Abstract: Rolling bearings are the key components of rotating machinery. The working principle and environment determine that they are easy to wear and tear. Fault identification and diagnosis are necessary tools to ensure the safe and reliable operation of the equipment. In engineering applications, the probability of bearing compound faults is higher than that of a single fault, and the identification of compound fault characteristics is more difficult. In this paper, aiming at the bearing compound fault diagnosis algorithm based on vibration signal, various diagnosis algorithms are discussed and analyzed from the point of view of algorithm history, basic principle, application effect, advantages and disadvantages and so on according to the traditional diagnosis and intelligent diagnosis classification. In the end, the research on bearing compound fault diagnosis is summarized and prospected.