Optimized neuro genetic fast estimator (ONGFE) for efficient distributed intelligence instantiation within embedded systems
Francisco J. Maldonado, Stephen Oonk, Tasso Politopoulos · 2013
The Optimized Neuro Genetic Fast Estimator (ONGFE) is a software tool that allows for embedding system, subsystem, and component failure detection, identification, and prognostics (FDI&P) capability by using Intelligent Software Elements (ISE) based upon Artificial Neural Networks (ANN). With an Application Programming Interface (API), highly innovative algorithms are compiled for efficient distributed intelligence instantiation within embedded systems. The original design had the purpose of providing a real time kernel to deploy health monitoring functions for Condition Based Maintenance (CBM) and Real Time Monitoring (RTM) systems in a broad variety of applications (such as aerospace, structural, and widely distributed support systems). The ONGFE contains embedded fast and on-line training for designing ANNs to perform several high performance FDI&P functions. A key advantage of this technology is an optimization block based upon pseudogenetic algorithms which compensate for effects due to initial weight values and local minimums without the computational burden of genetic algorithms. The ONGFE also provides a synchronization block for communication with secondary diagnostic modules. The algorithms are designed for a distributed, scalar, and modular deployment. Based on this technology, a scheme for conducting sensor data validation has been embedded in Smart Sensors.