Vibration event mode identification method

Abstract

The invention discloses a vibration event mode identification method. The method includes acquiring and obtaining the original vibration signals, including the vibration signal and the non-vibration signal, via a vibration sensor; separating the vibration signal in the original vibration signals; denoising the vibration signal; performing feature extraction on the denoised vibration signal and obtaining the characteristic vector including three characteristics of: A performing wavelet packet decomposition on the time-frequency domain and obtaining the energy characteristic vector, B performing the cepstrum analysis and extracting the cepstrum parameter characteristics, and C extracting the signal characteristic on the time domain; and establishing an identification model composed of two grades of classifiers, wherein the first grade of classifier is a classifier based on SVM and divides the vibration events into non-intrusive events and intrusion events by taking the characteristic vector extracted from the vibration signal as the input, and the second grade of classifier performs the identification based on the artificial nerve network for the intrusion events to obtain the classification result.

Description

technical field [0001] The invention relates to the field of pattern recognition, in particular to a method for pattern recognition of vibration events. Background technique [0002] Vibration sensors are everywhere along national borders, railways, industrial pipelines, important places, and residential quarters, and have been widely used in security monitoring and other fields. For example, in the defense along the railway line, potential safety hazards can be found, so that the staff can prevent them in advance; another example is the perimeter defense, which can be used in places such as homes, schools, residences, important institutions, financial centers, etc., to detect external intrusions immediately; in addition, Vibration sensors have also found important applications in earthquake and tsunami detection. However, at present, commercial perimeter intrusion warning systems have appeared at home and abroad, and most of them can only be used to locate the location of ...

AI Technical Summary

Problems solved by technology

However, at present, commercial perimeter intrusion warning systems have appeared at home and abroad, and most of them can only be used to locate the location of possible abnormal events. The method used to identify intrusion behavior is usually to analyze the time domain and frequency domain of the vibration signal, but this method It is somewhat single and limited for identifying complex vibration events

The recognition rate of intrusion behavior is low, that is, it is impossible to effectively distinguish interference events from real intrusion events, resulting in the inability to accurately know the way of intrusion behavior, so that intrusion events cannot be effectively controlled and disposed of

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