Remaining Useful Life Interval Prediction for Complex System Based on BiGRU Optimized by Log-Norm

Abstract

The task of remaining useful life (RUL) uncertainty management is the major challenge in solving the failure of the complex mechanical system. Primary research methods use statistical models or stochastic processes to fit the distribution of historical degradation data. However, it is difficult to accurately capture the degradation information of monitoring big data through statistics in practice. In this paper, the prediction interval (PI) obtained by the proposed feature attention-log-norm bidirectional gated recurrent unit (FA-LBiGRU) model is adopted to quantify the prediction uncertainty of RUL. Initially, the critical feature vectors are extracted from multi-dimensional, nonlinear, and large-scale sensor signals using the feature attention mechanism. Additionally, the BiGRU network is used to model and learn the time-varying characteristics of the attention-weighted features from the forward and backward directions, and the network parameters are trained by the maximum log-likelihood loss function. Ultimately, the probability density function based on the lognormal distribution is calculated to measure the uncertainty of the equipment RUL. The effectiveness of the proposed method is verified through the well-known benchmark data set of the turbofan engines provided by NASA. The experimental results show that the proposed methods can obtain higher point prediction accuracy for the complex system compared with state-of-the-art approaches and highquality PIs satisfying real-time requirements.INDEX TERMS fusion model, gated recurrent unit, prediction intervals, remaining useful life, system prognostics, uncertainty management.

An MTBWO Algorithm Based on BiGRU Model

“…The BiGRU model [14] used in this paper reduces parameters by combining the hidden state with the cell state and incorporates two unique gates: the reset gate and the update gate. A unidirectional GRU model can only access information from the forward time steps.…”