Reliability assessment of the vertical roller mill based on ARIMA and multi-observation HMM

Figures & data

Figure 1. System framework for machine reliability analysis.

Figure 2. Displacement and hydraulic monitoring points of VRM.

Figure 3. Acceleration monitoring points of VRM’s shell.

Figure 4. Mapping of hidden state and observation for HMM.

Figure 5. The characteristic value sampling of the operating parameters.

Table 1. Parameter estimation of ARIMA model for the positive pressure signal

Variables	Coefficients	Variables	Coefficients
AR (1)	−1.998	MA (1)	−1.933
AR (2)	0.9985	MA (2)	0.9256
–	–	MA (3)	0.002142
–	–	MA (4)	0.004805

Table 2. Parameter estimation of ARIMA model for the negative pressure signal

Variables	Coefficients	Variables	Coefficients
AR (1)	−0.9965	MA (1)	−0.7157
–	–	MA (2)	−0.03432
–	–	MA (3)	−0.07581

Table 3. Parameter estimation of ARIMA model for the displacement signal

Variables	Coefficients	Variables	Coefficients
AR (1)	−1.14	MA (1)	−0.936
AR (2)	0.149	MA (2)	0.2338

Table 4. The failure criterion of hydraulic pressure sensor

Hydraulic range (Mpa)	Wavelength variation (pm)	Deterioration degree
(4, 13)	(40, 130)	Normal
(3, 4) or (13, 14)	(30, 40) or (130, 140)	Slight deterioration
(0, 3) or (14, ∞)	(0, 30) or (140, ∞)	Serious deterioration

Figure 6. The discrete observation sequences of hydraulic pressure signal.

Figure 7. Convergence curve of iterative training.

Figure 8. Reliability changing curve.