Equipment malfunction in electric power plant may lead to catastrophic losses which can lead to significant economic losses, as well as harm to the reputation of the utility who is operating the power plant. Therefore, it is desirable to detect anomalous behavior in equipment, that in the future, might lead to damage or failure of that or other connected equipment. Equipment damage can increase operations and maintenance costs as well as result in lost revenue for power producers. A robust and sophisticated monitoring program is likely to avoid such incidences. However, due to the heterogeneity of equipment in an electric power plant, it may be difficult and costly to implement a comprehensive monitoring program. A cost-effective approach is to develop a non-invasive, area-wide monitoring system that, from a distance, can collect signals emitted from a variety of electrical and mechanical equipment and perform data analysis that can reveal potential anomalies or provide an early indication of developing malfunctions. Sensing changes in the acoustic and electromagnetic (AEM) signatures of equipment using sensors that monitor sound pressure (acoustic signature) and electromagnetic data (electromagnetic signature) can be incorporated at a particular angle and distance from the equipment to trend changes in equipment performance, and indicate a potential failure. This type of monitoring is simple, cost-effective, and can survey a large area for the purpose of improving equipment reliability.