Current Measurement and Fault Detection Based on the Non-Invasive Smart Internet of Things Technique - Abhrodeep Chanda; Abhishek Gudipalli (Engineering Proceedings)
Graphing the consumption of daily essentials like electricity and water is crucial for minimising waste and estimating per-user usage in light of the modern-day data acquisition rally for a better understanding of customer consumption and patterns. Traditional methods of electrical measurement require the involvement of a trained professional, while more advanced alternatives can be prohibitively expensive or offer limited customisation options. We address the cost factor, flexibility, and complexity issues by using a non-intrusive clamp current transformer around power lines to measure current, estimate power, and upload it to the cloud with proper statistical data. For domestic and industrial applications, the filtered and referenced outputs are read by a low-cost CPU (ultra-low power) equipped with Wi-Fi, an analog-to-digital converter, and Bluetooth capabilities, which then determines the apparent power with an accuracy of 0.37 to 0.8%. Nonlinearity varies from 0.2% to 0.3% as a function of increasing current; nonetheless, offsets are imperceptible under typical operating conditions. Safety in the event of a sudden, large change in the current profile is one of several factors that determine the current measuring limit, together with the rating of the current transformer utilised and other related filtering, reference, calibration, and coding criteria. Our goal is to make the power consumption statistics accessible on the move at little cost by simplifying the circuit and coding of traditional metres. It is smart in that no hard coding is required to send credentials across routers, and fault signals are detected and relayed in accordance with an algorithm. User-specific servers save data for monitoring and conserving energy usage; users do not need to consult specialists or put their own security at risk. Data are acquired from the power line and sent to the cloud where statistical functions are performed to increase insight into consumption and failure. It has impressive range and accuracy in terms of power and current for residential and business applications.