Cutting tool wear degrades the machining quality and reliability of CNC machine tool significantly in machining processes. Methods for monitoring tool wear online are therefore crucial to implement optimization of the cutting parameters and improvement of manufacturing processes performance. An intelligent tool wear estimation system that integrates condition monitoring, pattern recognition and trend prediction has been presented in this paper. The raw signals contain useful information from several sensors measuring process variables are acquired and analyzed utilizing monitoring units. The obtained feature elements are processed using support vector machine algorithm to identify tool wear degree. The implementation mode and specific functions of the integrated system architecture is detailed described. The experimental results show that the integrated tool wear monitoring system is feasible and effective.