THE HONG KONG INSTITUTION OF ENGINEERS ELECTRICAL DIVISION - Free Download PDF

26d ago
1 Views
0 Downloads
6.09 MB
55 Pages
Transcription

THE HONG KONGINSTITUTION OF ENGINEERSELECTRICAL DIVISIONThe 37th Annual SymposiumThursday24th October 2019INNOVATION FORENGINEERING ADVANCEMENTatBallroomSheraton HotelNathan RoadKowloonHong Kong

SYMPOSIUM PROGRAMME08.30 Registration and Coffee09.00 Welcome Address- Ir Tony K.T. YeungChairman, Electrical Division, The HKIE09.05 Opening Address- Ir Ringo S.M. YuPresident, The HKIE09.10 Keynote Speech- Mr K.K. LingDirectorJockey Club Design Institute for Social InnovationHong Kong Polytechnic University1.Smart Air Transportation09.40 Realizing Smart Airport Vision using Digital Twin- Ir Kelvin K.W. Wong, Deputy General Manager- Mr Stanley K.C. To, Senior Manager, Technical Systems- Mr Tiger K.Y. Lau, Assistant Engineer, Electrical & MechanicalTechnical Services DepartmentAirport Authority Hong Kong10.00 Multi-illuminator Passive Radar (MIPAR) Technology- Dr Feng ChengDeputy ProfessorElectronic Information SchoolWuhan University- Ir Stanley K.W. LeungGeneral ManagerGDEPRI Power Control Systems & Equipment (HK) Ltd.10.20 Discussion10.50 Coffee Break-1-

2.Environmentally Friendly Power Supply11.20 Environmentally Friendly F-gas Free and IoT HV Switchgear- Dr. Mark Kuschel, Chief Technology OfficerHigh Voltage Gas-insulated SwitchgearSiemens AG Germany- Ir Alex S.H. Chan, Senior ManagerGas & Power DivisionSiemens HK & Macao11.40 Review of Electric Vehicle Charging Facilities- Dr Lawrence C.K. PoonGeneral ManagerAutomotive Platforms & Application Systems R&D CentreHong Kong Productivity Council12.00 Discussion12.30 Lunch14.00 Special Talk on Innovation- Mr Vivek MahbubaniStand-up Comedian3.Building Services Management14.20 Retro-commissioning of Building Services Installation- Ir Victor W.T. LeungDirectorVictor Leung & Associates Limited14.40 IoT Enabled Smart Building Operation and Maintenance- Ir C.K. Lee, Chief Engineer- Ir Steve H.Y. Chan, Senior Engineer- Ir Grace K.M. Yip, Engineer- Ir Francis P.H. Yuen, Engineer- Mr T.C. Chan, Assistant Engineer- Ms P.Y. Cheung, Assistant EngineerElectrical & Mechanical Services DepartmentThe Government of the HKSAR15.00 Discussion15.20 Coffee Break-2-

4.Emerging Technological Applications15.50 Bring the World into 5G Era- Mr Philip H.F. YickSolution DirectorHuawei International Co. Ltd.16.10 Dynamic Optimisation of Peak Demand Charge usingMachine Learning Algorithms- Ir Dave C.H. Chan, Director- Mr Kenneth K.Y. Lee, Technical Manager- Dr Pan P. Lee, Senior R&D EngineerInformation, Communications and Building TechnologiesATAL Building Services Engineering Ltd.16.30 Discussion16.45 Summing Up- Ir T.K. ChiangSymposium ChairmanElectrical Division, The HKIEClosing Address- Ir Professor H.C. ManDeanFaculty of EngineeringHong Kong Polytechnic University-3-

AcknowledgementThe Electrical Division of The Hong Kong Institution of Engineers would like to express itssincere appreciation and gratitude to the following persons and organizations for theircontributions to the Symposium.Authors/SpeakersMr K.K. LingIr Prof. H.C. ManIr Kelvin K.W. WongMr Stanley K.C. ToMr Tiger K.Y. LauDr Feng ChengIr Stanley K.W. LeungDr Mark KuschelIr Alex S.H. ChanDr Lawrence C.K. PoonMr Vivek MahbubaniIr Victor W.T. LeungIr C.K. LeeIr Steve H.Y. ChanIr Grace K.M. YipIr Francis P.H. YuenMr T.C. ChanMs P.Y. CheungMr Philip H.F. YickIr Dave C.H. ChanMr Kenneth K.Y. LeeDr Pan P. LeeSponsorsSiemens Ltd.CLP Power Hong Kong Ltd.The Hongkong Electric Co., Ltd.The Jardine Engineering Corporation Ltd.Junefair Engineering Co. Ltd.Elibo Engineering Ltd.Keystone Electric Wire & Cable Co. Ltd.Netsphere Solution Ltd.MTR Corporation Ltd.Kum Shing GroupC&K Instrument (HK) Ltd.Greenland Engineering Co., Ltd.Schneider Electric (Hong Kong) LimitedMitsubishi Electric (Hong Kong) Ltd.TE Connectivity Hong Kong Ltd.Gammon E&M LimitedMetrix Engineering Co. Ltd.Chat Horn Engineering Ltd.FSE Engineering Group Ltd.S.G.H. Electric Wire & Cable Co. Ltd.Hong Kong Electrical Contractors’ Association Ltd.- 4-

37TH ANNUAL SYMPOSIUM ORGANIZING COMMITTEESymposium Chairman:Ir T.K. ChiangMembers:Ir Tony K.T. YeungIr W.S. TamIr Y.H. LeungIr Dr Edward W.C. LoIr Andrew K.W. YanIr Steve K.K. ChanIr C.L. WongIr Kit N.K. ChanIr Alex T.H. FuIr Hugo C.Y. ChanIr Joseph C.W. LeungIr Simon H.C. TsuiIr Jason K.H. ChanIr Raymond K.M. SzeMs Yani Y.Y. KoHon. Secretary and Treasurer:Ir Y.K. ChuNote:All material in this booklet is copyright and may not be reproduced in whole or in part without written permission from The HongKong Institution of Engineers. All information and views expressed by speakers and in their conference materials do not reflect theofficial opinion and position of the HKIE. No responsibility is accepted by the HKIE or their publisher for such information andviews including their accuracy, correctness and veracity.- 5-

Paper No. 1REALIZING SMART AIRPORT VISION USING DIGITAL TWINAuthors/Speakers: Ir Kelvin K.W. Wong, Deputy General ManagerMr Stanley K.C. To, Senior Manager, Technical SystemsMr Tiger K.Y. Lau, Assistant Engineer, Electrical & MechanicalTechnical Services DepartmentAirport Authority Hong Kong

REALIZING SMART AIRPORT VISION USING DIGITAL TWINIr Kelvin K.W. Wong, Deputy General ManagerMr Stanley K.C. To, Senior Manager, Technical SystemsMr Tiger K.Y. Lau, Assistant Engineer, Electrical & MechanicalTechnical Services DepartmentAirport Authority Hong Kongof our Digital Twin platform. The process of buildingthe platform can be divided into two parts. First, fromthe very beginning, we have been working with multiplepartners to develop a broad 3D model for the currentairport as a whole to ensure a shared platform forsubsequent expansion. Second, we then developdetailed 3D models and other applications based onbusiness demand so that it can be rolled out to use assoon as possible.ABSTRACTHong Kong International Airport is integrating five newenabling technologies into airport engineering andmanagement process to realize the Smart Airport Vision,including Advanced Biometrics, Robotics, Digital Twin,Mobile Technology and Big Data Intelligence. Thesetechnologies aim at automating passenger’s process,and improving operation and maintenance efficiency.Digital Twin, among them is a key enabling technologyto provide a virtual model in which data from differentsources will be integrated and made available instantly,visualized in a human-centric interface and analysed tomake predictions in an explainable way. In this paper,we will give an introduction of a Digital Twin platformwith various IoT integrations to gain insights intoairport operational processes in order to prolong thelifespan of airport facilities through predictivemaintenance and on-going optimization, and to use theairport operational data in research and development fora sustainable future smart airport.This paper first introduces the concept of Digital Twin.It then provides detailed discussion on the modellingmethods, including Building Information Modelling(BIM) and Geographic Information System (GIS).Finally, it presents a Digital Twin platform with variousIoT integrations to highlight some important developments in pursuing our Smart Airport vision.2. WHAT IS DIGITAL TWIN?The vision of the Digital Twin is to facilitate holisticairport management and predictive decision making. Itsapplication will cover design, construction, operationand maintenance for the complete asset life cycle.1. INTRODUCTIONHong Kong International Airport (HKIA) rolled out itsSmart Airport Vision in 2016. Our primary objective isto apply innovation and technology to create a moreenjoyable and memorable experience for our passengersand more efficient operating environment for the airport.For passenger experience, we want to achieve seamlesstravel, personalised attentive services, new retailexperience with fun and memories, and behind the scene:efficient operations and predictability. This vision isalso common goals of many international airports and islikely achievable in 10 years or less.There are different definitions of the term “Digital Twin”[1]. For Hong Kong International Airport, we define“Digital Twin” as a virtual model of our Airport, inwhich data from different sources can be integrated,made available instantly, visualized in a human-centricinterface, and analysed to make predictions in anexplainable way. Instant Availability, Human-centricVisualization and Explainable Predictability form thethree key pillars of our Digital Twin platform.2.1 Instant AvailabilityFig. 1 - Architecture of HKIA’s Digital Twin platformDigital Twin platform is one of the key elements ofbuilding a smart airport. Figure 1 shows the architectureFig. 2 - Digital Twin platform- 1.1 -

The first goal of our Digital Twin is to provide instantavailability of a complete, single source of truth of theentire airport at anywhere and anytime. From onesingle platform in Figure 2, users can get access to themost up-to-date and complete digital model of the entireairport infrastructure and facilities. When new worksare added or existing works are modified, each of thesechanges will be made in a timely manner to the DigitalTwin model, and then shared with other applicationsusing the same model so that the 3D model andapplications will always be kept up-to-date. The samemodel will also provide a unified and holistic view forthe entire airport.Fig.4 - Flooding simulationAs shown in Figure 4, users can easily visualise andunderstand the extent and possible impact of floodingduring a selected typhoon scenario. This can help us toplan the contingency arrangement to protect safety andcritical infrastructure at the airport [2].From the single Digital Twin platform, users will alsoget access to their needed key data about past, presentand future in a location-based context in addition toinfrastructure and facility information. Besides theavailability of all key data from a single platform, wealso aim to provide users with an intuitive interface and“3 clicks or less” navigation system from the mainscreen to ensure “Instant” availability of their mostneeded information.Fig. 5 - Airport height restriction checkingThe Digital Twin model also aims to provide insight ata glance to maximize operation efficiency. Figure 5shows an example of utilizing Digital Twin model toassess the impact of new development on airport heightrestriction. With the 3D model, vertical dimensions areeasier to be visualised and height encroachments arequickly revealed. This can save time, enhance efficiency,avoid unnecessary human errors and enable clash-freedesign.Fig. 3 - Mobile device accessibilityAs shown in Figure 3, the Digital Twin will also beaccessible from mobile devices to ensure airport staffwill get their needed data instantly. This is especiallyimportant for front line staff who interact withpassengers or airport facilities on a day-to-day basis andhave to respond immediately to any change incircumstances. The use of smart glasses is beingdeveloped so that it can free up both hands for othertasks during work.Fig. 6 - 4D Immersive Cave for 1st person experience2.2 Human-centric VisualizationThe Digital Twin must be adaptable to new andemerging human machine interfaces. We built anImmersive Cave shown in Figure 6 to provide userswith first-person immersive experience. Without theneed for VR glasses, the cave environment aligns theparticipants along common viewing platform andfacilitates communication and discussion.The second goal is to provide human-centricvisualization for users to interact with and intuitivelyrealize the underlying information or data. We aim topresent complex data output in the form ofphotorealistic animations over 3D models whereverpractical.- 1.2 -

For a new project like Sky Bridge, the Digital Twin willprovide users a virtual reality to experience the futuredesigns to facilitate efficient design review. This isespecially important because of our increasing use ofModular Integrated Construction and other off-siteconstruction methods. Due to their longer lead times,early design freeze is critical. With the 3D model,alternative design proposals can be easily andeffectively modelled, reviewed and compared in thecontext of the entire airport [3]. This can minimize thedesign alternation during the design stage inconstruction.provide the users to make informed decisions withunderstandable basis instead of simple probability.3. MODELLING METHODSIn Hong Kong International Airport, we are creatingdigital modelling or representation of our physicalairport infrastructure for a 3D based GIS model withBIM integration. This 3D model will contain all spatial,geographic data and building information, includingarchitecture, structure, civil, electrical, mechanical,plumbing services, to provide a solid foundation for ourDigital Twin platform. By integrating BIM into GISmodel, our Digital Twin platform can be benefited fromreduced hardware requirement so that every user canaccess to the data instantly and easily, fulfilling the firstgoal of our Digital Twin platform.Fig. 7 - 4D construction predictionBy expanding 3D to time-based 4D model as shown inFigure 7, we can critically review construction methodsand sequences well in-advanced of the actualconstruction and predict and mitigate potentialproblems on the new works and whole airportenvironment, like design clashes and operational impact.2.3Fig. 9 - Completed 3D modelsExplainable PredictabilityThe 3D model is a live modelling of our airport, withthe anticipated expansion and upgrading projects. Wemandated that all new designs to be done shall be basedon BIM. For existing facilities, we are building a broad3D model for the Terminal 1 building and an enterpriseGIS platform. Figure 9 shows the 3D models for thearrivals and departures levels of Terminal 1 buildingand the coming Sky Bridge.3.1 Building Information Modelling (BIM)Fig. 8 - Crowd prediction and controlThe third pillar is explainable predictability. With bigdata analytics, we can integrate the data collected fromIoT and other sources, analyse them to make futurepredictions and present it in the Digital Twin model.For example, in Figure 8, crowd control is a criticalairport operation especially during or after majordisruptions. The Digital Twin model may provide earlyalerts and help resource deployment based on its crowdprediction analytics using available historical and realtime data.Fig. 10 - Point cloud data collected from laser scanningTo create a 3D model of our existing infrastructure,laser scanning for obtaining point cloud data is used.The laser scanner contains a rotating laser rangefinderwhich measures the distance between each reachablepoint in the building and the scanner. By continuouslyOne point to note is that as we move from rule-based AIto more advanced machine learning, it is important toensure that explainable AI approach is adopted to- 1.3 -

rotating the rangefinder by 360 in x/y z axes, the laserscanner will become omnidirectional. Point cloud datais then collected at a particular reference point in thebuilding. Figure 10 shows an example of point clouddata collected through laser scanning in MidfieldConcourse.software by combining 2D as-built CAD drawing andthe building information from BIM.3.3 Integration with Other SystemsFig. 13 - 3D model with asset detailsWith the BIM model and enterprise GIS platform,construction and facility management will be a loteasier. As shown in Figure 13, this is made possiblewith integration to our asset management system so infuture we could easily retrieve the asset details in a 3Dbased virtual layout of the airport. This will makefacility management more effective and more accurate.We also target to integrate our different operations andmaintenance systems into a single environment layeredon top of the 3D based Digital Twin of the airport. Thisallows an agiler response and decision making whenhandling unforeseen disruptions at the airport.Fig. 11 - Real-time rendered image in BIM softwareAfter repeating the laser scanning many times in andaround the building, point cloud container model isformed and then linked into the working model in BIMsoftware as a background reference. Relevant elementswill be built in the main model to intelligently interpretthe point cloud data. After that, building informationwill be applied to the model in forms of materials andfinishes. Until this stage, the 3D model is basicallycreated. As shown in Figure 11, real-time rendering canhelp to visualize the model in a photorealistic context.4. IoT INTEGRATION3.2 Geographic Information System (GIS)When we further layer the IoT devices or smart sensoron top of the 3D Digital Twin model, more possibilitiescan be implemented to improve system reliability, aswell as prolonging the lifespan of airport facilities. Thisenables predictive maintenance, improves operationaleffectiveness, enhances the passenger experience, andfacilitates research and development, resulting incomprehensive airport facility designs into the newairport development.4.1 Predictive MaintenanceFig. 12 - Comparison of spatial data representationIntegrating BIM into GIS model can reduce hardwarerequirement for instant availability of data. As shown inFigure 12 , GIS model represents data in observablesurfaces while BIM represents data in parametricvolumes. For construction planning, design,implementation and monitoring, the high level of detailsprovided by BIM is critical for us to enable tasks likecrash analysis for various building services. For DigitalTwin platform, the purposes are different. We want tocreate a Digital Twin platform with Instant blePredictability. Driven by these purposes, our platformshall be simplified from the BIM to GIS model throughFig. 14 - Predictive maintenance for baggage handling systemWe see that predictive maintenance is a crucial strategyto help us reduce possible downtime of our facilities andequipment especially for our mission critical facilitiese.g. baggage handling system. With big data analytics,a combination of industrial IoT and new IoT, including- 1.4 -

cameras to collect real time data, we can eventuallypredict most major problems and fix them before theyoccur [4] . As shown in Figure 14 , we completed aProve of Concept (PoC) with a Hong Kong Start-up firmand successfully predicted a main primary sorter faultby the predictive analytics based on system logs andmaintenance history of our baggage system. We areabout to expand the scale to a comprehensive predictivemaintenance for our baggage handling system.sensing use cases. This is the development of an indoormulti-function, Human-assisted AI and collaborativelearning robot at terminals. With common autonomousplatform, we can modify the functional components atdifferent times for tasks such as patrolling, delivery,message dissemination etc. This demonstrates that IoTsensors do not have to be fixed installations, but insteadcan be dynamic and mobilized all around the airport andcollect data for the Digital Twin model.4.2 Smart CCTV4.4 Driverless VehiclesFig.17 - Autonomous electric tractorFig. 15 - Smart CCTV system with video analyticsAnother pilot is the autonomous electric tractor totransport baggage or cargo dollies in the dynamicenvironment from aircraft stands to baggage/cargoreception points. This is the first autonomous electrictractor pilot at major international airport. Our keypriority of the pilot is to control costs in particularpossible LIDAR sensors so as to ensure commercialviability for mass deployment.Another opportunity is with our new smart CCTVsystem shown in Figure 15, which will provide valuablevisual data for the Digital Twin model. A total of over4,500 digital camera sets based on 4K resolution arebeing installed to provide full coverage of the airport.With video analytics, these cameras will not onlyprovide surveillance video but also valuable real-timestructural data on people, vehicles and facilities withcharacteristics for further ana

The Electrical Division of The Hong Kong Institution of Engineers would like to express its sincere appreciation and gratitude to the following persons and organizations for their contributions to the Symposium. Authors/Speakers Mr K.K. Ling Ir Prof. H.C. Man Ir Kelvin K.W. Wong Mr Stanley K.C. To Mr Tiger K.Y. Lau Dr Feng Cheng