Abstract：Because that the alarm mode of current online monitoring system is hard to warn early mechanical failure, an early warning methodology is proposed in this paper. Based on statistical analysis of mass data in online monitoring system, taking advantage of dynamic self learning threshold algorithm calculates warning threshold, and using ℓ1 trend filtering technology obtains filtered trend which has eliminated random errors. With dynamic self-learning threshold instead of general alarm threshold on monitoring system, early warning can be acquired by comparing the self-learning warning threshold and filtered trend. It can be shown form the project cases that early warning of mechanical failure can be achieved by the proposed method, which plays an important role in preventing occurrence of mechanical failure.
2014, Vol. 33 
