KR20030050768A - Method for processing detection signal in duration test of vehicle - Google Patents

Abstract

PURPOSE: A detecting signal treating method is provided to achieve precise information regarding a breaking time, a breaking point, and a breaking speed and mode of components of a vehicle by analyzing a sound discharging signal. CONSTITUTION: A signal detected by sensors installed at each part of a vehicle is treated in real time in such a manner that the signal is divided into a sound discharging signal and a vibration signal(S105,S106). The sound discharging signal is converted into a scale signal by wavelet-transforming the sound discharging signal(S107). Then, the scale signal is analyzed in order to determine whether or not the scale signal has a fault(S108). If the scale signal has the fault, a fault generating position and a fault size are detected by calculating signal reaching time from each sensor through a circuit net(S109,S110).

Description

Detection signal processing method in vehicle endurance test {METHOD FOR PROCESSING DETECTION SIGNAL IN DURATION TEST OF VEHICLE}

The present invention relates to an endurance testing apparatus for a vehicle, and more particularly, to extract and analyze a signal obtained from a sensor attached to various parts of a vehicle into an acoustic emission signal and a vibration signal, thereby obtaining accurate test results for each part of the vehicle. The present invention relates to a detection signal processing method in a vehicle endurance test that can be obtained.

In general, the basic method of detecting damage or damage such as cracks generated in the vehicle body and chassis during the actual vehicle durability test or the target durability test of the vehicle is the endurance tester visually observed in the vehicle traveling over a certain distance to extract the results It is universal.

Therefore, in order to inspect an invisible part of the vehicle after driving a certain distance in the durability test using a real vehicle, the vehicle has to be disassembled and the vehicle has to be periodically inspected.

In order to overcome this disadvantage, non-destructive inspection method that detects damage and damage in real time is used in aerospace, but there is no suitable method to apply it to automobiles. In the case of a simple signal processing method for frequency analysis of a signal acquired from a sensor installed at a site, there is a disadvantage in that quantitative damage detection is difficult.

The present invention has been invented to solve the above problems, the object of which is to detect the damage during the endurance test of the vehicle to each part of the vehicle (X-MBR, S / ABS, SPRING, ARM, LINK, body, etc.) A suitable piezoelectric ceramic sensor is attached, and the signal obtained from the attached piezoelectric ceramic sensor is separated into an acoustic emission signal and a vibration signal through wavelet transform, and the analysis of the acoustic emission signal is used to determine the exact damage of each part of the vehicle. It provides accurate information about the timing and failure propagation rate and the final failure mode, and provides accurate life prediction and light weight design modifications for parts.

1 is a schematic configuration diagram of an endurance testing apparatus for a vehicle according to the present invention.

2 is a flow diagram of one embodiment for performing detection signal processing in a vehicle endurance test in accordance with the present invention.

Figure 3 is a waveform diagram of an embodiment showing a scale result of the acoustic emission signal step in the detection signal processing in accordance with the present invention.

4 is a waveform diagram of one embodiment for performing natural frequency extraction through spectral analysis in accordance with the present invention;

The present invention for realizing the above object is a process for real-time processing the signal obtained from the sensor installed in each part of the vehicle to separate the acoustic emission signal and the vibration signal, and the wavelet conversion of the separated acoustic emission signal step by step scale The process of decomposing it into a signal, analyzing the decomposed signal on a step-by-step scale to determine whether there is damage in any part, and if it is determined that there is damage in any part, calculating the difference in arrival time of each sensor and then calculating Analyzing the results through neural networks to detect the location of the damage, the corresponding parts and the size of the damage.

Spectral analysis of the separated vibration signal to extract a natural frequency, a process of detecting whether there is a change in natural frequency by comparing the extracted natural frequency with a set natural frequency for a corresponding region, and a change in natural frequency If is detected includes the process of determining that a large damage and breakage occurred in the site.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

As can be seen in Figure 1 is installed in each part necessary for the durability test of the vehicle, that is, X-MBR, S / ABS, SPRING, ARM, LINK, the vehicle body, etc., the deformation or crack of the corresponding parts as the durability test proceeds The sensor 10 for detecting the degree of damage and outputting the damage information, the amplifying unit 20 for amplifying the analog signal applied from the sensor 10 to a set level, and the amplified parts. Data is acquired by sampling the endurance test information in a set frequency unit, and a programming language (VISUAL C ++, MATLAB, LABVIEW) is set for processing the acquisition of signals in real time, and wavelet transform ( Wavelat Transform) to separate sound emission signal and vibration signal, and wavelet transform the separated sound emission signal to decompose the signal by the scale step. Detecting information of the production and size, it comprises a diagnostic unit 30 for detecting an impairment or damage to the components by spectral analysis of the isolated vibration signal.

In the present invention including the functions described above, a signal processing process acquired by the sensor installed at each site is as follows.

When the piezoelectric ceramic sensor 10 is installed on each part of the vehicle for durability test, that is, X-MBR, S / ABS, SPRING, ARM, LINK, body, etc. When the sensor 10 installed detects information such as deformation, cracks, and breakage of the corresponding part and applies the information to the amplifier 20, the amplifier 20 amplifies the applied signal to a predetermined level and diagnoses the diagnosis device. It is applied to the (30) side.

The data acquisition board (not shown) in the diagnostic apparatus 30 reads out the signal of the sensor 10 that is input and samples at the set sampling frequency, preferably 1 MHz, to acquire the endurance test signal for each part, VISUAL C ++, The real-time signal processing program set in MATLAB, LABVIEW, etc. allows the information to be acquired in real time (S101) (S102) (S103).

Subsequently, the signals acquired in real time are subjected to wavelet conversion, and the signals are separated into acoustic emission signals and vibration signals (S104) (S105) and S106.

The wavelet transforms the acoustic emission signal from the separated signal as described above, decomposes the scaled signal into stages (S107), and then detects whether there is a signal generation in a specific stage for abnormal detection (S108).

When the signal generation of a specific step is detected in the above step, the difference in arrival time between each sensor of the acoustic emission signal is calculated (S109), and the result of the analysis is analyzed using a neural network, where the damage occurs, the parts where the damage occurs, and the size of the damage. (S110) (S111).

As described above, the principle of detecting the location of the damage, the part where the damage occurred, and the magnitude of the damage by the step-by-step signal after wavelet conversion is as follows.

When an arbitrary structure material for analysis is determined, the acoustic emission signal according to the failure mode of the structure has a constant frequency component, so that the step-by-step scale after wavelet transformation is decomposed into at least three stages as shown in FIG. From this, it is possible to determine whether damage to the structure occurs.

In addition, by analyzing the components of the vibration signal separated by the wavelet transform and signal decomposition in S104 to detect the natural frequency (S113) (S114).

Thereafter, the detected natural frequency is compared with the natural frequency for the corresponding part to detect whether a change in the frequency is generated (S115).

If it is determined that a change in the natural frequency has occurred in the above, it is determined that a large damage and breakage has occurred for the corresponding site, and the information about it is instructed to the endurance test facilitator through the monitor (S116).

As can be seen in Figure 4, since the natural frequency of the structure has a very low frequency range compared to the acoustic emission signal, A3 is a low frequency signal containing the natural frequency is decomposed from the original signal (PZT) obtained from the sensor Fourier transform the signal to extract the natural frequency.

Then, by comparing the natural frequency for each of the preset portion and the natural frequency extracted through the Fourier transform, if there is a reduction due to the damage of the frequency, it is determined that a large damage and damage to the portion.

As described above, the present invention separates a signal detected from a sensor into an acoustic emission signal and a vibration signal, and then accurately analyzes the occurrence time, the propagation speed, and the final damage of the vehicle component by analyzing the scale of the acoustic emission signal and the neural network analysis. Accurate information about the mode can be obtained to provide reliability for endurance testing.

In addition, based on this, it is possible to accurately predict the life of the parts and to modify the design to reduce the weight, and to predict the propagation speed of the damage occurrence for each part, thereby eliminating endurance tests that should be performed periodically.

Claims (2)

Real-time processing the signals acquired from the sensors installed in each part of the vehicle and separating them into acoustic emission signals and vibration signals; Wavelet converting the separated sound emission signal into a stepwise scale signal; Analyzing the scaled-decomposed signal step by step to determine whether any part is damaged; If it is determined that there is damage to any part, the step of calculating the difference in the arrival time of each sensor, and then analyzing the calculated results through the neural network to detect the location of the damage occurs and the corresponding parts and the size of the damage characterized in that it comprises Detection signal processing method in a vehicle endurance test. The method of claim 1, Spectral analysis of the separated vibration signal to extract natural frequencies; Detecting whether there is a change in natural frequency by comparing the extracted natural frequency with a set natural frequency of a corresponding region; Detecting a change in the natural frequency is a detection signal processing method in a vehicle endurance test comprising the step of determining that a large damage and breakage occurred in the area.