KEYWORDS: Sensors, Energy harvesting, Analog electronics, Power meters, Microcontrollers, Capacitance, Energy efficiency, Transformers, Transceivers, Sensing systems
Monitoring current and voltage waveforms is fundamental to assess the power consumption of a system and to improve its energy efficiency. In this paper we present a smart meter for power consumption which does not need any electrical contact with the load or its conductors, and which can measure both current and voltage. Power metering becomes easier and safer and it is also self-sustainable because an energy harvesting module based on inductive coupling powers the entire device from the output of the current sensor. A low cost 32-bit wireless CPU architecture is used for data filtering and processing, while a wireless transceiver sends data via the IEEE 802.15.4 standard. We describe in detail the innovative contact-less voltage measurement system, which is based on capacitive coupling and on an algorithm that exploits two pre-processing channels. The system self-calibrates to perform precise measurements regardless the cable type. Experimental results demonstrate accuracy in comparison with commercial high-cost instruments, showing negligible deviations.
One of the major concerns in structural health monitoring (SHM) for aerospace systems is the impact localization in plate-like structures. The aim of this paper is to develop a miniaturized, self-contained and ultra-low power device for automated impact detection that can be used in a distributed scheme to control the structural integrity of large isotropic plates, such as those that can be found on an aircraft, without central coordination. The proposed system is based on a geometric composition of 4 different conventional piezoelectric transducers connected to a STM32F4 board equipped with an ARM Cortex-M4 microcontroller and a IEEE802.15.4 wireless transceiver. The processing framework and the algorithm are implemented on-board and optimized for speed and power consumption. The difference in travelled distances (DDOA) and the localization of the impact point are obtained by cross-correlating the signals related to the same event acquired by the different sensors in the warped frequency domain. The performance of the proposed SHM system is analysed in terms of DDOA accuracy and power consumption, showing the effectiveness of the proposed implementation.
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