Pd-doped MoS2 monolayer: A promising candidate for DGA in transformer oil based on DFT method

Density functional calculations have been carried out to study the adsorption of three characteristic oil-dissolved gases in transformers (C2H2, CH4 and CO) on pristine graphene, and Mn-doped graphene (Mn-graphene) to obtain an ideal gas sensing material. First, three possible doping sites of Mn atom on graphene surface were studied, and it is found that the Bridge-doping site was the steadiest one. Then, the adsorption of gas molecules on pristine graphene, and Mn-graphene surface with different positions and orientations, were analyzed and compared by calculating the adsorption energy of each structure to obtain the most stable adsorption structures. Furthermore, density of states, and molecular orbital theory were carried out to analyze the gas sensing mechanism. The results show that pristine graphene surface shows weak adsorption to the gases. By contrast, the adsorption energy of the gases on Mn-graphene has largely increased except CH4 due to the electronic hybridization. Therefore, we concluded that the Mn-graphene could be a possible gas sensing material for C2H2 and CO detection, but not appropriate for CH4 sensing because of the weak adsorption and small conductivity change.

Adsorption of C2H2, CH4 and CO on Mn-doped graphene: Atomic, electronic, and gas-sensing properties

Smart living is a trending and connected lifestyle that envisions efficient and sustainable energy utilization, stable and reliable power supply, intelligent and coordinated transportation and mobility, and personalized and cost-effective healthcare. Its realization needs the Internet of Things (IoT). IoT is a compelling platform connecting trillions of sensors and collecting data for connectivity and analytics. It is more advanced than traditional monitoring systems where limited sensors and wired communication can merely collect fragmented data in the application domains. Spintronic sensors with the superb measuring ability and multiple unique advantages can be one of the critical sensing devices supporting the IoT and enabling smart living. In this paper, we review successful applications of individual spintronic sensors in electrical current sensing, transmission and distribution lines monitoring, vehicle detection, and biodetection that can help to fulfill the promises of smart living in energy management, power delivery, transport, and healthcare. The wireless spintronic sensor networks (WSSNs) working at the massive interconnected network level are proposed and illustrated to provide pervasive monitoring systems, which facilitate the intelligent surveillance and management over building, power grid, transport, and healthcare. The database of collected information will be of great use to policy making in public services and city planning. This paper provides insights for realizing smart living through the integration of IoT with spintronic sensor technology.

Overview of Spintronic Sensors With Internet of Things for Smart Living

Adsorption characteristic of Rh-doped MoSe2 monolayer towards H2 and C2H2 for DGA in transformer oil based on DFT method

This opening chapter begins with a brief history of the development of the field of eddy-current (EC) nondestructive evaluation (NDE), beginning with Faraday’s discovery of the law of electromagnetic induction and including contributions of Henry, Hughes, and Förster. The role of the law of electromagnetic induction in EC NDE is described qualitatively and the principles via which a material defect may be detected are discussed. Finally, the parameters by which a simple EC surface coil may be described are introduced.

Eddy-Current Nondestructive Evaluation

The reliable analysis for identification of winding insulation defects in transformer and shunt reactor are necessary for power industries during lightning impulse test. In this paper, wavelet power ratio signature spectrum analysis is proposed to identify the short duration of partial discharge (PD) pulses of 170 ns and 30 ns within windings due to impulse voltage excitation. It provides a solution to the problems associated with several random features in the measured winding responses at neutral terminal of the winding due to PD pulse through visual assessment of mutual strength between normal winding response and one with PD response using appropriate mathematical formulation in wavelet transform. In this context, the normalized response due to reduced impulse voltage excitation is formed to be a basis function to identify the PD pulse. If the surge impedance characteristic of the winding is changed due to PD pulse at full wave impulse voltage excitation, then formulated wavelet power ratio signature spectrum analysis will extract the evidence of potentially interesting features through assessment between basis function response and one with PD response. To prove feasibility of the proposed analysis, experimental analysis is performed on a layer winding.

Wavelet power ratio signature spectrum analysis for prediction of winding insulation defects in transformer and shunt reactor

A common approach to detect a metal’s proximity or analyze some characteristic of it in applications, such as proximity sensing, non-destructive evaluation, and so on, is to generate eddy currents in it and then extract the desired information from the features of these eddy currents using eddy current sensors (ECSs). Some of the common ECS are Hall-effect sensors and inductive coils. Lately, giant magnetoresistive (GMR) sensors are also used for ECS due to their higher sensitivity and better low-frequency response. Due to these features, a new application has been identified for GMR-based ECS probes, which is real-time detection of metal shrapnel in human body during surgery. Since metal shrapnel cause grievous injuries to victims of bomb blasts, land mines, and so on, and the imaging modalities that doctors use presently to locate them do not provide any real-time information of their location during surgery, this probe will provide immense help to the doctors for tracing these shrapnel during surgery. However, existing GMR-based probes have limited sensing range, and therefore, they are not suitable for this application. Hence, a new probe topology is presented here, which has much longer sensing range than existing probes. The design of this probe, its performance, and the details of a new circuit that minimizes the temperature drift and hysteresis effects of the GMR sensor in the probe simultaneously are presented in this paper.

A Novel GMR-Based Eddy Current Sensing Probe With Extended Sensing Range

Shrapnel injury is a major cause of death in victims of bomb blast, land mines, and gun fire. Currently, doctors rely on imaging systems to locate the shrapnel before surgery. But, since these images do not provide any real-time information of the location of the shrapnel, effectiveness of surgery solely depends on the doctors' skill to trace them. Therefore, in some cases, the shrapnel, in spite of being visible in the images, may become untraceable during surgery. Hence, an online tool that can help the surgeon in finding the location of the shrapnel during the surgery will be very effective. A prototype of such a tool has been realized using an inductive proximity sensor (IPS). The new IPS is small enough for inserting into the victim's body. Since the detection depth (DD) of an IPS decreases with its diameter, this IPS uses a differential sensing scheme for detection. Hence, the new sensor achieves DDs longer than its diameter. The design of the sensor takes care of the effects of parasitic parameters that become predominant as the size gets smaller and ensures repeatable results. The tool also features a special excitation scheme that has multiple advantages when compared with existing schemes. The details of the sensor, its excitation and performance against different targets under various conditions are presented in this paper.

A New Inductive Proximity Sensor Based Guiding Tool to Locate Metal Shrapnel During Surgery

In this paper, an inductive proximity sensor with a longer range when compared to its diameter is presented. This sensor is intended to guide doctors, while performing surgery to remove metal shrapnel from victims of bomb blasts, gun fire, land mines etc. Presently doctors rely on imaging systems to locate shrapnel in the victim's body before surgery. Effectiveness of surgery and recovery solely depends on the doctors' skill to trace the shrapnel. In some cases the shrapnel may be visible in the images, but it may be untraceable during surgery. So in such cases, an inductive proximity sensor which is small enough to be introduced into the victim's body and can direct the recovery tool effectively to the exact location of the shrapnel, during the surgery, will be very useful to the doctor. Such a sensor, along with its details and experimental results are presented in this paper. This sensor works on a new comparison based method to detect tiny targets, as the detector size is a constraint here. The sensor can detect shrapnel materials such as steel, brass and Aluminium. A smaller, modified version of this sensor is also presented in the paper, along with a study of the effect of body tissues on sensor performance.

A new inductive proximity sensor as a guiding tool for removing metal shrapnel during surgery

Shrapnel injury is a major cause of death in victims of bomb blast, land mines and gun fire. In this paper, a Giant Magneto Resistance (GMR) sensor based online surgical tool that helps to remove metal shrapnel from victim's body is presented. This tool is intended to guide the surgeon to the exact location of the shrapnel during surgery. Presently doctors rely on imaging systems to locate them before surgery. Effectiveness of surgery solely depends on the doctors' skill to trace them, as these images do not provide real-time information of the location of the shrapnel during surgery. Therefore, in some cases, the shrapnel, in spite of being visible in the images, may become untraceable during surgery. So in such cases, a sensing tool that can guide the doctor to the location of the shrapnel will be very effective. An inductive proximity sensor can serve this purpose, but its output can be affected by its lead inductance or other parasitic circuit parameters. Therefore in order to overcome such effects, a GMR based sensing tool is proposed here. The details and experimental results obtained from this tool are presented in this paper. The tool can detect both ferromagnetic and paramagnetic metal targets.

Mithun Sakthivel

Papers

Wavelet power ratio signature spectrum analysis for prediction of winding insulation defects in transformer and shunt reactor

A Novel GMR-Based Eddy Current Sensing Probe With Extended Sensing Range

A New Inductive Proximity Sensor Based Guiding Tool to Locate Metal Shrapnel During Surgery

A new inductive proximity sensor as a guiding tool for removing metal shrapnel during surgery

A GMR sensor based guiding tool for location of metal shrapnel during surgery