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Control and monitoring systems evolution and future
Chapter 20
Control and monitoring systems evolution and future Chapter outline 20.1 Control and monitoring systems evolution and future 169
Abstract This chapter describes the evolution of control and monitoring systems from the 20th century to the present date. Also described are future trends automation systems including trends to design and build of autonomous ships. Also described are trends in development of Artificial Intelligence techniques in Integrated Automation Systems (IAS), Dynamic Positioning (DP) Systems, Position Mooring (PM) Systems and autonomous ships development.
20.1 Control and monitoring systems evolution and future Development of control and monitoring systems on board vessels began in the early 1950s. At that time an Engine Room Logbook was simply kept on a desk in the Engine Room near the main switchboard and was regularly updated by the Marine Engineer Watchkeeper and countersigned by the Chief Engineer. Control systems were mainly limited to remote control of main propulsion, automatic control of hydrophore pumps, air compressors etc. Later, the Chief Engineer desk was located in a small room that was separated from the Engine Room. Near the desk were installed some monitoring instruments. By the beginning of the 1960s most new ships had an Engine Control Room (ECR) containing the Engine Control Room Console (ECRC) as well as the engineer’s desk. Development of electric, electronic, pneumatic and hydraulic control systems allowed the control and monitoring of most Engine Room equipment from the ECRC. In the 1970s, development of programmable digital computers allowed the control and monitoring of machinery systems with Supervisory Control and Data Acquisition (SCADA) systems. In the 21st Century, ships and offshore units are fitted with Integrated Control Systems (ICS) including Integrated Automation Systems (IAS), Dynamic Positioning (DP) systems, Thruster Control Systems, and Safety Systems with Ship and Mobile Offshore Unit Automation. https://doi.org/10.1016/B978-0-12-818723-4.00020-X © 2019 Elsevier Inc. All rights reserved.
169
170 Ship and mobile offshore unit automation
Emergency Shutdown (ESD) and Fire & Gas functionality. Modern Integrated Control Systems are based on distributed processing and data acquisition units connected by redundant networks - either fibre optic cables or twisted pair cables. Main system elements are redundant, including Human Machine Interfaces (HMI) - operator stations, monitors, process controllers with dual computers, Input/Output (I/O) modules and Uninterruptable Power Suppliers (UPS). The number of digital and analogue I/O for control and monitoring systems varies greatly depending on the vessel type and size, but is typically between 5000 to 9000. Laser printers are used for data logging. Monitors on Operator Stations provide system mimic diagrams illustrating process flows, existing alarms and previous alarms and events list. The number of mimic diagrams (a.k.a. process views) can be about 150. Built-in self-diagnostic facilities monitor the system components and communication links. Fail-safe mechanisms are automatically activated in case of failure. Modern Integrated Control Systems software is built up from algorithms precisely defining different control and monitoring equipment operation sequences. Some Dynamic Positioning systems use a vessel mathematical model—Kalman Filter—for calculations of vessel positioning and heading response. A potential next step in vessels and offshore unit control systems development is fully or partly autonomous ships. There are extremely high requirements for systems to be installed on such vessels. Currently engineers and scientists are working on development of Maritime Autonomous Surface Ships (MASS) that can operate partially or fully independently of human interaction. Such systems require to accommodate new technologies including the highest level of digitalization and automation having in mind vessel safety. During design and development processes different degrees of autonomy will be taken into consideration, i.e. ●
●
● ●
Ship with automated processes and decision support in which some crew is on board to operate and control shipboard systems, and some operations are automated hip is remotely controlled and operated from another location but limited number of crew members are onboard Ship is fully remotely controlled and there is no crew onboard Ship is fully autonomous and all operating systems make decisions and determine actions by themselves
Maritime Autonomous Surface Ships (MASS) will require installation of advanced sensors which take care of the lookout duties onboard the vessel by continuously fusing sensor data from navigational systems such as Radio Detecting And Ranging - RADARs, Automatic Identification System (AIS) combined with daylight and infrared camera images. Autonomous ships additionally require designated autonomous navigation systems that follows
Control and monitoring systems evolution and future Chapter | 20 171
predefined voyage plans with certain degrees of freedom to adjust the route having in mind weather changes and navigational situations. Control and monitoring systems on autonomous ships will require to be designed to fulfil ship’s engine room and propulsion automation systems advanced failure pre-detection functionalities having in mind vessel optimal efficiency and propulsion redundancy. There will be additional challenges for interfacing autonomous ships systems with shore based personnel including: Shore Control Centre Operator who monitors the safe operation of several ships simultaneously from shore station and controls the vessels by giving high level commands for example “change voyage plan”, Shore Control Centre Engineer who assists the operator with any technical issues including maintenance plan based on condition based maintenance system program to ensure sufficient vessels technical systems reliability, and Shore Control Centre Situation Team that is able to take over direct remote of the vessel to ensure an appropriate situation awareness. Maritime Autonomous Surface Ships (MASS) will require development of ship-shore and ship-ship communication systems to ensure security and reliability of integrated ship data networks. Future autonomous ships will need special Advanced Sensor modules for objects detection and classification. Such systems will use input data from infrared and visual spectrum cameras, Radar, and Automatic Identification System (AIS) data to detect any surrounding objects and to determine if they may cause danger for the ship or need to be further investigated i.e. life rafts or other floating objects. This system shall collect all data from navigational, metrological and safety sensors to identify objects causing potential hazard for the ship. Control and monitoring systems on autonomous ships need to be more advanced than on today’s ships by adding sophisticated condition monitoring functions to prevent vessel critical systems malfunctions and breakdowns during the sea voyage. These systems need to be linked with maintenance planning systems. Control and monitoring systems shall deliver information necessary to monitor equipment diagnostics, for example equipment thermal overloads or vibration. This information will be used by decision support system in Shore Control Centres. Extended control and monitoring system data shall be aggregated to minimise satellite communication bandwidth. Development of control and monitoring systems for Maritime Autonomous Surface Ships (MASS) will have influence on designing Integrated Automation Systems (IAS) for vessels with unmanned Engine Room and automation systems, dynamic positioning and position mooring. All ship and offshore unit functions are based on condition detection, condition analysis, action planning and action control. To carry out a ship functions, new reliable vessel/offshore unit condition detection sensors must be employed, i.e. for example daylight cameras of different type as stereo or multispectral, infrared cameras and Light Detection and Ranging Cameras
172 Ship and mobile offshore unit automation
(LIDAR). These detectors shall be reliable in adverse conditions such as heavy seas, darkness, fog, heavy seas and snowfall. Autonomous ships need redundant Global Navigation Satellite System (GNSS) i.e. to existing USA Global Positioning System (GPS) another systems need to be used, for example European Union Global Navigation Satellite System Galileo, Russian Global Navigation Satellite System (GLONAS) or China BeiDou Navigation Satellite System (BDS). Additionally Maritime Autonomous Surface Ships (MASS) need reliable nautical charts identifying Zones of Confidence (ZOC) and risks of collision and grounding. Supplementary sensors will be required to assess the capability of propulsion and steering at defined time as well as for predicting any possible changes in this capability. Installed sensors will need to have homogenous redundancy by installing two or more sensors or heterogeneous redundancy by installing several sensors measuring different quantities and calculating the quantity without taking into account unexpected measurement. Condition analysis needs to be carried out by powerful computers when all relevant information is detected/measured. When processes conditions are determined then based on Artificial Intelligence computers develop an action plan and assign action control to assigned automated systems or onboard personnel. In the future, the quantity of control and monitoring data to be handled is expected to continue to grow and new Decision Support Systems (DSS) based on Artificial Intelligence (AI) techniques may start to be used on board vessels and offshore units. To increase safety, many sophisticated computer based systems are already installed on board vessels and offshore units, but a large percentage of sea accidents and collisions are the result of human errors arising from difficulties to make proper decisions under stress and having to process large amounts of information and alarms. Such Decision Support Systems will be based on Artificial Intelligence using expert knowledge and operating on neutral network principles. Artificial Intelligence technology requires development of AI-models that will help predict the most efficient way to operate a particular vessel or offshore unit automation system. One example of implementing Artificial Intelligence technology is ‘Control system to reduce vessel fuel consumption’ using AI simulations in different scenario before suggesting the most optimal route and performance setup taking into consideration a number of variables such as currents, weather conditions, shallow water and speed through water. Another example of using Artificial Intelligence technology to increase safe of navigation the vessel is development officer on watch ‘adviser’ that analyse data from shipboard sensors, cameras and microphones to create a picture of the hazards around the ship. Such picture may be presented on officer on watch portable tablet or Smartphone to help in safe navigation. In short time Artificial Intelligence will be used to reduce maintenance costs. Nowadays a Condition Based Monitoring (CBM) database is used to plan Condition Based Maintenance activities. Artificial Intelligence (AI) technology by deep learning
Control and monitoring systems evolution and future Chapter | 20 173
capacity to analyse very large amount of high dimensional data will change Preventive Maintenance System (PMS) to higher level predictive maintenance system that is particularly valuable in the case of hard worked assets such as Main Engines, by combining engine model data, maintenance history, data from sensors around engines such as sound, temperature etc., engine sensors data as lube oil temperature, cooling water temperature, vibration etc. and images from video cameras. Artificial Intelligence technology will reduce risks for workers in hydrocarbon exploration and production by replacing them with intelligent robots. Additionally, these robots will be used in oil fields exploration seep detection and so reduce sea pollution. In the future, on board Artificial Intelligence systems will be operated with a common operating system to enable the connection of various types of equipment in the ship to one common operating control system. For example, using such a system crew may be able to read the data and control equipment using special applications in their Smartphone. Before implementing above developments, all related cyber security threats, legal and liability matters must first be solved, and these are significant challenges in their own right. Cyber attacks may include remote or physical interaction with the vessel/offshore unit IAS or stealing/damaging control and monitoring sensors and actuators. Consequences of cyber attacks on fully autonomous ships could be extremely high because it may be not possible to correct the vessel situation by a crew.
Control and monitoring systems evolution and future Chapter outline 20.1 Control and monitoring systems evolution and future 169
Abstract This chapter describes the evolution of control and monitoring systems from the 20th century to the present date. Also described are future trends automation systems including trends to design and build of autonomous ships. Also described are trends in development of Artificial Intelligence techniques in Integrated Automation Systems (IAS), Dynamic Positioning (DP) Systems, Position Mooring (PM) Systems and autonomous ships development.
20.1 Control and monitoring systems evolution and future Development of control and monitoring systems on board vessels began in the early 1950s. At that time an Engine Room Logbook was simply kept on a desk in the Engine Room near the main switchboard and was regularly updated by the Marine Engineer Watchkeeper and countersigned by the Chief Engineer. Control systems were mainly limited to remote control of main propulsion, automatic control of hydrophore pumps, air compressors etc. Later, the Chief Engineer desk was located in a small room that was separated from the Engine Room. Near the desk were installed some monitoring instruments. By the beginning of the 1960s most new ships had an Engine Control Room (ECR) containing the Engine Control Room Console (ECRC) as well as the engineer’s desk. Development of electric, electronic, pneumatic and hydraulic control systems allowed the control and monitoring of most Engine Room equipment from the ECRC. In the 1970s, development of programmable digital computers allowed the control and monitoring of machinery systems with Supervisory Control and Data Acquisition (SCADA) systems. In the 21st Century, ships and offshore units are fitted with Integrated Control Systems (ICS) including Integrated Automation Systems (IAS), Dynamic Positioning (DP) systems, Thruster Control Systems, and Safety Systems with Ship and Mobile Offshore Unit Automation. https://doi.org/10.1016/B978-0-12-818723-4.00020-X © 2019 Elsevier Inc. All rights reserved.
169
170 Ship and mobile offshore unit automation
Emergency Shutdown (ESD) and Fire & Gas functionality. Modern Integrated Control Systems are based on distributed processing and data acquisition units connected by redundant networks - either fibre optic cables or twisted pair cables. Main system elements are redundant, including Human Machine Interfaces (HMI) - operator stations, monitors, process controllers with dual computers, Input/Output (I/O) modules and Uninterruptable Power Suppliers (UPS). The number of digital and analogue I/O for control and monitoring systems varies greatly depending on the vessel type and size, but is typically between 5000 to 9000. Laser printers are used for data logging. Monitors on Operator Stations provide system mimic diagrams illustrating process flows, existing alarms and previous alarms and events list. The number of mimic diagrams (a.k.a. process views) can be about 150. Built-in self-diagnostic facilities monitor the system components and communication links. Fail-safe mechanisms are automatically activated in case of failure. Modern Integrated Control Systems software is built up from algorithms precisely defining different control and monitoring equipment operation sequences. Some Dynamic Positioning systems use a vessel mathematical model—Kalman Filter—for calculations of vessel positioning and heading response. A potential next step in vessels and offshore unit control systems development is fully or partly autonomous ships. There are extremely high requirements for systems to be installed on such vessels. Currently engineers and scientists are working on development of Maritime Autonomous Surface Ships (MASS) that can operate partially or fully independently of human interaction. Such systems require to accommodate new technologies including the highest level of digitalization and automation having in mind vessel safety. During design and development processes different degrees of autonomy will be taken into consideration, i.e. ●
●
● ●
Ship with automated processes and decision support in which some crew is on board to operate and control shipboard systems, and some operations are automated hip is remotely controlled and operated from another location but limited number of crew members are onboard Ship is fully remotely controlled and there is no crew onboard Ship is fully autonomous and all operating systems make decisions and determine actions by themselves
Maritime Autonomous Surface Ships (MASS) will require installation of advanced sensors which take care of the lookout duties onboard the vessel by continuously fusing sensor data from navigational systems such as Radio Detecting And Ranging - RADARs, Automatic Identification System (AIS) combined with daylight and infrared camera images. Autonomous ships additionally require designated autonomous navigation systems that follows
Control and monitoring systems evolution and future Chapter | 20 171
predefined voyage plans with certain degrees of freedom to adjust the route having in mind weather changes and navigational situations. Control and monitoring systems on autonomous ships will require to be designed to fulfil ship’s engine room and propulsion automation systems advanced failure pre-detection functionalities having in mind vessel optimal efficiency and propulsion redundancy. There will be additional challenges for interfacing autonomous ships systems with shore based personnel including: Shore Control Centre Operator who monitors the safe operation of several ships simultaneously from shore station and controls the vessels by giving high level commands for example “change voyage plan”, Shore Control Centre Engineer who assists the operator with any technical issues including maintenance plan based on condition based maintenance system program to ensure sufficient vessels technical systems reliability, and Shore Control Centre Situation Team that is able to take over direct remote of the vessel to ensure an appropriate situation awareness. Maritime Autonomous Surface Ships (MASS) will require development of ship-shore and ship-ship communication systems to ensure security and reliability of integrated ship data networks. Future autonomous ships will need special Advanced Sensor modules for objects detection and classification. Such systems will use input data from infrared and visual spectrum cameras, Radar, and Automatic Identification System (AIS) data to detect any surrounding objects and to determine if they may cause danger for the ship or need to be further investigated i.e. life rafts or other floating objects. This system shall collect all data from navigational, metrological and safety sensors to identify objects causing potential hazard for the ship. Control and monitoring systems on autonomous ships need to be more advanced than on today’s ships by adding sophisticated condition monitoring functions to prevent vessel critical systems malfunctions and breakdowns during the sea voyage. These systems need to be linked with maintenance planning systems. Control and monitoring systems shall deliver information necessary to monitor equipment diagnostics, for example equipment thermal overloads or vibration. This information will be used by decision support system in Shore Control Centres. Extended control and monitoring system data shall be aggregated to minimise satellite communication bandwidth. Development of control and monitoring systems for Maritime Autonomous Surface Ships (MASS) will have influence on designing Integrated Automation Systems (IAS) for vessels with unmanned Engine Room and automation systems, dynamic positioning and position mooring. All ship and offshore unit functions are based on condition detection, condition analysis, action planning and action control. To carry out a ship functions, new reliable vessel/offshore unit condition detection sensors must be employed, i.e. for example daylight cameras of different type as stereo or multispectral, infrared cameras and Light Detection and Ranging Cameras
172 Ship and mobile offshore unit automation
(LIDAR). These detectors shall be reliable in adverse conditions such as heavy seas, darkness, fog, heavy seas and snowfall. Autonomous ships need redundant Global Navigation Satellite System (GNSS) i.e. to existing USA Global Positioning System (GPS) another systems need to be used, for example European Union Global Navigation Satellite System Galileo, Russian Global Navigation Satellite System (GLONAS) or China BeiDou Navigation Satellite System (BDS). Additionally Maritime Autonomous Surface Ships (MASS) need reliable nautical charts identifying Zones of Confidence (ZOC) and risks of collision and grounding. Supplementary sensors will be required to assess the capability of propulsion and steering at defined time as well as for predicting any possible changes in this capability. Installed sensors will need to have homogenous redundancy by installing two or more sensors or heterogeneous redundancy by installing several sensors measuring different quantities and calculating the quantity without taking into account unexpected measurement. Condition analysis needs to be carried out by powerful computers when all relevant information is detected/measured. When processes conditions are determined then based on Artificial Intelligence computers develop an action plan and assign action control to assigned automated systems or onboard personnel. In the future, the quantity of control and monitoring data to be handled is expected to continue to grow and new Decision Support Systems (DSS) based on Artificial Intelligence (AI) techniques may start to be used on board vessels and offshore units. To increase safety, many sophisticated computer based systems are already installed on board vessels and offshore units, but a large percentage of sea accidents and collisions are the result of human errors arising from difficulties to make proper decisions under stress and having to process large amounts of information and alarms. Such Decision Support Systems will be based on Artificial Intelligence using expert knowledge and operating on neutral network principles. Artificial Intelligence technology requires development of AI-models that will help predict the most efficient way to operate a particular vessel or offshore unit automation system. One example of implementing Artificial Intelligence technology is ‘Control system to reduce vessel fuel consumption’ using AI simulations in different scenario before suggesting the most optimal route and performance setup taking into consideration a number of variables such as currents, weather conditions, shallow water and speed through water. Another example of using Artificial Intelligence technology to increase safe of navigation the vessel is development officer on watch ‘adviser’ that analyse data from shipboard sensors, cameras and microphones to create a picture of the hazards around the ship. Such picture may be presented on officer on watch portable tablet or Smartphone to help in safe navigation. In short time Artificial Intelligence will be used to reduce maintenance costs. Nowadays a Condition Based Monitoring (CBM) database is used to plan Condition Based Maintenance activities. Artificial Intelligence (AI) technology by deep learning
Control and monitoring systems evolution and future Chapter | 20 173
capacity to analyse very large amount of high dimensional data will change Preventive Maintenance System (PMS) to higher level predictive maintenance system that is particularly valuable in the case of hard worked assets such as Main Engines, by combining engine model data, maintenance history, data from sensors around engines such as sound, temperature etc., engine sensors data as lube oil temperature, cooling water temperature, vibration etc. and images from video cameras. Artificial Intelligence technology will reduce risks for workers in hydrocarbon exploration and production by replacing them with intelligent robots. Additionally, these robots will be used in oil fields exploration seep detection and so reduce sea pollution. In the future, on board Artificial Intelligence systems will be operated with a common operating system to enable the connection of various types of equipment in the ship to one common operating control system. For example, using such a system crew may be able to read the data and control equipment using special applications in their Smartphone. Before implementing above developments, all related cyber security threats, legal and liability matters must first be solved, and these are significant challenges in their own right. Cyber attacks may include remote or physical interaction with the vessel/offshore unit IAS or stealing/damaging control and monitoring sensors and actuators. Consequences of cyber attacks on fully autonomous ships could be extremely high because it may be not possible to correct the vessel situation by a crew.