Abstract: Ash content of coal is a core indicator in coal washing operation of a coal preparation plant. Realization of online ash monitoring is of vital significance for development of intelligent coal preparation plant. The R & D work in this respect starts from the development of basic core elements and then extends to the study of system integration, system control, spectrum-ash computational model and algorithms. Through the research work, the air-cooled Nd∶YAG solid state laser, the high-efficiency reflection spectrometer and the transmission grating spectrometer, as well as the spectral imaging technology suitable for use under conditions with high matrix effect, the spectrum processing algorithm suitable for online measuring purpose, and the spectrum-ash computational model are successively developed. Based on the research-derived achievements, the laser-induced plasma total coal ash-forming elements detection system is finally developed. As evidenced by result of industrial test at Lvlin Energy & Chemistry Company's coal preparation plant, the system is easy to operate and maintain and can yield a reliable result. The maximum deviation between the measured value and analytical value is 1.06% with an average error of 0.373%; for the measurement of the same coal sample, the average deviation between the system-measured value and analytical value is less than 0.3% with a repetitive error of smaller than 0.2%, which are well up to the specified standard in both precision and measuring accuracy. Compared to the case before the use of the system, the average monthly yield of flotation concentrate is increased by 0.7 percentage point, and the monthly average consumption of flotation agents is reduced by 18 g/t.