Key technologies for health monitoring of intelligent mine hoisting systems

At present, health monitoring of mine hoisting systems faces challenges such as large system span and dispersed component distribution, which makes it difficult to achieve full coverage, continuous online monitoring, and cost-effective deployment for key components. Early degradation of key components often manifests as weak features. Under multi-source disturbances and strong noise backgrounds, weak fault information is easily masked, significantly increasing the difficulty of feature extraction. In addition, harsh service conditions and high reliability requirements further complicate monitoring tasks. This study introduces the structural composition and functions of mine hoisting systems, with a focus on analyzing the core requirements for health state monitoring of key components such as the drum, main shaft, steel wire rope, and bearings during long-term service. On this basis, two types of core sensing technologies used in current mine hoisting system health monitoring are described in detail. One type is fixed-point sensing technology based on multiple monitoring signals such as vibration, sound, vision, and temperature, and the acquisition methods, sensing principles, and applicable scenarios of each type of signal are explained. The other type is mobile sensing technology based on inspection using mobile robots and integrated inspection of hoisting conveyances, and the characteristics, operating processes, and application limitations of these technologies are analyzed. In addition, the application of health state assessment methods in the state monitoring of key components of mine hoisting systems is analyzed, and the principles, effectiveness, and characteristics of intelligent assessment methods based on signal processing, machine learning, and deep learning are discussed. The development status and technical characteristics of traditional mine hoisting system monitoring platforms and digital twin platforms are summarized. Based on the existing problems and challenges in current health monitoring technologies for mine hoisting systems, future development directions are proposed, including optimization of sensing under complex operating conditions, intelligent mobile sensing, efficient evaluation models, and integrated monitoring systems.