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Design of Hardware-In-the-Loop Simulation(HILS) of Control and Monitoring System for Deep-Seabed Manganese Nodule MinerSoung-Jea Park, Tea-Kyeong yeu, Sup Hong, Jong-Su Choi and Hyung-Woo KimOcean Engineering Research Division, Maritime & Ocean Engineering Research Institue, KORDI, Daejeon, KOREASang-Bong KimDepartment of Mechanical Engineering, Pukyong National University, Busan, KOREAABSTRACTA deep-seabed manganese nodule miner(DSNM) is being developed. DSNM consists of a tracked vehicle, nodule pick-up device, nodule crusher and so on, which are controlled remotely in real-time. This type miner has many sensors and actuators with embedded controller. Expansive, fragile and unique systems are hard to test. Hardware-in-the-loop simulation(HILS) can substantially lower the cost and save the time of testing. In this paper, we design a HILS of the control and monitoring system for DSNM, which aims at an efficient pre-test of the system design performance.KEY WORDS: HILS; DSNM; Real-time; Embedded controllerINTRODUCTIONThe general deep-sea mineral resources are know as manganese nodule, manganese crust, undersea hydrothermal deposit which has nonferrous metal, and petroleum, natural gas and methane hydrate which used for energy resources. Petroleum and natural gas are already used but manganese crust and undersea hydrothermal deposit has been explored. Specially, manganese nodule has received resources. It consists of manganese, nickel, copper, cobalt which is necessary materials for hi-technology industry. To develop a mining system for deep-sea mineral resources like manganese nodules is a challenging task in ocean engineering. A deep-seabed manganese nodule miner(DSNM) system is composed of collecting system, lifting system and surface vessel. Commercial deep underwater mining is expected to be realized in the recent future because of depletion of mining resources from land. As a method for the deep underwater mining, self propelled vehicle aims at proper positioning for the collecting system along the mining tracks on deep seafloor. Mining research using a tracked vehicle system has been studied in many countries including Germany, U.S.A., China, and Korea (Hong et.al., 2002). The tracked vehicle is operated on extremely soft cohesive soil to excavate valuable metals such as manganese nodule, and send those to surface vessel through lifting system.The control and monitoring of deep-sea miner in DSNM system is fragile and unique so that are hard to test and design system. This system is remotely operated in real-tine. The miner has many sensors and actuators with embedded controller.In this paper, we introduce about developing Hardware-in-the Loop Simulation(HILS) of control and monitoring system for DSNM. HILS is efficient tool of industrial application field for testing and estimating electronic devices or systems.HARDWARE-IN-THE-LOOP SIMULATIONExpansive, fragile, and unique systems are hared to test. You know the first releases of the software embedded in them will fail. But how? Hardware-in-the-loop simulation can substantially lower the cost of finding out.Now that we have PCs on every engineers desktop,simulation has become a common tool. Many engineers will either write a custom program to simulate the behavior of their product, or use an off-the-shelf tool.For instance, the controls engineer who designs the autopilots control algorithm will very likely simulate it in MATLAB, or with a custom C program running much faster than the real system on his PC. Similarly, many embedded software engineers first test the embedded code by running a reasonable facsimile of it on a desktop PC before porting it to the final microcontroller (or whatever). They “fake” the embedded systems I/O and environment with custom code executing on their PC. There are three key differences between such a simulation and a HILS.First, the outputs of simulations are just squiggly lines plotted on a graph, not hardware signals. Second, the HILS runs in real time, and third, in a HILS the embedded software runs on the “real” hardware that you will eventually build into your product, not a workstation.The control and monitoring system hardware of DSNM consist of two embedded controller (Fig. 4). We design architecture for testing embedded system using HILS, like Fig. 1.Fig. 1 A simple block diagram of an embedded system being tested using a HILSFig. 2 is components of simple HILS. This architecture is embodied H/W and S/W for input and output, and S/W for real model or physical model.Fig. 2 The components of a simple HILSThe consideration of developing and configuring HILS is as follows:a. Digitizing and iteration rateb. Choice of hardware platformc. Expansion usability to real modeld. Data logging and communicatione. Reusability and Flexibility HILS has many advantages of using real H/W and model,but the drawback of HILS is limit to represent internal operation of S/W and H/W. That is, only HILS does not alternate in-circuit, interface, logic emulator or analyzer of real system. And it is not S/W debugger. For configuration and design of system, therefore engineers technique that selects H/W and manages S/W is in the drivers seat. Another drawback of HILS is hard to stop while testing of system because HILS configure their loop. So these take in a reef for testing.DEEP-SEABED MANGANESE NODULE MINER SYSTMEThe DSNM largely consists of control, power and mechanical part, but signal processing, electronic control and hydraulic power part in viewpoint of control and monitoring.Mechanical part is water jet, rotary scraper, collector posture device, nodule crusher and driving sprocket which are controlled by proportional valve from hydraulic power part. And on purpose of DSNM miner, control signals must be sent to actuator parts properly. For this acquisition sensor data must be monitored consequently. Fig. 3 is composition of DSNM miner. Table 1 is measurement item and range for DSNM monitoring.Fig.3 Composition of DSNMTable 1. Measurement item and rangeThe control and monitoring embedded system designed like Fig. 4.Two embedded controller configured in “Local” and “Remote”. Each controller is connected by umbilical cable using fiber-optic communication. “Remote” controller takes in some function device such as vision acquisition, data acquisition, serial communication, digital I/O board. We use embedded controller, NI inc. PXI platform.This controller is high speed and industrial standard PCI bus with modular chassis. PXI(PCI Extensions for Instrumentation) was created in response to the needs of a variety of instrumentation and automation users who require ever increasing performance, functionality, and reliability from compact rugged systems that are easy to integrate and use. Existing industry standard are leveraged by PXI to benefit from high component availability at lower costs. Most importantly, by maintaining software compatibility with industry-standard personal computers, PXI allows industrial customers to use the same software tools and environments with which they are familiar.Fig.4 Diagram of control and monitoring embedded system for minerHILS OF DSNMThe concept of HILS for control and monitoring system of DSNM designed as Fig.5. Tow embedded controller and mineral simulator was made for HILS. In this research we simulate embedded controller and its GUI for developing control and monitoring system of DSNM.Fig.5 Diagram of a mix of real and simulated components LabVIEW is used for embedded controller and GUI programming tools. LabVIEW is graphic language for developing tool of control and monitoring system on NI inc. product.Fig. 6 is architecture of control and monitoring GUI part. Host program operate remote PXI controller for data acquisition and monitoring program manage monitoring data and service GUI for user. Video program is separated because of data traffic. Joystick is used for outer-input such as console and/or operating devices.Fig.6 Developed GUI using HILSFig. 7 is photo of simulator and control station for HILS we used. The simulator was not used real H/W (sensor and actuator). But electronic signal and data protocol type is similar to designing system for DSNM.Fig.7 Photo of simulator for control and monitoring system HILSFig. 8 is total architecture of HILS and H/W including control station, communication, PXI embedded controller and simulator. It is described as control and monitoring system of DSNM.CONCLUSIONSIn this paper we design HILS of control and monitoring system for DSNM. Control and monitoring simulator is used and PXI controller. Simulator just used for H/W signal representation but it is important that embedded controller tested and HILS tested. And DSNM control and monitoring system design properness is estimated.The test DSNM is already constructed like Fig. 9(MOERI, Daejeon, Korea). But this system just configures mechanical part and electronic and control part is designing now. In future work, simulator is used for testing real sensors and actuators and developing operation testing program for test miner.Fig.9 The test DSNMACKNOWLEDGEMENTSThis study is a part of the results of the R&D project, Development of Deep-Seabed Mining Technology supported by Korean Government. Authors are dept to appreciate Ministry of Maritime Affairs and Fisheries for the full support of this work.Fig.8 Total architecture of control and monitoring system for HILS of DSNM minerREFERENCESHong , S , Kim ,HW and Choi , JS (2002) . “Transient Dynamic Analysis of Tracked Vehicle on Extremely Soft Cohesive Soil” , Proc. 5th ISOPE Pacific/Asia Offshore Mechanics Sym. ,Daejeon , pp. 100-107. David M.Lane, G.J. Falconer, G. Randall, Ian Edwards, Jonathon Evans, Jeremy Smith, Julia Hunter, John Standeven ,Martin Colley (2001). “Interoperability and Synchronisation of Distributed Hardware-in-the-Loop Simulation for Underwater Robot Development: Issue and Experiments ” , Proc. of ICRA 2001 , Vol. 1, pp 909-914.D.Virzonis , T. Jukna , D. Ramunas (2004). “Design of the Embedded Software Using Flexible Hardware-in-Loop Simulation Scheme” , MELECON 2004,Vol .1, pp 351-354.Feijun Song , Andress Folleco , Edgar An (2001). “High Fidelity Hardware-In-the-Loop Simulation Development for an Autonomous Underwater Vehicle”, OCEANS 2001, Vol. 1, pp 444-449.Feijun Song , P. Edgar An, Andres Folleco (2003).”Modeling and Simulation of Autonomous Underwater Vehicles: Design and Implementation” , IEEE Journal of Oceanic Engineering, Vol.28, Issue 2,pp 283-296.Mark Karpenko , Nariman Sepehri (2006).”Hardware-in-the-Loop Simulation for Research on Fault Tolerant C

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