Bolt vibration signal correction method based on white noise statistical characteristics

Abstract

The invention discloses a bolt vibration signal correction method based on white noise statistical characteristics for correcting vibration signals detected by a bolt vibration detection unit arranged on a tested bolt. The method comprises a first step of carrying out empirical mode decomposition on the vibration signals in which empirical mode decomposition is carried out on the vibration signals detected by the bolt vibration detection unit, and n intrinsic mode function components and a trend term are acquired, a second step of carrying out effectiveness recognition on the intrinsic mode function components in which an intrinsic mode function component effectiveness recognition module is called, and according to a pre-built white noise approximate entropy distribution interval module, effectiveness recognition is carried out on the decomposed n intrinsic mode function components, and a third step of carrying out signal reconstruction in which all recognized effective intrinsic mode function components after empirical mode decomposition is carried out on the vibration signals are used for reconstructing the vibration signals. The method of the invention has the advantages that the step is simple, the design is reasonable, realization is convenient, the use effects are good, the bolt vibration signals can be effectively corrected, and the real vibration state of the bolt can be acquired.

Description

technical field [0001] The invention relates to a signal correction method, in particular to a bolt vibration signal correction method based on white noise statistical characteristics. Background technique [0002] According to the safety production regulations of coal mining enterprises (that is, "Coal Mine Safety Regulations"), before production, technical means such as drilling, geophysical prospecting and roadway exploration should be used to detect the geological structure, hydrogeology, environment, coal, rock formations and other relevant geological conditions, prevent gas outburst and water inrush accidents, and ensure safe production. However, with the increase of coal mining depth and mining scale in my country in the past ten years, the mining conditions have become more complex; and the traditional advanced detection method cannot dynamically and high-resolution track the near-field coal and rock fracture field of the fully mechanized mining face Variety. Among ...

AI Technical Summary

Problems solved by technology

Because EMD uses the local extremum information of the signal to screen the IMF component is one of the reasons for the generation of false modes. In addition, due to the noise interference mixed into the detected vibration signal, false extremum points appear in the real signal, which also leads to some high-frequency Spurious modes such as noise and low frequency components

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