Flame detector deterioration determination device, program, and flame detection system

The deterioration level determination device addresses inaccurate flame detection by estimating component deterioration in flame detectors, ensuring timely replacements for accurate operation.

JP7783385B2Active Publication Date: 2025-12-09NOHMI BOSAI LTD
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Patent Information

Application Number
JP2024194190
Authority / Receiving Office
JP · JP
Patent Type
Patents
Current Assignee / Owner
Filing Date
2024-11-06
Publication Date
2025-12-09
Estimated Expiration
2040-03-30

AI Technical Summary

Technical Problem

Flame detectors experience component deterioration, leading to inaccurate flame detection due to irregular signal fluctuations, which can be addressed by determining the degree of deterioration to maintain accuracy.

Method used

A deterioration level determination device that includes an acquisition unit for night vision noise data, a memory unit for storing data, and a deterioration level determination unit that calculates average values and variation indices to estimate which parts need replacement, using machine learning with past maintenance data.

Benefits of technology

Enables accurate assessment of flame detector deterioration, allowing timely replacement of components to maintain detection accuracy.

✦ Generated by Eureka AI based on patent content.

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Patent Text Reader

Abstract

To enable a user to know a type of components to be replaced among the components of a flame detector.SOLUTION: A deterioration level determination device 123 provided by a disaster prevention receiver panel 12 acquires night vision noise data from a flame detector 11 by means of an acquisition unit 1232 and stores the data in a memory unit 1231. The night vision noise data is data indicating the light intensity measured by the flame detector 11 during the period when the light is blocked. The deterioration level determination device 123 calculates an average value and the standard deviation of the light intensity indicated by the night vision noise data stored in the memory unit 1231, estimates an amplifier of the flame detector 11 as a component to be replaced when the average value is greater than a predetermined threshold value, and estimates a sensor of the flame detector 11 as a component to be replaced when the standard deviation is greater than a predetermined threshold value.SELECTED DRAWING: Figure 10
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Description

[Technical Field]

[0001] The present invention relates to techniques for maintaining flame detectors. [Background technology]

[0002] Disaster prevention systems may stop working properly due to deterioration. Various technologies have been proposed to prevent such problems. For example, Patent Document 1 proposes a disaster prevention system that monitors the value of the current flowing in a signal line connecting a terminal device that outputs a fire signal to a disaster prevention receiving panel when a fire is detected and the disaster prevention receiving panel, and determines that a large change in the current value is a sign of a failure due to insulation deterioration of the signal line, etc., and outputs a warning. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-67032 Summary of the Invention [Problem to be solved by the invention]

[0004] Some flame detectors detect flames using a sensor that is sensitive to the light emitted by the flame. One of the causes of malfunctions in such flame detectors is the deterioration of the components that make up the flame detector. For example, if the light-sensitive sensor included in the flame detector deteriorates, the amplitude of the signal output from the sensor may exhibit irregular fluctuations regardless of the presence or absence of light. Also, if the amplifier that amplifies the signal generated by the sensor deteriorates, the amplitude of the signal amplified by the amplifier from the sensor may exhibit a steadily high value regardless of the presence or absence of light.

[0005] As the components deteriorate, the accuracy of the flame detection determination made by the flame detector decreases. Therefore, if the degree of deterioration of the flame detector can be known, the accuracy of the flame detection determination required of the flame detector can be maintained by replacing the components, etc.

[0006] In view of the above circumstances, an object of the present invention is to make it possible to know the degree of deterioration of a flame detector. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems, in one aspect, the present invention provides a deterioration level determination device that includes an acquisition unit that acquires night vision noise data indicating the intensity of light measured by a flame detector that detects flames based on the intensity of light measured by a sensor during a period when light from the outside world toward the sensor is blocked; a memory unit that stores the night vision noise data acquired by the acquisition unit; and a deterioration level determination unit that calculates an average value of the light intensity indicated by the night vision noise data stored in the memory unit and an index indicating the variation in the light intensity indicated by the night vision noise data stored in the memory unit, and if the average value satisfies a predetermined condition, estimates a first type of part among the parts equipped in the flame detector as a part that needs to be replaced, and if the index indicating the variation satisfies a predetermined condition, estimates a second type of part among the parts equipped in the flame detector that is different from the first type of part as a part that needs to be replaced.

[0008] In addition, as one aspect, the present invention provides a deterioration level determination device that includes an acquisition unit that acquires night vision noise data indicating the intensity of light measured by a flame detector that detects flames based on the intensity of light measured by a sensor during a period when light traveling from the outside world toward the sensor is blocked, and a deterioration level determination unit that inputs the night vision noise data acquired by the acquisition unit into a learning model generated by machine learning using training data that uses the type of part replaced in past maintenance work for a flame detector of the same type as the flame detector and the degree of deterioration of the part as the objective variable and the night vision noise data before the part was replaced as the explanatory variable, and outputs from the learning model the type of part that needs to be replaced among the parts of the flame detector and the degree of deterioration of the part.

[0009] In addition, the present invention provides, as one aspect, a program for realizing the above-described deterioration level determination device by a computer.

[0010] In one aspect, the present invention provides a flame detection system comprising a flame detector and the above-described deterioration level determination device, wherein the flame detector comprises: a sensor that measures light intensity; a flame detection unit that detects a flame based on the light intensity measured by the sensor; a shielding member detection unit that detects that a shielding member that blocks light directed toward the sensor from the outside has been attached to the device; a shielding period determination unit that determines a period during which light directed toward the sensor from the outside is blocked based on the detection result by the shielding member detection unit; and an output unit that outputs night vision noise data indicating the light intensity measured by the sensor during the period determined by the shielding period determination unit, wherein the shielding member detection unit comprises any of a contact sensor that detects contact with the shielding member, a magnetic sensor that detects magnetic force emitted by the shielding member, and a proximity sensor that detects electromagnetic waves emitted by the shielding member in accordance with a short-range wireless communication standard, and the acquisition unit of the deterioration level determination device acquires the night vision noise data output by the output unit of the flame detector. [Effects of the Invention]

[0011] According to the present invention, the degree of deterioration of a flame detector can be known. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a diagram showing the overall configuration of a flame detection system according to an embodiment; [Figure 2] FIG. 1 is a diagram schematically illustrating a hardware configuration of a flame detector according to an embodiment. [Figure 3] FIG. 1 is a diagram illustrating an example of the appearance of a flame detector according to an embodiment. [Figure 4] 1 is a diagram illustrating an example of the appearance of a shielding device according to an embodiment; [Figure 5] FIG. 2 is a diagram schematically illustrating the functional configuration of a flame detector according to an embodiment. [Figure 6] FIG. 10 is a diagram illustrating the configuration of a measurement value log table according to an embodiment. [Figure 7] FIG. 4 is a diagram illustrating the configuration of a temperature correction constant table according to an embodiment. [Figure 8]10 is a graph illustrating a method for identifying an occlusion period by an occlusion period identifying unit according to an embodiment; [Figure 9] FIG. 2 is a diagram illustrating a hardware configuration of a disaster prevention receiving panel according to an embodiment. [Figure 10] FIG. 2 is a diagram illustrating a functional configuration of a disaster prevention receiving panel according to an embodiment. [Figure 11] FIG. 4 is a diagram illustrating the configuration of a night vision noise table according to an embodiment. [Figure 12] 6 is a graph illustrating a method in which a deterioration level determining device according to an embodiment determines a deterioration level and estimates deteriorated parts. [Figure 13] 6 is a graph illustrating a method in which a deterioration level determining device according to an embodiment determines a deterioration level and estimates deteriorated parts. [Figure 14] FIG. 10 is a diagram illustrating the configuration of a degradation diagnosis result table according to an embodiment. [Figure 15] FIG. 10 is a diagram illustrating an example of a degradation diagnosis screen displayed by a terminal device according to an embodiment. [Figure 16] FIG. 10 is a diagram schematically illustrating a hardware configuration of a flame detector according to a modified example. [Figure 17] FIG. 10 is a diagram schematically illustrating the functional configuration of a flame detector according to a modified example.

[0013] [Embodiment] A flame detection system 1 according to one embodiment of the present invention will now be described. Figure 1 is a diagram showing the overall configuration of the flame detection system 1. The flame detection system 1 is a system that detects a flame occurring in a tunnel TN.

[0014] The flame detection system 1 includes n flame detectors, i.e., flame detectors 11(1), 11(2), 11(3), ..., 11(n), installed at approximately equal intervals along the direction of vehicle travel inside the tunnel TN. Hereinafter, these n flame detectors will be collectively referred to as flame detectors 11.

[0015] Each flame detector 11 essentially integrates two flame detectors. Specifically, each flame detector 11 integrates a flame detector whose monitoring area is a predetermined area on the right side of the flame detector 11 (hereinafter referred to as the "right flame detector"), and a flame detector whose monitoring area is a predetermined area on the left side of the flame detector 11 (hereinafter referred to as the "left flame detector").

[0016] The tunnel TN is divided into monitoring areas A(1), A(2), A(3), ..., A(n-1). Hereinafter, these (n-1) monitoring areas will be collectively referred to as monitoring area A. Each of the monitoring areas A is monitored by two adjacent flame detectors 11 in an overlapping manner. For example, monitoring area A(1) is monitored by the left flame detector of flame detector 11(1) and the right flame detector of flame detector 11(2). Therefore, even if one of the two adjacent flame detectors 11 fails, monitoring of monitoring area A will not be interrupted unless the other fails at the same time.

[0017] In addition to the flame detectors 11, the flame detection system 1 includes a disaster prevention receiving panel 12 that is communicatively connected to each of the flame detectors 11, a server device 13 that is communicatively connected to the disaster prevention receiving panel 12, and a terminal device 14 that can communicate with the server device 13.

[0018] 2 is a diagram showing a schematic diagram of the hardware configuration of the flame detector 11. The flame detector 11 includes a computer 101, four sensors connected to the computer 101, namely, sensor 111R, sensor 112R, sensor 111L, and sensor 112L, four amplifiers corresponding to the four sensors, namely, amplifier 113R, amplifier 114R, amplifier 113L, and amplifier 114L, and a thermometer 115 connected to the computer 101.

[0019] The sensors 111R and 112R are optical sensors for monitoring the monitoring area A on the right side as viewed from the flame detector 11. The sensors 111L and 112L are optical sensors for monitoring the monitoring area A on the left side as viewed from the flame detector 11.

[0020] The sensors 111R and 111L are long wavelength optical sensors that respond with high sensitivity to the long wavelength band emitted by a flame (heat source). For example, optical sensors using pyroelectric elements are used as the sensors 111R and 111L. Hereinafter, the sensors 111R and 111L are collectively referred to as sensors 111.

[0021] The sensors 112R and 112L are short wavelength optical sensors that respond with high sensitivity to the short wavelength band emitted by the flame (heat source). For example, optical sensors using photodiodes are used as the sensors 112R and 112L. Hereinafter, the sensors 112R and 112L are collectively referred to as sensors 112.

[0022] Amplifier 113R is connected between computer 101 and sensor 111R and amplifies a signal generated by sensor 111R in response to light. Amplifier 114R is connected between computer 101 and sensor 112R and amplifies a signal generated by sensor 112R in response to light. Amplifier 113L is connected between computer 101 and sensor 111L and amplifies a signal generated by sensor 111L in response to light. Amplifier 114L is connected between computer 101 and sensor 112L and amplifies a signal generated by sensor 112R in response to light.

[0023] In the following description, unless otherwise specified, the signal output from the sensor 111 or the sensor 112 refers to the signal output from the sensor 111 or the sensor 112 and amplified by the amplifier 113 or the amplifier 114.

[0024] The thermometer 115 measures the temperature inside the housing of the flame detector 11 and outputs temperature data indicating the measured temperature to the computer 101 .

[0025] The computer 101 includes a processor 1011 that processes data according to a program, a memory 1012 that stores various data including programs, an input / output interface 1013 that receives signal input from four sensors via four amplifiers and temperature data input from a thermometer 115, and a communication interface 1014 that communicates data with the disaster prevention receiving panel 12.

[0026] In addition to the components shown in Figure 2, the flame detector 11 also has components such as an A / D converter that converts the analog signals output by the four sensors into digital signals. However, since these components are unrelated to the features of the present invention, they are omitted from Figure 2 and will not be described in the following explanation.

[0027] 3 is a diagram illustrating an example of the appearance of flame detector 11. Flame detector 11 has a light-transmitting window W, and light enters the housing of flame detector 11 from the outside through window W. Sensors 111 and 112 respond to the light that enters from the outside through window W. Note that the housing of flame detector 11 (portions other than window W) does not transmit light.

[0028] A maintenance worker who performs maintenance on the flame detection system 1, for example, periodically visits the tunnel TN and continuously covers the window W of each flame detector 11 with a shielding device S for approximately a predetermined time (e.g., 30 seconds). This work is performed to measure noise (hereinafter referred to as "night vision noise"), which is a component not derived from light, contained in the signal output from the sensor 111 or the sensor 112 of the flame detector 11.

[0029] FIG. 4 is a diagram illustrating the appearance of the shielding device S. FIG. 4(a) is a diagram of the shielding device S as seen from the front, FIG. 4(b) is a diagram of the shielding device S as seen from the back, and FIG. 4(c) is a diagram of the shielding device S as seen from above. The shielding device S comprises a shielding plate P that does not transmit light, a handle H attached to the front side of the shielding plate P, and an oval ring-shaped elastic member C (which, together with the shielding plate P, constitutes an example of a shielding member) attached to the back side of the shielding plate P. A maintenance worker grasps the handle H and presses the shielding device S against the flame detector 11 at a position where the elastic member C roughly coincides with the outer periphery of the window W of the flame detector 11, thereby covering the window W.

[0030] Fig. 5 is a diagram showing a schematic functional configuration of the flame detector 11. That is, the processor 1011 of the computer 101 executes processing according to the program according to this embodiment, thereby realizing the flame detector 11 equipped with a determination device indicated by reference numeral 116 in Fig. 5. The functional configuration of the determination device 116 will be described below.

[0031] Determination device 116 includes determination device 116R that determines whether flame is detected using signals output from sensors 111R and 112R, and determination device 116L that determines whether flame is detected using signals output from sensors 111L and 112L. Since determination device 116R and determination device 116L have a common configuration, the configuration of determination device 116R will be described below as an example, and a description of the configuration of determination device 116L will be omitted.

[0032] The determination device 116R includes a storage unit 1161R, an acquisition unit 1162R, a correction unit 1163R, a shielding period specification unit 1164R, a flame detection unit 1165R, a transmission / reception unit 1166R, and a timing unit 1167R.

[0033] The storage unit 1161R is realized by the memory 1012 that operates under the control of the processor 1011. The storage unit 1161R stores various data. The data stored in the storage unit 1161R includes a measurement value log table, a temperature correction constant table, and steady-state correction constant data.

[0034] FIG. 6 is a diagram illustrating the configuration of a measurement value log table. A measurement value log table is prepared for each of the sensors 111R and 112R. The measurement value log table has a "Time" column, a "Temperature" column, a "Intensity (Actual Measurement)" column, a "Intensity (After Temperature Correction)" column, and a "Intensity (After Steady-State Correction)" column. The "Time" column stores the time measured by the timer unit 1167R when a signal is output from the sensor. The "Temperature" column stores the temperature measured by the thermometer 115 when a signal is output from the sensor. The "Intensity (Actual Measurement)" column stores the amplitude value of the signal output from the sensor. The "Intensity (After Temperature Correction)" column stores a value obtained by correcting the amplitude value stored in the "Intensity (Actual Measurement)" column using a temperature correction constant, which will be described later, by the correction unit 1163R. The "Intensity (After Steady-State Correction)" column stores a value obtained by correcting the amplitude value stored in the "Intensity (After Temperature Correction)" column using a steady-state correction constant, which will be described later, by the correction unit 1163R.

[0035] FIG. 7 is a diagram illustrating the configuration of a temperature correction constant table. A temperature correction constant table is prepared for each of sensors 111R and 112R. The temperature correction constant table has columns for "Temperature" and "Temperature Correction Constant." Various temperatures are stored in the "Temperature" column. A temperature correction constant corresponding to the temperature stored in the "Temperature" column is stored in the "Temperature Correction Constant" column. The amplitude values ​​of the signals generated by sensors 111R and 112R are biased by the influence of temperature. The temperature correction constant is a value that is subtracted from the amplitude value of the signal generated by sensor 111R or sensor 112R to cancel the bias due to the influence of temperature, and is a value measured in advance through an experiment using sensor 111R or sensor 112R.

[0036] The steady-state correction constant data is data indicating a steady-state correction constant. The amplitude values ​​of the signals generated by the sensors 111R and 112R are subject to a bias unrelated to temperature in addition to the bias due to the temperature influence described above. The steady-state correction constant is a value that is subtracted from the amplitude value of the signal generated by the sensor 111R or the sensor 112R to cancel the bias unrelated to temperature. In this embodiment, the average value of the amplitude values ​​indicated by the night vision noise data described below is used as the steady-state correction constant.

[0037] The functional configuration of the flame detector 11 (FIG. 5) will be explained further. The acquisition unit 1162R is realized by the input / output interface 1013 that operates under the control of the processor 1011. The acquisition unit 1162R continuously acquires the signal output from the sensor 111R and the signal output from the sensor 112R. The amplitude values ​​of these signals acquired by the acquisition unit 1162R are stored in a measurement value log table together with the time and temperature at that time.

[0038] The correction unit 1163R is realized by the processor 1011. When new data is stored in the "Time", "Temperature" and "Intensity (Actual Measurement)" columns of the measurement value log table, the correction unit 1163R refers to the temperature correction constant table, identifies a temperature correction constant corresponding to the temperature stored in the "Temperature" column, and stores the value obtained by subtracting the temperature correction constant from the amplitude value stored in the "Intensity (Actual Measurement)" column in the "Intensity (After Temperature Correction)" column. Next, the correction unit 1163R subtracts the steady-state correction constant from the value stored in the "Intensity (After Temperature Correction)" column, and stores the value obtained by subtracting the steady-state correction constant from the value stored in the "Intensity (After Temperature Correction)" column in the "Intensity (After Steady-State Correction)" column.

[0039] The blocking period identification unit 1164R is realized by the processor 1011. The blocking period identification unit 1164R identifies, for each of the sensors 111R and 112R, a period during which light traveling from the outside to the sensor is blocked (hereinafter referred to as a "blocking period"), based on data stored in the measurement value log table corresponding to the sensor.

[0040] Fig. 8 is a graph for explaining a method for identifying the occlusion period performed by the occlusion period identification unit 1164R. The graph in Fig. 8 shows the change over time in the light intensity indicated by the amplitude values ​​stored in the "Intensity (actual measurement)" column of the measurement value log table corresponding to the sensor 111, for example. Note that since the graph in Fig. 8 is a graph relating to a short period of time, such as several minutes, the values ​​stored in the "Intensity (temperature corrected)" column or the "Intensity (steady-state corrected)" column may be used instead of the amplitude values ​​stored in the "Intensity (actual measurement)" column.

[0041] Based on the data stored in the measurement value log table, for example, if the intensity suddenly drops, and then the intensity fluctuations continue to be within a predetermined threshold for a predetermined time (for example, 25 seconds to 35 seconds), and then the intensity suddenly rises, the shielding period identification unit 1164R identifies the period from the timing when the intensity suddenly drops to the timing when the intensity suddenly rises as the shielding period. In the example of the graph in Figure 8, the shielding period identification unit 1164R identifies period Q1 as the shielding period.

[0042] The functional configuration of the flame detector 11 (FIG. 5) will be explained further. The flame detection unit 1165R is realized by the processor 1011. The flame detection unit 1165R refers to the measurement value log table, and if it determines that the amplitude value of the signal output from the sensor 111R (the value in the "Intensity (after steady-state correction)" column) and the amplitude value of the signal output from the sensor 112R (the value in the "Intensity (after steady-state correction)" column) satisfy a predetermined condition, it stores data indicating that a flame has been detected in the memory unit 1161R. If it determines that the condition is not satisfied, the flame detection unit 1165R stores data indicating that a flame has not been detected in the memory unit 1161R.

[0043] Examples of conditions used by the flame detection unit 1165R to determine whether a flame has been detected are shown below. (Condition 1) The amplitude value of the signal output from the sensor 111R is equal to or greater than the threshold value T1. (Condition 2) The amplitude value of the signal output from the sensor 112R is equal to or greater than the threshold value T2. (Condition 3) The ratio of the amplitude value of the signal output from the sensor 111R to the amplitude value of the signal output from the sensor 112R is equal to or greater than a threshold T3 and equal to or less than a threshold T4 (however, T3 <T4)である。

[0044] The flame detection unit 1165R determines that a flame has occurred when all of the above conditions 1 to 3 have been met a predetermined number of times or more within a past predetermined length of time (for example, 10 seconds).

[0045] The transmitter / receiver 1166R (an example of an output unit) is realized by the communication interface 1014 that operates under the control of the processor 1011. The transmitter / receiver 1166R continuously outputs a flame detection signal to the disaster prevention receiving panel 12 while data indicating that a flame has been detected is stored in the memory unit 1161R. The transmitter / receiver 1166R also outputs data stored in the measurement value log table that is for the blocking period identified by the blocking period identifying unit 1164R to the disaster prevention receiving panel 12 as data indicating night vision noise (hereinafter referred to as "night vision noise data").

[0046] Furthermore, the transmitting / receiving unit 1166R receives steady-state correction constant data transmitted from the disaster prevention receiving panel 12. The steady-state correction constant data received by the transmitting / receiving unit 1166R is overwritten on the steady-state correction constant data already stored in the memory unit 1161R.

[0047] The timekeeping unit 1167R is realized by the processor 1011. The timekeeping unit 1167R continuously measures the time that has elapsed since a reference time, identifies the current time, and generates a time signal that indicates the identified current time.

[0048] The disaster prevention receiving panel 12 (Fig. 1) that constitutes the flame detection system 1 is installed inside the tunnel TN, and when it receives a flame detection signal from the flame detector 11, it warns people in the vicinity by displaying and sounding an alarm, and also sends a notification that a flame has been detected to the server device 13. In addition to the functions of such a general disaster prevention receiving panel, the disaster prevention receiving panel 12 also has the function of determining the degree of deterioration of the flame detector 11 based on the night vision noise data output from the flame detector 11.

[0049] 9 is a diagram showing a schematic diagram of the hardware configuration of the disaster prevention receiving panel 12. The disaster prevention receiving panel 12 includes a computer 102, and a display 121 and an operation unit 122 connected to the computer 102.

[0050] The computer 102 includes a processor 1021 that processes data according to a program, a memory 1022 that stores various data including the program, an input / output interface 1023 that inputs and outputs signals between the display 121 and the operation unit 122, and a communication interface 1024 that communicates data between the n flame detectors 11 and the server device 13.

[0051] Fig. 10 is a diagram showing a schematic functional configuration of the disaster prevention receiving panel 12. That is, the processor 1021 of the computer 102 executes processing according to the program according to this embodiment, thereby realizing the disaster prevention receiving panel 12 equipped with a deterioration level determination device indicated by reference numeral 123 in Fig. 10. The functional configuration of the deterioration level determination device 123 will be described below.

[0052] The deterioration level determining device 123 includes a storage unit 1231 , an acquisition unit 1232 , a deterioration level determining unit 1233 , a transmission unit 1234 , a display control unit 1235 , and an operation receiving unit 1236 .

[0053] The storage unit 1231 is realized by the memory 1022 that operates under the control of the processor 1021, and stores various data. For example, night vision noise data transmitted from the flame detector 11 and acquired by the acquisition unit 1232 is stored in the storage unit 1231. Fig. 11 is a diagram illustrating the configuration of a table (hereinafter referred to as "night vision noise table") that the storage unit 1231 stores to store night vision noise data. The storage unit 1231 stores a night vision noise table corresponding to each of the four sensors for each of the multiple flame detectors 11.

[0054] The night vision noise table has the following columns: "Date and Time," "Night Vision Noise Data," "Average Value," "Standard Deviation," and "Data Abnormality." The "Date and Time" column stores, for example, the first date and time of the night vision period indicated by the night vision noise data. The "Night Vision Noise Data" column stores night vision noise data. Note that each piece of night vision noise data is a portion of the data extracted from the measurement value log table (Figure 6), and therefore contains multiple records. The "Average Value" column stores the average value of the values ​​stored in the "Intensity (Temperature Corrected)" column of the night vision noise data. The "Standard Deviation" column stores the standard deviation of the values ​​stored in the "Intensity (Temperature Corrected)" column of the night vision noise data. The "Data Abnormality" column stores data indicating whether the night vision noise data stored in the "Night Vision Noise Data" column is abnormal.

[0055] Returning to the explanation of the functional configuration (FIG. 10) of the disaster prevention receiving panel 12, the acquisition unit 1232 is realized by the communication interface 1024 that operates under the control of the processor 1021. The acquisition unit 1232 acquires the flame detection signal and the night-vision noise data from each of the n flame detectors 11. The night-vision noise data acquired by the acquisition unit 1232 is stored in a night-vision noise table.

[0056] The deterioration degree determination unit 1233 is realized by the processor 1021. When new night vision noise data is stored in any of the night vision noise tables, the deterioration degree determination unit 1233 calculates the average value and standard deviation of the values ​​stored in the "Intensity (after temperature correction)" column of that night vision noise data and stores them in the corresponding columns of the night vision noise table. In addition, the deterioration degree determination unit 1233 determines that, among the night vision noise data stored in the night vision noise table, any data whose average value or standard deviation deviates from the average value or standard deviation of other night vision noise data before and after it by more than a predetermined threshold value is abnormal data, and stores data indicating the determination result in the "Data Abnormality" column.

[0057] In addition, the deterioration level determination unit 1233 makes the following determinations and estimates for each of the four sensors of each of the multiple flame detectors 11 based on the data stored in the night vision noise table corresponding to those sensors (excluding data of records in which data indicating that the data is abnormal is stored in the ``Data Abnormality'' column).

[0058] (1) If the average intensity value indicated by the most recent night vision noise data is equal to or greater than a predetermined threshold A1, it is determined that the part needs to be replaced. In addition, the amplifier is estimated as the part that needs to be replaced. (2) If the standard deviation of the intensity indicated by the most recent night vision noise data is equal to or greater than a predetermined threshold B1, it is determined that the part needs to be replaced. In addition, the sensor is estimated as the part that needs to be replaced. (3) If the day on which the average intensity value indicated by the night vision noise data will reach a predetermined threshold A1, which is estimated based on the change over time of the average intensity value indicated by the night vision noise data over a predetermined period of time in the past, is within a predetermined number of days from the present, it is determined that the part will need to be replaced in the near future. In addition, it is estimated that the amplifier is the part that needs to be replaced. (4) If the day on which the standard deviation of intensity, estimated based on the time-dependent change in the standard deviation of intensity indicated by the night vision noise data over a predetermined period in the past, reaches a predetermined threshold B1, is within a predetermined number of days from the present, it is determined that the part will need to be replaced in the near future. In addition, the sensor is estimated as the part that needs to be replaced.

[0059] 12 and 13 are graphs for explaining the method by which the deterioration level determining device 123 performs the above-mentioned determination and estimation. The graphs in Fig. 12(a) and Fig. 13(a) are curves that approximate points corresponding to the values ​​in the "Date and Time" and "Average Value" columns of the night vision noise table. Note that the solid line portion of the curve shows the progress of the average value up to the present, and the dashed dotted line portion shows the progress of the average value predicted for the future.

[0060] The graphs in Figures 12(b) and 13(b) are curves that approximate the points corresponding to the values ​​in the "Date and Time" and "Standard Deviation" columns of the night vision noise table. Note that the solid line of the curves shows the progress of the standard deviation up to the present, and the dashed dotted line shows the predicted progress of the standard deviation in the future.

[0061] The graph in Figure 12(a) shows that at the current date and time d1, the average intensity value indicated by the night vision noise data does not reach the threshold value A1. Also, the graph in Figure 12(b) shows that at the current date and time d1, the standard deviation of the intensity indicated by the night vision noise data does not reach the threshold value B1. Therefore, based on these data, the deterioration level determination unit 1233 determines that the sensor corresponding to these data or the amplifier connected to that sensor does not need to be replaced.

[0062] 12(a) indicates that the average intensity value indicated by the night vision noise data is estimated to reach threshold A1 at date and time d2 within a predetermined number of days D1 from the current date and time d1. Also, the graph in FIG. 12(b) indicates that the standard deviation of the intensity indicated by the night vision noise data is estimated not to reach threshold B1 within a predetermined number of days D1 from the current date and time d1. Therefore, based on these data, the deterioration level determination unit 1233 determines that the sensor corresponding to these data or the amplifier connected to that sensor will soon need to be replaced, and in this case, estimates that the part to be replaced is the amplifier.

[0063] The graph in Figure 13(a) shows that at the current date and time d1, the average intensity value indicated by the night vision noise data does not reach the threshold value A1. The graph in Figure 13(b) shows that at the current date and time d1, the standard deviation of the intensity indicated by the night vision noise data reaches the threshold value B1. Therefore, based on these data, the deterioration level determination unit 1233 determines that the sensor corresponding to these data or the amplifier connected to that sensor needs to be replaced, and estimates that the part to be replaced is the sensor.

[0064] The deterioration level determination unit 1233 stores data indicating the results of the determination and estimation performed as described above in the storage unit 1231. FIG. 14 is a diagram illustrating the configuration of a table (hereinafter referred to as the "deterioration diagnosis result table") for storing data indicating the results of the determination and estimation performed by the deterioration level determination unit 1233. The deterioration diagnosis result table has a "device ID" column, a "right long wavelength" column, a "right short wavelength" column, a "left long wavelength" column, and a "left short wavelength" column. The "device ID" column stores identification information of the flame detector 11. The "right long wavelength" column, the "right short wavelength" column, the "left long wavelength" column, and the "left short wavelength" column correspond to the sensors 111R, 112R, 111L, and 112L, respectively, and stores data regarding these sensors in any of the following formats (a) to (c), for example:

[0065] (a) "Normal": Indicates that the part does not need to be replaced at present and that the part will not need to be replaced within a predetermined number of days D1 from now. (b) "Replacement Required (##)": This indicates that a part currently needs to be replaced, and that it is estimated that the part indicated by "##" (either the sensor or the amplifier, or both) needs to be replaced. (c) "Replacement required soon (##) (XX month XX day)": It is estimated that the part will need to be replaced around XX month XX day, and in that case, it is estimated that the part indicated in "##" (either the sensor or the amplifier, or both) will need to be replaced.

[0066] Returning to the explanation of the functional configuration of the disaster prevention receiving panel 12 (FIG. 10), the transmitting unit 1234 is realized by the communication interface 1024 that operates under the control of the processor 1021. The transmitting unit 1234 transmits the night vision noise table and the deterioration diagnosis result table to the server device 13. In addition, the transmitting unit 1234 periodically transmits data indicating the value in the "average value" column of the most recent record in the night vision noise table (excluding records in which data indicating abnormality is stored in the "data abnormality" column) to the flame detector 11 as steady-state correction constant data, for example.

[0067] The display control unit 1235 is realized by the processor 1021. The display control unit 1235 performs control to display various images on the display 121. For example, when a flame detection signal is received from any of the flame detectors 11, the display control unit 1235 generates image data representing the characters "Flame Detection Area ##" and causes the display 121 to display the image represented by the image data. Here, "Area ##" is identification information of the monitoring area A corresponding to the right flame detector or left flame detector of the flame detector 11 that detected the flame.

[0068] The operation reception unit 1236 is realized by the input / output interface 1023 that operates under the control of the processor 1021. The operation reception unit 1236 receives operations performed by a user such as a maintenance worker on the operation unit 122. Note that the operations performed by the user on the disaster prevention receiving panel 12 using the operation unit 122 include, for example, an operation to instruct the start of operation of a fire extinguishing device controlled by the disaster prevention receiving panel 12 when a fire is detected.

[0069] The above is a description of the disaster prevention receiving panel 12. The server device 13 (see FIG. 1) is a general server device having a Web server function, and therefore a description of its hardware configuration and functional configuration will be omitted.

[0070] The terminal device 14 (see FIG. 1) is a terminal device used by a maintenance person. The terminal device 14 is a general terminal device equipped with a web browser function, and therefore a description of its hardware configuration and functional configuration will be omitted.

[0071] The server device 13 receives the night vision noise table and the degradation diagnosis result table from the disaster prevention receiving panel 12 and stores the received data. In addition, in response to a request from the terminal device 14, the server device 13 generates display instruction data (e.g., HTML data) that instructs the display of a screen such as that shown in FIG. 15 (hereinafter referred to as the "degradation diagnosis screen") and transmits it to the terminal device 14. The terminal device 14 displays the degradation diagnosis screen in accordance with the display instruction data transmitted from the server device 13.

[0072] The deterioration diagnosis screen includes a table displaying information about flame detectors 11 that currently require part replacement, and a table displaying information about flame detectors 11 that are estimated to require part replacement in the near future. Maintenance personnel can easily find out which flame detectors 11 require maintenance work by looking at the deterioration diagnosis screen.

[0073] Furthermore, when the maintenance technician touches or clicks on any row in the table on the degradation diagnosis screen, the terminal device 14 transmits a request including the identification information of the sensor corresponding to that row to the server device 13. In response to the request from the terminal device 14, the server device 13 generates display instruction data instructing the display of a screen including a graph related to the sensor identified by the identification information included in the request (hereinafter referred to as the "graph display screen") and transmits it to the terminal device 14. The graph included in the graph display screen is a graph such as that shown in FIG. 12 or FIG. 13. The terminal device 14 displays the graph display screen in accordance with the display instruction data transmitted from the server device 13. By viewing the graph display screen, the maintenance technician can confirm the state of deterioration of the flame detector 11, which requires part replacement now or in the near future.

[0074] [Variations] The above-described embodiment is a specific example of the present invention, and various modifications are possible within the scope of the technical concept of the present invention. Examples of such modifications are shown below. Note that two or more of the following modifications may be combined as appropriate.

[0075] (1) The shielding period determination unit 1164 of the flame detector 11 included in the flame detection system 1 described above determines the shielding period based on the measurement results of the sensor 111 or the sensor 112. The method by which the shielding period determination unit 1164 determines the shielding period is not limited to this. For example, the flame detector 11 may include a shielding member detection unit that detects that a shielding member that blocks light from traveling toward the sensor from the outside has been attached to the flame detector, and the shielding period determination unit 1164 may determine the shielding period based on the detection results of the shielding member detection unit.

[0076] 16 is a diagram showing a schematic diagram of the hardware configuration of a flame detector 21 according to this modified example. In addition to the components included in the flame detector 11 (see FIG. 2) according to the embodiment described above, the flame detector 21 also includes a sensor 117 (an example of a shielding member detection unit) connected to the computer 101. The sensor 117 is a contact sensor, and when a shielding device S is pressed against the flame detector 21, it detects the contact of the shielding device S and outputs a contact detection signal.

[0077] 17 is a diagram schematically illustrating the functional configuration of flame detector 21. That is, processor 1011 of computer 101 included in flame detector 21 executes processing in accordance with the program of this modification, thereby realizing flame detector 21 including a determination device indicated by reference numeral 116 in FIG. 17. Acquisition unit 1162 of determination device 116 included in flame detector 21 acquires a contact detection signal output from sensor 117.

[0078] When the acquisition unit 1162 acquires contact detection signals continuously for a predetermined period of time (for example, 25 seconds or more and 35 seconds or less), the shielding period identification unit 1164 of the determination device 116 included in the flame detector 21 identifies the period during which the contact detection signals were acquired as the shielding period, excluding a predetermined period of time (for example, 3 seconds) immediately after the start and a predetermined period of time (for example, 3 seconds) immediately before the end. The reason for excluding part of the period during which the contact detection signals were acquired in this way is to exclude from the shielding period any period during which the window W may not be securely shielded by the shielding device S.

[0079] The flame detector 21 also extracts data for the shielding period from the measurement value log table as night vision noise data and outputs it to the disaster prevention receiving panel 12.

[0080] The type of sensor 117 included in the flame detector 21 is not limited to a contact sensor. For example, a magnetic sensor may be used as the sensor 117. In this case, the shielding device S includes a magnet that is placed in a position facing the sensor 117 when pressed against the flame detector 21 to shield the window W. When the shielding device S is pressed against the flame detector 21, the sensor 117 detects the magnetic force emitted by the magnet included in the shielding device S and outputs a contact detection signal.

[0081] Alternatively, a proximity sensor (NFC tag reader) that detects electromagnetic waves conforming to a short-range wireless communication standard may be employed as the sensor 117. In this case, the shielding device S includes an NFC tag that is placed in a position facing the sensor 117 while pressed against the flame detector 21 to shield the window W. When the shielding device S is pressed against the flame detector 21, the sensor 117 detects the electromagnetic waves emitted by the NFC tag included in the shielding device S and outputs a contact detection signal.

[0082] Furthermore, the flame detector 21 may include an operator (for example, a switch for switching ON and OFF) that is operated by a maintenance person, and the sensor 117 may detect that the operator has been operated by the maintenance person (for example, that the switch has been switched ON or OFF). In this case, the shielding period determination unit 1164 determines the shielding period based on the timing at which the sensor 117 detects the operation of the operator by the maintenance person.

[0083] (2) The flame detector 11 provided in the flame detection system 1 described above is a dual-wavelength flame detector, but the number of wavelength bands used by the flame detector provided in the flame detection system 1 to detect a flame may be three or more.

[0084] (3) In the above-described flame detection system 1, part of the processing that is to be performed by the disaster prevention receiving panel 12 may be performed by the flame detector 11, the server device 13, or the terminal device 14. For example, the flame detector 11 may be provided with a deterioration degree determination unit 1233. In addition, part of the processing that is to be performed by the flame detector 11 in the above-described flame detection system 1 may be performed by the disaster prevention receiving panel 12, the server device 13, or the terminal device 14.

[0085] (4) The flame detector 11 provided in the flame detection system 1 described above monitors the space inside the tunnel TN, but the area monitored by the flame detection system 1 is not limited to the inside of the tunnel. For example, the flame detector 11 may monitor a space inside a factory where there is a risk of a flame occurring.

[0086] (5) The flame detector 11 provided in the above-described flame detection system 1 includes a right flame detector and a left flame detector, but the flame detector 11 may also be a monocular flame detector that monitors only one area.

[0087] (6) In the above-described flame detection system 1, the flame detector 11 transmits night vision noise data to the disaster prevention receiving panel 12 without waiting for a request from the disaster prevention receiving panel 12, but the flame detector 11 may also transmit night vision noise data to the disaster prevention receiving panel 12 in response to a request from the disaster prevention receiving panel 12.

[0088] (7) In the flame detection system 1 described above, the method of determining the deterioration level of the flame detector 11 described using the graphs in FIGS. 12 and 13 is merely an example, and various other methods may be employed. For example, instead of standard deviation, variance, coefficient of variation, or the difference between the maximum and minimum amplitude values ​​may be used as an index indicating the variation in amplitude values ​​contained in the night vision noise data. Furthermore, the deterioration level may be determined or the parts to be replaced may be estimated based on the shape of the graphs illustrated in FIGS. 12 and 13. For example, a learning model may be generated by machine learning using a large amount of training data in which the type of part replaced in a past maintenance operation and the degree of deterioration of that part are used as objective variables, and night vision noise data corresponding to that part immediately before replacement is used as an explanatory variable. Night vision noise data output from a flame detector 11 in operation may be input into the learning model, and the learning model may output the type of part to be replaced and the degree of deterioration of that part.

[0089] (8) In the flame detection system 1 described above, the degree of deterioration determined by the deterioration degree determination unit 1233 is one of three levels: (a) part replacement is currently required, (b) part replacement will be required in the near future, and (c) normal. The deterioration degree determination unit 1233 may determine the degree of deterioration in a different expression format. For example, the ratio of the average value of the amplitude values ​​included in the night vision noise data to threshold value A1, or the ratio of the standard deviation of the amplitude values ​​included in the night vision noise data to threshold value B1 may be used as the degree of deterioration of the flame detector 11.

[0090] (9) In the above-described flame detection system 1, the components of the flame detector 11 that may deteriorate are the sensor and the amplifier, but the components that may deteriorate are not limited to these. For example, deterioration of wiring, contacts, etc. may also be suspected. [Explanation of symbols]

[0091] 1...flame detection system, 11...flame detector, 12...disaster prevention receiving panel, 13...server device, 14...terminal device, 21...flame detector, 101...computer, 102...computer, 111...sensor, 112...sensor, 113...amplifier, 114...amplifier, 115...thermometer, 116...determination device, 117...sensor, 121...display, 122...operation unit, 123...deterioration degree determination device, 1011...processor, 1012...memory, 1013...input / output interface base, 1014...communication interface, 1021...processor, 1022...memory, 1023...input / output interface, 1024...communication interface, 1161...storage unit, 1162...acquisition unit, 1163...correction unit, 1164...shielding period determination unit, 1165...flame detection unit, 1166...transmission / reception unit, 1167...timing unit, 1231...storage unit, 1232...acquisition unit, 1233...deterioration degree determination unit, 1234...transmission unit, 1235...display control unit, 1236...operation reception unit.

Claims

1. an acquisition unit that acquires night vision noise data indicating the intensity of light measured by a flame detector that detects a flame based on the intensity of light measured by a sensor during a period when light from the outside toward the sensor is blocked; a storage unit that stores the night vision noise data acquired by the acquisition unit; a deterioration degree determination unit that calculates an average value of the light intensity indicated by the night vision noise data stored in the storage unit and an index indicating the variation in the light intensity indicated by the night vision noise data stored in the storage unit, and estimates a first type of part among the parts included in the flame detector as a part that should be replaced if the average value satisfies a predetermined condition, and estimates a second type of part, different from the first type of part, among the parts included in the flame detector as a part that should be replaced if the index indicating the variation satisfies a predetermined condition; A deterioration level determination device comprising:

2. the flame detector includes an amplifier that amplifies a signal indicative of the intensity of light measured by the sensor; The deterioration degree determination unit estimates the amplifier as a part to be replaced when an average value of noise intensity indicated by the data stored in the memory unit satisfies a predetermined condition, and estimates the sensor as a part to be replaced when an index indicating a variation in noise intensity indicated by the data stored in the memory unit satisfies a predetermined condition. The deterioration level determining device according to claim 1 .

3. an acquisition unit that acquires night vision noise data indicating the intensity of light measured by a flame detector that detects a flame based on the intensity of light measured by a sensor during a period when light from the outside toward the sensor is blocked; a deterioration level determination unit that inputs the night vision noise data acquired by the acquisition unit into a learning model generated by machine learning using training data in which the type of part replaced in past maintenance work for a flame detector of the same type as the flame detector and the deterioration level of the part are used as objective variables and the night vision noise data before the part was replaced is used as an explanatory variable, and outputs from the learning model the type of part to be replaced among the parts included in the flame detector and the deterioration level of the part; A deterioration level determination device comprising:

4. On the computer, A process of acquiring night vision noise data indicating the intensity of light measured by a flame detector that detects a flame based on the intensity of light measured by a sensor during a period when light from the outside world toward the sensor is blocked; A process of storing the acquired night vision noise data; a process of calculating an average value of the light intensity indicated by the stored night vision noise data and an index indicating the variation in the light intensity indicated by the stored night vision noise data, and estimating a first type of part among the parts included in the flame detector as a part that should be replaced if the average value satisfies a predetermined condition, and estimating a second type of part, different from the first type of part, among the parts included in the flame detector as a part that should be replaced if the index indicating the variation satisfies a predetermined condition; A program to execute.

5. On the computer, A process of acquiring night vision noise data indicating the intensity of light measured by a flame detector that detects a flame based on the intensity of light measured by a sensor during a period when light from the outside world toward the sensor is blocked; a process of inputting the night vision noise data acquired in the acquiring process into a learning model generated by machine learning using training data in which the type of part replaced in past maintenance work for a flame detector of the same type as the flame detector and the degree of deterioration of the part are used as objective variables and the night vision noise data before the part was replaced is used as an explanatory variable, and outputting from the learning model the type of part to be replaced among the parts equipped in the flame detector and the degree of deterioration of the part; A program to execute.

6. A flame detector; The deterioration level determination device according to any one of claims 1 to 3, Equipped with The flame detector comprises: a sensor for measuring light intensity; a flame detection unit that detects a flame based on the intensity of light measured by the sensor; a shielding member detection unit that detects that a shielding member that blocks light from the outside toward the sensor has been attached to the device; a blocking period determination unit that determines a period during which light traveling from the outside to the sensor is blocked based on a detection result by the blocking member detection unit; an output unit that outputs night vision noise data indicating the intensity of light measured by the sensor during the period specified by the occlusion period specifying unit; Equipped with the shielding member detection unit includes one of a contact sensor that detects contact with the shielding member, a magnetic sensor that detects a magnetic force emitted by the shielding member, and a proximity sensor that detects electromagnetic waves that comply with a short-range wireless communication standard emitted by the shielding member; The acquisition unit of the deterioration level determination device acquires night vision noise data output by the output unit of the flame detector. Flame detection system.

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