<title>Minimization of the effect of fault-clearance period in the fault-tolerant sensing of an intelligent system</title>

Abstract

An intelligent system (IS) senses, reasons and acts to perform its required tasks. Sensors are used to sense environmental parameters, and through the computational intelligence the system understands the situation and takes appropriate steps toward the desired performance. To deploy systems for mission- critical applications, the underlying technology should have the ability to detect the failure of the components as well as to replace faulty components with fault-free ones within a specified time window known as fault-clearance period. The presence of fault-clearance period in the perception phase of system operation results in the loss of on-line data from different sensors and the subsequent loss of valuable information about the environmental parameters. After fault- clearance, a repetition of the sensing cycle will not recover the lost data in sensing highly transient non-periodic signals. Moreover, the unpredictable repetition will create significant overhead to satisfy the stringent timing requirements of the system. A new scheme has been developed to minimize the loss of these real-time sensor's data during fault-clearance period. This scheme is based on the restoration of data through parallel sensing. The restoration processes for both dual and triple modular redundancy schemes have been developed. The effects of both hardware and software implementation of voting logic on the performance of the system and the quality of restoration have been shown. It has been shown that this scheme is capable to recover most of the lost data during fault-clearance.