A Wireless Condition Monitoring System Powered by a Sub-100 $\mu$W Vibration Energy Harvester

Jang, Jaehyuk; Berdy, D. F.; Lee, Jangjoon; Peroulis, Dimitrios; Jung, Byunghoo

doi:10.1109/tcsi.2012.2215395

Cited by 24 publications

(9 citation statements)

References 20 publications

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“…To reduce such maintenance operations, wireless sensor nodes are usually designed with restricted computation capability and limited memory to keep their power consumption to a minimum level and thus prolong their lifespan. In recent years, different energy harvesting techniques are emerging to provide power for the sensor nodes by absorbing energy from their ambient environment, like wasted heat [3] or mechanical vibrations [4] from machines. By utilising such energy resources, it is expected to significantly prolong the lifespan of these wireless sensor nodes.…”

Section: Introductionmentioning

confidence: 99%

Efficient implementation of envelope analysis on resources limited wireless sensor nodes for accurate bearing fault diagnosis

Feng

Zhao

et al. 2017

Measurement

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With the fast development of electronics and wireless communication technologies in recent years, intelligent wireless sensor nodes are becoming increasingly popular in the online machinery condition monitoring systems. They bring a number of benefits, such as reduced investment on the installation and maintenance of expensive communication cables, ease of deployment and upgrading. For the condition monitoring of dynamic signals, distributed computation on wireless sensor nodes is getting popular with wireless sensor nodes becoming more computation powerful and power efficient. As a widely recognised algorithm for bearing fault diagnosis, envelope analysis has been previously proved suitable for being embedded on the wireless sensor nodes to effectively extract fault features from common machinery components such as bearings and gears. As a continuation, this paper studies into several envelope detection methods, including Hilbert transform, spectral correlation, band-pass squared rectifier and short-time RMS. Regarding to the fact that only low frequency components in the bearing envelope is of interest, spectral correlation can be simplified for fast calculation and short-time RMS method can be considered as a simplified band-pass squared rectifier, in which partial aliasing is allowed. Thereafter, spectral correlation and short-time RMS are employed to speed up the calculation of envelope analysis on a wireless sensor node, which thereafter provides the potential to reduce power consumption of wireless sensor nodes. The computation speed comparison shows that the spectral correlation method and short-time RMS can speed up the computation speed by more than two times and five times in comparison with the Hilbert transform method. The simulation study shows that spectral correlation and shorttime RMS based methods achieves similar level of accuracy as Hilbert transform. Furthermore, the experimental study shows that spectral correlation and short-time RMS based methods can well reveal the simulated three types of bearing faults while with the computation speed significantly improved.

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Section: Introductionmentioning

confidence: 99%

Efficient implementation of envelope analysis on resources limited wireless sensor nodes for accurate bearing fault diagnosis

Feng

Zhao

et al. 2017

Measurement

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“…Since these devices are implanted, the use of batteries is not desirable because of their bulky size, and replacing a battery leads to a surgical procedure that can cause infections. To eliminate the use of battery, there are various techniques to scavenge ambient energy such as electromagnetic, inductive, thermoelectric, solar and motion energy [6,[8][9][10]. Unfortunately, inductive energy has very limited link distance, and delivering uniform power to multiple nodes is still a challenge [11].…”

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confidence: 99%

“…Electromyography (EMG) data requires more than 2 kbps of sampling rate [2,3], forcing the transmitter to be active more than other high duty-cycled sensor nodes [8,10], which increases the required power of transmitter. To minimize the power consumption of the transmitter, some have used the passive radio frequency identification (RFID) technology for data transmission [12,13].…”

mentioning

confidence: 99%

“…There are numerous multiple access techniques but due to the complexity and power consumption, TDMA is considered in this application. Multiple node operation is a problem that is overlooked in most of the literature and some overcome this by implementing a conventional receiver [8,14] or changing the strength of the powering signal [15], which leads to a significant overhead in power consumption or loss in available power.…”

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confidence: 99%

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An Ultra-Low-Power RF Energy-Harvesting Transceiver for Multiple-Node Sensor Application

Kim

Bhamra

Joseph

et al. 2015

IEEE Trans. Circuits Syst. II

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An ultra low power, wirelessly-powered RF transceiver for wireless sensor network is implemented using 180 nm CMOS technology. We propose a 98 μW, 457.5 MHz transmitter with output radiation power of -22 dBm. This transmitter utilizes 915 MHz wirelessly powering RF signal by frequency division using a true-single-phase-clock (TSPC) divider to generate the carrier frequency with very low power consumption and small die area. The transmitter can support up to 5 Mbps data rate. The telemetry system uses an 8-stage Cockcroft-Walton rectifier to convert RF to DC voltage for energy harvesting. The bandgap reference and linear regulators provide stable DC voltage throughout the system. The receiver recovers data from the modulated wireless powering RF signal to perform time division multiple access (TMDA) for the multiple node system. Power consumption of the TDMA receiver is less than 15 μW. Our proposed transmitter and receiver each occupies 0.0018 mm 2 and 0.0135 mm 2 of active die area, respectively.Index Terms-Energy harvest, low power wireless transceiver, time division multiple access, wireless sensor network.

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“…A 120-Hz, cantilever-type piezoelectric energy harvester has been presented in detail, and the operation of a custom-designed transmitter on the harvested energy with a 1.6% duty cycle has been demonstrated in [15]. A low-power sensor node for condition monitoring in [25] was autonomously powered by a meandering piezoelectric energy harvester excited with 0.45 g at 40.8 Hz. In this battery-free system, initially, the required energy was added up in a storage buffer while the system was off, and after a threshold was reached, the sensor node was turned on to read the sensors and to receive and transmit data within a determined time interval.…”

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confidence: 99%

Powering-up Wireless Sensor Nodes Utilizing Rechargeable Batteries and an Electromagnetic Vibration Energy Harvesting System

et al. 2014

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This paper presents a wireless sensor node (WSN) system where an electromagnetic (EM) energy harvester is utilized for charging its rechargeable batteries while the system is operational. The capability and the performance of an in-house low-frequency EM energy harvester for charging rechargeable NiMH batteries were experimentally verified in comparison to a regular battery charger. Furthermore, the power consumption of MicaZ motes, used as the WSN, was evaluated in detail for different operation conditions. The battery voltage and current were experimentally monitored during the operation of the MicaZ sensor node equipped with the EM vibration energy harvester. A compact (24.5 cm 3 ) in-house EM energy harvester provides approximately 65 µA charging current to the batteries when excited by 0.4 g acceleration at 7.4 Hz. It has been shown that the current demand of the MicaZ mote can be compensated for by the energy harvester for a specific low-power operation scenario, with more than a 10-fold increase in the battery lifetime. The presented results demonstrate the autonomous operation of the WSN, with the utilization of a vibration-based energy harvester. OPEN ACCESSEnergies 2014, 7 6324

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A Wireless Condition Monitoring System Powered by a Sub-100 $\mu$W Vibration Energy Harvester

Cited by 24 publications

References 20 publications

Efficient implementation of envelope analysis on resources limited wireless sensor nodes for accurate bearing fault diagnosis

Efficient implementation of envelope analysis on resources limited wireless sensor nodes for accurate bearing fault diagnosis

An Ultra-Low-Power RF Energy-Harvesting Transceiver for Multiple-Node Sensor Application

Powering-up Wireless Sensor Nodes Utilizing Rechargeable Batteries and an Electromagnetic Vibration Energy Harvesting System

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