HEALTH & SAFETY
SMOKE ALARM SYSTEM 2.0 U
nderwriters Laboratories (UL), the author of the U.S. and Canada smoke detection standards, has released a revised UL 217 specification 8th edition that will come into effect at the end of June 2022. These new standards are significantly more technically challenging to meet than the current regulations. Yet in many cases, businesses continue to rely on manual, time-consuming, paper-based monitoring processes which are not only inefficient but also have a high likelihood of inaccuracy. With pressures increasing on businesses to improve productivity and streamline their operations, they need a means of performing these critical regulatory processes in a way that not only saves valuable time but also provides peace of mind that these checks are timely and crucially – accurate.
New Smoke Detector Tests
One major change to the standards is the introduction of the hamburger nuisance test. In this test, hamburgers are placed in an oven set at a high enough level to burn, and the detectors must not issue an alarm before a certain amount of smoke has been generated. This requirement to not alarm will bound the maximum sensitivity of a detection system. This test reduces the number of false alarms generated due to cooking events, as residents disconnecting alarms because of high false alarm rates is one of the leading cases of death in fire-related events.
Another addition to the standard is the flaming polyurethane (PU) test, also known as the burning couch cushion test. Due to the optical scattering cross- sections and physics of different smoke types, sensor response from flaming PU is lower than the response from other smokes at a similar obscuration. The ability to detect flaming PU smoke at specified levels will bound the minimum sensitivity of most, if not all, optical detection systems. The sensor response to the flaming polyurethane smoke can be difficult to separate from the hamburger nuisance test. In the past, setting the pass/fail criteria for a detector was straightforward, at least to minimally meet agency requirements. For the upcoming requirements, the manufacturing and calibration margins are much tighter and may require an increase in algorithmic complexity. The flaming polyurethane and hamburger nuisance tests occur on different time scales, and it is straightforward to create a simple algorithm that looks at the slope or rate of change in the smoke to distinguish between the two fires to pass the UL requirements. However, there is a question of how effective this algorithm is in real-world applications.
Figure 1
Particles scatter LED light of a specific wavelength onto a photodiode. As shown in Figure 2, the distance between the LED and the photodiode is usually a few centimetres.
However, both the discrete design of the smoke alarm and the measurement method result in a few disadvantages. The main one is that monochromatic LEDs lead to a higher false alarm rate because they make it harder for different particles to be distinguished from one another. In addition, a discrete implementation is large and associated with a higher power consumption. Laborious calibrations are also necessary. The technology for the optical components has advanced to where the LEDs and the photodiodes, along with the optical front end, can be integrated into a small housing.
Adressing the New Challenge
ADI has created a technology to help address these issues: the ADPD188BI. It directly integrates two LEDs (blue and infrared), a photodiode, and an analogue front end. Digital output over I²C or SPI enables a connection to a microcontroller. A block diagram of the ADPD188BI is shown in Figure 4. As can be seen in the figure, the complete signal chain is realized in a single 5 mm × 3.8 mm chip.
The ADPD188BI works by emitting a short LED pulse of a few microseconds. Figure 3
In fire room tests, the pass criteria are specified in either time passed since the test was initiated or at a defined obscuration level. A typical obscuration sensor is shown in Figure 1, with a light on one end and the photodetector on the other end. For UL tests, the beam is a sodium vapour lamp 4” diameter and 5’ long. Particles in the beam’s path absorb or scatter light out of the beam path, reducing the amount of light that reaches the detector. For different types of smoke, the relationships between an optical scattering system and an obscuration are different. In the case of the hamburger nuisance test and flaming polyurethane test, a 3× difference in obscuration can be nearly impossible to differentiate in an optical scattering system.
Figure 2
A Typical Smoke Detector
A typical smoke detector is made up of a detector, a microcontroller with an algorithm, and additional components such as loudspeakers, LED indicators, and CO sensors. Photoelectric smoke alarms often use a discrete LED (typically near- infrared, 850 nm or 880 nm) and a discrete photodiode with a typical 135° angle between them and a separation of several cm.
26 FEBRUARY 2022 | FACTORY&HANDLINGSOLUTIONS
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58
