration characteristic information of a steel wire in a sheath of an automobile cable within a preset time period and preset standard vibration characteristic information.

[0023] The end moment of the preset time period is the current moment.

[0024] Specifically, step S1 includes: Step S11 : pre-processing the vibration signal of the steel wire in the automobile cable sheath within a preset time period to obtain a pre-processed vibration signal.

[0025] It should be noted that the vibration signal refers to the steel wire vibration signal collected in real time by a non-contact vibration sensor installed on the outer wall of the cable sheath. The signal contains the periodic vibration information generated by the steel wire during the driving of the car and the noise interference components from environmental factors such as the engine, road surface, and wind resistance.

[0026] Specifically, step S11 includes the following steps: Filtering the vibration signal through a digital bandpass filter to obtain a first filtered signal; performing adaptive filtering on the first filtered signal to obtain a second filtered signal; The second filtered signal is smoothed to obtain the preprocessed vibration signal.

[0027] For example, in a car equipped with a front-wheel cable, a laser Doppler vibration sensor is mounted on the outer wall of the left front-wheel cable jacket, 3 mm from the jacket's outer wall. When the car travels in a straight line at a stress wave propagation velocity of 60 km / h, the sensor's laser emits a laser beam with a wavelength of 632.8 nm, illuminating the jacket's outer surface. The jacket's vibration stress wave propagation velocity is measured by detecting the Doppler shift of the reflected light. At this time, the steel wire within the jacket experiences periodic vibrations due to wheel rotation and road excitation, with the primary frequency component between 300 and 500 Hz. The sensor continuously acquires signals at a sampling frequency of 5000 Hz, generating 5000 data points per second. The collected raw signal contains steel wire vibration information, as well as 50 Hz fundamental noise from the engine, 10-30 Hz low-frequency interference from road bumps, and high-frequency noise from the electromagnetic system. This collected vibration signal is then processed using a digital bandpass filter. The filter's low-frequency cutoff frequency is set at 80Hz, and its high-frequency cutoff frequency is set at 2000Hz. This filter removes 50Hz engine fundamental noise, 10-30Hz road vibration, and electromagnetic interference above 2000Hz. The filtered signal amplitude is reduced from ±2V to ±0.8V, forming the first filtered signal. An adaptive filter using a 32nd-order FIR structure with a step size of 0.01 is applied to this first filtered signal. The signal collected by the engine vibration sensor serves as the reference input. After a 100-millisecond convergence process, the second filtered signal is output, improving the signal-to-noise ratio from 12dB to 28dB. This second filtered signal is then smoothed using a moving average filter with a window length of 20 samples, equivalent to a 4-millisecond time window. This smoothing process further suppresses random impulse noise in the signal, resulting in a preprocessed vibration signal. The signal waveform is clear, with the primary frequency components concentrated near the natural frequency of the steel wire between 300-500Hz, providing a foundation for subsequent time-frequency analysis.

[0028] Step S12: performing feature analysis on the preprocessed vibration signal to obtain the vibration feature information.

[0029] Specifically, the preprocessed vibration signal is analyzed in the time and frequency domains to obtain the vibration characteristic information.

[0030] It should be noted that the time-frequency domain analysis refers to analyzing the preprocessed vibration signal using short-time Fourier transform technology to obtain the spectrum distribution characteristics of the signal in different time periods, thereby extracting multidimensional characteristic parameters that can characterize the vibration state of the steel wire.

[0031] In step S12, a Hamming window is selected as the window function, the window length is set to 1024 sampling points, and the overlap rate is set to 50%. Short-time Fourier transform analysis is performed on the preprocessed vibration signal. This transformation generates a time-frequency spectrum, from which three types of characteristic parameters are extracted: frequency-domain features include the main frequency, main frequency amplitude, harmonic frequency distribution, and harmonic amplitude ratio; time-domain features include the signal's root mean square value, crest factor, skewness, and kurtosis; and joint time-frequency features include the spectral center of gravity, spectral width, and spectral entropy. A sliding window technique is used to perform time-domain averaging of the characteristic parameters, setting the sliding window length to 1 second and the step size to 0.1 seconds. The characteristic parameters of 10 consecutive windows are arithmetic averaged. This multidimensional feature extraction method can comprehensively characterize the vibration characteristics of the steel wire and provide a rich basis for broken wire detection. Time-domain averaging effectively suppresses the impact of transient interference on feature extraction and improves the stability and reliability of the characteristic parameters.

[0032] For example, based on the aforementioned car as an example, a time-frequency analysis is performed on the pre-processed vibration signal of the left front wheel cable. A 1024-point Hamming window is selected, corresponding to a 204.8 millisecond time window at a sampling rate of 5000 Hz, with a window overlap rate of 50%, that is, each window moves forward 512 sampling points. The spectrum of each window is calculated by fast Fourier transform, and a spectrum diagram with a frequency resolution of 4.88 Hz is obtained. Under normal operating conditions, the main frequency of the steel wire appears at 420 Hz, with a main frequency amplitude of 0.65 V, the second harmonic appears at 840 Hz, with an amplitude of 0.26 V, and the third harmonic appears at 1260 Hz, with an amplitude of 0.08 V. The calculated second harmonic ratio is 0.26 / 0.65=0.40, and the third harmonic ratio is 0.08 / 0.65=0.12. In terms of time domain characteristics, the signal's RMS value is 0.42V, crest factor is 1.85, skewness is 0.03, and kurtosis is 2.95. In terms of joint time-frequency characteristics, the spectral center of gravity is calculated to be 456Hz, the spectral width is 185Hz, and the spectral entropy is 3.24. Using a sliding window technique, each 1-second window contains 10 short-time Fourier transform results, and the characteristic parameters of these 10 results are arithmetic averaged. For example, the dominant frequencies of the 10 windows are 418, 422, 419, 421, 420, 423, 417, 420, 424, and 416Hz, respectively, with an average of 420Hz. Similarly, the average values ​​of the other 10 characteristic parameters are calculated, and an 11-dimensional characteristic vector is finally obtained: [420, 0.65, 0.40, 0.12, 0.42, 1.85, 0.03, 2.95, 456, 185, 3.24]. This vector fully characterizes the vibration characteristic information of the cable within the preset time period.

[0033] Step S13: performing a difference analysis between the vibration characteristic information and the standard vibration characteristic information to obtain the difference information, and determining whether a broken wire exists based on the difference information.

[0034] Specifically, a component-by-component deviation rate is calculated between the vibration characteristic information and the standard vibration characteristic information, and whether a broken wire exists is determined based on a preset deviation rate threshold and the component-by-component deviation rate calculation result.

[0035] It should be noted that the standard vibration characteristic information refers to a reference standard established through statistical analysis of the vibration characteristics of intact steel wire under various normal operating conditions. It contains 11 components corresponding to the normal variation range of each characteristic parameter. The component-by-component deviation rate comparison refers to comparing each component of the vibration characteristic information when the cable breaks with the corresponding component of the standard vibration characteristic information to calculate the deviation rate, i.e., (value when the cable breaks - reference value) / reference value × 100%.

[0036] In step S13, the deviation rate between the vibration characteristic information of the cable break and each component of the standard vibration characteristic information is calculated and compared with a preset threshold. The deviation threshold is set at ±25% for frequency domain characteristics, ±30% for time domain characteristics, and ±20% for combined time-frequency characteristics. A multi-parameter joint judgment strategy is employed, assigning weight coefficients to each characteristic parameter. The weight of main frequency-related parameters (including main frequency frequency and amplitude) is 0.2, the weight of harmonic-related parameters (including second harmonic ratio and third harmonic ratio) is 0.15, the weight of time domain characteristics (including root mean square value, crest factor, skewness, and kurtosis) is 0.1, and the weight of combined time-frequency characteristics (including spectral center of gravity, spectral width, and spectral entropy) is 0.05. When a characteristic parameter exceeds the threshold, its weight coefficient is added to the anomaly score. When the anomaly score exceeds 0.5, a preliminary judgment is made that a broken wire may be present. A time persistence verification mechanism is introduced, requiring the abnormal state to persist for more than 5 seconds before a final determination of a broken wire is made. This multi-parameter joint judgment strategy can avoid misjudgment caused by fluctuations in a single parameter and improve the accuracy and reliability of detection.

[0037] For example, wire breakage determination is performed based on the eigenvector obtained in step S2. The preset standard vibration characteristic information is [420, 0.65, 0.40, 0.12, 0.42, 1.85, 0.03, 2.95, 456, 185, 3.24], which corresponds to the baseline values ​​of each characteristic parameter under normal operating conditions. Assume that the eigenvector of a cable breakage detected at a certain moment is [385, 0.48, 0.28, 0.08, 0.38, 2.15, 0.08, 3.45, 398, 220, 4.12]. Calculating the deviation rate component by component: The main frequency deviation rate is (385-420) / 420×100% = -8.3%, the main amplitude deviation rate is (0.48-0.65) / 0.65×100% = -26.2%, the second harmonic proportional deviation rate is (0.28-0.40) / 0.40×100% = -30.0%, and the third harmonic proportional deviation rate is (0.08-0.12) / 0.12×100% = -33.3%. Compared with the preset thresholds, the main frequency deviation rate of -8.3% is within the ±25% range, the main amplitude deviation rate of -26.2% exceeds the ±25% threshold, the second harmonic proportional deviation rate of -30.0% exceeds the ±25% threshold, and the third harmonic proportional deviation rate of -33.3% exceeds the ±25% threshold. Calculate the anomaly score: The main frequency amplitude weight is 0.2, the second harmonic ratio weight is 0.15, and the third harmonic ratio weight is 0.15. The total anomaly score is 0.2 + 0.15 + 0.15 = 0.5. Because the anomaly score reaches the threshold of 0.5, the system begins time continuity verification. Over the next 5 seconds, the feature vector and anomaly score are recalculated every 1 second. If the anomaly score is no less than 0.5 for five consecutive times, the final wire breakage determination result is "1".

[0038] Step S2: If it exists, obtain the cable state parameter information and the time difference between the stress wave sensors at both ends of the sheath receiving the stress wave.

[0039] It should be noted that the cable state parameter information includes cable tension, cable temperature, and cable bending angle.

[0040] In step S2, a cable tension sensor is installed in the middle area of ​​the cable sheath, using a strain gauge sensor to convert the cable tension value by measuring the strain of the steel wire. Three temperature sensors are evenly arranged on the outer surface of the sheath, using thermocouple sensors to monitor the cable temperature in real time. An inclination sensor is installed at each end and the middle of the sheath, using a MEMS gyroscope to measure the spatial bending angle of the cable. Stress wave sensors are installed at both ends of the sheath, and microsecond-level clock synchronization is achieved through the GPS timing module. The arrival time of the stress wave is recorded and the time difference is calculated. This multi-sensor collaborative arrangement scheme helps to accurately obtain the real-time state parameters of the cable, providing a reliable data basis for the subsequent cable length correction calculation and stress wave propagation speed correction calculation.

[0041] For example, based on the aforementioned situation of a broken left front wheel cable in step S1, when determining the cable break, data is collected using a tension sensor installed in the middle of the cable. This sensor uses a 120Ω strain gauge with a sensitivity coefficient of 2.1 and an excitation voltage of 5V. When the break occurs, the measured output voltage is 15mV. Using a calibration formula, the cable tension at the time of break is calculated to be 1200N. Three temperature sensors are installed at 300mm, 600mm, and 900mm from the left end of the sheath, respectively. They use K-type thermocouples with a temperature measurement range of -40°C to 125°C and a measurement accuracy of ±0.5°C. The real-time temperature data collected are 34.8°C, 35.2°C, and 34.6°C, respectively. The average value of 35°C is taken as the cable temperature at the time of break. The MEMS inclination sensor has a measurement range of ±30° and a resolution of 0.01°. Three-point measurements revealed that the cable's projection angles on the horizontal plane were 0°, 8°, and 0°, respectively. This indicates that the cable is bent in the middle at an angle of 8°. Stress wave sensors at both ends of the sheath began recording data. Sensor 1 detected a stress wave at 14:30:25:000090000, and sensor 2 detected a stress wave at 14:30:25:000150000. The calculated time difference is 60 microseconds.

[0042] Step S3: Correcting the cable length and stress wave propagation velocity based on the cable state parameter information to obtain a corrected cable length and a corrected stress wave propagation velocity.

[0043] It should be noted that the stress wave propagation velocity refers to the stress wave propagation velocity along the steel wire caused by the mechanical vibration generated when the steel wire breaks. For example, for commonly used steel strands, under standard conditions (normal temperature and standard tension), the stress wave propagation velocity is typically between 4800 and 5200 m / s.

[0044] In step S3, a length correction model and a stress wave propagation velocity correction model are established. The length correction takes into account the influence of cable bending and adopts the equivalent path calculation formula: L eff= L × (1 + β × θ²), where, L eff is the corrected equivalent length, L is the original length, β is the geometric correction coefficient, and θ is the bending angle. The stress wave propagation velocity correction comprehensively considers the influence of tension and temperature. First, tension correction is performed: V' = V0× (1 + k × (T - T0) / T0), where V' is the stress wave propagation velocity after tension correction, V0 is the stress wave propagation velocity under standard tension, k is the material correction coefficient, T is the tension when the cable breaks, and T0 is the standard tension. Then, temperature correction is performed: V temp = V' × (1 + α × (t current -t reference )), where V temp is the final corrected stress wave propagation velocity, α is the temperature correction coefficient, t current is the temperature when the cable breaks, t reference This step-by-step correction method can accurately compensate for the influence of various factors on the measurement and improve positioning accuracy.

[0045] For example, the correction calculation is performed based on the cable state parameters obtained in the above step S2. The original cable length L = 1.2 meters, the geometric correction coefficient β = 0.0001, the measured bending angle θ = 8 degrees, and the length correction formula is substituted: L eff = 1.2 × (1 + 0.0001 × 8²) = 1.2 × 1.0064 = 1.208 m. The standard stress wave propagation velocity V0 = 5000 m / s, the material correction factor k = 0.03, the tension at the time of cable breakage T = 1200 N, the standard tension T0 = 1000 N, substituting into the tension correction formula: V' = 5000 × (1 + 0.03 × (1200-1000) / 1000) = 5000 × 1.006 = 5030 m / s. The temperature correction factor α = -0.0005 / °C, the temperature at the time of cable breakage t current =35℃, reference temperature t reference =20℃, substitute the tension-corrected stress wave propagation velocity into the temperature correction formula: V temp = 5030 × (1 - 0.0005 × (35-20)) = 5030 × 0.9925 = 4992 m / s. These corrections ultimately yield an equivalent propagation distance of 1.208 m and a corrected stress wave propagation velocity of 4992 m / s. These corrected parameters fully account for the impact of actual operating conditions and provide effective basic data for the final calculation of the broken wire location.

[0046] Step S4: determining the position of the broken wire based on the time difference, the corrected cable length, and the corrected stress wave propagation velocity.

[0047] In step S4, a broken wire position calculation model is constructed based on the physical characteristics of stress wave propagation: d = (L eff -V temp × Δt) / 2, where d is the distance between the stress wave sensor that first receives the stress wave and the broken wire point, and L eff is the corrected equivalent length, V temp is the corrected stress wave propagation velocity, and Δt is the measured time difference. The corrected parameters are used to calculate the broken wire location. When the cable has multiple bends, the equivalent length calculation is further subdivided, and a segmented accumulation method is used to obtain a more accurate broken wire location. This method helps improve the accuracy of the broken wire location and provides accurate location information for subsequent repair work.

[0048] For example, the broken wire position is calculated based on the corrected cable length and the corrected stress wave propagation velocity obtained in step S3. eff = 1.208 m, the corrected stress wave propagation velocity V temp = 4992 m / s. Substituting the measured time difference Δt = 60 μs into the position calculation formula: d = (1.208 - 4992 × 0.000060) / 2 = (1.208 - 0.2995) / 2 = 0.454 m. Because sensor 1 detects the stress wave first in step S4, the broken wire is located near the end of sensor 1. This location information allows maintenance personnel to quickly locate the broken wire, improving maintenance efficiency.

[0049] The method provided in this embodiment, on the one hand, realizes non-destructive detection of broken steel wires inside the cable during driving of the car by installing a non-contact vibration sensor on the outer wall of the sheath and adopting a multi-stage filtering strategy to process the vibration signal, thereby avoiding damage to the sheath structure caused by traditional disassembly detection. On the other hand, the accuracy of judging the occurrence of broken wires is improved by establishing a joint judgment mechanism of multi-dimensional characteristic parameters and a time continuity verification mechanism. On the other hand, by correcting the cable length and stress wave propagation velocity based on the cable state parameter information, the corrected cable length and corrected stress wave propagation velocity are obtained, thereby realizing accurate positioning of the broken wire position, providing accurate position information for subsequent maintenance, and improving maintenance efficiency.

[0050] In some embodiments, performing time-frequency domain analysis on the preprocessed vibration signal to obtain vibration characteristic information of the cable includes: Performing frame processing on the pre-processed vibration signal through a Hamming window to obtain a time window signal; For example, a 1024-point Hamming window is selected as the window function to perform frame processing on the preprocessed vibration signal. At a sampling rate of 5000 Hz, each time window corresponds to a signal length of 204.8 milliseconds. The window overlap ratio is set to 50%, that is, each window moves forward 512 sampling points. Through this framing method, the continuous preprocessed vibration signal is divided into a series of overlapping time window signals; Performing short-time Fourier transform processing on the time window signal to obtain a spectrum distribution signal; For example, the time window signal obtained above is subjected to a short-time Fourier transform. Since the sampling frequency is 5000 Hz and the window length is 1024 points, a spectrum distribution signal with a frequency resolution of 4.88 Hz is obtained through fast Fourier transform calculation. This spectrum distribution signal contains the frequency components of the steel wire vibration and their corresponding amplitude information. Extracting frequency domain feature parameters, time domain feature parameters and time-frequency joint feature parameters from the spectrum distribution signal; It should be noted that the frequency domain characteristic parameters include the main frequency, main frequency amplitude, harmonic frequency distribution and harmonic amplitude ratio; the time domain characteristic parameters include root mean square value, peak factor, skewness and kurtosis; the time-frequency joint characteristic parameters include spectrum center of gravity, spectrum width and spectrum entropy; Exemplarily, characteristic parameters are extracted based on the spectrum distribution signal obtained above. In terms of frequency domain characteristics, it is detected that the main frequency is located at 420Hz, the main frequency amplitude is 0.65V, the second harmonic is located at 840Hz, the amplitude is 0.26V, the third harmonic is located at 1260Hz, the amplitude is 0.08V, and the calculated second harmonic ratio is 0.40, and the third harmonic ratio is 0.12. In terms of time domain characteristics, the calculated root mean square value is 0.42V, the peak factor is 1.85, the skewness is 0.03, and the kurtosis is 2.95. In terms of time-frequency joint characteristics, the calculated spectral center of gravity is 456Hz, the spectral width is 185Hz, and the spectral entropy is 3.24; Performing sliding window averaging processing on the frequency domain characteristic parameters, the time domain characteristic parameters, and the time-frequency joint characteristic parameters to obtain the vibration characteristic information; For example, the extracted feature parameters are subjected to sliding window averaging. The sliding window length is set to 1 second, the step size is 0.1 second, and each window contains 10 short-time Fourier transform results. Taking the main frequency as an example, the values ​​of the 10 windows are 418, 422, 419, 421, 420, 423, 417, 420, 424, and 416 Hz, respectively. The arithmetic mean is 420 Hz. The other feature parameters are averaged using the same method, and an 11-dimensional feature vector is finally obtained: [420, 0.65, 0.40, 0.12, 0.42, 1.85, 0.03, 2.95, 456, 185, 3.24].

[0051] In some embodiments, calculating the component-by-component deviation rate of the vibration characteristic information and the standard vibration characteristic information, and determining whether there is a broken wire based on a preset deviation rate threshold and the component-by-component deviation rate calculation result, includes: For each component of the vibration characteristic information, calculating a deviation rate between a first value and a second value of the component; wherein the first value is a value corresponding to the component in the vibration characteristic information, and the second value is a value corresponding to the component in the standard vibration characteristic information; It should be noted that the deviation rate refers to the value corresponding to (first value - second value) / second value × 100%; For example, the vibration feature information [385, 0.48, 0.28, 0.08, 0.38, 2.15, 0.08, 3.45, 398, 220, 4.12] is compared component by component with the standard vibration feature information [420, 0.65, 0.40, 0.12, 0.42, 1.85, 0.03, 2.95, 456, 185, 3.24]. The calculated main frequency deviation rate is (385-420) / 420×100%=-8.3%, the main frequency amplitude deviation rate is (0.48-0.65) / 0.65×100%=-26.2%, the second harmonic ratio deviation rate is (0.28-0.40) / 0.40×100%=-30.0%, the third harmonic ratio deviation rate is (0.08-0.12) / 0.12×100%=-33.3%, the root mean square value deviation rate is (0.38-0.42) / 0.42×100%=-9.5%, and the peak factor deviation rate is (2.1 5-1.85) / 1.85×100%=+16.2%, skewness deviation rate is (0.08-0.03) / 0.03×100%=+166.7%, kurtosis deviation rate is (3.45-2.95) / 2.95×100%=+16.9%, spectral center deviation rate is (398-456) / 456×100%=-12.7%, spectral width deviation rate is (220-185) / 185×100%=+18.9%, spectral entropy deviation rate is (4.12-3.24) / 3.24×100%=+27.2%; Determine the over-limit parameter corresponding to each component based on the deviation rate corresponding to each component and the preset deviation rate threshold corresponding to each component; It should be noted that the over-limit parameter refers to the mark when the deviation rate of each component exceeds the corresponding preset threshold range, which is 1 if exceeded and 0 if not exceeded; For example, the deviation threshold of the frequency domain feature is set to ±25%, the deviation threshold of the time domain feature is set to ±30%, and the deviation threshold of the time-frequency joint feature is set to ±20%. The main frequency over-parameter is -8.3%: does not exceed ±25%, over-limit parameter = 0; the main frequency amplitude over-parameter is -26.2%: exceeds ±25%, over-limit parameter = 1; the second harmonic ratio over-parameter is -30.0%: exceeds ±25%, over-limit parameter = 1; the third harmonic ratio over-parameter is -33.3%: exceeds ±25%, over-limit parameter = 1; the root mean square value over-parameter is -9.5%: does not exceed ±30%, over-limit parameter = 0; the peak factor over-parameter is +16.2 %: does not exceed ±30%, over-limit parameter = 0; skewness over-parameter +166.7%: exceeds ±30%, over-limit parameter = 1; kurtosis over-parameter +16.9%: does not exceed ±30%, over-limit parameter = 0; spectral center of gravity over-parameter -12.7%: does not exceed ±20%, over-limit parameter = 0; spectral width over-parameter +18.9%: does not exceed ±20%, over-limit parameter = 0; spectral entropy over-parameter +27.2%: exceeds ±20%, over-limit parameter = 1; Performing weighted summation on the out-of-limit parameters corresponding to each of the components to obtain an anomaly score; Exemplarily, the weights of the main frequency, main frequency amplitude, harmonic frequency distribution, harmonic amplitude ratio, root mean square value, crest factor, skewness and kurtosis, spectral center of gravity, spectral width and spectral entropy are 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.05, and 0.05 respectively, then the anomaly score is 0+0.1+0.1+0.1+0+0+0.1+0+0+0+0=0.45; Determining whether the abnormality score is greater than a preset score; If it is greater than the preset score, the abnormality score is continuously calculated based on the preset time step within the preset time period after the current moment, and when the abnormality score calculated each time is greater than the preset score, it is determined that the wire is broken at the current moment; For example, if the preset score is 0.4, the preset time period is 5 seconds, the time step is 1 second, and the abnormality scores continuously calculated within 5 seconds after the current moment are 0.46, 0.47, 0.5, 0.51, and 0.48 respectively, it is determined that a broken wire occurs at the current moment.

[0052] In some embodiments, the cable state parameter information includes cable tension, cable temperature, and cable bending angle, and the cable length and stress wave propagation velocity are corrected based on the cable state parameter information to obtain the corrected cable length and the corrected stress wave propagation velocity, including: Correcting the cable length based on the cable bending angle and a preset equivalent path calculation formula to obtain a corrected cable length; Performing tension correction on the stress wave propagation velocity based on the cable tension to obtain a tension-corrected stress wave propagation velocity; The stress wave propagation velocity after tension correction is corrected based on the cable temperature to obtain the corrected stress wave propagation velocity.

[0053] It should be noted that the example of this embodiment refers to the example corresponding to the aforementioned step S3, which will not be repeated here.

[0054] See also Figure 2 , Figure 2 The schematic block diagram of the structure of the broken wire detection device 100 for the automobile cable provided in the embodiment of the present application is as follows: Figure 2 As shown, the broken wire detection device 100 for an automobile cable provided in an embodiment of the present application includes: The judgment module 110 is used to judge whether there is a broken wire based on the difference between the vibration characteristic information of the steel wire in the automobile cable sheath within a preset time period and the preset standard vibration characteristic information.

[0055] The acquisition module 120 is used to obtain the cable state parameter information and the time difference between the stress wave sensors at both ends of the sheath receiving the stress wave if a broken wire exists.

[0056] The correction module 130 is configured to correct the cable length and the stress wave propagation velocity based on the cable state parameter information to obtain a corrected cable length and a corrected stress wave propagation velocity.

[0057] The determination module 140 is configured to determine a broken wire position based on the time difference, the corrected cable length, and the corrected stress wave propagation velocity.

[0058] In some embodiments, the determination module 110 includes: The preprocessing unit 111 is used to preprocess the vibration signal of the steel wire in the sheath of the automobile cable within a preset time period to obtain a preprocessed vibration signal.

[0059] The feature analysis unit 112 is configured to perform feature analysis on the preprocessed vibration signal to obtain the vibration feature information.

[0060] The judging unit 113 is configured to perform a difference analysis between the vibration characteristic information and the standard vibration characteristic information to obtain the difference information, and judge whether a broken wire exists based on the difference information.

[0061] It should be noted that, those skilled in the art will clearly understand that for the sake of convenience and brevity of description, the specific working processes of the above-described devices, modules and units can refer to the processes in the aforementioned embodiment of the broken wire detection method for automobile cables, and will not be repeated here.

[0062] The broken wire detection device 100 for automobile cable provided in the above embodiment can be implemented in the form of a computer program. The computer program can be used in Figure 3 The system runs on the terminal device 200 shown.

[0063] See also Figure 3 , Figure 3 This is a schematic block diagram of the structure of a terminal device 200 provided in an embodiment of the present application. The terminal device 200 includes a processor 201 and a memory 202. The processor 201 and the memory 202 are connected via a device bus 203, wherein the memory 202 may include a non-volatile storage medium and an internal memory.

[0064] The non-volatile storage medium can store a computer program. The computer program includes program instructions. When the program instructions are executed by the processor 201, the processor 201 can execute any of the above-mentioned methods for detecting broken wires in automobile cables.

[0065] The processor 201 is used to provide computing and control capabilities to support the operation of the entire terminal device 200.

[0066] The internal memory provides an environment for running the computer program in the non-volatile storage medium. When the computer program is executed by the processor 201, the processor 201 can execute any of the above-mentioned methods for detecting broken wires in automobile cables.

[0067] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the terminal device 200 involved in the solution of the present application. The specific terminal device 200 may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0068] It should be understood that the processor 201 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0069] In some embodiments, the processor 201 is configured to execute a computer program stored in the memory to implement the following steps: Determine whether the wire is broken based on the difference between the vibration characteristic information of the steel wire in the automobile cable sheath within a preset time period and the preset standard vibration characteristic information; If it exists, obtain the cable state parameter information and the time difference between the stress wave sensors at both ends of the sheath receiving the stress wave; Correcting the cable length and the stress wave propagation velocity based on the cable state parameter information to obtain a corrected cable length and a corrected stress wave propagation velocity; The broken wire position is determined based on the time difference, the corrected cable length, and the corrected stress wave propagation velocity.

[0070] It should be noted that those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process of the terminal device 200 described above can refer to the corresponding process of the aforementioned automobile cable broken wire detection method, which will not be repeated here.

[0071] An embodiment of the present application further provides a computer-readable storage medium storing a computer program. When the computer program is executed by one or more processors, the one or more processors implement the method for detecting broken wires in an automobile cable as provided in an embodiment of the present application.

[0072] The computer-readable storage medium may be an internal storage unit of the terminal device 200 in the aforementioned embodiment, such as a hard disk or memory of the terminal device 200. The computer-readable storage medium may also be an external storage device of the terminal device 200, such as a plug-in hard disk, a smart memory card (SMC), a secure digital (SD) card, a flash card, etc. equipped with the terminal device 200.

[0073] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present application, and such modifications or substitutions should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for detecting broken wires in automobile cables, characterized in that: include: Determine whether the wire is broken based on the difference between the vibration characteristic information of the steel wire in the automobile cable sheath within a preset time period and the preset standard vibration characteristic information; If it exists, obtain the cable state parameter information and the time difference between the stress wave sensors at both ends of the sheath receiving the stress wave; Correcting the cable length and the stress wave propagation velocity based on the cable state parameter information to obtain a corrected cable length and a corrected stress wave propagation velocity; The broken wire position is determined based on the time difference, the corrected cable length, and the corrected stress wave propagation velocity.

2. The method for detecting broken wires in automobile cables according to claim 1, wherein: The method of judging whether a wire is broken based on difference information between vibration characteristic information of the steel wire in the automobile cable sheath within a preset time period and preset standard vibration characteristic information includes: Preprocessing the vibration signal of the steel wire in the sheath of the automobile cable within a preset time period to obtain a preprocessed vibration signal; Performing feature analysis on the preprocessed vibration signal to obtain the vibration feature information; A difference analysis is performed on the vibration characteristic information and the standard vibration characteristic information to obtain the difference information, and whether a broken wire exists is determined based on the difference information.

3. The method for detecting broken wires in automobile cables according to claim 2, wherein: The preprocessing of the vibration signal of the steel wire in the automobile cable sheath within a preset time period to obtain the preprocessed vibration signal includes: Filtering the vibration signal through a digital bandpass filter to obtain a first filtered signal; performing adaptive filtering on the first filtered signal to obtain a second filtered signal; The second filtered signal is smoothed to obtain the preprocessed vibration signal.

4. The method for detecting broken wires in automobile cables according to claim 2, wherein: The performing feature analysis on the preprocessed vibration signal to obtain the vibration feature information includes: Performing time-frequency domain analysis on the preprocessed vibration signal to obtain the vibration characteristic information.

5. The method for detecting broken wires of automobile cables according to claim 2, characterized in that: The performing difference analysis on the vibration characteristic information and the standard vibration characteristic information to obtain the difference information, and judging whether there is a broken wire based on the difference information, includes: A component-by-component deviation rate is calculated between the vibration characteristic information and the standard vibration characteristic information, and whether a broken wire exists is determined based on a preset deviation rate threshold and the component-by-component deviation rate calculation result.

6. The method for detecting broken wires in automobile cables according to claim 4, wherein: The performing time-frequency domain analysis on the pre-processed vibration signal to obtain vibration characteristic information of the cable includes: Performing frame processing on the pre-processed vibration signal through a Hamming window to obtain a time window signal; Performing short-time Fourier transform processing on the time window signal to obtain a spectrum distribution signal; Extracting frequency domain feature parameters, time domain feature parameters and time-frequency joint feature parameters from the spectrum distribution signal; Perform sliding window averaging processing on the frequency domain characteristic parameters, the time domain characteristic parameters and the time-frequency joint characteristic parameters to obtain the vibration characteristic information.

7. The method for detecting broken wires in automobile cables according to claim 5, wherein: The step of calculating the component-by-component deviation rate of the vibration characteristic information and the standard vibration characteristic information, and determining whether a broken wire exists based on a preset deviation rate threshold and the calculation result of the component-by-component deviation rate, includes: For each component of the vibration characteristic information, calculating a deviation rate between a first value and a second value of the component; wherein the first value is a value corresponding to the component in the vibration characteristic information, and the second value is a value corresponding to the component in the standard vibration characteristic information; Determine the over-limit parameter corresponding to each component based on the deviation rate corresponding to each component and the preset deviation rate threshold corresponding to each component; Performing weighted summation on the out-of-limit parameters corresponding to each of the components to obtain an anomaly score; Determining whether the abnormality score is greater than a preset score; If it is greater than the preset score, the abnormality score is continuously calculated based on the preset time step within a preset time period after the current moment, and when the abnormality score calculated each time is greater than the preset score, it is determined that a broken wire occurs at the current moment.

8. The method for detecting broken wires in automobile cables according to claim 1, wherein: The cable state parameter information includes cable tension, cable temperature, and cable bending angle. The cable length and stress wave propagation velocity are corrected based on the cable state parameter information to obtain the corrected cable length and the corrected stress wave propagation velocity, including: Correcting the cable length based on the cable bending angle and a preset equivalent path calculation formula to obtain a corrected cable length; Performing tension correction on the stress wave propagation velocity based on the cable tension to obtain a tension-corrected stress wave propagation velocity; The stress wave propagation velocity after tension correction is corrected based on the cable temperature to obtain the corrected stress wave propagation velocity.

9. A broken wire detection device for automobile cable, characterized in that: include: A judgment module, configured to judge whether a wire is broken based on the difference between vibration characteristic information of the steel wire in the sheath of the automobile cable within a preset time period and preset standard vibration characteristic information; An acquisition module is used to obtain the cable state parameter information and the time difference between the stress wave sensors at both ends of the sheath receiving the stress wave if a broken wire exists; a correction module, configured to correct the cable length and the stress wave propagation velocity based on the cable state parameter information to obtain a corrected cable length and a corrected stress wave propagation velocity; A determination module is used to determine the broken wire position based on the time difference, the corrected cable length and the corrected stress wave propagation speed.

10. The broken wire detection device for automobile cable according to claim 9, characterized in that: The judgment module includes: A preprocessing unit, configured to preprocess a vibration signal of a steel wire in a sheath of an automobile cable within a preset time period to obtain a preprocessed vibration signal; a feature analysis unit, configured to perform feature analysis on the preprocessed vibration signal to obtain the vibration feature information; The judging unit is configured to perform a difference analysis between the vibration characteristic information and the standard vibration characteristic information to obtain the difference information, and judge whether a broken wire exists based on the difference information.

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