Method of generating model crash waveforms for testing vehicle crash detection systems

• US 5,251,161 A
• Filed: 02/25/1992
• Issued: 10/05/1993
• Est. Priority Date: 02/25/1992
• Status: Expired due to Term

• Current Assignee: Automotive Systems Laboratory, Incorporated (Ningbo Junsheng Investment Group Co., Ltd.)
• Original Assignee: Automatic Systems Laboratories Limited (WIKA Alexander Wiegand SE & Company KG)
• Inventors: Gioutsos, Tony, Piskie, Michael A.
• Primary Examiner(s): Harvey, Jack B.
• Assistant Examiner(s): BUROKER, BRIAN
• Application Number:
  US07/841,381
• Time in Patent Office: 588 Days
• Field of Search: 364/578, 364/424.05, 364/424.01, 364/425, 364/566, 307/10.1, 180/271, 180/282, 280/734, 280/735, 340/436, 340/438, 340/655
• US Class Current: 703/2
• CPC Class Codes: B60R 21/0132 responsive to vehicle motion parameters , e.g. to vehicle longitudinal or transversal deceleration or speed value
• CPC Class Codes: B60R 21/01332 by frequency or waveform analysis
• CPC Class Codes: G01M 17/0078 Shock-testing of vehicles

Abstract

A method of modeling a vehicle crash waveform to generate an infinite set of crash waveforms comprises breaking down a predetermined crash waveform into a crash pulse (signal of interest) and multiplicative noise signal. The multiplicative noise signal is then statistically characterized as a function of time. Randomly variable waveforms from a white noise generator are then modified with the statistical characterization and multiplied with the signal of interest to generate the infinite set of model crash waveforms. These model crash waveforms can then be used to evaluate the performance of crash detection system in accordance with a "Monte Carlo" probability determination technique.

Claims

1. A method of modeling a vehicle crash waveform comprising the steps of:

separating a signal of interest from a predetermined crash data set;

generating a signal indicative of noise present in said predetermined crash data set based on said signal of interest;

generating information characteristic of said noise signal;

generating a randomly variable waveform;

modifying said randomly variable waveform with said characteristic information; and

combining said modified randomly variable waveform with said signal of interest to generate said model crash waveform.

4. The method of claim 1 further comprising the step of generating a plurality of randomly variable waveforms, and wherein said steps of modifying and multiplying generate a corresponding plurality of model crash waveforms.

2. The method of claim wherein said signal indicative of noise is representative of multiplicative noise present in said crash data set.

3. The method of claim wherein said step of generating information characteristic of said noise signal comprises determining a mean and variance of said noise signal as a function of time.

5. The method of claim wherein said step of combining comprises multiplying said modified randomly variable waveform with said signal of interest.

6. A method of evaluating a vehicle crash detection system performance comprising the steps of:

separating a signal of interest from a predetermined data set;

generating a signal indicative of noise present in said predetermined data set based on said signal of interest;

generating information characteristic of said noise signal;

generating a plurality of randomly variable waveforms;

modifying each of said plurality of randomly variable waveforms with said characteristic information; and

multiplying each of said modified randomly variable waveforms with said signal of interest to generate a plurality of model waveforms;

inputting said plurality of model waveforms into said crash detection system; and

evaluating said crash detection system performance by determining an average crash detection system response to said plurality of model waveforms.

7. The method of claim 6 wherein said step of evaluating comprises the step of determining a crash detection system actuation probability based on said average crash detection system response.

8. The method of claim 6 further comprising the step of modifying said information characteristic of said noise signal to generate a different set of plurality of model crash waveforms.