Concepts for validating intelligent process measurements

Abstract

With increased automation, operational validation is vital for effective control, maintenance and management of industrial plants and processes. Validation should be traceable, starting from the interface to the process up to the highest level of operations. At present, validation is focused at the systems level and current methods are based on condition monitoring, and fault detection and isolation techniques using functional, analytical and hardware redundancy. With the focus at the systems level, redundancy methods exploit integration and fusion of information from multiple measurement devices, and thus tend to disregard validation of the operation of the individual devices themselves. Transducers and sensors provide an interface to the process and produce measurement information. Validation of the measurement output from a sensor is imperative in situations where the cost of redundancy may be prohibitive. This paper presents concepts for validating measurements made with intelligent devices. The proposition is that an intelligent device should provide both measurement and condition information. The condition information should be used to assess the validity of the measurement by identifying metrics which describe the sensor and process conditions, respectively. This is the lowest level of validation because it occurs at the interface with the process being monitored. The information required for this level of validation can be obtained by utilizing all the components of the signal produced by a sensor, providing that the sensor has a wide frequency response. An example of a validation approach which follows from this argument is briefly described.