A multimodal piezoelectric matrix framework for high-density kinetic energy harvesting in industrial weaving looms

The pressing demand to operationalize electrokinetic energy (EKE) applications in the weaving department of the textile industry is the motivation behind this large-scale study. In order to solve these problems, this paper introduces three new manners of energy conversion for the proposed electrokinetic phenomena. A novel approach to energy harvest optimization is represented by the first approach, i.e., the modified series–parallel piezo matrix. By appropriately arranging a number of piezoelectric devices in serial and parallel forms, this approach achieves unprecedented efficiency gains. Bidirectional linear generation is a second approach, and it reconsiders how to store energy in one way. This deep learning method achieves remarkable enhancement in energy harvesting and optimization with the aid of mechanical force from both forward and backward motions of weaving procedures. The third approach is a field tuning method referred to as unidirectional nonlinear power extraction force tuning. In order to maximize energy recovery, it focuses on specific instances in the weaving cycle where there is maximum kinetic energy. In conclusion, this project is a pioneering step to optimize utilization of EKE in the weaving section of the textile industry. Data-center efficiency, cost reduction, and sustainability are the primary focus areas. This research's value proposition in a nutshell is the conversion of wasted kinetic energy into useful forms with deep-reaching implications for the power landscape of textile industry and beyond.