inspection intervals of a CBM policy for a deteriorating
system by minimizing the long-run average cost per unit
time. Wang (2003) developed a model for optimal
condition monitoring intervals based on the failure delay
time concept and the conditional residual time concept.
Mohammadi et al. (2011) performed condition
monitoring of MF285 and MF399 tractors using engine
oil analysis to find the optimum life time of tractor
substitution in comparison with the breakdown
maintenance method in Iran.
10 Conclusion
The basic aim of this paper was to reveal the
introducing of preventive maintenance specially
condition monitoring system at supporting maintenance
management of agricultural machinery. So, the primary
focus of this article was reviewing condition monitoring
system and application of it to agricultural machinery.
Then, recent research and developments in machinery
diagnostics and prognostics used in implementing CBM
have been summarized. Various techniques, models and
algorithms were reviewed. Of the three main steps of a
CBM program, namely, data acquisition, signal
processing, and maintenance decision making, the latter
two were the focus.
There are various techniques for supporting
maintenance management each component of agricultural
machinery and for all of these techniques there are
methods available and were referenced in the literature.
The main problems facing the designers of condition
monitoring systems for agricultural machinery obviously
continue to be:
1) selection of the number and type of sensors for data
acquisition step;
2) selection of effective signal processing methods
associated with the selected sensors;
3) design of a sufficient and efficient maintenance
decision making.
Acknowledgments
The authors would like to thank Ferdowsi University
of Mashhad for providing financial support