I am Rick Jeffress and I handle sales for Fike Video Image Detection. We thank the AFAA for coordinating the venue for this presentation, and we

Transcription

1 I am Rick Jeffress and I handle sales for Fike Video Image Detection. We thank the AFAA for coordinating the venue for this presentation, and we appreciate your taking the time to learn more about this exciting technology. 1

2 In this discussion, you ll find that, in many cases video image detection (VID) systems can effectively provide earlier detection than other types of detectors. As we re using video analytics and software, you will also see that we can customize the detector to the application based on layout and environment for best results. There are about 7 VID systems that we know of on the market, they all use video analytics for detection, however processing of the video, customization and video output available are all unique. Since we have only worked with one system, we will discuss, in general, how all systems work and details of the system with which we are familiar.

3 This is the UL test facility, an engineer lights a smoke emitter. The blue outline and word smoke on the bottom of the screen indicate the system is in alarm and relay has activated. Notice the clear stratification layer, other detectors mounted at ceiling by code may not be in alarm. VID allows detection in the entire camera field of view, effectively eliminating stratification detection issues.

4 Video analytics are used in manufacturing, security systems and video games and has been around for decades, we are using the technology in a different manner to detect flame and smoke.

5 Video Image Detection systems use visual imaging and analytics, some use artificial intelligence and a neural network (to process a lot of information quickly) to detect fire and motion very early. The analytics software was trained using videos of real fires and images representing false fires. Common camera resolution is 480X640 which is 300,000 pixels, some systems analyze 15 frames per second, in this case the camera is performing 4.5M calculations/second analyzing the field of view for flame and smoke.

6 This is an example of an IP camera based system, the analytics are in the camera. The fire alarm panel is providing power and monitoring the relay contacts for alarm and trouble. A network video recorder is recording the video and acting as an interface between a computer terminal running the interface software and the camera. Video image detector video output can also be integrated into existing video surveillance systems.

7 This is an example of a server based system, an analog or digital camera is connected to a DVR where the analytics are analyzing the camera video for fire. Relays on the DVR are monitored by the fire alarm system.

8 Common field of view of VID cameras is 82 degrees horizontally and 62 degrees vertically, layout begins in the hazard corners to follow the 90 degree angle of the walls. The cameras are installed at about ¾ of the ceiling height around the perimeter of a space, and in most cases well within reach of a ladder. Ceiling construction and beam pockets do not effect the listed detection area of VID detectors. Installed cost of VID systems average 35% lower than some other detector types in high ceiling applications.

9 These are common applications for VID; large volume and high ceiling spaces. Imagine the system operating in the center location, and a fire has occurred. Viewing live video, the control room operator can direct first responders to the fire and away from danger. The recorded video can be used to identify cause of fire and train first responders. Fire investigation is simple with the recorded video.

10 VID systems have available algorithms to detect flame, smoke, reflected firelight and motion. Each detection type (algorithm) can be used independently or in any combination based on the hazard and environment. For each algorithm we can create detect/blocking zones, set a schedule for the zones, adjust sensitivities, set alarm verification time delays and program the relays to follow any single or combination of algorithms.

11 The camera is a visual spectrum detector, it does not use heat, UV, or IR to detect flame. The camera analyzes slow changing brightness effecting the pixels, flame movement and dynamic flicker consistent with known flame signatures. This information is processed in the neural network and is identified as a flame.

12 The left image is what the camera sees; slow changing brightness and flame movement as well as reflection of the flame effecting the camera pixels. The right image is what we see and the analytics have identified the source of the flicker and outlined the flame with a red box.

13 Some VID systems can detect the reflection of flame without seeing the flame directly in the camera field of view. This is great for machinery spaces and areas where there are a lot of obstructions. There are no listings for this algorithm but it can be helpful in fire detection. 13

14 This video is a VID system detecting flame at a power plant. When we set up a new system, we install the cameras and let the system record to see how it will react with the environment. After a few days we return and identify any detection issues and fine tune the settings for highest sensitivity and low false alarms.

15 Further to the previous slide, this is a Magnesium plant where there is an open flame normally in the process. There is a 40 high ceiling, cannot use heat detection, smoky environment, cannot use conventional smoke detection. Due to the open flame, UV/IR flame detectors cannot be used. We recorded detections during the normal process and placed blocking zones where flame occurs. The plant operates 9-5 during the week, therefore we set the blocking zones on a schedule to turn on at 8 am and off at 6 pm allowing full detection nights and weekends. Smoke and motion detection can be scheduled for night and weekends if desired.

16 We ve discussed flame and reflected firelight. For smoke detection, in normal conditions there is a sharp image, when smoke is present, the pixels become opaque or fuzzy. The camera identifies and tracks the group of effected pixels and generates a blue outline on alarm. The camera also tracks the movement of the smoke by tracking the amount of time the pixels are effected, looking for plume movement consistent with a smoke signature.

17 A smoke emitter was set up on the left side of the screen and smoke is drifting into the camera s field of view. The camera is detecting the smoke as it is moving in the center of the space and not near the ceiling or the walls. There may be stratification in this case, however we cannot tell for sure.

18 Depending on the size of fire and distance from the camera, the camera can still detect large fires in their field of view.

19 Even if we cannot see the smoke, sometimes the camera can see smoke before we do.

20 For motion detection, the yellow lines represent the X-Y axis of the object in the camera s field of view.

21 Standard IP VID detector back plate. 24vdc power connection, two alarm and one trouble relay contacts, Ethernet and coax connection and status lights. Some systems have the ability to provide Modbus TCP signals used in industrial applications.

22 Cameras can be installed in enclosures based on the hazard classification and environmental conditions. Heaters and fans are options. 22

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24 Detectors can be UL, ULC and/or FM listed. UL uses UL 268B for video smoke detection with listing based on a 4 minute smoke emitter at 100 and FM Global has FM 3260 or 3232 with listing based on a 1 pan fire at 100. This confirms that they are both on board with the VID technology.

25 FM recently published datasheet 5-48 specifically recommending VID in special hazard applications. Hazards include: Read list

26 NFPA defined and adopted video image detection in Discussion of VID is similar to other types of detection and wording is similar in the 2010 and 2013 editions. 26

27 This is the NFPA 72 section on VID smoke detection, note the requirement for a performance based design. Performance based design, in general, includes determining expected fire type and size and designing the system coverage with an evaluation of the hazard. 27

28 This is a low fire hazard, therefore we ve extended the coverage to detect an 18 pan fire at 150 based on a performance based design. A camera will be installed in the upper left and lower right corners. The yellow boxes represent approximately 20 spot smoke detectors that will be replaced by each camera. With coverage at 150 on center the coverage area is 17,600 sq ft compared to 7,800 sq ft with 100 coverage. The coverage area is basically a quarter circle with a radius based on size of fire the system is designed to detect.

29 For high fire hazards we stay close to the listed 100 coverage per detector and assure that all areas of the hazard are covered. 29

30 This is an example of high rack storage design. Detectors can have two lenses, 82 degree and 34 degree. The 34 degree lenses have a narrower field of view and are used to see down the aisles and 82 degree lens can see over the top of low storage. VID detectors are great for cold storage applications and can be installed in a heated enclosure.

31 Comparative testing was witnessed by Aon Engineering of VID detectors and other detector types covering the same area to determine which detected first. In this test series, seven different fire sources were tested at three different fire locations for a total of 21 different fire scenarios. Each fire scenario was tested three times for repeatability, yielding 63 total tests.

32 The only fire where VID detected after aspiration on its highest sensitivity was where the fire was between racks and the VID detector had to wait for the smoke to break over the top of the racks. If early detection was required, VID detectors would be placed with the camera looking down the aisle rather than over the top of the racks. 32

33 The test determined that the VID system detected smoke first 88% of the time while aspiration only detected first 6% of the time where the ceiling is 18ft or greater. And we can see why, VID is analyzing the area for smoke from floor to ceiling and does not need to physically interact with the products of combustion. 33

34 VID systems need at least 1 foot candle of light to see motion and smoke. This may be covered by the emergency lighting that is required by NFPA 101. Some VID systems use IR lighting to see in low light, however there is potential that the imager may be overwhelmed and go into trouble in the case of a large flaming fire. 34

35 This is a typical system architecture of an IP based VID system. The cameras are powered either over Ethernet (PoE) or 24VDC from the fire alarm system and networked to the NVR. Computers on the same LAN running interface software can view video, and manage the camera settings with an administrator password. If the LAN is connected to the Internet, computers running the interface software that have access to the LAN can also view live video and manage the camera settings, even assist in commissioning remotely. Some VID NVR s can be configured to send an message with alarm information and a picture of the camera image upon alarm. There are compliance considerations when powering cameras by Ethernet and this is usually for supplemental systems only.

36 Server based systems are available with the same analytics using existing CCTV cameras. This usually provides higher resolution and can be added as supplemental detection as a non-listed system. Listed VID cameras can also be connected on the same network and NVR. 36

37 This is a example of a VID interface program browser showing live video and building layout with an icon indicating camera coverage area in red. The browser can double for video surveillance and indicate alarm status and location.

38 Blocking zones can be configured to avoid false alarms as required in the camera s field of view. In the top picture there is steam creating a false alarm and a blocking zone is shown in the middle picture. If smoke originates in the blocking zone and grows and breaks the plane of the zone, the camera will go into alarm immediately as it has been tracking the detection inside of the zone. If the steam is only produced during the day on weekdays, the zone can be on a schedule to turn on the in morning and off at the end of the workday. As indicated on the bottom picture, we can also set up detect zones to target detection on specific hazards, we ve turned off all algorithms except for flame and are detecting only inside the red box to target the specific hazard.

39 In hazards where there is potential for false alarms due to sunlight and movement by people, we can place detect or alarm zones in areas not prone to these distractions. The smoke will be tracked by the camera analytics and go into alarm only when the smoke moves into the blue detect area. These zones can be set on a schedule to be enabled during the day and return to full smoke detection at night. Motion detection and flame can also be enabled during hours the facility is closed.

40 Here is an example of a machine shop where hotwork is performed in designated areas. Smoke detection can be set up in the blue areas, with flame blocking in the red areas and flame is detected everywhere outside of the red boxes. During hours when the shop is closed, flame, smoke and motion can all be turned on automatically with the scheduler.

41 Shown here is a waste process facility where the AHJ requires flame and smoke detection. Smoke detection is a challenge for any smoke detector in this environment. With video image detection, we would be concerned with areas where sunlight shines on dust particles in the air that can cause false alarms. To avoid false smoke alarm, we set up smoke detect zones in areas not prone to direct sunlight during the daylight hours. Flame detection will be enabled 24/7 in the entire field of view and smoke detection may be opened up to the full field of view at nighttime hours.

42 Aircraft hangars typically have underwing flame detection, video image detection can provide the usual flame detection, however add smoke detection as indicated in the blue detect area. Anything that looks like smoke would be tracked anywhere in the field of view, if a smoke signature meets detection parameters and rises into the zone, the system will go into alarm. We set the smoke detect zone during the day due to sunlight issues, however can enable full smoke and motion detection to turn on via a schedule at nighttime.

43 High hazards in stable environments allow us to enable all algorithms at high sensitivity. This enables potential detection of oil or fuel spray caused by leaks that may occur prior to a fire as well as the normal fire signatures. Video image detection is being used in this application and uses available algorithms to detect any movement in the hazard.

44 This is the timeline screen, it allows us to easily locate and view events and is useful when commissioning systems. The top lines are a compressed view of events and the lower lines are an expanded view. Green is motion, red is flame and blue is smoke. The events are expanded on the bottom section, double click on an event and a video of the event is viewed or downloaded in a.wmv file format. The system is recording 24/7 and any time on the timeline can be viewed and video downloaded whether associated with an event or not.

45 When the system has been commissioned, an audit report is generated. The audit report includes a picture of the camera s field of view including zones as well as all specifics of firmware version and settings. The software also generates a sketch of the image. This sketch is from an engine room of an offshore drilling rig. Per NFPA 72, VID systems are inspected semi-annually. Inspection is by performing a Verify routine in the software comparing the commissioning report file with the current camera condition. The imager is checked internally, the sketch and settings are compared and if everything matches up, the system inspection is complete and a report generated. This is all done at the computer terminal and can be performed remotely over the internet. 45

46 This is an illustration of a fire detection sequence of events; the camera detects the fire, IP or analog video can be viewed at a central station where the response is coordinated, an message is sent with a picture of the current camera image, and the fire alarm panel monitors the dry contacts for alarm condition.

47 Typical VID application 47

48 Typical VID application 48

49 Cultural properties are a great application and in some applications VID has been approved as early detection in lieu of sprinkler protection. 49

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