Coal Preparation » Process Control
This report covers two main areas, firstly technical advances in process instrumentation used in coal preparation and secondly, equipment health monitoring systems applicable to coal preparation plant equipment.
In recent years, automation technology has migrated to new methods of transferring information. Increasingly, field sensors, actuators and measuring instruments have internal intelligent capabilities and significant advances in process instrumentation in recent times has seen the development of digital two?way communication buses connecting field instruments to their respective control systems. The integration of computing power into the field instruments themselves has developed to the stage where these can now be regarded as computing nodes.
The "field buses" as they are known, conform to open International (and in some cases pseudo) Standards and provide a vehicle for the proliferation of both process and equipment diagnostics data.
The combination of the computing power available in modern instrumentation and field bus technology allows control applications to be moved from centralised control systems into the field, thus opening control systems outwards without the need to purchase additional equipment.
Field bus technology has been promoted in the past as providing cost savings in wiring, however this is debatable; the real advantage being the ability to report large amounts of data to, now available, powerful predictive maintenance software packages.
Equipment health monitoring systems, in most cases, incorporate analytical techniques that can improve the warning interval before equipment failure occurs. While from a production point of view, equipment may seem to be working correctly, techniques such as thermography, oil and vibration analysis can provide early detection of problems.
World's best practice includes the use of Predictive Maintenance approaches rather than Failure?Based and Preventative Maintenance Techniques. Among the barriers to increased predictive maintenance has been the cost of frequent health testing and extra instrumentation required plus the resources required to analyse the large amount of data provided, however field bus technology and predictive maintenance software overcome these barTiers, providing a knowledge base that translates symptoms through diagnostic stages to maintenance actions.
The ability to map normal operating parameters into maintenance alert systems, the addition of symptom to fault verification and the ability to then validate performance on a reliability model are tools to support the plant goal of maintenance based on equipment condition thus allowing maintenance decisions to be made on production impact and life cycle costs.
It should be noted that process control software and equipment health monitoring software are outside the scope of this report.