Non-intrusive load monitoring and disaggregation (NILMD) technology is an important data acquisition method for deep improvement of residents' energy service and the interaction between power supply and demand. However,it is unable to disaggregate accurately the electrothermal load by the NILMD algorithm of edge detection which is widely used in current engineering. In order to solve this problem,a NILMD algorithm for typical electrothermal load based on three dimensional characteristics vector is proposed in this paper. Firstly,the edge detection algorithm is used to extract the electrothermal events through active power,reactive power and current harmonic,and the three dimensional characteristics vector model is constructed together with the non-electric characteristics such as running duration,start and stop times based on active power. Then,the learning rules and algorithm for typical electrothermal load detailed disaggregation are designed by sequential covering. Finally,the disaggregation accuracy of the electrothermal load is more than 85% based on experimental verification. Experimental results show that the NILMD algorithm for typical electrothermal load proposed in this paper effectively improve the disaggregation accuracy of four typical electrothermal load.