Abstract

Detection of the loose particles is urgently required in the spacecraft production processes. PIND (particle impact noise detection) is the most commonly used method for the detection of loose particles in the aerospace electronic components. However, when the mass of loose particles is smaller than 0.01 mg, the weak signals are difficult to be detected accurately. In this paper, the aperiodic stochastic resonance (ASR) is firstly used to detect weak signals of loose particles. The loose particle signal is simulated by the oscillation attenuation signal. The influences of structure parameters on the potential height and detection performance of ASR are studied by a numerical iteration method. The cross-correlation coefficient C1 between input and output is chosen as a criterion for whether there is an existing a particle or not. Through normalization, the loose particle signal-labeled high frequency of 135 kHz is converted into the low-frequency band, which can be detected by the ASR method. According to the algorithm, weak signals covered by noise could be detected. The experimental results show that the detection accuracy is 66.7%. This algorithm improves the detection range of weak loose particle signals effectively.

Highlights

  • Loose particles are impurities in aerospace electronic components, which is composed of metal debris, solder slag, conductor skin, etc

  • We introduced a loose particle signal detection algorithm based on the aperiodic stochastic resonance (ASR) system for detecting nonperiodic high-frequency signals and showed this achieved higher classification accuracy

  • An ASR system for detecting weak signals is constructed, and the loose particle signal is simulated by oscillating the attenuation signal

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Summary

Introduction

Loose particles are impurities in aerospace electronic components, which is composed of metal debris, solder slag, conductor skin, etc. PIND signals caused by the small particles whose mass is smaller than 0.01 mg are very weak and submerged in noise background, which makes it impossible to be detected [4,5,6,7,8]. Initial research on SR was limited to the detection of periodic sinusoidal signals in the background of white noise using a nonlinear bistable system. The ASR method is used to detect the weak loose particle signals covered in the noise background for the first time. By fine-tuning the structure parameters, when the cross-correlation coefficient is higher than the threshold value, it is determined that the experimental signal contains weak loose particle signals. The experimental results show that even if the particle signals are covered, noise can be detected. This algorithm effectively improves the detection capability of weakly loose particles

Aperiodic Stochastic Resonance Theory
D λmx2
Establishment of the Bistable Stochastic Resonance System
Experimental Verification
Result
Findings
Discussion
Conclusions
Full Text
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