VALVE MAGAZINE Summer 2023

Fig. 1: Example of SWE sensor location. Photo courtesy of Curtiss-Wright.

motion of two objects. These readings can detect internal mechanical damage that is valuable for operational mitiga tion and maintenance planning purposes. An increase in stress waves indicates an increase in component friction and impact events, which can be an early indicator of potential issues such as high energy process leakage across valve seating surfaces. This type of stress wave monitoring can detect valve leakage that bypasses the gen eration process when combined with a complete cycle isola tion program. In some cases, leaking steam cycle valves can

tion software, predictive technology, historical maintenance data and routine testing to provide a basis for extending valve maintenance and testing intervals, as well as a means of early detection of valve seat leakage. Optimum spring characteristics, seat geometry and seat surface finishes are critical to valve seating tightness and subsequent leakage parameters. SWE testing can quantify these maintenance practices into a number that can be trended and analyzed. For example, tightly seated valves typically have SWE readings that are less than the defined upper control limit (UCL) criteria, and leaky valves have UCLs greater than the defined criteria. Since the UCL is a continuous measurement of valve performance, engineers can develop a comparison trend between this data and performance data. Proper atten tion to these SWE measurements enables power plants to quantify maintenance practices and valve sealing ability so that reliable valve performance can be achieved consistently. This methodology has the unique ability to not only accu rately gauge seat tightness of an SRV, but also help engineers and maintenance experts determine the safety margin to cold bar failure. Inputs include thermal imaging data, valve information, data on fuel costs and thermal efficiency calcu lations. Outputs include heat loss calculations plus estimated monetary losses based on cost per megawatt. THE UNIQUE ATTRIBUTES OF STRESS WAVE TESTING Stress wave measurements study seat tightness conditions all the time, such as minute quantities of steam escaping through a faulty valve seat. Unlike other forms of condition monitoring, which measure vibration, stress waves reveal minute vibroacoustic energy changes created by the relative

result in many megawatts of lost generation. These losses are compounded by the undetected valve leakage continuously damaging the valve, increasing the leak, and leading to addi tional losses in generation and increased heat rate. To detect stress waves, a specially designed sensor that is tuned to a specific ultrasonic frequency range is attached to the valve’s surface (see Figure 1). The energy can be mea sured anywhere along the acoustic path that the energy traverses. When steam escapes around the seating surfaces of a valve, it creates stress wave energy, immediately detected by the SWE sensor. This data can be combined with other plant process data, such as pressure, temperature and flow, to detect leaks at an early stage and quantify cycle losses and thermal efficiencies. To analyze the data, a complete Valve Maintenance Opti mization Program (VMOP) includes a pattern recognition software application that acquires data from DCS and other monitoring systems, as shown in Figure 2. The program may also use Equipment Anomaly Detection (EAD) software to diagnose equipment behavior. CASE IN POINT: CONSTELLATION ENERGY Constellation Energy is the nation’s largest producer of car bon-free energy and the leading competitive retail supplier of power and energy products and services for homes and businesses across the United States. Constellation’s nucle ar fleet includes 21 reactors at 12 stations. Each reactor includes from eight to 20 SRVs in main steam service, for a total population of more than 300 SRVs. Over the last 15 years, Constellation has used SWE testing and cycle-isolation technology to detect and eliminate leaks

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