###### Abstract  
A method to estimate modal frequency based on empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) is proposed. This method can decrease the difficulties in identifying modal frequency of combine harvesters. First, we used 16 acceleration sensors installed at different test points to collect vibration signals of a corn combine harvester under operating conditions (mass time-varying conditions). Second, we calculated mean value, variance and root mean square (RMS) value of the vibration signals, and analyzed its stationarity of vibration signals. Third, the main frequencies of the 16 points were extracted using the EMD and EEMD methods. Finally, we considered modal frequencies identified by the SSI algorithm as standard, and calculated the fitting degrees of the EMD and EEMD methods. The results show that in different time periods (0-60 s and 60-120 s), the maximum differences of the mean value, variance and RMS value of signals were 0.8633, 171.1629 and 11.3767, and the vibration signal under the operating condition of field harvesting can be regarded as a typical non-stationary random vibration signal. The EMD method had more modal aliasing than EEMD, and when we obtained the fitting equations of EMD, EEMD and SSI methods, the value of the Euler distance between the EMD fitting equation and the SSI fitting equation was 446.7883, while that for EEMD and SSI was 417.2845. The vibration frequencies calculated by the EEMD method is closer to the modal frequencies identified by SSI algorithm. The proposed method provides a reference for modal frequency identification and vibration control in a complex working environment. h 2022  
The research on the modal frequency identification of agricultural machinery has concentrated on the finite element method (FEM) [4; 5], experimental modal analysis (EMA) [6; 7; 8] and operational modal analysis (OMA) [9; 10]. The FEM is widely used to identify the modal frequency of agricultural machinery. Relevant experts and scholars established finite element models for machinery such as harvesters [11; 12], cleaning sieve [13], seeder [14], etc. In the OMA method, authors normally use the frequency response function (FRF) of the structure to calculate modal frequency [15; 16; 17]. In order to rebuild the real operating environment of machinery, OMA method is proposed based on EMA, which only uses output vibration response function to calculate modal frequency. The mathematical methods include enhanced frequency domain decomposition (EFDD) [18; 19], stochastic subspace identification (SSI) [20; 21; 22], PolyMax [23], etc. In relevant research, two or more methods are usually combined to verify the modal frequency of a structure, such as FRF combined with FEM [24; 25; 26], or time-frequency transformation (fast Fourier transform, continuous wavelet transform, short-time Fourier transform) combined with FEM [27; 28]. Furthermore, with the development of modal parameter identification theory, other methods are used to obtain the modal frequency of the mechanical system. [PERSON] et al. used the transmissibility method to calculate the modal frequency of a tractor seat [29]. [PERSON] et al. used the method of dynamic energy analysis to process FEM and obtain modal frequency of a tractor [30]. [PERSON] et al. used a convolutional neural network combined with OMA to obtain modal frequency [31]. [PERSON] et al. used a sequential quadratic program to identify the modal parameters of a support arm [32]. [PERSON] et al. used the random decrement technique (RDT) and an enhanced Ibrahim time method (EITM) to calculate modal frequency [33]. [PERSON] et al. used sensor measured vibration displacement of the structure, calculated the frequency response, and obtained the frequency parameters of the structure [34]. Researchers have already carried out a great deal of basic research, but there are still problems. The FEM method struggles to simulate the boundary conditions under operating conditions accurately.