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Siemens Joins Power Diagnostics And Specialty Monitors Power Diagnostics remote monitoring system can be combined with Siemens specialty monitors for power plant operation and maintenance by roberta prandi

As fossil fuel-powered energy plants are becoming more sophisticated and as they are increasingly being used to balance power needs of fluctuating renewable resources, the flexibility and reliability of the power plants will need to be more closely monitored. “Renewable energy, like wind and solar energy, is of increasing importance, but especially wind power is not easy to forecast and not at all under control of the utilities due to the nature of the wind,” said Andreas Feldmüller, head of service technology implementation at Siemens AG – Energy Service Division.

Blade tip vibration monitoring and blade stress diagnostics are among several specialty monitor and diagnostic systems offered by Siemens.

“As a consequence, the volatile renewable energy will be fully supplied to the grid and the remaining power demand less predictable and more fluctuating than in the past will
have to be covered by the existing power plants. This will lead to more and faster start-ups and more frequent part-load operation with fast load ramps to increase or decrease power.” To this extent, Siemens developed several systems called specialty monitors to continuously observe specific components or functions in a plant. “Specialty monitors work as standalone as well as add-on solutions, though the highest benefit can be achieved by connecting these monitors to a higher-level diagnostic platform,” explained Feldmüller.

In combination with a diagnostic platform, it is possible to combine data from the monitors with information from standard plant DCS to correlate and process all data together. In addition to the operation monitors typically displayed in the control room of the power plant, specialty monitors give additional insight in the behavior or condition of individual plant components. “For example, the foreign object detection system (FODS) continuously monitors the potential loss of combustion chamber parts to protect the turbine blades and vanes from subsequent damage caused by foreign objects,” Feldmüller said. “The system detects potential blockages of the first row vanes and therefore prevents consequential damage of turbine blades and vanes.”

FODS is an acoustic system based on the analysis of structure-borne noise and the detection of burst signals produced by the impact of loose parts to the chamber or to the guide blades of the turbine. The next example is a specialty monitor that measures the blade tip vibrations of a steam turbine’s laststage laststage blades. “This module may have a special importance for plants that  operate in a more flexible manner, as low-load operation may create higher stresses in the blades than full-load operation,” said Feldmüller. Another specialty monitor in this application is related to generators and other high-voltage components, as described by Feldmüller, “The specialty monitor Siemon HF 10-2 is designed to detect partial discharges and to give power plant operators advance notice of possible damage to insulation. These partial discharges bridge a portion of the high-voltage insulation, and their highfrequency nature can be detected.”

While specialty monitors are often stand-alone systems, Siemens allows customers to adopt these tools according to the operators’ needs, following a three-level approach. “The first level uses specialty monitors to allow the operators a closer and continuous look at the performance or condition of their components. The equipment is permanently installed in the plant and the operator judges trends and deviations from normal behavior on his own,” Feldmüller said. “In this case, several specialty monitors may also be connected to a higher-level diagnostic platform.

Schematic of Siemens single-shaft rotor train with special monitoring and diagnostic systems.

“In the second level, a Power Diagnostics service contract is signed between the customer and the equipment supplier to involve the engineering expertise of the supplier to judge the plant components.” In such instances, expert-based diagnostics takes place in defined intervals such as monthly or quarterly. The specialty monitor’s data, including operational values from the plant controls, is sent to Siemens via CD/ DVD or a network data exchange. The third level of the service concept for specialty monitors uses a daily Power Diagnostics service. “Data from the specialty monitors or a higher- level diagnostic platform is sent with a certain set of predefined operational data to the Power Diagnostics Centre (PDC), which allows the use of advanced Siemens diagnostic tools to correlate all available plant data and analyze trends and unexpected deviations with the help of the expert network,” Feldmüller said.

Power Diagnostics is Siemens’ data acquisition system, first commissioned in 1998. Nowadays, approximately 400 units are monitored worldwide, including gas turbines, steam turbines, generators and combined-cycle balance-ofplant equipment. Power Diagnostics uses a data acquisition system at the site, which transfers the plant data to the Siemens network to detect deviation from normal behavior. Siemens Power Diagnostics engineers check data consistency and completeness on a daily basis. “The PC-based data acquisition system is passively connected to the control system, receiving data from the I&C system along a one-way nonreactivedata highway, with no influence to the site’s I&C system,” said Feldmüller.

The site-based data acquisition system also has real-time data viewing capabilities and graphing tools that can be used locally by plant personnel as well as remotely per customer request for immediate expert support. Training is also available by the Power Diagnostics engineering technician during installation of the system. Feldmüller also emphasized that the Power Diagnostics uses software based on standard, commercially available products. These tools are completed with proprietary software for diagnostics, data processing and data mining using OEM knowledge.

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