Bearing Fault Diagnosis Using a Vector-Based Convolutional Fuzzy Neural Network

The spindle of a machine tool plays key role in machining because the wear might result inaccurate production and decreased productivity. To understand condition tool, vector-based convolutional fuzzy neural network (vector-CFNN) was developed this study to diagnose faults from signals. vector-CFNN mainly comprises feature extraction part classification part. phase encompasses use layers pooling layers, while is facilitated through deployment network. fusion layer an important by being placed between parts. It combines characteristics then passes information improve model’s performance. experimentally evaluated against existing methods; required fewer parameters achieved highest average accuracy (99.84%) fault diagnosis relative conventional networks, networks. Moreover, superior using vibration signals its counterparts, indicating feasibility for online monitoring.