Effective data collection and conditioning monitoring of auxiliary equipment are vital tasks for a modern power plant operator. Plant IQ is the latest response to this, which RWE is implementing, and is now adopting Wi-Fi technology to carry out this more effectively.
The energy market in the 21st century is an immensely competitive environment. Commercial pressures have meant that plant often operates beyond its original design life, and at times outside the original operational specifications.
In the power industry, various techniques are used to monitor plant condition. High-cost commercial systems are predominantly employed to monitor steam and gas turbines, whereas labour intensive, manual collection is still commonplace for smaller items of auxiliary rotating plant. The task of manual data collection will be familiar to many plant operatives, and normally consists of a time-consuming, periodic circuit of the plant with a handheld device.
If carried out infrequently this approach can prevent engineers gaining a clear understanding of plant behaviour. This in turn impacts on the early identification of problems, which is essential if maintenance is to be planned effectively and distressed plant kept in service with confidence until a convenient shut down time is available for repairs.
Figure 1: Rotor flux waveform with shortened turn
Plant availability is a critical factor, so a cost effective automated approach to data collection on auxiliary plant is highly desirable. Plant IQ is RWE Power International’s (RPI) response to this.
Ease of use & low cost
The drive behind the development of Plant IQ was the identification of a gap in the market between high cost, commercial on-line monitoring systems and manual data collection for smaller items of rotating plant, such as pumps, fans and gearboxes. RPI’s aim was to produce an easy-to-use tool for condition monitoring that would make data analysis both efficient and effective. At the same time, the system had to be low cost and flexible enough to replace the data collection previously achieved through manual measurements.
Continuous plant monitoring systems in general produce large amounts of data that make the process of data analysis extremely time consuming. Plant IQ, in contrast, uses a unique alarm checking algorithm to continuously compare plant measurements to known good reference data, and automatically highlights any changes allowing analysts to concentrate on problems rather than routine data analysis.
Plant IQ’s first UK installation was at Scottish Power’s Long-annet station, where it was fitted during a statutory outage in 1995. Prior to its installation, each month staff toured the plant and manually collected data. They took vibration and temperature readings, and noted the general condition of key auxiliary plant, i.e. ID fans, FD fans, main boiler feed pump, auxiliary boiler feed pumps, DA lift pumps and condensate extraction pumps. A paper report was then prepared and submitted to the station’s reliability engineer for review. The introduction of the Plant IQ system completely changed this process.
Since its initial installation, Scottish Power has added Plant IQ to all other units at Longannet, and is now monitoring 74 items of rotating plant, with further expansion planned.
Plant IQ also underwent development at the station to incorporate specialist electrical monitoring techniques that had previously required periodic manual measurement. These included motor current signature analysis to provide condition assessment of key induction motors, flux monitoring using search coils to detect shorted turns in large generator rotors, and the analysis of shaft earth currents to detect electrical faults and prevent bearing damage in large turbo-generators. By combining electrical condition data with vibration data, and correlating with process measurements within the same system, a powerful tool is created that provides a total condition assessment of the plant. This approach facilitates the identification of the root cause of plant problems, rather than the traditional approach of using separate and independent electrical and mechanical measurements.
Gordon Thomson, reliability and condition monitoring engineer at Longannet, knows only too well how the availability of regular data has improved operations at the station. “Plant IQ gives engineering and operational staff the capability to view the current condition of a plant item on a 24/7 basis, which in turn allows us to diagnose and detect the development of problems. This diagnosis has allowed us to plan work on these items, rather than have them fail and cause the potential loss of around 300 MW, or half a unit’s worth of power in some cases.”
The Plant IQ system recently demonstrated its ability to detect and manage a problem with one of the 300 MW generator at Longannet. The system was being used to monitor the air gap search coils on all the generators at the plant. Shortly after a rewound rotor was returned to service an intermittent shorted turn on the pole face winding was detected and soon became a permanent feature. The search coil waveform (Figure 1) showed a difference in the flux on the corresponding ‘A’ side and ‘B’ side windings (red), confirming an electrical fault in the rotor. The alternator also showed in-creased vibration, with a high correlation to rotor current that is consistent with thermally induced bending of the rotor (Figure 2).
Generator experts from RPI monitored the problem remotely for a further three years, allowing continued operation until the next major planned outage. A subsequent inspection of the rotor at the OEM works revealed that a failed connector to the pole face winding was the cause of the shorted turn. The problem was subsequently proven to be due to a manufacturing defect during the original rewind, so the repair was made at no cost to the customer.
One specific benefit of the system at Longannet has been its ability to provide access to data remotely using a combination of the ethernet and the internet. This has allowed plant staff to make ‘first pass’ judgements on particular problems with-out the need to visit the site.
RPI has the advantage of being independent of any equipment manufacturer, so it is able to select ‘best-in-class’ instrumentation to ensure the optimum measurement integrity at the best price. Plant IQ, therefore, supports instrumentation from a number of manufacturers. One company is UK based Icon Research Ltd, which by working in tandem with RPI, has been able to design hardware that maximizes the capabilities of Plant IQ.
Figure 2: Correlation with vibration and excitation current
Initially, Plant IQ used Icon’s Intelligent Transducer Adaptor (ITA) series hardware. However, as ethernet usage spread from the office to the industrial environment, Icon began to explore the potential of the medium for condition monitoring data acquisition. Subsequently, Icon’s Iconet on Ethernet System using ITA nodes became the backbone of Plant IQ.
By locating the instrumentation at or near the plant being monitored, and using existing plant network infrastructure, the ITA node technology eliminates the requirement for extended cable runs to a central location. The distributed hardware approach makes the system highly scalable, and therefore easy to increase plant coverage by deploying additional instrumentation.
The ITA series hardware is designed to interface with almost any sensor type used for machinery monitoring, and can also accommodate static parameters, such as temperatures and pressures, for the monitoring of process measurements. It also provides on board programmable signal conditioning: gain, high and low pass filters, integration, etc, configurable on a per channel basis.
In addition to the measurement channels, the ITA series hardware also provides four channels to allow measurements to be synchronized to trigger a signal, such as a shaft once per revolution pulse. This allows techniques such as order analysis to be performed on vibration measurements.
Incorporating this type of distributed hardware Plant IQ’s operating performance has been proven at a number of facilities, and for a wide variety of applications that include:
- Vibration monitoring of key auxiliary rotating plant in both fossil and hydro power plants
- Pump performance monitoring at a CCGT plant
- Cooling tower fan monitoring at a petrochemical plant
- Monitoring of reactor coolant temperatures at a nuclear power station
- Monitoring of electrical condition of large generators at both fossil and CCGT power plants
- Monitoring of rotor and stator condition for critical induction motors at both fossil and CCGT plants
There is little doubt that the proliferation of this type of monitoring system has helped plant analysts deliver a more effective condition monitoring regime. The use of standard ethernet communications between components to facilitate the use of existing plant infrastructure, coupled with a modular scalable design, helps to keep installation costs to a minimum. It also ensures a low cost per point, with a low entry cost for smaller systems. Furthermore, being able to locate measurement modules at the plant also helps to reduce cabling costs.
That said, this form of hardwired set-up does have its limitations. Permanently installing cables can still be an expensive and time-consuming process, especially when difficult to reach or hazardous areas of plant are included.
With wireless technology (Wi-Fi) now being recognized as a reliable technology in a harsh industrial environment, new opportunities are opening up in condition monitoring. Wi-Fi offers the potential for dramatically reducing installation costs, often by up to two thirds of the cost of a hardwired system, and typically has a much quicker deployment time. Equipment can also be moved around if necessary, making it ideal for temporary installations (often necessary due to cost limitations), with no cables and connectors that can be damaged.
In the United States Wi-Fi technology has been incorporated into the Plant IQ system using state-of-the-art wireless transducers that eliminate the need for permanent cabling. This means plant data can be accessed globally via the ethernet or internet.
Figure 3: Eight-channel Wi-Fi instrument
This system upgrade was successfully implemented at a nuclear power plant in Texas, and remains in long-term operation. In this project, which was funded by a major research institution, wireless sensor networks supplemented existing hardwired systems to provide predictive maintenance. Furthermore, the Wi-Fi system was designed by plant staff to suit their specific requirements, with external help sought for the sensor network and associated software.
A subsequent comparison of information collected by the wireless sensor network and the traditional hand-held methods was made and highlighted a direct correlation. The trial also successfully demonstrated the system’s Wi-Fi capability in a harsh operating environment.
In contrast, the adoption of wireless condition monitoring in the UK industrial environment has some way to go before it matches the level of use that currently exists in the USA. As a result, the majority of Wi-Fi Plant IQ systems are currently sold abroad.
Ted Hopenwasser of Zeefax Inc., the appointed agent for Plant IQ sales in the USA, believes the fact that Wi-Fi internet use is more prevalent in everyday life in the United States than in the UK is likely to be a contributory factor in the increased use of wireless technology in US industrial environments. However, looking to the future he is confident that “As domestic adoption of Wi-Fi technology in the UK increases, it won’t seem so alien and industrial adoption will rise as a result.”
It is important to remember that some plants lend themselves better to collection by hardwired systems, while others such as those located in remote or hazardous locations are more suitable for Wi-Fi. However, what Wi-Fi certainly provides, as Hopenwasser explains, is greater flexibility,
“In nearly all cases, networks will be set up for a combination of wireless and hardwired use. Some plants will be right for wireless use, others will not, and PCs can deal with both approaches in a seamless way. Wireless is undoubtedly very useful for inaccessible areas of a plant.”
Hardwired systems are generally accepted as being more expensive to install than wireless systems, which can understandably make cost justification extremely difficult.
Wireless technology drastically reduces the time and cost of installing permanent systems, and provides added flexibility with the ability to move wireless sensors quickly and cheaply where investigation is required.
As wireless monitoring continues to prove its reliability it is easy to forget that the technology is still in its infancy. In the same manner that satellite television can sometimes be disrupted by weather conditions, wireless monitoring can also be interrupted. While not impacting on the capability of Plant IQ, which carries out surveillance on a pre-set schedule, it does mean that the technology is not currently suitable for mission critical plant control systems. However, antennae and industrial access point technology is improving all the time, making wireless more immune to interference, and therefore increasing its effectiveness within a power plant environment.
With predictive maintenance set to remain an integral element of plant optimization, RPI recognises the importance of remaining at the forefront of all technological developments that have the potential to enhance the Plant IQ system’s capabilities even further. A recent development is an eight-channel instrument (Figure 3) that can digitally interface a variety of standard sensors directly to the internet using Wi-Fi communications, reducing the cost of vibration measurement on a per-channel basis even further.
Phil Orpin of RWE, who has been closely involved with the system’s development, explains “PlantIQ has been the subject of a number of significant upgrades since its launch and is certain to undergo more. For operators that cannot contemplate the loss of availability of key distressed plant, but don’t have the resources for manual monitoring, PlantIQ provides the opportunity to manage problems and schedule maintenance when convenient The positive feedback from users, including RPI technical consultants, has revealed that the system has already prevented a number of significant plant failures and saved a considerable amount of money.” He added that, “ We think that Plant IQ will alter the culture of predictive maintenance, allowing experts to concentrate on solving problems rather becoming pre-occupied with data analysis. This is definitely a change for the good within the industry.”