Unlock instant, AI-driven research and patent intelligence for your innovation.

Vehicle Operating Condition Recognition Method Based on Vibration Signal Analysis

A vibration signal, working condition identification technology, applied in vehicle testing, machine/structural component testing, measuring devices, etc., can solve problems such as inconvenient installation and use, and achieve the effect of ensuring integrity

Active Publication Date: 2018-01-30
HARBIN INST OF TECH
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the technical means for vehicle condition monitoring mainly include performance parameter monitoring, oil analysis and monitoring, etc. These two methods need to select different monitoring parameters for different types of vehicles and are inconvenient to install and use

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Vehicle Operating Condition Recognition Method Based on Vibration Signal Analysis
  • Vehicle Operating Condition Recognition Method Based on Vibration Signal Analysis
  • Vehicle Operating Condition Recognition Method Based on Vibration Signal Analysis

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach 1

[0012] Specific implementation mode one: the following combination figure 1 Describe this embodiment, the vehicle operating condition identification method based on vibration signal analysis described in this embodiment, the method includes the following steps:

[0013] Step 1. Collect the vibration signal of the vehicle and perform denoising processing on it;

[0014] Step 2, performing signal feature value extraction on the denoised vibration signal;

[0015] Step 3. Carry out intelligent identification of working conditions according to the feature values ​​extracted in step 2; output the vehicle working condition type.

specific Embodiment approach 2

[0016] Embodiment 2: This embodiment will further explain Embodiment 1. In step 1, the vibration signal of the vehicle is denoised using the singular value decomposition noise reduction method, and the observed vehicle vibration signal sequence x i ={x 1 ,x 2 ,...x Q} Carry out singular value decomposition for noise reduction, Q is the sampling point, the specific process is:

[0017] Step 1-1. Select the subsequence {x in the observed signal sequence 1 ,x 2 ,...x q} as the first row vector y of the p×q-dimensional phase space matrix 1 ;

[0018] Step 1-2, move one step to the right to get the subsequence {x 2 ,x 3 ,...x q+1}, as the second row vector y of the p×q-dimensional phase space matrix 2 ;

[0019] Steps 1-3, and so on, get a column vector (y 1 ,y 2 ,...y p ) T ;

[0020] Steps 1-4, each vector corresponds to a point in the phase space, and all vectors constitute the p×q-dimensional reconstructed phase space orbit matrix H:

[0021]

[0022] In the...

specific Embodiment approach 3

[0026] Specific implementation mode three: this implementation mode further explains implementation mode two. In step two, the process of extracting the signal feature value of the vibration signal after denoising is as follows:

[0027] The denoised signal G is x i ={x 1 ,x 2 ,...x N}, its Fourier transform expression is:

[0028]

[0029] The amplitude spectrum expression of the signal is:

[0030]

[0031] The power spectrum expression of the signal is:

[0032]

[0033] Among them, X R (k) represents the real part, X I (k) represents the imaginary part:

[0034]

[0035]

[0036] Then draw the spectrum diagram of the vibration signal to present the frequency distribution of the vibration signal, and select the frequency components under different working conditions as the signal characteristic value.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a vibration signal analysis-based vehicle working condition identification method and belongs to the vehicle performance monitoring field. The objective of the invention is to provide a method for monitoring vehicle operating conditions online. With the method adopted, on the one hand, the type of a vehicle can be identified intelligently, and on the other hand, the different operating conditions of the vehicle can be identified, and therefore, the requirements of vehicle condition monitoring can be satisfied. The method of the invention includes the following steps that: steps 1, vibration signals of a vehicle are acquired, de-noising processing is performed on the vibration signals; step 2, signal characteristic value extraction is performed on the de-noised vibration signals; and step 3, intelligent working condition identification is carried out according to characteristic values extracted in the step 2, and the type of the working condition of the vehicle is outputted. The method of the invention is used for monitoring the operating conditions of vehicles.

Description

technical field [0001] The invention relates to a technology for monitoring vehicle operating conditions, and belongs to the field of vehicle performance monitoring. Background technique [0002] Vehicle operating conditions, that is, the process operating status of the vehicle. With the complex and changeable operating conditions of the vehicle, its operating time under different operating conditions will affect its health status and service life. In order to obtain the operating status of the vehicle, it is necessary to monitor its operating conditions. At present, the status monitoring of the vehicle mainly collects the running status data of the vehicle and adopts the offline processing method to evaluate the running status of the vehicle. There is a lack of effective online monitoring means for the operating conditions of the vehicle. In order to realize the online monitoring of the operating conditions of the vehicle, it is necessary to design and implement a state mo...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G01M17/007G01H17/00
CPCG01H17/00G01M17/007
Inventor 刘大同牛广行刘连胜彭宇彭喜元
Owner HARBIN INST OF TECH