A Novel Wireless Wear Monitoring Sensor for Grinding Mill Lifter-Bars

This article focuses on the wireless monitoring of rubber lifter-bar wear, which has been used for years in mills to grind ore under harsh environmental conditions. Due to the abrasive nature of the process, worn lifter-bars must be replaced after a certain period to prevent damage to the mill body, which is extremely costly. Since predicting this wear in advance is challenging, replacements often occur at incorrect times, leading to financial losses in the mining industry. Additionally, lifter-bars that are not fully worn are frequently discarded, resulting in unnecessary waste. In this study, two partially conductive resistive sensor probes (RSPs) were designed and embedded into the lifter-bar. The resistance between the RSP terminals becomes part of a proposed modified relaxation oscillator. Due to the applied electric field and the presence of carbon black within the lifter-bar, an electric current related to the degree of wear flows between the RSP terminals, causing the oscillator’s frequency to vary accordingly. A microprocessor-based electronic circuit was developed to convert this frequency into digital wear data. The sensor board contains a transceiver operating at 2.4 GHz with a receiver sensitivity better than -120 dBm. The sensor circuit and antenna are located in a safe area of the lifter-bar, away from the wear zone, for wireless wear monitoring. The proposed sensor was installed on a commercial lifter-bar in an operational grinding mill located in Bingöl Province, Turkey. To verify its reliability, battery power planning was conducted based on the proposed data packet structure, and wear data were monitored over a 100-day period. Despite the thick metallic structure of the mill and the presence of hundreds of rotating metal balls inside, the wireless sensor successfully transmitted signals at -104 dBm with a 2.8 dB signal-to-noise ratio (SNR) outside the mill, achieving a 6 percent wear resolution. Simulations and experimental results showed strong agreement with the theoretical model.