Towards the establishment of effectiveness evaluation indicator system for complex equipment, the one-dimensional convolution neural network is introduced, and a parallel processing framework with multi-scale convolution kernels is constructed.Then, the original data of equipment is learned adaptively from multiple dimensions, then the characteristics are integrated into a new effectiveness evaluation indicator system, which avoids limitation of subjective factors and computational difficulty, and lays a foundation for intelligent methods of effectiveness evaluation.