Say no to false alarms! Test this ADI smoke detector!

ADPD188BI launched by ADI can perfectly solve this problem. This product is mainly designed for the standard requirements of UL217 Rev8 in the North American market. After system testing, the ADPD188BI solution can fully meet the standard requirements of UL217. This product adopts a dual photoelectric tube design. The chip integrates infrared light and blue light LED. Through the emission of light of different wavelengths, the size of the measured object can be indirectly determined by ratio. In order to achieve the purpose of distinguishing real smoke from interference sources.

《Design requirements and integrated solutions for smoke detectors based on ADPD188BI》

Scan the QR code to watch the training for free

In response to this, Abel Bian, an engineer at Excelpoint, an ADI distributor, conducted a series of tests in the laboratory. The following figure shows some of the test results. The engineer used a European standard test smoke box to test aerosol smoke.

Figures 1, 3 and 5 show the sampling values ​​and PTR (ratio of received light power to transmitted light power) ratio of blue light and infrared light displayed by the ADPD188BI evaluation board. In the figure, SlotA represents the PTR value of blue light, and SlotB represents the PTR value of infrared light. The purpose of this is to minimize the impact of noise interference on the results.

Figures 1 and 2 show the initial values ​​of ADPD188BI when the shielding rate is 0. It can be seen that the average PTR value of blue light and infrared light is about 11.53. The ratio is about 0.970.

Figures 3 and 4 show the initial values ​​of ADPD188BI when the shielding rate is 0.2. It can be seen that the average PTR value of blue light and infrared light is about 11.73. The ratio is about 0.983.

Figures 5 and 6 show the initial values ​​of ADPD188BI when the shielding rate is 0.4. It can be seen that the average PTR value of blue light and infrared light is about 12.13. The ratio is about 1.005.

"We can process the PTR values ​​we see through smoothing filters to make smoke alarm judgments, which is exactly the same as before," said Abel. "Second, we can also use the slope of the PTR ratio and the obscuration ratio in the corresponding standard (such as 12%/foot) to determine whether the measured material is smoke from real combustion."

Later, Abel conducted another experiment, but due to limited experimental conditions, he only used a simple humidifier to simulate the water mist. Through this experiment, we can see that the PTR ratio is a very important parameter at this time, which can help determine the occurrence of real smoke.

PTRA/PTRB shows the trend of the PTR ratio of all sampled outputs, which shows that the PTR ratio will also change slightly under different shading ratios (PRTA represents blue light and PTRB represents infrared light)

The PTR output values ​​of infrared light and blue light indicate the degree of change in smoke concentration. It can be seen that PRTA is more sensitive to changes in smoke concentration than PRTB.

The above is the experimental result of Abel for aerosol testing. It can be seen that in terms of accuracy, very fine collection can be achieved, and the additional PTR ratio information can give software personnel more basis for judgment. Under lower shading ratio, the occurrence of real flames can be judged in advance.

Finally, in order to show the output changes of the product for different smoke sources, he tested the input of high-temperature water vapor and human smoking. The specific results are shown in the following perspective diagram:

High temperature water vapor and smoke PTR results

The bulge in the front half of the above figure is the high-temperature steam output generated by boiling the electric kettle. After removing the condensation result, it can be seen that when encountering high-temperature water vapor, the PTR values ​​of the two lights will instantly rise to more than 35nW/mW.

After a period of air cooling and water vapor cleaning, the output changes caused by smoking can be seen in the second half. Of course, this is closer to the sensor, and the output value is the result of a higher smoke masking rate, which can reach a maximum of about 25nW/mW.

The above figure can well demonstrate the importance of PTR ratio in judging substances. In the first half, it can be seen that the PTR ratio of high-temperature water vapor rises instantly, and the ratio is close to 1.8. In the second half, the PTR ratio rises relatively slowly, and the ratio is around 1.55.

Ratio information cannot be used alone to distinguish real smoke from interference smoke. Software personnel can make relatively stable experimental statistics based on the rising speed and final ratio of the PTR value, and use this as the basis for judging the type of smoke, thereby minimizing the false alarm rate.