Vibration‐Induced Triboelectric Signal Waveform Characteristic Enrichment Enabled by Fabricating Micron‐Scale Reinforcing Phase

ABSTRACT Recent advancements in triboelectric vibration sensor technologies have enabled the monitoring of mechanical vibration signals, opening new opportunities for intelligent manufacturing applications. Enriching the signal waveform characteristics is beneficial for enhancing sensing accuracy. However, the present strategies remain insufficient in promoting surface charge retention, as modulation of multi‐component composite design remains challenging. Hence, effective strategies for simultaneously improving charge generation and stability are developed to enrich the waveform characteristics of triboelectric signals based on the systematic design of unique polydimethylsiloxane (PDMS)/reinforcement phase interfacial architectures. Micron‐scale polyamide 6@carbon black (PA6@CB) composite particles are synthesized via in situ polymerization. The triboelectric effect occurs simultaneously at both the PDMS/PA6@CB and PDMS/honeycomb nickel interfaces, thereby enriching the triboelectric signal waveform. Specifically, a clear correlation exists between the input vibration characteristics (frequency, waveform, and amplitude) and the triboelectric output signal waveform. Besides, the integration of a deep learning algorithm enables high‐resolution classification of vibration states, achieving effective monitoring on the operating status of the mixer shaker, jaw crusher, and vibrating screen. The prepared TENG vibration sensors demonstrate a promising potential to detect machine working conditions.