Efficient Fault Detection for Industrial Automation Processes with Observable Process Variables
Abstract—In this paper, stochastic models for fault detection in industrial automation processes are investigated. Thereby, nonlinear, time-variant systems are considered. The basic idea consists in building a probability distribution model and evaluating the likelihood of observations under that model. In contrast to the existing methods, this paper considers the practically important case in which measurement noise is negligible and all process variables are observable. This assumption allows the direct evaluation of a probability distribution for fault detection without approximations such as second order statistics or particles. The main part of this paper deals with adequate models for this probability distribution such as Gaussian and Hidden Markov models. Such models require predictions of the expectation values of the respective probability distributions. Regression models such as (multivariate) linear regression models and neural networks are investigated for this purpose. Evaluations are conducted with respect to prediction accuracies and fault detection capabilities of the employed models. Evaluations show superior results of the novel approach compared to existing fault detection methods, which are based on approximations such as second order statistics.
Network-on-Chip Packet Prioritisation based on Instantaneous Slack Awareness
Abstract— Arbitration policies and predictability enhancement measures typically employ packet priority as the decisive parameter. Though packet timeliness is a key attribute, Network-on-Chip designs rarely consider timeliness as a parameter mostly due to the impracticality of utilising time stamping which relay on the notion of a global time. In this paper, we introduce a low overhead approach where packets carry a slack value, which would notify the router of the latency the packet can suffer without any adverse effects. This would enable routers to service late packets (even lower priority ones) by trading the expendable time associated with the high priority packets hence improving overall quality of service. Utilising a Hardware Description Language coded prototype, we demonstrate the effectiveness of the technique and quantify the associated hardware overhead.
Measuring Delays of Ethernet Communication for Distributed Real-Time Applications using Carrier Sense
Abstract—Ethernet is emerging for many distributed real-time applications in industrial environments. It is also considered for substation automation in power systems with regard to IEC 61850 offering many advantages over conventional parallel wiring with analog signals.
Mission-critical for protection and control systems as well as other demanding applications is the end-to-end delay of messages. Beside the frame duration of an Ethernet message on the physical layer, the overall delay is affected by processing times of communication stacks and applications significantly.
A timing analysis of Ethernet frames is possible with standard network interface cards (NICs) but a high-resolution is only given with specific hardware or professional network analyzers. Furthermore, to determine stack processing delays, immediate signals are required from the application prior to the transmission and after retrieval additionally.
This paper proposes a method to measure delays of Ethernet communication with a common transceiver. The achievable timing resolution is less than 0.1µs using a typical micro-controller unit (MCU).
Adaptive Congestion Control in Cognitive Industrial Wireless Sensor Networks
Abstract—Strict quality of service requirements of industrial applications, challenged by harsh environments and huge interference especially in multi-vendor sites, demand incorporation of
cognition in industrial wireless sensor networks (IWSNs). In this paper, a distributed protocol of light complexity for congestion regulation in cognitive IWSNs is proposed to improve the channel utilization while ensuring predetermined performance for specific devices, called primary devices. By sensing the congestion level of a channel with local measurements, a novel congestion control protocol is proposed by which every device decides whether it should continue operating on the channel, or vacate it in case of saturation. Such a protocol dynamically changes the congestion level based on variations of non-stationary wireless environment as well as traffic demands of the devices. The proposed protocol is implemented on STM32W108 chips that offer IEEE 802.15.4 standard communications. Experimental results confirm substantial performance enhancement compared to the original standard, while imposing almost no signaling/computational overhead. In particular, channel utilization is increased by 56% with fairness and delay guarantees. The presented results provide useful insights on low-complexity adaptive congestion control mechanism in IWSNs.