“Today’s buildings are equipped with many different sensors to make daily life more convenient and at the same time provide safety protection. In addition to environmental sensors and smart home applications (such as electricity and heating regulation), safety-related sensors also play an important role in safety protection. This includes smoke alarms. Smoke alarms are indispensable and must be equipped by law. However, many smoke alarms on the market are not suitable for use in the kitchen or bathroom, because cooking smoke or other steam will increase the risk of false alarms.We cannot underestimate false alarms, they will entice users to turn off the smoke alarms, and because of unnecessary firefighting deployments

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Author: Christoph Kämmerer, Field Application Engineer, Analog Devices

Modern smoke alarms-improve detection performance and increase safety

Today’s buildings are equipped with many different sensors to make daily life more convenient and at the same time provide safety protection. In addition to environmental sensors and smart home applications (such as electricity and heating regulation), safety-related sensors also play an important role in safety protection. This includes smoke alarms. Smoke alarms are indispensable and must be equipped by law. However, many smoke alarms on the market are not suitable for use in the kitchen or bathroom, because cooking smoke or other steam will increase the risk of false alarms. We cannot underestimate false alarms, they will entice users to turn off smoke alarms and incur high costs due to unnecessary firefighting deployments.

However, the lack of smoke alarms in bathrooms and kitchens is a serious problem because it increases the risk of fire, especially in kitchens. The kitchen in a modern apartment is usually integrated with the living room and therefore faces greater risks. Modern buildings use a large number of synthetic building materials, and once a fire breaks out, it will spread quickly. Therefore, in order to accurately implement fire detection, it is necessary to accurately deploy a smoke alarm network.

Many standards around the world require new tests to detect different types of smoke to meet these new requirements. Different regions have slightly different standards: Europe adopts EN standards, North America adopts UL standards, and international standards adopt ISO standards. In the latest version released in June 2021 (UL 268: 7th edition and UL 217: 8th edition), UL has added a new test, the hamburger smoke interference alarm test. In this test, it is necessary to be able to distinguish the concentration of smoke produced by hamburger patties from the concentration of smoke produced by flammable polyurethane. This test helps reduce the false alarm rate in the kitchen. This article will introduce this test and discuss how to design a new detector to pass this new test.

Focus on UL’s Hamburger Smoke Interference Alarm Test

This hamburger smoke interference test is designed to replicate real cooking smoke. The concept of hamburger smoke interference alarm testing is simple, but even modern smoke alarms face a challenge: hamburger patties need to be grilled for a certain amount of time. During this process, it will be checked whether the smoke alarm is triggered by rising smoke (starting to rise within a certain time limit). This is also a standardized test, so all smoke alarms can be tested under exactly the same conditions. Take the measured value of the dimming rate as a reference. In this test, a light source is placed at a distance of approximately 2 meters, with a beam diameter between 10 and 15 cm. Use a steam lamp with a wavelength of 589 nm as the light source. The smoke between the steam lamp and the detector will block the light. Figure 1 shows the principle and schematic diagram of the reference measurement setup.

Figure 1. Schematic diagram of the reference system based on the UL standard.

The degree to which the beam is obscured by smoke is compared with the reference signal in a smoke-free environment. According to the dimming rate, the smoke density and smoke concentration can be obtained. For the same particle, the higher the dimming rate, the higher the concentration. Of course, the dimming rate varies not only with concentration, but also with particle type. According to the scattering cross section, different particle types have obvious differences.

The dimming time is also closely related to the alarm trigger. Therefore, according to this standard, an alarm will be triggered after reaching a certain time limit in the reference system or reaching the masking limit. Therefore, the hamburger interference alarm test stipulates that during the frying and grilling of hamburger patties, no alarm shall be issued before the light reduction rate reaches more than 1.5%/ft.

In the second phase of the test, polyurethane is ignited to simulate real objects such as armchairs. The smoke alarm must distinguish the difference between the two and trigger an alarm when the dimming rate reaches 5%/ft.

Since real fire smoke and cooking smoke are difficult to distinguish, this test is very challenging. However, this test is just one of many tests defined in UL 217 and UL 268. It is also necessary to use multiple identical smoke alarms to pass this test to eliminate random results and ensure that the detector has a wide range of high-quality densities.

How the smoke alarm passed this test

Most modern smoke alarms use the photoelectric working principle. In the hamburger smoke interference test, the light beam is reflected by the particles after it is emitted. The scattering depends on the particle type, particle concentration and scattering angle. The smoke alarm decides whether to trigger the alarm according to the scattered signal.

In order to pass the hamburger smoke interference alarm test, the detector must have a high signal-to-noise ratio to distinguish hamburger smoke from other types of smoke.

Analog Devices’ ADPD188BI integrated optical sensor module equips smoke alarm manufacturers with the technology that can pass this difficult test. Figure 2 demonstrates the working principle of the ADPD188BI.

ADI’s ADPD188BI integrated optical sensor module helps smoke alarm manufacturers’ products pass this rigorous test. Figure 2 shows the working principle of ADPD188BI.

Figure 2. Working principle of ADPD188BI.

This new type of smoke detection integrated module housing contains two emitter LEDs-a blue LED with a wavelength of 470 nm and an infrared LED with a wavelength of 850 nm. Both emitters are located in the chamber on the left. On the right side of the housing is a photodiode and analog front end. The LED emits a light beam, and the smoke particles reflect the light beam back to the photodiode. In addition, an LED driver is integrated, which is switched by an internal time slot. Through these time slots, users can adjust the timing of the entire front end without having to constantly rewrite registers.

The analog front end includes a current-voltage converter and an ambient light analog filter. The latter consists of a band-pass filter that detects constant ambient light and an integrator that detects variable ambient light (such as light from fluorescent lamps). After that, the integrated analog-to-digital converter converts the voltage into a digital signal.

The ADPD188BI smoke sensor module has a high integration density and has many advantages. Since only a few external components are required, the entire system is easier to calibrate. Through dual-color light wavelength detection, it not only supports individual measurement of a single wavelength, but also supports the composition of the analysis ratio, thereby further reducing the false alarm rate. In addition, this module has a smaller volume and lower power consumption than traditional detectors. The working power consumption of infrared LED is ~5 μW/Hz. By fully integrating LEDs and photodiodes into the analog front end, smoke alarm manufacturers can provide a total module solution.

The high integration of the ADPD188BI module is related to the “success and failure” of the hamburger smoke interference test. At a fixed current, the luminous intensity of different LEDs is usually very different, so in the past, the smoke alarm manufacturer was used to perform the calibration of the smoke alarm. Calibrating the slope and offset between LED luminous intensity and current can ensure that all LEDs maintain the same performance. Because the LEDs and the entire signal path are integrated into the ADPD188BI, ADI will pre-calibrate the sensor module so that the differences between devices can be reduced. Because smoke alarm manufacturers can use pre-calibrated modules, the system design is simplified.

The calibration method used by ADI is to directly calibrate the slope and offset of the LED. Therefore, the ADPD188BI is placed under the reflector, and then the reflected light is measured by the integrated photodiode. The slope and offset can be determined separately for each ADPD188BI, and the calibration coefficients are stored in the chip’s non-volatile memory (ie, eFUSE register). By reading these coefficients, the differences between chips can be reduced as much as possible. This means that the alarm threshold can be set more accurately in the algorithm, thereby reducing the false alarm rate, and ultimately passing the UL test.

Figure 3 shows the test results of ADPD188BI in a standardized UL test environment-one time for Hamburg smoke (left) and one time for flammable polyurethane smoke (right).

Figure 3. ADPPD188BI Ul test results: Hamburg smoke and flammable polyurethane smoke detection in a smoke-free room.

The figure shows the test results over time (X axis) under two conditions, and the left Y axis represents the ADPD188BI signal. Expressed in power transfer ratio, it describes the relationship between the operating power of the LED and the received power of the photodiode. The power transfer ratio formula is as follows:

This parameter allows different modules to be compared with each other. The Y-axis on the right represents the dimming rate (unit: %/ft). The green curve is the UL reference beam, and the blue and purple curves are the blue and infrared signals emitted by ADPD188BI.

As shown in Figure 3, the two signal curves emitted by ADPD188BI are very different in the two scenarios, indicating that the sensor can clearly distinguish the two types of smoke. One of the differences is the change of the signal over time. It can be seen that the polyurethane reaches the alarm threshold after 220 seconds, and the length of time is 1/4 of the Hamburg smoke reaching the alarm threshold (after 1000 seconds). After 4 minutes of burning the polyurethane, a critical level can be detected.

As shown in the figure, the high signal-to-noise ratio of the sensor can also be used to clearly distinguish and record changes in particle concentration. For example, in the flammable polyurethane test, the slope suddenly increases. The red mark in Figure 3.

In addition, ADPD188BI measures two wavelengths. The ratio of the two is another parameter, which can be used to calibrate the reliable algorithm used to detect hamburger smoke to determine whether it has passed the hamburger smoke test.

in conclusion

Why the new integrated optical smoke detection module is an important turning point

The newly launched hamburger smoke interference test is difficult to pass, because the smoke particles produced when grilling hamburger patties are not much different from normal smoke particles. Therefore, the smoke sensor needs to have a high signal-to-noise ratio to distinguish the smoke produced by the hamburger from other types of smoke. In this process, the low difference between the sensors plays a decisive role. Only by reliably completing the measurement and passing the test can the false alarms of the smoke sensor in the final application be reduced. ADI’s new integrated optical smoke detection module ADPD188BI is a highly sensitive integrated sensor module that not only has a high signal-to-noise ratio, supports two-color detection, but also fully reduces the differences between devices, thereby simplifying design and algorithm development.

About the Author

Christoph Kämmerer has been working for ADI in Germany since February 2015. He graduated from Erlangen-Nuremberg University in 2014 with a master’s degree in physics. Then worked as a process development intern at ADI in Limerick. After the end of the trainee project in December 2016, Christoph officially became a field application engineer of ADI, focusing on emerging applications. Contact information:[email protected]