This book contains results of the theoretical and experimental research of mining and metallurgical machines aimed at developing new methods for condition monitoring, active vibration damping and process control. The main goals are to reduce machine dynamics, avoid abrupt failures, predict resonance phenomena and provide process stability, estimate the remaining useful life of elements, and diminish operational and maintenance costs.
Instead of the usually used data-driven approach, the proposed methodology is based on several known classes of dynamical models, of which some appropriate ones have been implemented for certain types of industrial machines and technological processes (articulated loaders and dump trucks, sieving screens, hydraulic machines, different steel rolling mills). The standard vibration sensors are used and in parallel special instrumentation is developed and tested for wireless torque monitoring and backlash measurement in the drivelines of machines.
The main idea of research is to use the non-stationary regimes, which excite natural modes of vibrations in multibody systems, and apply transient signals processing in conjunction with modal analysis for diagnosing wear of main elements, namely, angular backlashes in drivelines, radial clearances in the bearings, stiffness changes in supports and loosening of bolted joints. The influence of nonlinearities on the machine dynamics is highlighted including statistical distribution analysis and spectral representation of loads. The nonlinear features of multibody systems are utilised as the diagnostic parameters, which provide robustness to external non-Gaussian noise and impulsive disturbances.
The developed model-based condition monitoring and diagnostics methodology is realized in online computerized maintenance management systems and process automation implemented in different industrial plants.
