This paper looks at the multiple characteristics and investigations of two grinding anomalies: grinding burn and grinding chatter. A genetic programming (GP) of multiple classifications was investigated for different machining strategies and associated anomaly phenomena. Such a GP paradigm could evolve rules to provide the correlation between monitored signals and grinding phenomena. The investigation also looks at both Short-Time Fourier Transforms (STFT) and Wavelet Packet Transforms (WPT) to convert the raw acoustic emission (AE) signal into a time based frequency signal, segmented into different frequency bands. A set of encouraging results is presented.