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Purpose -In order to find the relationship between operation machine status and oil monitoring information, the oil monitoring information characteristics abstraction and fault diagnostic system is established. The purpose of this paper is to find an effective method to monitor and diagnose the machine running status, and consequently, serve the industry. Design/methodology/approach -The operation status information of equipments is obtained through applying the methods of statistical, trend, entropy and clustering characteristics as a whole; and the multi-characteristic integration method is established based on the existing literature, industry practices and oil characteristic analysis. Findings -Using multi-characteristic integration method, an oil monitoring and diagnostic system is established based on the above status information. This multi-characteristic integration method is applied to D-100/8 air compressor sets in the status monitoring project of a shipbuilding company. The analysis conclusions of the operation status can be obtained promptly and accurately by the method, and can provide guidance for the equipment maintenance. Originality/value -A novel comprehensive oil monitoring data processing method are presented in this paper, which can scientifically distill latent laws among the monitoring information and detect accurately the measurement index of the fault states and abnormity data.