An Improved Approach of Incomplete Information Fusion and Its Application in Sensor Data-Based Fault Diagnosis

The Dempster–Shafer evidence theory has been widely used in the field of data fusion. However, with further research, incomplete information under open world assumption discovered as a new type uncertain information. classical Dempster’s combination rules are difficult to solve related problems assumption. At same time, partial entropy, such Deng entropy is also not applicable deal Therefore, this paper proposes method framework process and fuse data. This based on an extension assumption, negation basic probability assignment (BPA), generalized rule. proposed can problem obtain more through negative processing BPA, which improves accuracy results. results applying fault diagnosis electronic rotor examples show that, compared other fusion methods, wider adaptability higher accuracy, conducive practical engineering applications.