The invention provides an offshore crane gearbox fault diagnosis device and method based on multivariate data. The device comprises a temperature sensor, an acceleration sensor, an embedded monitoring unit and a remote monitoring and maintenance center. Temperature and acceleration sensors are arranged. A GPRS module transmits collected data to an upper computer. Bearing temperature trend prediction based on a gray model and support vector regression model residual compensation is carried out according to a collected temperature signal. Vibration fault feature extraction is carried out on a vibration signal by using the combination of empirical mode decomposition and envelope spectrum analysis. Gearbox lubricating oil samples are regularly extracted for convention physical and chemical property analyzing and emission spectrographic analyzing. Wear trend analysis and fault early warning are carried out according to the content of metal wear in oil samples. Fusion comparing is carried out on three analysis results to give a gearbox fault diagnosis result. According to the invention, the fault diagnosis accuracy of an offshore crane gearbox can be effectively improved, and the diagnosis result is accurate and reliable.