Cotton Picker Fire Risk Analysis and Dynamic Threshold Setting Using Multi-Point Sensing and Seed Cotton Moisture

Fire hazards during cotton picker operations pose a significant safety concern, primarily caused by cotton blockages and friction-induced heat generation between the picking spindle and seed cotton under high-load conditions. Existing fire monitoring systems typically employ a uniform temperature threshold across multiple sensors. However, this approach overlooks the distinct characteristics of different cotton picker mechanisms and the influence of seed cotton moisture content, resulting in frequent false alarms and missed detections. To address these issues, this study pioneers and tests a dynamic, tiered temperature threshold warning strategy. This approach accounts for key cotton picker components and varying seed cotton moisture content (MC), specifically MC 9–12% and MC 12–15%. Additionally, based on the operational characteristics of the cotton conveying tube, this study proposes monitoring the wall surface temperature of the conveying tube and investigates the threshold for this temperature. Results indicate that during seed cotton open burning, the average temperature is 324 °C for MC < 9%, 261.9 °C for MC 9–12%, and 178.4 °C for MC 12–15%. After transitioning to smoldering, the temperatures were 226.6 °C, 191.5 °C, and 163.5 °C, respectively, with 163.5 °C being the lowest threshold for seed cotton open burning in the cotton bin. For smoldering seed cotton, the temperature thresholds were 240 °C for MC < 9% and MC 9–12%, and 280 °C for MC 12–15%. The temperature threshold for the cotton conveyor pipe wall surface was 49 °C. The friction-induced heat generation temperature threshold at the picking head, determined through combined testing and simulation, is set at 289 °C for MC < 9%, 306 °C for MC 9–12%, and 319 °C for MC 12–15%. The aforementioned tiered early warning strategy, developed through multi-source experiments and simulations, can be directly configured into controllers. It enables dynamic threshold alarms based on harvester location, seed cotton moisture content, and temperature zones, providing quantitative support for cotton harvester fire monitoring and risk management.