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JUL-AUG 2019

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INTECH JULY/AUGUST 2019 37 AUTOMATION IT units. Thus, a data interface is required to retrieve process data from the SCA DA or control system. Here, we have multiple possibilities. And this is also where the North American Elec- tric Reliability Corporation (NERC) Critical Infrastructure Protection (CIP) standards for cybersecurity have to be consulted. The cybersecurity standards of NERC are aimed at protecting "criti- cal infrastructure" by law. They are enforced in the U.S. for large power plants, for example. But their exis- tence also increases the awareness of IT security topics in smaller plants and influences other industries. Depending on the total network lay- out of the plant, measures can be used to permit data transfer only in one direction: from SCADA or the control system to OnCare.Acoustic. Such mea- sures may include: l Routers for network separation and with communication traffic control l Protocol converters to connect to existing historians or other data lay- ers on the customer side, instead of connecting directly to the SCADA or control system l Data diodes, and especially physical data diodes. In this case, the connec - tion is established through a single fiber optical channel. Thus, sending data toward the SCADA or control system is physically impossible. Therefore, part of the scope of such new monitoring systems is a thorough site assessment to determine the best possibilities for IT security. Promising results The proposed solution shows prom- ising results and offers opportunities to improve the availability of hydro- power plants by reducing the risk of unplanned outages. It allows plants to recognize degrading equipment early and supports maintenance crews by guiding them to the proper area inside the hydropower plant. It thereby has the potential to also reduce operation- al risk and maintenance costs. By combining the solution with re- mote expert services, it can also con- tinuously guide local crews in gain- ing experience and expert knowledge faster. It is easy to retrofit for existing hydropower plants, even without ex ist- ing monitoring systems. Unmanned power stations and hydropower plants in remote areas with only limited ac- cessibility especially benefit from such an advanced and integral monitoring approach. It is a safe and secure so- lution due to the network separation from any existing SCADA or control system. Building on the experience gathered from the first long-term installation of the system, similar, if not the same, algorithms can be applied to existing data from classical monitoring systems. This will have even greater potential to detect possible equipment failures. Overall, enriching the existing portfo- lio of monitoring solutions by cloud- based approaches brings new benefits to the operators of hydropower equip- ment and will lead to predictive main- tenance strategies in the future. n ABOUT THE AUTHOR Rudolf Muench, Dipl.-Ing. (Rudolf.Muench@ voith.com), is development project manager and expert for data analytics at Voith Digi- tal Ventures, Germany. Over more than 25 years, he has been working in advanced con- trol systems, artificial intelligence, and data- driven applications for process supervision. Muench studied electrical engineering at the Technical University of Munich. He published multiple papers and holds several patents in the field of automation technology. View the online version at www.isa.org/intech/20190805. Figure 4. Examples of potential failures to be captured by sensing audible noise (collected from past experience). Power plant type Rated power Type of noise Root cause Damage Kaplan 20 MW Noise at blade passing and gate passing frequency Larger blade tilt resulted in interaction with draft tube man door High vibrations, potential leakage of man door Kaplan 40 MW Rattling of cast oil pressure line Resonance in hydraulic system in certain operating states Potential rupture of pipe Kaplan 160 MW Periodical noise at slip ring Generator unbalance Fire at slip ring Francis 180 MW Transformer noise Audible strange noise was not reported to maintenance Fire in transformer Francis 440 MW High-pitch audible noise Runner blade crack Potential bigger damage Pump storage 50 MW Generator ventilator caused noises around 100 Hz Faulty mounting (insufficient stiffness) Potential loss of equipment Pump storage 240 MW Potentially audible noise inside generator housing Loose rotor fan blades Stator required significant refurbishment RESOURCES "Monitoring, Analysis and Diagnosis" http://voith.com/ca-en/t_3385_e_HyCon_MD_ screen.pdf DIN ISO 7919-5 "Evaluation of machine vibration by measurements on rotating shafts, Part 5: Machine sets in hydraulic power generation and pumping plants" "Python-based ecosystem of open- source software" http://scikit-learn.org/stable "MLlib is Spark's scalable machine learning library consisting of common learning algorithms and utilities" https://spark.apache.org/docs/1.1.1/mllib-guide. html Products and success stories www.amqp.org/about/examples NERC CIP Standards https://www.nerc.com/pa/Stand/Pages/Reliabili- tyStandards.aspx

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