为了能够快速准确地进行煤岩自动分析，设计了一个数字化煤岩分析系统.该数字化煤岩分析系统是一个集显微图象采集、煤岩成分识别和煤质分析 3大功能于一体的综合性系统.在用该系统进行煤岩分析时，首先使用代价函数极值法实现自动聚焦，然后采用瞬间曝光测试法来实现自动曝光，最后用主分量分析法实现煤岩纹理分析和煤岩成分识别，并应用神经网络实现混煤分析中的函数参数估计.由上述方法构成的煤岩分析系统已投入实际应用，实际应用效果表明，应用该系统不仅提高了煤岩分析的效率和准确性，且运行稳定可靠，在速度和精度方面均令人满意.

Digital coal petrography analysis system introduced in this paper is an integrated system that has three main functions: image acquisition, composition recognition and analysis of quality of coal. The key techniques of this system are auto focus, auto exposure, texture analysis, pattern recognition and analysis of coal petrography. A price function is used to implement auto focus; it is the sum of the gray grads of all pixels in three small windows in the same image, and is determined by the Z Axis of the lens of microscope; the need is met when the function takes extremum value. Auto exposure is achieved by using a test of exposing in a very short time; the correct exposure time can be calculated with the gray histogram of the image obtained in the testing exposure. Studied the features of the composition of coal, the methods of classifying by gray threshold and principal component analysis (PCA) are adopted to implement texture analysis and pattern recognition. Moreover, some other techniques like estimating of parameters by use of artificial neural network are used in this system. The experimental results show that all these methods can greatly improve the efficiency and veracity of analysis of coal petrography. Both the speed and the precision of coal petrography analysis are satisfactory. The system is used in the industrial research successfully.