As the mining industry continues to expand and international oil prices increase,more rigorous demands are being placed on the design of mining equipment.Given this,there is an urgent need to develop new power-driven ...As the mining industry continues to expand and international oil prices increase,more rigorous demands are being placed on the design of mining equipment.Given this,there is an urgent need to develop new power-driven mining equipment to solve the problems of high energy consumption and insufficient power coupling of current equipment.This study proposed a design of a hybrid power system for underground Load Haul Dump(LHD).The proposed design integrated Quality Function Deployment(QFD)and Theory of Inventive Problem Solving(TRIZ).It identified 7 user requirements and 10 related technical features,formulated 11 innovative design solutions,and ultimately adopting an electric drive hybrid power scheme.This scheme effectively addressesd power transmission coupling problems and improve the efficiency of loaders.A 6 m³hybrid power loader prototype has been developed,which reduces operational energy consumption and advances the electrification and green,low-carbon evolution of mining equipment.展开更多
混合动力铲运机工作环境恶劣,电气系统复杂,故障原因耦合性强,故障种类多,数据大多呈非线性关系,针对传统单一的方法难以精确预测铲运机电气系统故障的问题,提出了一种把最小二乘支持向量机(Least Square Support Vector Machine,LSSVM...混合动力铲运机工作环境恶劣,电气系统复杂,故障原因耦合性强,故障种类多,数据大多呈非线性关系,针对传统单一的方法难以精确预测铲运机电气系统故障的问题,提出了一种把最小二乘支持向量机(Least Square Support Vector Machine,LSSVM)和隐马尔科夫模型(Hidden Markov Model,HMM)相结合并进行改进的故障预测方法。首先用历史时刻的铲运机运行状态数据通过LSSVM进行训练,将当前时刻状态数据输入训练好的LSSVM中预测出未来时刻的状态数据;然后通过历史数据训练不同故障状态下的HMM模型;最后把当前状态数据及通过LSSVM预测的状态数据导入训练好的HMM模型中,预测出未来时刻铲运机的状态及其变化趋势。针对传统用经验方法训练LSSVM参数和用Baum-Welch方法选择HMM参数容易陷入局部最优解和收敛速度慢等缺点问题,提出在LSSVM和HMM参数选择时采用人工鱼群算法(Artificial Fish Swarm Algorithm,AFSA)进行改进,提高了LSSVM和HMM的参数估计性能,得到LSSVM所需的最优惩罚参数和径向基核函数。整个过程所用到的数据是14 t混合动力铲运机在矿山现场工作时采集的数据。研究结果表明,通过LSSVM预测出来的铲运机状态数据与采集到的真实状态数据相比,误差较小,吻合度高。应用优化后的LSSVM-HMM方法进行铲运机故障预测准确率达到了91.1%,该方法能精确预测出混合动力铲运机电气系统的故障及其状态变化趋势。展开更多
文摘As the mining industry continues to expand and international oil prices increase,more rigorous demands are being placed on the design of mining equipment.Given this,there is an urgent need to develop new power-driven mining equipment to solve the problems of high energy consumption and insufficient power coupling of current equipment.This study proposed a design of a hybrid power system for underground Load Haul Dump(LHD).The proposed design integrated Quality Function Deployment(QFD)and Theory of Inventive Problem Solving(TRIZ).It identified 7 user requirements and 10 related technical features,formulated 11 innovative design solutions,and ultimately adopting an electric drive hybrid power scheme.This scheme effectively addressesd power transmission coupling problems and improve the efficiency of loaders.A 6 m³hybrid power loader prototype has been developed,which reduces operational energy consumption and advances the electrification and green,low-carbon evolution of mining equipment.
