Gas Distribution Networks
£134,000.00
Condition monitoring plays an increasingly important role in asset management
and diagnostics for high-value equipment. New technology and advances in
sensing capabilities enable us to understand more about the asset and thus
make optimal maintenance decisions (e.g. maintain on condition). Minimising the
requirements for installation and maintenance of these sensors, and removing
the need for cables and batteries are the key aspects of the desirable fit and
forget functionality.
Existing approaches to substation diagnostics typically involve mains-tethered
instrumentation for data acquisition. It is prohibitively expensive to roll out this
type of scheme widely due to cost and cabling constraints, which inevitably
leaves gaps in condition monitoring coverage that should ideally be filled. In
addition, diagnostic systems have become significant assets in themselves,
requiring trained personnel to operate them. This approach adds additional
complexity to the task of a monitoring engineer, whose primary concern must be
the operational state of plant rather than the intricacies of a diagnostic system.
Therefore, a non-obtrusive, integrated approach to diagnostics should be
followed.
Recent developments in miniaturisation of digital electronic devices have fuelled
the development of wireless sensor network technology. These networks are
made up of a number of discrete sensor nodes, which integrate processing,
sampling, storage and communications capabilities. By taking advantage of this
technology, wireless diagnostic sensors have the potential to increase condition
monitoring coverage without the need for cross-site cabling, simplifying deployment and reducing costs.
Through identifying general requirements for wireless condition monitoring
systems, a modular approach could be defined for a multitude of sensors to be
attached to the same underlying platform (for instance: RF, ultrasonic and
thermal). In addition to sensing, wireless sensors such as this with suitable
analytical capabilities can also support a level of on-board defect diagnosis. By
diagnosing defects on-sensor, the volume of monitoring data can be drastically
reduced at source so that only pertinent defect information is transmitted to
monitoring engineers. This reduces the burden of transmitting data back to
corporate networks, increasing system scalability and minimising the
requirement for wideband communications links.
An initial laboratory study into this type of approach, targeted at Partial Discharge (PD) monitoring,
has resulted in a promising new diagnostic technique built upon wireless sensor
technology. This method has demonstrated detection and basic classification
capabilities and, based on the knowledge gained from this study, implementing
the UHF technique on a wireless sensor node has been recognised as feasible.
Based upon this prior work, a wireless condition monitoring platform technology
demonstrator could be created using partial discharge detection and diagnosis
as a reference application.