Monitoring System of Marine Engine Using Dynamic ID priority Allocation base on CAN

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1 , pp Monitoring System of Marine Engine Using Dynamic ID priority Allocation base on CAN Hyun Lee 1 and Kun Su Yoon 1 1 Seongnam Campus of Korea Polytechnic, Seongnam, 13590, Korea 2 Aviation Campus of Korea Polytechnic, Sacheon, 52549, Korea {hlee81, unikyoon}@kopo.ac.kr Abstract. This paper proposes a marine engine state monitoring system using a dynamic ID application and a scheduling method of CAN network sensors which collect the temperatures of bearings and pressures of engine through the network. This paper aims at developing an effective monitoring method for marine engine system, which is implemented based upon CAN (Controller Area Network) network. Keywords: Controller area network, dynamic ID priority allocation mode, Engine State Monitoring Systems 1 Introduction A marine engine state monitoring system purposes precise and rapid transmission of engine condition data from various measurement instruments to the engine control room. A failure of engine in sailing ships affects very critically to the operating ship, and may cause enormous financial losses. Bearing damage can be happened suddenly and unpredictably. This is causes serious damage of main structure of engine and finally engine can t be operated. So, real-time monitoring system for preventing the unpredictable failure and maintaining support of marine engine is needed. There are many methods on-line monitoring the wear of the piston ring, including cylinder pressure monitoring, oil monitoring, vibration and noise monitoring, thin layer activation (TLA) method and magnetic sensor monitoring etc [1]. A major advantage in using the CAN technology [2-3] against other kinds of field-buses available is wide choices of very cheap electronic components. Engine management system can be started with measuring of each part of engine (Fig. 1). Engine State Monitoring System can be divided into three parts. Status measuring sensors which measures temperature, pressure, perception of flowing and various status indication factors are equipped with the CAN Module. And CAN Module consist of microprocessor and CAN transceiver and transmits data from sensors to the SCU, respectively. And SCU (Signal Control Unit) collects entire network data and transmits engine condition signal to the ECR (Engine Control Room) and ER (Engine Room) via RS-485. ISSN: ASTL Copyright 2016 SERSC

2 Fig. 1. Marine Engine Management System 2 Controller Area Network Protocol The CAN protocol is based on a CSMA/CS channel access technique, modified to enforce a deterministic resolution of collisions on a network which uses a priority scheme based on the identifiers of exchanged objects. The CAN protocol adopts a layered architecture which is based on the OSI reference model, even though it is not fully OSI compliant. As with other networks conceived for the factory automation environment, it relies on a reduced protocol stack, consisting only of the Physical layer, Data link layer, and Application layer. This paper is focused on the data link layer. S O F Arbitration Control Data CRC 1 bit 11 bit or 29 bit 4 bit 0~8 bytes 15 bit 2 bit 7 bit Fig. 2. CAN Standard Data Frame The worst-caste response time of the message includes the queuing jitter, the queuing time and the time taken to send the rest of the message [4-6]. Jm R J C m m m m where the queuing jitter corresponding to the longest time between the initiating event and the message being queued, ready to be transmitted on the bus. The queuing delay m corresponding to the longest time that the message can remain in the CAN controller slot or device driver queue, before commencing successful transmission on C the bus. The transmission time m represents the longest time needed to physically transmit a message (m) over the CAN network. There are lots of stuffing bits and A C K E O F (1) Copyright 2016 SERSC 461

3 various other things (CRC etc) but the message time for a message with size bytes is bit where is the time to send one bit. The maximum amount of blocking occurs when a lower priority message starts transmission immediately before message (m) is queued and hence ready to be transmitted on the bus. Message (m) must wait until the bus is idle before it can be entered into arbitration. The maximum blocking time is where lp( m) g 8sm 1 Cm ( g 8sm 13 [ ] bit ) 4 max( C ) k k lp ( m) is the set of messages with lower priority than (m). Bus utilization relates the proportion of the bus busy time by message transmissions including sporadic messages to total time of system run. Bus utilization can be expressed as B m s m data (2) B m (3) U n Ci T i 1 i (4) 3 Dynamic ID Priority Allocation To distinguish the dangerous situation of component of marine monitoring system, it has setting value, physical range for measurement, limited bounded bandwidth and frequency response of sensor. In case of measurement of physical rare, high value is generally considered dangerous state and flow detection sensor indicate high or low. So, if marine engine has problem in shipping operation. We have to slow down speed of marine engine or indicating alarm in shipping operation. After AD Conversion through the Microprocessor, this data is transmitted by CAN bus. Fig. 3. Dynamic ID allocation Mode 462 Copyright 2016 SERSC

So, CAN Module classifies Group ID 3bit of Shut Down, Slow Down, Alarm for marine engine state monitoring. Fig. 3 Shows Dynamic ID allocation mode of Arbitration in CAN data frame.

4 So, CAN Module classifies Group ID 3bit of Shut Down, Slow Down, Alarm for marine engine state monitoring. Fig. 3 Shows Dynamic ID allocation mode of Arbitration in CAN data frame. Dynamic ID Priority Allocation Mode. In this paper, we proposed marine engine state monitoring system as assignment of each node priority by dynamic ID priority allocation and task scheduling which is used Group classification of shut down (90%), slow down (80%), alarm (70%) of engine state for efficient utilization on CAN bus. 3.1 Task Scheduling Using Transmission Period Time The transmission period of each node is 500us and baud rate is 500kbps. Equation of CAN bus utilization was as follow using equation (4) depending on time of received message to SCU. C m T r U is the worst-case response time of message and is time period of received message and n Ci T CmN T B i 1 i r B N is baud rate. (5) is total number of message. Fig. 4. CAN Module hardware structure. Fig. 4 is a CAN communication module. Each object was used STM32F107 Cortex-M3 32bit RISC with CAN communication module. 4 Experiments and Results In this paper, the engine state monitoring system has been implemented, which is composed of ten CAN modules and one SCU to evaluate the effectiveness of the proposed method. Copyright 2016 SERSC 463

not to lose any necessary information for the engine control.

5 Fig. 5. Experiment system architecture Fig. 6. Received message using dynamic ID Priority allocation mode. 5 Conclusion In this paper, dynamic allocation CAN priority for the marine engine state monitoring system is proposed not to lose any necessary information for the engine control. Scheduling technique is applied for the groups of the sensor nodes, which improves the efficiency of bus utilization by the dynamic ID allocation to each sensor node. 464 Copyright 2016 SERSC

6 Acknowledgments. This research was supported by the Agency for Defense Development, South Korea, under Grant (UD160014DD). References 1. Research on Monitoring wear of Piston Ring Based on Magneto-Resistive Sensor for Marine Diesel Engine 2. Bosch, CAN Specification Version 2.0, Robert Bosch GmbH. Stuttgard (1991) 3. International Standard Organization, Road - vehicles Interchange of digital information - Controller area network for high-speed communication, ISO 11898, November (1993) 4. Tindell, K., Burns, A., Wellings, A.J.: Calculating Controller Area Network Message Response Times, Control Engineering Practice, Huang, S., Li, W., Li, W.: Editors. Proceedings of the First International conference on Innovative Computing, Information and Control, (2006) August 30-Septmber 1; Beijing, China 6. Davis, R. I., Burns, A.: J. Real-Time Syst. 41, 2 (2009) Copyright 2016 SERSC 465

Development of Technique for Healing Data Races based on Software Transactional Memory

, pp.482-487 http://dx.doi.org/10.14257/astl.2016.139.96 Development of Technique for Healing Data Races based on Software Transactional Memory Eu-Teum Choi 1,, Kun Su Yoon 2, Ok-Kyoon Ha 3, Yong-Kee Jun