January-February 2019 NPJ

Nuclear Plant Journal, January-February 2019 NuclearPlantJournal.com 45 2. Developed a test bed to quantify and characterize the changes in electromagnetic signatures of representative equipment as one or more of its internal components were intentionally degraded. This activity has provided baseline electromagnetic signatures by measurement of four types of signals; current, voltage, electric field, and magnetic field. Voltage and current probes, antennas, and near-field probes were used to measure these signals. 3. Representative electrical and physical phenomena that can cause degradation of electrical and I&C equipment have been identified as shown in Table 4. Going forward, these phenomena will be simulated using applicable EMC susceptibility test methods endorsed by the NRC and Electric Power Research Institute (EPRI) such as the MIL-STD-461 and the International Electrotechnical Commission (IEC) 61000-4 series of tests. Where a standard test method does not exist, AMS will develop test methods and procedures to achieve consistent test results during degradation testing. 4. Emissions data from test beds with electromagnetically controlled conditions such as the AMS anechoic chambers and in an electromagnetically diverse environment such as what would be experienced in a nuclear power plant were collected. The environment was simulated using emissions data previously collected by AMS from various locations within nuclear power plants. Because electrical and I&C equipment in a nuclear power plant operate in close proximity to other sources of electromagnetic energy, both “clean” and “noisy” sources of data from a test bed must be employed to determine the best methods for isolating the electromagnetic signatures of the equipment under test from background noise. Future Plans Going forward, the research towards development of SECA will focus on the following tasks: 1. There are three activities associated with the analysis of condition monitoring data. These are fault detection, component diagnostics, and equipment prognostics as illustrated in Figure 2. AMS will verify that fault detection can be accomplished using traditional signal processing algorithms to determine whether or not the electromagnetic signature deviates from its baseline measurement. Any detectable change in the emissions signature of the test bed equipment will serve as proof of concept that a fault introduced into the equipment can be detected using electromagnetic signals. 2. To determine the root cause of a fault requires diagnostic algorithms to compare the emissions signature of the degraded equipment with a database of faulty component signatures already developed through laboratory tests. This research correlation can help identify the most likely cause of a fault within a power supply, whether it’s from a degraded output capacitor, internal rectifier diode, or voltage regulator. Contact: H.M. Hashemian, AMS, telephone: (865) 691-1756, email: hash@ams-corp.com. Table 4. Examples of Degradation Phenomena in Electrical/I&C Components. Figure 2. Selection of Measurements and Algorithms.