A highly precise cross-capacitive sensor for metal debris detection in insulating oil

Islam, Tarikul; Yousuf, Mujeeb; Nauman, Mohd

doi:10.1063/1.5139925

Cited by 28 publications

(9 citation statements)

References 18 publications

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“…For instance, an investigation on application of sensor-based chips was analyzed as they had the potential to inhibit oxygen and maintain food quality (Gaikwad et al 2018). In recent years, machines have also been equipped with sensors to detect foreign particles or waste in food (Islam et al 2020). Thus, we can conclude that the utilization of creative and innovative technologies could have a huge potential in changing the methodology of production, delivery, and consumption of foods.…”

Section: Digitalizationmentioning

confidence: 99%

“…The chip, once installed, can detect the quality of the food product within seconds. In recent years, machines have also been equipped with sensors to detect foreign particles or waste in the food production line (Islam et al, 2020). They serve as a dual purpose in helping the whole supply chain in analyzing crop conditions and detecting weeds or pests in large farms thus balancing the overall yield.…”

Section: Digitalizationmentioning

confidence: 99%

See 1 more Smart Citation

Global impact of COVID-19 on agriculture: role of sustainable agriculture and digital farming

Sridhar

Balakrishnan

Jacob

et al. 2022

Environ Sci Pollut Res

134

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The rise and spread of the coronavirus pandemic (COVID-19) has created an imbalance in all sectors worldwide, massively disrupting the global economy. Social distancing, quarantine regulations, and strict travel restrictions have led to a major reduction in the workforce and loss of jobs across all industrial sectors. One of the sectors completely exposed was the agriculture and food sector. The initiation of a nationwide lockdown by the government resulted in the shutdown of industries globally impacting the overall supply chain from farmer to consumer. The need of the hour is to propose effective solutions which can serve the dual purpose of market growth as well as customer satisfaction. This paper reviews the impact of COVID-19 on the agro-food system and its economy stressing critical factors like food production, demand, price hikes, security, and supply chain resilience. To conserve natural resources and meet the sustainable development goals (SDG), importance has been given to adopting sustainable agricultural practices with a prime focus on techniques like urban agriculture, crop rotation, hydroponics, and family farming. Possible advancements like the use of digital tools, mainly artificial intelligence, machine learning, deep learning, and block-chain technology, in the agro-food sector have been discussed as they could be a promising tool to develop a self-reliant society. This work would be a perfect platform to understand the growing impact of the pandemic as well as supporting cost-effective solutions for a green ecosystem.

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Section: Digitalizationmentioning

confidence: 99%

Section: Digitalizationmentioning

confidence: 99%

Global impact of COVID-19 on agriculture: role of sustainable agriculture and digital farming

Sridhar

Balakrishnan

Jacob

et al. 2022

Environ Sci Pollut Res

134

View full text Add to dashboard Cite

show abstract

“…In 2020, Islam et al introduced a novel non-contact cross-capacitive sensor that operates on the Thompson-Lampard principle. This sensor was designed specifically for the detection of abrasive particles in lubricating oil, as depicted in Figure 4 [72]. The sensor, consisting of four cylindrical electrodes, underwent testing using metal particles of varying weights (ranging from 10.5 mg to 27.5 mg) in a lubricating oil.…”

Section: Capacitive Sensormentioning

confidence: 99%

A Critical Review of On-Line Oil Wear Debris Particle Detection Sensors

Han,

Mu,

Liu

et al. 2023

JMSE

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In the field of marine engineering, the friction and wear experienced by rotating mechanisms are recognized as significant contributors to the failure of marine machinery. In order to enhance the safety and dependability of marine ship operations, the implementation of on-line oil wear debris particle detection sensors enables the on-line monitoring of oil and facilitates the rapid identification of abnormal wear locations. This paper provides a critical review of the recent research progress and development trends in the field of sensors for on-line detection of oil wear debris particles. According to the method of sensor detection, wear debris particle detection sensors can be classified into two distinct categories: electrical and non-electrical sensors. Electrical sensors encompass a range of types, including inductive, capacitive, and resistive sensors. Non-electrical sensors encompass a range of technologies, such as image processing sensors, optical sensors, and ultrasonic sensors. Finally, this review addresses the future research directions for wear debris particle detection sensors in light of the challenging problems currently faced by these sensors.

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“…The device has high sensitivity and a low detection limit but also has a low throughput. Islam et al [15] proposed a Thompson-Lampard theorem based cross-capacitive sensor to detect metal particles in lubricating oil. The sensor has four identical symmetrically placed electrodes, and the presence of metal debris in lubricant oil can be detected by monitoring changes in the cross-capacitance value.…”

Section: Introductionmentioning

confidence: 99%

A New In Situ Coaxial Capacitive Sensor Network for Debris Monitoring of Lubricating Oil

Wang

Lin

et al. 2022

Sensors

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Wear debris monitoring of lubricant oil is an important method to determine the health and failure mode of key components such as bearings and gears in rotatory machines. The permittivity of lubricant oil can be changed when the wear debris enters the oil. Capacitive sensing methods showed potential in monitoring debris in lubricant due to the simple structure and good response. In order to improve the detection sensitivity and reliability, this study proposes a new coaxial capacitive sensor network featured with parallel curved electrodes and non-parallel plane electrodes. As a kind of through-flow sensor, the proposed capacitive sensor network can be in situ integrated into the oil pipeline. The theoretical models of sensing mechanisms were established to figure out the relationship between the two types of capacitive sensors in the sensor network. The intensity distributions of the electric field in the coaxial capacitive sensor network are simulated to verify the theoretical analysis, and the effects of different debris sizes and debris numbers on the capacitance values were also simulated. Finally, the theoretical model and simulation results were experimentally validated to verify the feasibility of the proposed sensor network.

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A highly precise cross-capacitive sensor for metal debris detection in insulating oil

Cited by 28 publications

References 18 publications

Global impact of COVID-19 on agriculture: role of sustainable agriculture and digital farming

Global impact of COVID-19 on agriculture: role of sustainable agriculture and digital farming

A Critical Review of On-Line Oil Wear Debris Particle Detection Sensors

A New In Situ Coaxial Capacitive Sensor Network for Debris Monitoring of Lubricating Oil

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