Forever committed to improving shipboard safety, maritime classification society DNV GL has developed the new notation F(M-P), which guides increased prevention of fires in machinery spaces.
This new classification identifies possible machine room hazard areas, including oil leakage and ignition, and recommends solutions offered by Fike Corporation to prevent oil mist-related fires and explosions.
Dangers of Oil Mist
One of the most common sources of marine engine room fires, oil mist is caused by minor leaks in pressurized fuel lines or when fuel makes contact with a hot surface and vaporizes. Common hazard areas include diesel generators, diesel propulsion generators, boilers, purifiers and fuel modules, emergency diesel generators, and incinerator rooms.
An effective solution to meet the F(M-P) notation, DNV GL lists automatic oil detection by video analytics
“…the majority of fires which have occurred in engine rooms are generally caused by a leak or fracture from a flammable liquid system, the fuel system being the main problem area.” – Maritime Safety Committee, 75 Session, Agenda Item 22
Solutions of oil Mist
Included in the F(M-P) notation is the requirement for a “rapid oil leak detection system” to protect critical leakage points in an engine room.
As an effective solution to meet the F(M-P) notation, DNV GL lists “automatic oil detection by video analytics,” a product engineered and offered by Fike Corporation.
What is Video Analytics?
Fike Video Analytics’ detection algorithms visually identify oil mist, smoke, flame, and reflected flame
Monitoring video from commonly available cameras with ONVIF certification, Fike Video Analytics’ detection algorithms visually identify oil mist, smoke, flame, and reflected flame. When a hazard is detected, engine room staff is often alerted by the alarm, and a live “pop-up” video with analytics overlay identifies the oil mist, smoke, or flame and its location.
“Several years were spent developing our analytics to specifically detect oil mist for the machinery space environment,” said Rick Jeffress, Fike Director of Video Analytics Business Development.
detection of oil mist
“We’ve had more than a year of shipboard trials and received technical input from major cruise lines to help fine-tune the algorithms. After evaluating their requests, we’ve made numerous upgrades to the software in both features and function.”
While the F(M-P) classification went into effect in July 2019, major cruise lines, cargo vessels, naval ships, and others have been using Fike Video Analytics to detect oil mist for years. Some major cruise lines specifically include Fike in their corporate safety standards. Currently, more than 3,400 of their machinery space cameras are monitored by Fike Video Analytics.
Fike Machinery Space Monitoring Solutions
Fike’s alarms may be set to activate at any temperature and signal the crew to take action
In addition to video analytics, Fike also offers Thermal Imaging Technology, which addresses another F(M-P) requirement. Section 4.5.2.1 of F(M-P) focuses on solutions for hot surface insulation, stating that “maximum allowed surface temperature in Category A machinery spaces shall be 150° C upon completion of installation or after maintenance, and 180°C during operation.”
Fike’s Thermal Imaging Technology cameras monitor the temperature of engines using thermal radiometry, and predefined alarms may be set to activate at any temperature and signal the crew to take action. These systems may be remotely monitored via a live video feed.
Monitoring temperature changes
Furthermore, historical data may be monitored to measure gradual or immediate increases in temperatures. “Without a fixed thermal imaging camera, the crew is required to take readings with handheld devices,” Jeffress said.
“It is difficult to obtain consistent readings with these devices because readings may be taken from different spots or varying angles than those captured previously. With a fixed camera, you get a consistent view and therefore may confidently measure temperatures or monitor them over time.”