- September 09, 2013
- National Instruments Corporation
- Case Study
By Bill Lydon, Editor
Duke Energy, the largest electric power company in the United States, has deployed National Instruments (NI) technology for monitoring, analytics, and diagnostics in their electric utilities in an effort to improve operations and optimize workforce activities.
EPRI & Duke Energy SmartM&D (Monitoring & Diagnostics) Collaboration Project
By Bill Lydon, Editor
Duke Energy has deployed National Instruments (NI) technology for monitoring, analytics, and diagnostics in their electric utilities. The application was described by Bernie Cook, Director of Maintenance & Diagnostics at Duke Energy, Brian Hollingshaus, Senior Project Manager at Electric Power Research Institute (EPRI), and Kamalina Srikant, Market Development Manager at NI, in a keynote presentation at NIWeek 2013 on August 7, 2013 in Austin, Texas.
Duke Energy is the largest electric power company in the United States and has operations in Latin America. Duke and other EPRI member utilities are facing major challenges to maintain an appropriate level of condition monitoring to control costs and increase generation availability to avoid forced outages from equipment failures. Utility industry executives are challenging their staffs to leverage new technologies in an effort to address increasing reliability demands and optimize use of their workforce. These efforts led to collaboration with EPRI (Electric Power Research Institute) so they could address this challenge from an industry perspective. The goal is to use technology innovations to improve operations and optimize workforce activities.
Hollingshaus noted that electric generation equipment is aging with most of them being coal fired systems that are more than 30 years old. Many are being replaced by natural gas turbines because they are more efficient but they are also more complex to operate, monitor and maintain. Compounding the situation is an aging workforce, with an average age of 55 years old, that has the knowledge, experience, and knowhow to monitor and operated these machines. The goal is to use technology to bridge the gaps and address the challenges to keep equipment running at peak performance.
Industry practice has been to send predictive maintenance personnel to remote sites with handheld test equipment, collect hundreds of data samples, return to the office and perform analysis to assess the condition of equipment. This method is obviously highly labor-intensive and time-consuming. Cook illustrated this by describing how they take 60,000 vibration collections a month spending 80% of personnel time collecting data and only 20% analyzing the data.
SmartM&D (Monitoring & Diagnostics)
The collaboration vision is to use technology to identify issues and notify specialists no matter where they’re located so they can do analysis that leads to avoiding downtime and improving operations. The project, referred to as SmartM&D (Monitoring & Diagnostics), is being executed by EPRI, National Instruments and other key vendors to put in place a monitoring and diagnostic infrastructure to be used across all equipment at utilities.
In the case of Duke Energy, they have identified more than 10,000 assets across their fleet of generation where they will place more than 30,000 sensors to detect equipment condition and operation. Monitored equipment includes turbines plus balance of plant equipment including transformers, boilers, valves, motors, pumps, fans and generators. Sensors include accelerometers, temperature sensors, oil analysis sensors, thermal cameras, and proximity probes. The sensors are being connected to more than 2,000 NI Compact RIO units that perform data collection and signal processing.
The sensor information is transmitted wired and wirelessly to plant servers that do alarming and full waveform analysis for plant specialists. This information is also sent to the company’s monitoring and diagnostic center that uses InStep PRiSM pattern recognition and GP Strategies EtaPRO efficiency monitoring & thermal modeling software. The software offers advanced pattern recognition and thermal models to identify small changes in behavior that can be sent to EPRI’s PlantView asset plant management system to identify the fault in its signature database. These systems notify specialists that use National Instruments DIAdem software to remotely perform a full analysis of the data at the remote Compact RIO units. The data is also stored in an OSIsoft PI database for analysis. This is a “Big Data” application generating many terabytes of data every week. To date, 450 CompactRIO systems have been installed in six plants and seven more plants are being added.
Brian Hollingshaus of EPRI summed up the project:
“Smart monitoring and diagnostics - SmartM&D - is as an industry collaborative effort which EPRI is partnering with suppliers and vendors like National Instruments, and utilities like Duke Energy, and other stakeholders to really push the leading edge of this technology to enable advanced condition monitoring and condition assessment. We firmly believe this is a game changer for the industry. The ability to do remote and automated monitoring and diagnostics for plant equipment is an imperative for the cost of power generation.”
Hollingshaus emphasized that with innovative technology available from a wide range of vendors, open architecture, plug-n-play systems are essential for building these applications.
Thoughts & Observations
This is an example of the accelerating trend to have more analytics at the sensor level of systems. It also is part of the overall trend I have been observing of a simplification of automation system hierarchies.
This is a great application for the National Instruments NI 9232 module that is well suited for vibration analysis applications.
The NI Sound and Vibration Measurement software suite enhances the vibration analysis functions that are native to LabVIEW with a collection of NI analysis and signal processing tools for noise, vibration, and harshness for machine condition monitoring. The suite includes industry signal processing techniques including order analysis, torsional vibration, envelope analysis, waterfall graphs, orbit plot, shaft centerlines, and color maps.
Users are being exposed to a great deal of new, flexible, plug-n-play, open architecture and powerful technologies used in automobiles, appliances, computers, games, and smart phones. These architectures and technologies are not incorporated in traditional automation systems. In a recent article I posed this question, “Is it time for a new automation architecture?” . The article is striking a cord with readers and creating an interesting LinkedIn discussion. Feel free to add your thoughts.
Did you enjoy this great article?
Check out our free e-newsletters to read more great articles..Subscribe