No abstract

On-Line Continuous Partial Discharge (PD) measurements of medium voltage substations are an excellent way to determine the overall health of the equipment. Partial discharge measurements can provide maintenance alerts to allow scheduling of equipment outages based on actual condition data as opposed to scheduling based on time intervals. PD measurements provide information about the insulation system that is impossible to extract with other methods. Remote monitoring adds additional value to continuous monitoring by relieving customers of the burden of data analysis, readily involving remote experts. This paper discusses the effectiveness of PD measurements using multiple sensors. Multiple sensors provide additional noise reduction and the ability to localize PD activity for measurements made in higher frequency bands. The importance of continuous PD monitoring vs. periodic walk in PD measurements for switchgear is also discussed. PD activity in switchgear can be unstable and dependent on ambient conditions. Negative periodic PD tests in switchgear can result in a false sense of security. Case studies from field experience are presented to support the discussions. INTRODUCTIONOn-line Partial Discharge measurements in industrial environments face three major problems: high noise in the low frequency range, signal attenuation in the high frequency range and significant variation in PD activity over time. A measurement system operating within the 1-20 MHz range with multiple PD sensors distributed throughout the equipment can limit the PD attenuation problem while providing the location of the PD activity. Microprocessor-based signal processing can significantly reduce the background noise. PD sensors include Coupling Capacitors (CC) and Radio Frequency Current Transformers (RFCT). These sensors are used in switchgear line-ups and dry type transformers. Continuous monitoring, compared to infrequent periodic testing, assures that variable PD activity is captured and its correlation to operating parameters such as temperature, humidity, and system voltage is established. Adding remote communication capability to the continuous monitoring system opens the possibility for Remote Monitoring (RM), featuring automatic alarms, remote data access/storage, and instant analysis by PD experts without bringing experts on site. NOISE AND ATTENUATION ISSUESIndustrial noise typically originates from radio communication systems, thyristors firing in exciters and rectifiers, digital metering systems and electronic transducers. Radio noise is typically found in 0.8-1 MHz range and can be avoided by signal acquisition in a higher frequency range. Thyristor firing commonly has pulse widths wider than PD pulses and can be rejected by microprocessor-based signal processing. Rejecting "digital noise" is the most difficult. This problem is resolved by designing "noise immune" sensors. Coupling capacitors directly connected to HV conductors are not susceptible to low frequency noise and "digital noise" commonly does not exist in HV circuits....

No abstract

Predictive diagnostics offering early failure detection of large induction motors applied in metals, pulp & paper and other process industries are becoming increasingly important. As motors grow larger, industry has become increasingly reliant on technologies to detect rotor faults via on line prognostics and arrange optimal maintenance intervals to increase productivity. Traditional broken rotor bar fault detection algorithms have historically relied largely on monitoring changes in the stator current spectra. This often results in nuisance warnings when the motor operates at different load levels, or when baseline data at healthy motor operations are not available. To address this issue, a fault severity evaluation technique is introduced in this paper to detect rotor cage failures using only current and voltage measurements, plus selected motor nameplate data and motor's geometric dimensions. The fault severity index can indicate the possibility of a rotor cage fault even in the absence of baseline data. This guarantees the algorithm's reliability in practical applications. In addition, a decision-making system, including an adaptive filter and fuzzy logic, is proposed to warn the user in the case of a rotor cage failure. Experimental results show that the proposed fault severity evaluation algorithm can reliably reflect the rotor cage status under different operating conditions, which can be further applied in the detection of rotor cage failures. Index Terms--Induction motor, mechanical stress, medium voltage motor, metal industries, process industries, rotor cage fault, thermal stress.I.