A survey of sag monitoring methods for power grid transmission lines

The transmission line is a fundamental asset in the power grid. The sag condition of the transmission line between two support towers requires accurate real-time monitoring in order to avoid any health and safety hazards or power failure. In this paper, state-of-the-art methods on transmission line sag monitoring are thoroughly reviewed and compared. Both the direct methods that use the direct video or image of the transmission line and the indirect methods that use the relationships between sag and line parameters are investigated. Sag prediction methods and relevant industry standards are also examined. Based on these investigation and examination, future research challenges are outlined and useful recommendations on the choices of sag monitoring methods in different applications are made

Digital twinning of railway overhead line equipment from airborne lidar data

The automated generation of geometry-only digital twins of Overhead Line Equipment (OLE) system in existing railways from point clouds is an unsolved problem. Currently, this process is highly reliant upon manual inputs, needing 10 times more labour hours than scanning the physical asset. The resulting modelling cost counteracts the expected benefits of the digital twin. We tackle this challenge using a novel model-driven method that exploits the highly regulated and standardised nature of railways. It starts by restricting the search for OLE elements relative to point clusters of the railway masts. The resulting point clusters of the OLE elements are then converged with various parametric models of different catenary configurations to verify the presence of OLE elements and to find the best possible fit. The method outputs a geometry-only digital twin of the OLE system in Industry Foundation Classes (IFC) format. The method was tested on an 18 km railway point cloud and achieves overall detection rates of 93.2% F1 score for OLE cables and 98.1% F1 score for other OLE elements. The accuracy of the generated model is evaluated using distance-based metrics between the ground truth model and the automated model. The average modelling distance is 3.82 cm Root Mean Square Error (RMSE) for all 18 km dataCambridge Commonwealth, European & International Trust Bentley Systems UK Plc

2d Suspended Fet Technology: Overcoming Scattering Effect For Ultrasensitive Reliable Biosensor

TMDs such as MoS2 is playing an important role in the field of FETs, photodetectors, thin film transistors and efficient biosensors because of their direct band-gap, high mobility, and biocompatibility. Despite these strengths, the performance and reliability of such atomic layer are easily influenced by supporting substrate. Interaction between the supporting substrate and MoS2 implies that interface control is vital for performance of devices consisting of monolayer MoS2. In particular, the Silicon dioxide (SiO2) supporting substrate has an uneven morphology and is chemically active because of trapped environmental gases, unknown functional groups, chemical adsorbates, and charges. Thus, adding another layer of MoS2 on the top of SiO2 cannot contribute charge transport clearly, which leads to the unreliable function of every single device. To solve the interface problem, suspended 2D layer devices have been reported by wet etching silicon di oxide underneath the monolayer. Freestanding MoS2 has shown 10 times greater back gate electronic mobility than the supporting on the SiO2 substrate. However, the existing SiO2 requires hazardous chemical etchants such as hydrofluoric acid (HF), which is difficult to handle and affects the 2D film structure and purity. Secondly, freestanding MoS2 sags between the two electrodes because of the high spacing (~ 2 µm), which makes it impossible to coat another layer such as hafnium oxide (HfO2) and antibodies on top of monolayer. Therefore, this structure impedes making top gate FET biosensors, which allows for only back gating. However, back gate mobility is far lesser than the top gate mobility which hinders making a highly sensitive FET-based biosensor because the sensitivity of a sensor depends on its mobility. In this work, CVD grown MoS2 channel material is transferred on self-assembled photolithographically patterned nano-gaps to achieve suspension and is covered with HfO2 to eliminate the direct functionalization of channel material. These nano-gap arrays provide mechanical strength to the monolayer and do not allow the supporting substrate to touch after coating another thin insulating layer as well as linkers/antibodies. HfO2 can be easily functionalized by silane-based linkers and antibodies (E-coli antibodies) to bring variation to the suspended 2D material by targeting a charged biomolecule (E-coli). In addition, termination of the supporting substrate leads to decrement of subthreshold swing which is inversly proportional to the sensitivity of the FET biosensor. The proposed FET biosensor has the capability to detect one molecule because of its single atomic layer as a channel material, its scalability due to the involvement of optical photolithography, and its fast response because of higher mobility

3D Classification of Power Line Scene Using Airborne Lidar Data

Failure to adequately maintain vegetation within a power line corridor has been identified as a main cause of the August 14, 2003 electric power blackout. Such that, timely and accurate corridor mapping and monitoring are indispensible to mitigate such disaster. Moreover, airborne LiDAR (Light Detection And Ranging) has been recently introduced and widely utilized in industries and academies thanks to its potential to automate the data processing for scene analysis including power line corridor mapping. However, today’s corridor mapping practice using LiDAR in industries still remains an expensive manual process that is not suitable for the large-scale, rapid commercial compilation of corridor maps. Additionally, in academies only few studies have developed algorithms capable of recognizing corridor objects in the power line scene, which are mostly based on 2-dimensional classification. Thus, the objective of this dissertation is to develop a 3-dimensional classification system which is able to automatically identify key objects in the power line corridor from large-scale LiDAR data. This dissertation introduces new features for power structures, especially for the electric pylon, and existing features which are derived through diverse piecewise (i.e., point, line and plane) feature extraction, and then constructs a classification model pool by building individual models according to the piecewise feature sets and diverse voltage training samples using Random Forests. Finally, this dissertation proposes a Multiple Classifier System (MCS) which provides an optimal committee of models from the model pool for classification of new incoming power line scene. The proposed MCS has been tested on a power line corridor where medium voltage transmission lines (115 kV and 230 kV) pass. The classification results based on the MCS applied by optimally selecting the pre-built classification models according to the voltage type of the test corridor demonstrate a good accuracy (89.07%) and computationally effective time cost (approximately 4 hours/km) without additional training fees

A facility to Search for Hidden Particles (SHiP) at the CERN SPS

A new general purpose fixed target facility is proposed at the CERN SPS accelerator which is aimed at exploring the domain of hidden particles and make measurements with tau neutrinos. Hidden particles are predicted by a large number of models beyond the Standard Model. The high intensity of the SPS 400~GeV beam allows probing a wide variety of models containing light long-lived exotic particles with masses below ${\cal O}$(10)~GeV/c$^2$, including very weakly interacting low-energy SUSY states. The experimental programme of the proposed facility is capable of being extended in the future, e.g. to include direct searches for Dark Matter and Lepton Flavour Violation.Comment: Technical Proposa

Phase 1 of the First Solar Small Power System Experiment (experimental System No. 1). Volume 2: Appendix A - D

Recommended conceptual designs for the baseline solar concentrator and electrical subsystems are defined, and trade offs that were evaluated to arrive at the baseline systems are presented. In addition, the developmental history of the Stirling engine is reviewed, the U4 configuration is described, and a Stirling engine heat pipe system is evaluated for solar application where sodium vapor is used as the heat source. An organic Rankine cycle engine is also evaluated for solar small power system application

Intelligent control of an automated adhesive dispensing cell.

Imperial Users onl

Model driven segmentation and the detection of bone fractures

Bibliography: leaves 83-90.The introduction of lower dosage image acquisition devices and the increase in computational power means that there is an increased focus on producing diagnostic aids for the medical trauma environment. The focus of this research is to explore whether geometric criteria can be used to detect bone fractures from Computed Tomography data. Conventional image processing of CT data is aimed at the production of simple iso-surfaces for surgical planning or diagnosis - such methods are not suitable for the automated detection of fractures. Our hypothesis is that through a model-based technique a triangulated surface representing the bone can be speedily and accurately produced. And, that there is sufficient structural information present that by examining the geometric structure of this representation we can accurately detect bone fractures. In this dissertation we describe the algorithms and framework that we built to facilitate the detection of bone fractures and evaluate the validity of our approach

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0