When a speech communication is performed in the industrial environment of collaborative operation, the speech is often submerged in the industrial noise. In this case, the effectiveness of speech communication is affected. For the speech environment with industrial noise, a Kalman speech enhancement algorithm using multi-microphone was proposed. In the algorithm, the difference equation in the State Space Model (SSM) was simplified to reduce the complexity, and the denoising signal was obtained in each sampling point to improve the real-time performance. In addition, to further simplify the complexity, the least square method was used to enhance the speech. In experiments, the speech signals and factory noise signals from a public database were used to simulate the noisy speech under multi-microphone environment, and the proposed algorithm was compared with the traditional algorithm. The experimental results show that the proposed algorithm has the output speech-to-noise ratio (a ratio of enhanced speech to residual noise) higher than the traditional algorithm by about 2 dB, and the running time less than 2% of that of the traditional algorithm. At the same time, the delay time of the algorithm is only several milliseconds.