Online chatter detection considering beat effect based on Inception and LSTM neural networks

•The ILR-DNN is an effective approach for online chatter detection considering the beat effect.•The LSTM branch can capture the amplitude modulation characteristic induced by the beat effect.•The Inception branch helps to extract multiscale features concerning different machining states.•Results show the ILR-DNN achieves the detection accuracy as high as 97.29%.