False alarm immunity capability of a multispectral sensor using multichannel frequency division

Abstract

An optical flame detection system includes a housing having a window and a single infrared sensor positioned proximate the window and configured to receive infrared illumination through the window. A digitizer is operably coupled to the single infrared sensor and configured to provide a digital representation of an analog sensor signal obtained from the single infrared sensor. A processor is operably coupled to the digitizer and configured to receive a series of time-spaced-apart digital representations from the digitizer and classify the representations into a plurality of groups. The processor is further configured to determine a first intensity value for a first group of the plurality of groups and a second intensity value for a second group of the plurality of groups. The processor is further configured to compute a ratio between the first intensity value and the second intensity value and compare the computed ratio to a threshold value to provide a flame detection decision output having improved anti-misalarm capability. A computer-implemented method of optical flame detection using a single infrared sensor is also provided.

Description

Technical Field

[0001] This invention relates to an optical flame detection system. Background Technology

[0002] The process control and monitoring industry supports a wide range of process industries. Some process industries may use or handle highly flammable or even explosive materials. Examples of such industries include chemical processing facilities and oil extraction and refining. In such environments, fire and explosion are significant hazards. In these highly unstable environments, the use of one or more optical detectors (e.g., optical flame detectors that detect any flame in the process environment such that such flames can be quickly extinguished) is useful, and sometimes necessary.

[0003] Flame detection using a single infrared (IR) channel relies on identifying the unique IR radiation emitted by flames, typically at a wavelength of around 4.3 micrometers. An IR sensor tuned to this specific wavelength monitors increases in IR intensity, which indicate the presence of a flame. The detected IR signal is then processed to confirm a match with characteristic patterns of a flame, such as intensity and flicker frequency. Once a flame is detected, the system triggers an alarm or initiates safety measures to address the potential fire hazard. This method is highly sensitive and provides a fast detection speed, making it crucial for industrial safety and fire alarm applications.

[0004] However, single-IR flame detection is prone to false alarms triggered by non-flame IR sources (e.g., sunlight or high-temperature machinery). Providing single-IR flame detectors with improved resistance to false alarms would allow such detectors to be used in more locations (e.g., around sunlight or high-temperature machinery) and / or allow flame detection based on such single-IR flame detectors to be more reliable. Summary of the Invention

[0005] An optical flame detection system is provided. The optical flame detection system includes: a housing having a window; and a single infrared sensor positioned near the window and configured to receive infrared illumination through the window. A digitizer is operatively coupled to the single infrared sensor and configured to provide a digital representation of an analog sensor signal obtained from the single infrared sensor. A processor is operatively coupled to the digitizer and configured to receive a series of time-spaced digital representations from the digitizer and classify the representations into multiple groups. The processor is also configured to determine a first intensity value for a first group and a second intensity value for a second group. The processor is further configured to calculate a ratio between the first and second intensity values ​​and compare the calculated ratio with a threshold to provide a flame detection decision output with improved immunity to false alarms. A computer-implemented method for optical flame detection using a single infrared sensor is also provided. Attached Figure Description

[0006] Figure 1 This is a system block diagram of a multi-channel optical sensor, and the embodiments described herein are particularly applicable to this multi-channel optical sensor.

[0007] Figure 2 This is a flowchart of a computer implementation method for operating a single IR flame detector according to an embodiment of the present invention.

[0008] Figure 3 This is a graph showing the signal strength versus frequency of the interference source behavior in the frequency domain.

[0009] Figure 4 This is a graph showing the signal strength versus frequency of flame behavior in the frequency domain. Detailed Implementation

[0010] Advanced multi-IR flame detection utilizes multiple IR sensors and determines the ratio between the IR signal channels and a reference channel, as well as the correlation between the frequency responses of all channels. However, single-IR flame detection relies primarily on the signal channel strength. While multi-IR flame detection is useful, it is generally more expensive than single-IR flame detection. Therefore, providing better false alarm protection against single-IR flame detection would be beneficial in this field.

[0011] The embodiments described herein reduce or prevent false alarms in flame detection systems employing single IR sensors. While conventional single-channel detectors are effective at measuring light energy, they typically lack the ability to distinguish between radiation emitted by a genuine fire source and radiation emitted by common false alarm triggers, such as sunlight, fluorescent lights, or other non-flame heat sources. This limitation often leads to high false alarm rates, causing unnecessary disruptions, and potentially jeopardizing safety through the use of user-specific alarm desensitization.

[0012] Figure 1This is a system block diagram of a single IR flame detection system, the embodiments described herein being particularly applicable to such a system. System 10 includes a housing 12 having a lens 14 through which a flame 16 is visible. The flame 16 emits a broad spectrum of infrared radiation. System 10 includes a single IR sensor 17 sensitive to the emission wavelength of the flame 16 (typically around 4.3 micrometers). Sensor 17 can be any suitable device sensitive to the wavelength of the flame. However, in some examples, sensor 17 is a pyroelectric sensor capable of detecting rapid fluctuations in the IR emitted by a flickering flame. When a flame is present, the changing IR radiation heats the pyroelectric material of the pyroelectric sensor, generating a voltage signal. Sensor 17 is operatively coupled to a digitizer 18 including circuitry that converts the analog signal from sensor 17 into its digital representation. Digitizer 18 is coupled to processor 20 and configured to provide processor 20 with a digital representation associated with the IR sensor 17.

[0013] Processor 20 is any suitable device capable of executing program steps or functions to provide various characteristics of sensor 10. Examples of such devices include digital signal processors, microcontrollers, field-programmable gate arrays, and application-specific integrated circuits. In some examples, processor 20 is a microprocessor. Digitizer 18 provides processor 20 with a digital representation of the IR sensor signal for signal processing. Processor 20 processes the digitized signal from IR sensor 17 and analyzes the signal strength and flicker frequency to detect the presence of flame 16.

[0014] When the processor 20 confirms the presence of a flame, it generates an output 22 (e.g., triggering an alarm and / or other appropriate action). The sensor 10 can also activate automatic safety measures (e.g., shutting off devices, activating safety measures, and / or activating a fire suppression system).

[0015] The embodiments described herein typically utilize a single-spectrum sensor (e.g., sensor 17) and employ digital processing techniques to generate multi-band channel frequency divisions. This novel signal processing technique for single-IR flame detection systems significantly reduces false alarms. In one example, a Fast Fourier Transform (FFT) is used to convert the digitized signal sampled from IR sensor 17 into the frequency domain.

[0016] In the frequency domain, the processor is configured to detect typical frequencies of flame emission between approximately 1 and 5 Hz (see [link to relevant documentation]). Figure 4 The processor 20 is also configured to analyze the strength of the signal from the sensor 17 at a high frequency of approximately 5-15 Hz (see [link]). Figure 3 While it is expected that real flames will have a very low response at those frequencies, false alarm sources such as high-temperature machinery will cause a uniform response across the entire frequency range.

[0017] In contrast to most false alarm sources that emit a wide frequency range, the embodiments described herein apply the characteristic emission spectrum of a real fire by transforming the detected optical signal into the frequency domain and analyzing the ratios between different frequencies. This allows for the accurate identification of the true characteristics of a fire and significantly reduces the likelihood of false alarms.

[0018] Figure 2 This is a flowchart of a computer implementation method for operating a single IR flame detector according to an embodiment of the present invention. Method 100 begins at block 102, where the processor initiates the method. This may include clearing previous samples from memory and / or resetting buffers or registers. Next, at block 104, the processor 20 performs signal sampling from the single IR sensor. In some examples, the single IR sensor may be a pyroelectric sensor. During block 104, the processor 20 receives multiple digital representations of an analog signal from sensor 17, these multiple digital representations being time-spaced by a sampling frequency. For example, known pyroelectric sensors still have sufficient signal-to-noise ratios at modulation frequencies up to 4 kHz. During the sampling period, the processor 20 stores multiple digital representations associated with the single IR sensor. For example, in an embodiment with a sampling frequency of 4 kHz and a sampling time of one second, the processor 20 would store 4000 digital representations of the single IR sensor signal.

[0019] After signal sampling at block 104, processor 20 proceeds to block 106, where the stored samples are filtered. Preferably, if processor 20 is configured to provide background processing, this filtering process occurs as a background process of processor 20. In one example, filtering may remove any DC component and / or 60Hz. However, those skilled in the art will recognize that, given a signal of interest typically between 1 and 15Hz, any suitable filtering can be performed at block 106. At block 106, processor 20 also performs a Fast Fourier Transform (FFT) on the stored data. FFT is an example of a transform used to evaluate data samples in the frequency domain. However, any suitable transform can be used. The Fast Fourier Transform is the process of computing the Discrete Fourier Transform (DFT) of a sequence or its inverse transform (IDFT). Fourier analysis transforms a signal from its original domain (typically time or space) to a representation in the frequency domain and vice versa. As a result of performing an FFT on the stored data, the data is divided into data with frequencies between 1 and 5 Hz (defined as low-frequency data in this paper) and data with frequencies between 5 and 15 Hz (defined as high-frequency data in this paper).

[0020] Next, at block 108, processor 20 integrates or otherwise adds the high-frequency data to generate a high-frequency intensity value. Similarly, at block 110, processor 20 integrates or otherwise adds the low-frequency data to generate a low-frequency intensity value. Although block 108 occurs before block 110 in the description of method 100, it is clearly conceivable that block 110 may actually occur before or simultaneously with block 108.

[0021] At box 112, processor 20 calculates the ratio between the high-frequency intensity value and the low-frequency intensity value. Processor 20 then compares the calculated ratio to a threshold, as shown in box 114. Based on the comparison between the calculated ratio and the threshold, processor 20 provides a decision regarding whether the signal indicates a flame, as shown in box 116. The threshold may be a predefined threshold input into processor 20 during manufacturing. In another example, the threshold may be based on the type of flame predicted for the flame detection system. The flame type can be selected by allowing the user to configure one or more jumpers or DIP switches in the circuitry coupled to processor 20. In another example, the threshold may be user-adjustable. For example, processor 20 may be configured to adjust the threshold in response to a flame detection output if a false alarm input is received from the user.

[0022] The decision can be output locally as a fire alarm, sent to one or more remote devices, or both. In the event that processor 20 determines the signal is a false alarm, processor 20 can simply provide a no-flame decision output. However, it is clearly envisioned that the no-flame decision output can be supplemented with a false alarm indication, thereby allowing personnel to investigate one or more sources that led to the false alarm detection. As shown in line 118, method 100 typically iterates by returning to block 104 to sample additional data from the single IR sensor 17.

[0023] Figure 3 This is a graph showing the signal strength versus frequency of the interference source behavior in the frequency domain. It can be seen that, for interference, the area under the curve from 1 to 5 Hz is significantly smaller than the area under the curve from 5 to 15 Hz. For example, the high signal strength / low signal strength ratio is significantly greater than 1.0.

[0024] Figure 4This is a graph showing the signal strength versus frequency of flame behavior in the frequency domain. It can be seen that the area under the curve for 1 to 5 Hz is similar to the area under the curve for 5 to 15 Hz. Therefore, the ratio of high to low frequencies is much closer to 1.0 than the same ratio for interference (above 1). Thus, in one example, flame detection can be performed by comparing this ratio to a threshold (e.g., 1.2) and providing a flame output if the ratio is less than 1.2. Additional aspects such as detecting the overall signal strength and flame flicker (e.g., the frequency and / or amplitude of intensity changes) can also be combined with the improved detection presented herein.

[0025] Compared to existing methods or devices that rely on single-frequency or multi-sensor approaches, the embodiments described herein offer numerous advantages in terms of effectiveness and efficiency. The use of a single sensor reduces system complexity, maintenance requirements, and costs, while innovative frequency segmentation and the calculation of ratios between intensities at different frequencies enhance the detector's specificity for fire-related radiation. Therefore, the embodiments described herein are considered to achieve superior immunity to false alarms, ensuring a higher level of safety and operational integrity. This is accomplished by accurately distinguishing fire from other infrared sources using the unique spectral characteristics of fire, without the need for multiple sensors or complex processing.

[0026] While the invention has been described with reference to preferred embodiments, those skilled in the art will recognize that modifications in form and detail may be made without departing from the spirit and scope of the invention. Although embodiments of the invention have been described with respect to optical flame sensors, it is clearly envisioned that other industries and applications will benefit from the embodiments disclosed herein. For example, in crop monitoring, embodiments can be employed to detect stress based on the infrared emission characteristics of plants. Different stress conditions, such as drought or disease, may alter the typical infrared spectrum of plants, thus allowing for early intervention. In another example, embodiments can be employed for pollution detection and monitoring by detecting and quantifying contaminants in air or water. Identifying the unique spectral characteristics of various contaminants allows for targeted measures to reduce pollution levels. In yet another example, embodiments can be employed for industrial process control to monitor and control industrial processes (e.g., chemical reactions or the quality of materials produced).

Claims

1. A computer-implemented method for optical flame detection using a single infrared sensor, the computer-implemented method comprising: Multiple samples are obtained from a single infrared sensor, the samples being spaced apart in time; The samples are classified into high-frequency samples and low-frequency samples; The high-frequency samples are summed together to provide a high-frequency intensity value; The low-frequency samples are summed together to provide a low-frequency intensity value; Calculate the ratio between the high-frequency intensity value and the low-frequency intensity value; Compare the ratio to a threshold; as well as Flame detection is selectively provided based on comparing the ratio with the threshold.

2. The computer-implemented method according to claim 1, wherein, The flame detection has improved resistance to false alarms.

3. The computer-implemented method according to claim 1, wherein, Flame detection is also provided based on the flash frequency calculated from the plurality of samples from the single infrared sensor.

4. The computer-implemented method according to claim 1, wherein, Classifying the samples into high-frequency and low-frequency samples includes applying a fast Fourier transform to the samples obtained from the single infrared sensor.

5. The computer-implemented method according to claim 4, wherein, Low-frequency samples have frequencies in the range of 1 Hz to 5 Hz.

6. The computer-implemented method according to claim 4, wherein, High-frequency samples have frequencies in the range of 5 Hz to 15 Hz.

7. The computer-implemented method according to claim 1, further comprising: The samples are filtered before being classified into low-frequency and high-frequency samples.

8. The computer-implemented method according to claim 7, wherein, The filtering of the samples occurs as a background process.

9. The computer-implemented method according to claim 1, wherein, The threshold is based on the expected flame type.

10. The computer-implemented method according to claim 1, wherein, The threshold is adjustable by the user.

11. An optical flame detection system, comprising: The casing has a window; A single infrared sensor is positioned near the window and configured to receive infrared illumination through the window; A digitizer is operatively coupled to the single infrared sensor and configured to provide a digital representation of the analog sensor signal obtained from the single infrared sensor; as well as A processor, operatively coupled to the digitizer, is configured to receive a series of time-spaced digital representations from the digitizer and classify the representations into multiple groups. The processor is also configured to determine a first intensity value for a first group and a second intensity value for a second group. The processor is further configured to calculate a ratio between the first intensity value and the second intensity value and compare the calculated ratio with a threshold to provide a flame detection decision output with improved resistance to false alarms.

12. The optical flame detection system according to claim 11, wherein, The first group is the low-frequency group.

13. The optical flame detection system according to claim 12, wherein, The low-frequency group is selected from frequencies in the range of 1 Hz to 5 Hz.

14. The optical flame detection system according to claim 11, wherein, The second group is the high-frequency group.

15. The optical flame detection system according to claim 14, wherein, The high-frequency group is selected from frequencies in the range of 5 Hz to 15 Hz.

16. The optical flame detection system according to claim 11, wherein, The processor is configured to perform a transformation operation on the series of time-spaced digital representations to transform the series of time-spaced digital representations to the frequency domain.

17. The optical flame detection system according to claim 16, wherein, The transformation is a Fast Fourier Transform.

18. The optical flame detection system according to claim 11, wherein, The single infrared sensor is a pyroelectric sensor.

19. The optical flame detection system according to claim 11, wherein, The single infrared sensor is sensitive to illumination with a wavelength of approximately 4.3 micrometers.

Images