TY - JOUR

T1 - Vibration Converter with Passive Energy Management for Battery‐Less Wireless Sensor Nodes in Predictive Maintenance

AU - Bradai, Sonia

AU - Bouattour, Ghada

AU - El Houssaini, Dhouha

AU - Kanoun, Olfa

N1 - Funding Information: Funding: This research was funded by the Bundesministeriums für Wirtschaft und Energie (BMWi), within the project “Entwicklung einer KI‐gestützten, miniaturisierten energieautarken Multisensorplattform als universelle IoT‐Lösung (KI‐NO)” (grant number 16KN087924). Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2022/3/8

Y1 - 2022/3/8

N2 - Predictive maintenance is becoming increasingly important in industry and requires continuous monitoring to prevent failures and anticipate maintenance processes, resulting in reduced downtime. Vibration is often used for failure detection and equipment conditioning as it is well correlated to the machine’s operation and its variation is an indicator of process changes. In this context, we propose a novel energy‐autonomous wireless sensor system that is able to measure without the use of batteries and automatically deliver alerts once the machine has an anomaly by the variation in acceleration. For this, we designed a wideband electromagnetic energy harvester and realized passive energy management to supply a wireless sensor node, which does not need an external energy supply. The advantage of the solution is that the designed circuit is able to detect the failure without the use of additional sensors, but by the Analog Digital Converter (ADC) of the Wireless Sensor Nodes (WSN) themselves, which makes it more compact and have lower energy consumption. The electromagnetic converter can harvest the relevant energy levels from weak vibration, with an acceleration of 0.1 g for a frequency bandwidth of 7 Hz. Further, the energy‐management circuit enabled fast recharging of the super capacitor on a maximum of 31 s. The designed energy‐management circuit consists of a six‐stage voltage multiplier circuit connected to a wide-band DC‐DC converter, as well as an under‐voltage lock‐out (UVLO) circuit to connect to the storage device to the WSN. In the failure condition with a frequency of 13 Hz and an acceleration of 0.3 g, the super capacitor recharging time was estimated to be 24 s. The proposed solution was validated by implementing real failure detection scenarios with random acceleration levels and, alternatively, modus. The results show that the WSN can directly measure the harvester’s response and decide about the occurrence of failure based on its characteristic threshold voltage without the use of an additional sensor.

AB - Predictive maintenance is becoming increasingly important in industry and requires continuous monitoring to prevent failures and anticipate maintenance processes, resulting in reduced downtime. Vibration is often used for failure detection and equipment conditioning as it is well correlated to the machine’s operation and its variation is an indicator of process changes. In this context, we propose a novel energy‐autonomous wireless sensor system that is able to measure without the use of batteries and automatically deliver alerts once the machine has an anomaly by the variation in acceleration. For this, we designed a wideband electromagnetic energy harvester and realized passive energy management to supply a wireless sensor node, which does not need an external energy supply. The advantage of the solution is that the designed circuit is able to detect the failure without the use of additional sensors, but by the Analog Digital Converter (ADC) of the Wireless Sensor Nodes (WSN) themselves, which makes it more compact and have lower energy consumption. The electromagnetic converter can harvest the relevant energy levels from weak vibration, with an acceleration of 0.1 g for a frequency bandwidth of 7 Hz. Further, the energy‐management circuit enabled fast recharging of the super capacitor on a maximum of 31 s. The designed energy‐management circuit consists of a six‐stage voltage multiplier circuit connected to a wide-band DC‐DC converter, as well as an under‐voltage lock‐out (UVLO) circuit to connect to the storage device to the WSN. In the failure condition with a frequency of 13 Hz and an acceleration of 0.3 g, the super capacitor recharging time was estimated to be 24 s. The proposed solution was validated by implementing real failure detection scenarios with random acceleration levels and, alternatively, modus. The results show that the WSN can directly measure the harvester’s response and decide about the occurrence of failure based on its characteristic threshold voltage without the use of an additional sensor.

KW - Autonomous wireless sensor

KW - Electromagnetic converter

KW - Energy harvesting

KW - Failure detection

KW - Passive energy management

KW - Planar spring

KW - Predictive maintenance

KW - Rectifier

KW - Voltage multiplier

KW - Weak vibration

KW - Wideband

KW - WSN

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85126321782&partnerID=8YFLogxK

U2 - 10.3390/en15061982

DO - 10.3390/en15061982

M3 - Journal articles

AN - SCOPUS:85126321782

VL - 15

JO - Energies

JF - Energies

SN - 1996-1073

IS - 6

M1 - 1982

ER -