In order to solve the problems of the low efficiency of manual detection, the lack of automatic detection methods, the independence of the detection parameters and the difficulty of supporting correlation analysis in corn silage harvester, a multi-parameter data monitoring system for silage machines based on CAN bus and virtual instruments was designed. The monitoring system was composed of operation quality detection device, mechanical parts power detection device, hydraulic component power monitoring device and monitoring software, which can realize systematic measurement and comprehensive analysis of various parameters such as engine speed and torque, stubble retention height, harvesting efficiency, header part speed and torque, chopping roller speed and torque, throwing fan speed and torque, walking part speed and torque, feeding pump inlet and outlet pressure and hydraulic pipeline flow, etc. And the qualification evaluation of the whole machine can be realized under the current national standard. The field test results showed that the multiparameter test system can realize the comprehensive, dynamic, continuous and stable measurement of the operating parameters in the field, and the maximum relative error of torque parameters in the static measurement was not more than ±0.5%. The mean difference between the test groups was not more than 0.75N·m under no-load condition, while the maximum range of the repeatability measurement was 1.28N·m, and the maximum coefficient of variation was 0.012;the monitoring data was always consistent with the actual working conditions under harvesting condition, and the dynamic trend of torque and speed parameters for the whole machine can be accurately obtained under different harvest conditions;the maximum relative error of hydraulic flow parameter in the dynamic measurement was 1.13%, and the relative error was 0.53% under the rated operating conditions. The model regression coefficient of harvesting efficiency measurement was 0.89, while the average relative error was 11.1%. The maximum relative error of stubble height detection was 4.78%. In summary, the comprehensive test system for the corn silage harvester had a good performance communication, and the data collection was stable, accurate and credible, which can effectively reduce the complexity of field detection, and can provide technical support for the online parameters detection, the comprehensive applicability evaluation and the machine design optimization in corn silage harvester.