A time–frequency analysis method of electromagnetic signal for coal and rock properties recognition while drilling based on CWT and GAPSO-ROA - Liu, Yang; Si, Lei; Wang, Zhongbin; Wei, Dong; Gu, Jinheng; Li, Xin; Dai, Jianbo (Measurement : journal of the International Measurement Confederation, 2025)
•A time–frequency analysis method is proposed based on electromagnetic detection.•The electromagnetic signals of coal and rock while drilling are analyzed in-depth.•The concept of energy concentration is introduced as the objective function of CWT.•GAPSO-ROA is proposed to adaptively optimize the parameter selection of CWT.•Simulation and experimental analysis have proved the effectivity and superiority. Complex coal seam structures and frequent stress fluctuations in the drilling pressure relief area bring a great challenge for the accurate identification of coal and rock properties (CRPs). Available approach to address this challenge is considered as electromagnetic detection with highly sensitive. Nevertheless, electromagnetic detection technology severely relies on the variability of electromagnetic parameters with different coal and rock, whereas only frequency-domain information is not sufficient to effectively distinguish the CRPs. Therefore, a time–frequency analysis method of electromagnetic signal for recognizing CRPs while drilling based on CWT and GAPSO-ROA is proposed. First, an electromagnetic detection simulation model for coal-rock while drilling is constructed to analyze the relationship between electromagnetic wave propagation characteristics and CRPs. Then, the concept of energy concentration is introduced to build the objective function for parameter selection of continuous wavelet transform (CWT). Additionally, a hybrid swarm intelligence optimization algorithm is developed to adaptively optimize the parameter selection of CWT by intelligently fusing genetic algorithm (GA), particle swarm optimization (PSO), and rime optimization algorithm (ROA). Finally, to validate the practicality of the proposed method, a coal and rock drilling electromagnetic detection experimental platform is established, and several comparison experiments are carried out. The outcomes indicate that the time–frequency diagram mapped by the proposed method possesses significant differences within the frequency and time ranges, greatly enhancing the accuracy of the model for recognizing CRPs.