基于模拟退火的粒子群算法优化的二次回归在矿井通风机故障诊断中的应用

Based on simulated annealing particle swarm optimization quadratic regression in mine fan fault diagnosis

针对矿井通风机故障诊断过程中样本数据有限的特点,提出了一种经模拟退火的粒子群算法优化的二次回归诊断方法。将样本数据分为建模数据和测试数据,测试结果表明该方法具有适用性强、操作简单、精准度高,且无需太多样本数据等特点,值得推广。

According to the characteristics of the sample ventilator fault diagnosis process limited data, we propose the simulated annealing particle swarm optimization algorithm two regression diagnosis method. The sample data put into the modeling data and test data,test results show that the method has strong applicability, simple operation, high accuracy, and does not need too many features such as sample data, worthy of promotion.