Autonomous, AI-based, engine health monitoring system · Autonomous, AI-based, engine health...
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Autonomous, AI-based, engine health monitoring system ¥ Machine learning/signal processing algorithm for autonomous health monitoring ¥ Remote User interface with health score reporting, trend analysis and user event logging ¥ Embedded system performing all calculations on board the vessel instantly ¥ Non-invasive vibration sensor magnetically attached to each cylinder head ¥ Crank angle sensor for TDC/RPM measurement ¥ Approvals in accordance with DNVGL-CG-0339 ¥ Ship-to-shore link (VSAT, FBB, cellular) ¥ Cloud-based portal for remote access to engine health data across a fleet ¥ Periodic Management Information System reporting/ performance assessment IConIC enables marine systems to be operated and maintained at optimum levels, reducing emissions and fuel consumption, and avoiding expensive downtime caused by unexpected engine faults. Easily retrofittable and using non-invasive sensors, IConIC uses Artificial Intelligence to learn what a healthy system looks like in a specific environment and then accurately monitors its health in real time to predict future faults, long before any other form of health monitoring, giving operators the insight required to determine the best possible maintenance strategy. Predictive Identifies failures earlier than any other platform-based techniques Immediate Delivers performance insight in real time to both ship’s crew and shore- side operations Measures system health Quantifies the system's health in its particular environment, rather than just a fault alarm Informs system-wide maintenance Combines intelligence from across platforms, enabling fleet-wide optimisation Complements maintenance operations Delivers visual diagnostics to the crew via portable devices Simple to implement Non-invasive, easy to install sensors, with compact, powerful processing units installed on board, rather than relying on remote processing Key Features Options
Transcript of Autonomous, AI-based, engine health monitoring system · Autonomous, AI-based, engine health...
Autonomous, AI-based, engine health monitoring system
¥ Machine learning/signal processing algorithm for autonomous health monitoring
¥ Remote User interface with health score reporting, trend analysis and user event logging
¥ Embedded system performing all calculations on board the vessel instantly
¥ Non-invasive vibration sensor magnetically attached to each cylinder head
¥ Crank angle sensor for TDC/RPM measurement ¥ Approvals in accordance with DNVGL-CG-0339
¥ Ship-to-shore link (VSAT, FBB, cellular) ¥ Cloud-based portal for remote access to engine health data across a fleet
¥ Periodic Management Information System reporting/performance assessment
IConIC enables marine systems to be operated and maintained at optimum levels, reducing emissions and fuel consumption, and avoiding expensive downtime caused by unexpected engine faults.
Easily retrofittable and using non-invasive sensors, IConIC uses Artificial Intelligence to learn what a healthy system looks like in a specific environment and then accurately monitors its health in real time to predict future faults, long before any other form of health monitoring, giving operators the insight required to determine the best possible maintenance strategy.
PredictiveIdentifies failures earlier than any other platform-based techniques
ImmediateDelivers performance insight in real time to both ship’s crew and shore-side operations
Measures system healthQuantifies the system's health in its particular environment, rather than just a fault alarm
Informs system-wide maintenanceCombines intelligence from across platforms, enabling fleet-wide optimisation
Complements maintenance operationsDelivers visual diagnostics to the crew via portable devices
Simple to implementNon-invasive, easy to install sensors, with compact, powerful processing units installed on board, rather than relying on remote processing
Key Features Options
Physical ¥ Dimensions: 500mm x 250mm x 125mm
¥ Display: 92mm x 31.5mm x 2.5mm OLED
¥ Housing: Aluminium ¥ Ingress protection: IP65 ¥ Power: PoE+ ¥ Interface: Ethernet ¥ Approvals tested DNVGL-CG0339
Operational ¥ Two 8-channel ADCs supporting 16 simultaneous accelerometers
¥ 2.4kHz sampling rate ¥ Dedicated TDC channel (Hall Effect)
¥ 32 thermocouple channels ¥ Internal data storage provision (2x SD card slots)
¥ Operating temperature range: 0 to 45° Celsius
Physical ¥ Dimensions: 500mm x 250mm x 125mm
¥ Housing: Aluminium ¥ Ingress protection: IP20 ¥ Power: 115-240V AC, PoE+ support for up to 2x DAUs
¥ Approvals tested DNVGL-CG0339
Operational ¥ IConIC application ¥ Feature sampling/Health Score generation (per channel): 520 per second
¥ GUI Health Score updates: once per minute
¥ Storage: 1TB M.2 SSD ¥ Interfaces: Ethernet [optional 802.11a/c + Bluetooth 4.0]
¥ Operating temperature range: 0 to 45° Celsius
¥ GUI compatible with Chrome/Firefox browsers, either via local RSU database or remote cloud-based portal
¥ Individual ship/engine selection ¥ Health score radar/history plots ¥ Minutes/hours/days trending ¥ Online maintenance logging ¥ Basic/Intermediate/Expert modes
¥ Auto-refresh mode ¥ Mobile interface with alerts
Technical Data
Data Acquisition Unit Remote Server Unit User Interface
Installation
¥ Retro-fit installation on existing/new vessels, in accordance with BS 7671:2018
¥ Fitting for propulsion systems, engines, generators and auxiliary machines
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Magnetically attached cylinder head accelerometers, IP67 with overbraided ETFE cable, temperature range -55 to 140°C
16-channel Data Acquisition Unit (DAU) with internal storage and independent real-time clock
Local database accessible via web browser over ship’s LAN
Mobile device access to server via WiFi (optional)
API for connection to cloud-based server via standard communications networks (cellular, FBB, VSAT)
Remote Server Unit (RSU) running up to two DAUs via POE+ (up to 100m range), with connection into ships LAN/other networks
