The modeling of data acquisition sampling and transmission planning for intelligent maintenance system

Abstract

The modern military weapons are getting much more complicated today. It is necessary to develop an information system that can automatically detects weapon devices problems and alarms before problems occur. Intelligent maintenance system (IMS) is a monitoring system and provides users with important values of remote detected devices. Those values are analyzed by data automatic learning mechanism to find out-patterns between values and the device status before the device fails. The pattern can inform maintenance personnel immediately via network after confirming alarms to enhance devices reliability. To achieve this goal, however, the key point is relied on the effective planning of data acquisition sampling and transmission. Due to the traditional algorithm's failure in determining both the discarding strategy and network bandwidth allocation within the system, this research proposes two methods to improve the known difficulty, one is the optimization of data transmission network bandwidth allocation, and the other is the optimization of the server queue discarding strategy. The methods used in this research can reduce the system development costs and enhance the overall efficiency.