Manus P. Henry

The self-validating sensor: rationale, definitions and examples

Abstract Traditionally, the industrial sensor has been viewed as a simple signal generator. The application of microprocessor technology, digital communications and fault detection techniques, coupled with increasing demands for measurement quality assurance, have rendered inadequate such a simplistic view. In this paper a new sensor model is proposed which encompasses new demands and capabilities. This self-validating sensor performs self-diagnostics and generates a variety of data types, including the on-line uncertainty of each measurement. A demonstration system is described. based upon a coriolis mass flow meter.

A self-validating digital Coriolis mass-flow meter: an overview

Abstract A new implementation of a Coriolis mass-flow meter transmitter is described. It is based on digital components, and has improved performance compared with the commercial, mostly analogue, transmitter using the same flowtube (transducer). Improvements are found in flowtube control, measurement precision, and performance with two-phase and partially-empty conditions, including batching from empty. The new transmitter is viewed as a second-generation sensor validation (SEVA) demonstrator, in which experience from validating the commercial analogue transmitter has led to a redesign using digital technology. The resulting SEVA transmitter provides improved measurement performance and reduced vulnerability to fault conditions, as well as on-line estimates of measurement quality and fault compensation (Henry and Clarke, Control Engineering practice, 1 (4) (1993) 585–610).

Sensor Validation in Biomedical Applications

Abstract The sensor validation or SEVA project (Henry and Clarke 1991; Henry and Clarke 1993) promotes use of the intelligence in ‘smart’ sensors and the use of standard metrics to efficiently communicate self-diagnostics to the outside world. The standard metrics describe the status of the sensor including on-line uncertainty and a status flag to describe how the current validated measurement value has been derived. The end result is to provide a compact generic description of the quality of a measurement to the controIIer with which decisions as to how to use the measurement can be made. This paper proposes the use of SEVA principles in interpretation of data from biomedical instrumentation in order to aid the decision making process, particularly in critical care. For these pwposes the pulse oximeter and polarographic oxygen tension meter will be used as working examples of typical ‘intelligent sensors’ because they make use of a microprocessor to perform self-diagnostics as well as implementing measurement algorithms.

A neural network to correct mass flow errors caused by two-phase flow in a digital coriolis mass flowmeter

Abstract Coriolis mass flow meters provide accurate measurement of single-phase flows, typically to 0.2%. However gas–liquid two-phase flow regimes may cause severe operating difficulties as well as measurement errors in these flow meters. As part of the Sensor Validation (SEVA) research at Oxford University a new fully digital coriolis transmitter has been developed which can operate with highly aerated fluids. This paper describes how a neural network has been used to correct the mass flow measurement for two-phase flow effects, based entirely on internally observed parameters, keeping errors to within 2%. The correction strategy has been successfully implemented on-line in the coriolis transmitter. As required by the SEVA philosophy, the quality of the corrected measurement is indicated by the on-line uncertainty provided with each measurement value.

Keynote paper: Hardware compilation - A new technique for rapid prototyping of digital systems - applied to sensor validation

Abstract This paper provides tutorial introductions to Field-Programmable Gate Arrays (FPGAs) and the concept of hardware compilation - the translation of a high-level programming language directly into a hardware design. As an illustration, a simple stepper motor control program is presented. The research aims of the sensor validation programme are described, and the benefits of using hardware compilation techniques are presented. This leads on in the conclusion of the paper to a more general discussion of the interaction between research and technology, and in particular the influence of information technology upon control engineering.

A Standard Interface for Self-Validating Sensors

Abstract A sensor provides information to the “next level up” (NLU), which may be a control, alarm or monitoring system, or an operator. Our thesis is that an intelligent sensor should interact with the NLU so as to provide enhanced information - not just the best estimate of the measurand but an associated validity. It is argued that validity has two principal components: “uncertainty” (a real value) and “status “ (taking one of a discrete set of values). These two validity components encompass fault detection and other factors influencing the utility of the data. This interface has been demonstrated on a commercial mass flowmeter.

The fusion of redundant SEVA measurements

The self-validating (SEVA) sensor carries out an internal quality assessment, and generates, for each measurement, standard metrics for its quality, including online uncertainty. This paper discusses consistency checking and data fusion between several SEVA sensors observing the same measurand. Consistency checking is shown to be equivalent to the maximum clique problem, which is NP-hard, but a linear approximation is described. A technique called uncertainty extension is proposed which causes a smooth reduction in the influence of outliers as they become increasingly inconsistent with the majority.

Response of a Coriolis mass flow meter to step changes in flow rate

Abstract Trials have taken place to determine the response of a prototype Coriolis mass flowmeter to step changes in flow rate. The meter typically exhibits a delay of 16 ms, and tracks step changes well. Comparison with previously published results suggests that this performance represents an improvement over several types of current commercial flowmeters. The effect of a correction technique to reduce noise is demonstrated. This is considered valuable, even though it is responsible for 6 ms of the overall delay. A good dynamic response is important in process industry applications with short batch times.

The Implications of Digital Communications on Sensor Validation

Abstract Intelligent sensors and Fieldbus standards for their inter-communication are syneigistic technologies that will greatly enhance process control systems of the future. Intelligence in sensors readily supports local sensor validation and Fieldbus enables timely communication using standard metrics and status values. Combined, they overcome some of the problems inherent in fault detection based on data from analogue sensors. The key features of the new Fieldbus standard of relevance to sensor validation are described. Suitable validation metrics and status parameters are introduced and proposed for consideration within the Fieldbus standard in the application layer. Finally, a brief description is given of a demonstration system which performs on-line validation of Foxboro’s Coriolis Meter, and which generates the proposed metrics.

Remote condition monitoring for railway point machine

This paper presents the research work carried out at Oxford University on condition monitoring of railway point machines. The developed condition monitoring system includes a variety of sensors for acquiring trackside data related to different parameters. Key events to be logged include time stamping of points operation, opening and closing of case cover associated with a points machine, insertion and removal of a hand-crank, loss of supply current and the passage of a train. The system also has built-in Web functions. This allows a remote operator using Internet Explorer to observe the condition of the point machine at any time, while the acquired data can be downloaded automatically for offline analysis, providing more detailed information on the health condition of the monitored point machine. A short daily condition report message can also be sent to relevant staff via email. Finally, experience is reported on the four trackside installed systems.