CN109060148B - Flame detector and its control method - Google Patents
Flame detector and its control method Download PDFInfo
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- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
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Abstract
The invention discloses a kind of flame detector and its control methods, including MCU Main Processing Unit, the MCU Main Processing Unit is connected with integrated infra red flame sensor, and the integrated infra red flame sensor integration has the first flame infrared sensor cell, the second flame infrared sensor cell, human-body infrared sensing unit and background infrared with reference to sensing unit；The MCU Main Processing Unit is also connected with environment parameter sensing unit, and the environment parameter sensing unit is for acquiring Atmosphere temp.and RH, illuminance and uitraviolet intensity signal；MCU Main Processing Unit obtains the infra red flame signal of integrated infra red flame sensor, and the illuminance signal of combining environmental parameter sensing unit carries out flame infrared identification；MCU Main Processing Unit is also connected with NB-IoT wireless communication unit.The present invention can improve the recognition accuracy of flame, improve the collecting efficiency and utilization efficiency of equipment power supply.
Description
Technical field
The present invention relates to forest fire monitoring technology field, in particular to a kind of flame detector and its control method.
Background technique
Traditional forest fire protection means mainly include forest ranger patrol, monitoring camera-shooting.Forest ranger, which patrols, is unable to real-time monitoring
All area of fire protection, and it is too many by manpower fire prevention uncontrollable factor；Monitoring camera-shooting power consumption is big, needs wired power supply, installation site
It is limited, and the early stage fire monitoring of surface-fire, hayashishita fire is more difficult, and it is more next to be unable to satisfy pursuit detection fire occurrence time point in the industry
More early developing direction.
Domestic correlation mostly sensing combination two waveband photo taking type mixed flame detectors and its detection method application is special at present
It is sharp few, and all have some limitations.Existing purple infrared flame detector cannot achieve visualization and take on the market
The problem of card；Built-in image collection is mainly used in field hunting camera, is not directed to the application of forest fire protection, can't resolve
The accuracy and reliability problem of the long-term forest fires real-time detection evidence obtaining in field.And currently exist flame sensor and image recognition
Technology, which combines, to be carried out the fire monitoring of hayashishita early stage and captures the apparatus of evidence obtaining, it can be achieved that the round-the-clock prison of low-power consumption self energizing
It surveys, makes great progress in terms of fire detection and scene evidence taking.In fact, field flame detector is by energy consumption and transmission belt
Tolerance system, it is seen that optical sensor pixel has to be lowered, and live image has to return after compression, causes merely by figure
As carrying out final flame confirmation, clearly the high intensity light spots such as live illumination, light can not be foreclosed.In practice scene
In equally exist and can not judge live flame conditions, also resulting in needs forester manually to patrol confirmation, increases human cost simultaneously
And very likely delay best fire disaster emergency disposition opportunity.
With the development of information technology and sensing technology, the flame identification sensing technology and embedded image of low-power consumption are used
Identification technology is acquired, low-consumption wireless transmission technology just can effectively solve the problem of forest fire prevention and evidence obtaining difficulty.
Bibliography 1, application number 201721203568.9 discloses a kind of photo taking type mixed flame detector, attached referring to its
The infrared flame detector of Fig. 5, the patent are single pass infra red flame sensor, pertain only to a kind of infrared letter of flame of wavelength
Number, therefore it is poor to the infrared signal recognition capability of flame, it in addition will receive the infrared signal of animal sending, what environmental background issued
The interference of infrared signal, therefore anti-interference ability is weak.
The not set interference cancellation circuit of ultraviolet Acquisition Circuit of bibliography 1, acquisition flame UV signal be easy by
To the interference of ambient ultraviolet optical signal, it is easy to happen false alarm.
From 1 attached drawing 2 of bibliography as it can be seen that solar panel is directly to rechargeable battery powered, lack power supply acquisition mould
Block, therefore lack, to the charging effect of rechargeable battery poor, rechargeable battery and super capacitor poor to the collection effect of solar energy
It powers through multiple voltage conversion chips to modules, waste electric energy is more, therefore the utilizing status of power supply is poor；To being set to open country
Low energy consumption is extremely important for outer flame detector.
Bibliography 2: application number 201710847837.3 discloses photo taking type mixed flame detector and its detection method；
The still undisclosed above-mentioned distinguishing feature of the patent, lacks the technological means for solving above-mentioned Related Technical Issues.
Bibliography 3, application number 201610702532.9, a kind of flame identification side of double infrared channel flame detectors
Method, double infrared channel flame detectors pertain only to a kind of blazed wavelength signal of infrared channel, imitate to the identification of flare up fire
Fruit is poor, and in addition the flame detector is not directed to human body infrared channel wavelength signal, is easy the infrared signal by sendings such as animals
Interference.
Summary of the invention
In view of at least one defect of the prior art, the object of the present invention is to provide a kind of flame detector and its controls
Method acquires a variety of infrared signals and carries out flame identification, the identification for improving flame is accurate using integrated infra red flame sensor
Degree.
In order to achieve the above object, the present invention adopts the following technical scheme: a kind of flame detector, key are: packet
MCU Main Processing Unit is included, which is connected with integrated infra red flame sensor, the integrated infra red flame sensor collection
At having the first flame infrared sensor cell, the second flame infrared sensor cell, human-body infrared sensing unit and the infrared ginseng of background
Examine sensing unit；
The MCU Main Processing Unit is also connected with environment parameter sensing unit, and the environment parameter sensing unit is for acquiring
Atmosphere temp.and RH, illuminance and uitraviolet intensity signal；
MCU Main Processing Unit obtains the infra red flame signal of integrated infra red flame sensor, combining environmental parameter sensing unit
Illuminance signal carry out flame infrared identification；MCU Main Processing Unit is also connected with NB-IoT wireless communication unit.
It acquires a variety of infrared signals using integrated infra red flame sensor by above-mentioned structure setting and carries out flame knowledge
Not, the recognition accuracy of flame is improved.
Wherein the first flame infrared sensor cell, the second flame infrared sensor cell are respectively used to two kinds of different wave lengths of acquisition
Flame infrared signal, human-body infrared sensing unit is for acquiring human body infrared interference signal, i.e., for acquiring human or animal's hair
The infrared infrared wavelength signal for being used to acquire background environment sending with reference to sensing unit of interference infrared signal and background out；
Fourier transform is carried out by the signal to the first flame infrared sensor cell, the acquisition of the second flame infrared sensor cell, if sentencing
It is disconnected that there is flare up fire feature, then seek respectively infrared with reference to the related of sensing unit to human-body infrared sensing unit and background
Coefficient, if related coefficient meets flame characteristic, recognition result is flare up fire.
Signal can be issued supervision by NB-IoT wireless communication unit, that is, protenchyma networking module by infrared identification completion
Personnel；Or can further acquire UV signal or live image again identified that after by NB-IoT wireless communication unit
Issue supervisor.
The MCU Main Processing Unit is also connected with ultraviolet flame sensor through ultraviolet Acquisition Circuit；MCU Main Processing Unit obtains purple
The uitraviolet intensity signal of the signal combining environmental parameter sensing unit of outer flame sensor carries out flare up fire confirmation.
By above-mentioned structure setting, a variety of infrared signals are acquired using integrated infra red flame sensor and are known for the first time
Not, secondary-confirmation is carried out by the flame UV signal that ultraviolet flame sensor acquires, improves the recognition accuracy of flame.
The environment that ultraviolet flame sensor is used to acquire the UV signal combining environmental parameter sensing unit acquisition of flame is purple
External signal carries out secondary-confirmation.
Signal can be issued into supervisor by NB-IoT wireless communication unit after the completion of secondary identification；Or acquisition fire
Signal by NB-IoT wireless communication unit is issued supervisor after further identifying by the image at calamity scene.
A kind of recognition methods of flame detector, for the flame detector, it is critical that including following step
Suddenly,
Step A1, MCU Main Processing Unit controls integrated infra red flame sensor and is powered；
Step A2, MCU Main Processing Unit enters dormant state；
Step A3, the interrupt signal that MCU Main Processing Unit obtains integrated infra red flame sensor wakes up；
Step A4, MCU Main Processing Unit obtains the data of the first flame infrared sensor cell of integrated infra red flame sensor
Ch_fire1 [i], the data Ch_fire2 [i] of the second flame infrared sensor cell, human-body infrared sensing unit data Ch_
Interference [i] and the infrared data Ch_background [i] with reference to sensing unit of background；
Step A5, MCU Main Processing Unit obtains illuminance information Light [n] by environment parameter sensing unit；
Step A6, MCU Main Processing Unit is respectively by the data Ch_fire1 [i] of the first flame infrared sensor cell, the second fire
The data Ch_fire2 [i] of flame infrared sensor cell carries out Fourier transform, respectively obtains Fourier transform results FFt_fire1
And FFt_fire2, Fourier transform results FFt_fire1 and FFt_fire2 are carried out respectively using frequency domain distribution statistical function
Statistics, respectively obtains statistical result Sta_fire1 and Sta_fire2；
Step A7, MCU Main Processing Unit judges whether statistical result Sta_fire1 and Sta_fire2 have the basic of flame
Frequecy characteristic, if do not had, return step A2；A8 is entered step if had；
Step A8, MCU Main Processing Unit determines infrared channel correlation coefficient threshold y by illuminance information Light [n]3；
Step A9, MCU Main Processing Unit acquires the correlation coefficient ρ of Ch_fire1 [i] Yu Ch_interference [i]1, Ch_
The correlation coefficient ρ of fire1 [i] and Ch_background [i]2, Ch_fire2 [i] is related to Ch_interference's [i]
Coefficient ρ3, the correlation coefficient ρ of Ch_fire2 [i] and Ch_background [i]4；
If step A10, MCU Main Processing Unit judges correlation coefficient ρ1, correlation coefficient ρ2, correlation coefficient ρ3, correlation coefficient ρ4Entirely
Less than infrared correlation coefficient threshold y3；Then first flame identification result is flare up fire, and first flame identification result is passed through NB-
IoT wireless communication unit uploads or further takes the ultraviolet identification of flame, otherwise return step A2.
The recognition methods of the flame detector, it is critical that the ultraviolet identification of flame further includes following steps:
Step B1, MCU Main Processing Unit obtains the UV intensity UV of environment by environment parameter sensing unit；
Step B2, MCU Main Processing Unit determines the recognition threshold UV_ of flame Ultraviolet sensor according to UV intensity UV
Threshold；
Step B3, MCU Main Processing Unit opens flame Ultraviolet sensor, obtains ultraviolet pulse frequency UV_Count；
If step B4, MCU Main Processing Unit judgement ultraviolet pulse frequency UV_Count is higher than recognition threshold UV_
Then secondary flame confirmation result is flare up fire to Threshold, and secondary flame is confirmed that result wirelessly communicates list by NB-IoT
Member uploads or further takes image recognition, otherwise return step A2.
Remarkable result: the present invention provides a kind of flame detector and its control methods, are sensed using integrated infra red flame
Device acquires a variety of infrared signals and carries out flame identification, improves the recognition accuracy of flame.
Detailed description of the invention
Fig. 1 is function structure chart of the invention；Fig. 2 is the circuit diagram of integrated infra red flame sensor；
Fig. 3 is the circuit diagram of MCU Main Processing Unit；Fig. 4 is the circuit diagram of ultraviolet Acquisition Circuit；
Fig. 5 is the circuit diagram of image identification unit；Fig. 6 is the circuit diagram of visible light photo sensor；
Fig. 7 is the circuit diagram of infrared image sensor array；Fig. 8 is the circuit diagram of light energy collection unit；
Fig. 9 is the circuit diagram of Power Management Unit；Figure 10 is flow chart of the method for the present invention.
Figure 11 is the control method flow chart of cloud platform.
Specific embodiment
Invention is further described in detail in the following with reference to the drawings and specific embodiments.
As shown in Figure 1-Figure 11, a kind of flame detector, including MCU Main Processing Unit 1, the MCU Main Processing Unit 1 are connected with collection
At infra red flame sensor 2, the integrated infra red flame sensor 2 is integrated with the first flame infrared sensor cell, the second flame
Infrared sensor cell, human-body infrared sensing unit and background are infrared with reference to sensing unit；The MCU Main Processing Unit 1 is also through purple
Outer Acquisition Circuit 3 is connected with ultraviolet flame sensor 4；
As shown in Fig. 2, S1, S3, S2, S4 respectively represent the first flame infrared sensor cell, the infrared biography of the second flame in figure
It is infrared with reference to sensing unit to feel unit, human-body infrared sensing unit and background；Due to sensor ePY122X belong to it is existing at
Ripe module, internal structure are not described in detail, and integrate infra red flame sensor 2 also by interrupting connecting pin INT and MCU master control list
Member 1 connects；Interrupt signal is requested to MCU Main Processing Unit 1；The wavelength of S2 is 5 μm, and the wavelength of S4 is 3.91 μm, and the wavelength of S1 is
4.64 μm, the wavelength of S3 is 4.48 μm.The MCU Main Processing Unit 1 is also connected with environment parameter sensing unit 5, the environment ginseng
Number sensing unit 5 is for acquiring Atmosphere temp.and RH, illuminance and uitraviolet intensity signal；
The MCU Main Processing Unit 1 is also connected with image identification unit 6, and described image recognition unit 6 is connected with visible light figure
As sensor 61 and infrared image sensor array 62；Visible light image sensor 61 is used to capture the visible light figure of scene of fire
Piece, infrared image sensor array 62 are used to capture each pixel temperatures in the infrared thermal imaging picture and picture of scene of fire
Value；
MCU Main Processing Unit 1 obtains the infra red flame signal of integrated infra red flame sensor 2, and combining environmental parameter sensing is single
The illuminance signal of member 5 carries out flame infrared identification, obtains the signal combining environmental parameter sensing unit of ultraviolet flame sensor 4
5 uitraviolet intensity signal carries out flare up fire confirmation, and MCU Main Processing Unit 1 obtains the visible light picture knot of image identification unit 6
It closes infrared thermal imaging picture and carries out final fire identification；
MCU Main Processing Unit 1 is also connected with NB-IoT wireless communication unit 7 and sends fire information.
It acquires a variety of infrared signals using integrated infra red flame sensor 2 by above-mentioned structure setting and is known for the first time
Not, secondary-confirmation is carried out by the flame UV signal that ultraviolet flame sensor 4 acquires, finally by visible light image sensor
61 and infrared image sensor array 62 finally confirmed using visible light picture combination infrared thermal imaging picture, raising flame
Recognition accuracy.
Wherein the first flame infrared sensor cell, the second flame infrared sensor cell are respectively used to two kinds of different wave lengths of acquisition
Flame infrared signal, human-body infrared sensing unit is for acquiring human body infrared interference signal, i.e., for acquiring human or animal's hair
The infrared infrared wavelength signal for being used to acquire background environment sending with reference to sensing unit of interference infrared signal and background out；
Fourier transform is carried out by the signal to the first flame infrared sensor cell, the acquisition of the second flame infrared sensor cell, if sentencing
It is disconnected that there is flare up fire feature, then seek respectively infrared with reference to the related of sensing unit to human-body infrared sensing unit and background
Coefficient is identified as flare up fire if related coefficient meets flame characteristic for the first time.
Ultraviolet flame sensor 4 is used to acquire the UV signal of the UV signal combining environmental parameter sensing unit 5 of flame
Carry out secondary-confirmation.
Due to only being easy to be influenced by live illumination with visible light picture recognition, the present invention passes through acquisition visible light picture
It is handled in conjunction with infrared thermal imaging picture, seeks its related coefficient, finally confirmed.
Signal is issued into supervisor finally by NB-IoT wireless communication unit 7 i.e. protenchyma networking module.
Further include light energy collection unit 8, is directly MCU Main Processing Unit after light energy collection unit 8 converts light energy into electric energy
1 power supply, light energy collection unit 8 are integrated infra red flame sensor 2, ultraviolet Acquisition Circuit 3, environment ginseng by Power Management Unit 81
Number sensing unit 5, image identification unit 6, visible light image sensor 61, infrared image sensor array 62, NB-IoT is wireless
Communication unit 7 is powered.MCU Main Processing Unit 1 controls Power Management Unit 81 and powers.
It is arranged by above structure, the present invention acquires solar energy by light energy collection unit 8 and powers for flame detector, can
Not have to set up in forest zone to use electric line.MCU Main Processing Unit 1 improves the receipts of power supply by the management power supply of Power Management Unit 81
Collection rate and utilization rate, this can significantly reduce the energy consumption of flame detector.The MCU Main Processing Unit 1 is MSP430 single-chip microcontroller；
The light energy collection unit 8 includes solar panel S1, ADP509X collection module, and MCU Main Processing Unit 1 is arranged
There is power supply collecting terminal group, MSP430 single-chip microcontroller connects the ADP509X collection module by power supply collecting terminal group；
Solar panel S1 power end connects one end of resistance R1, and the other end of resistance R1 is also grounded through capacitor C1, electricity
The other end of resistance R1 is also connected with the end VIN of ADP509X collection module；The end VIN of ADP509X collection module is connected through inductance L1
The end SW of ADP509X collection module；The ground terminal of solar panel S1 is grounded；
The ground terminal of ADP509X power module is grounded；
One end of resistance R1, which is also connected with field, should imitate the source electrode of pipe M1, and field should imitate the another of the drain electrode connection resistance R1 of pipe M1
End, one end of resistance R1 are also connected with one end of resistance R2, and the other end connection field of resistance R2 should imitate the grid of pipe M1, field Ying Xiaoguan
The drain electrode of M1 is also connected with one end of resistance R4, and the other end of resistance R4 is grounded through resistance R5, and the other end connection of resistance R4 is integrated
The non-inverting input terminal of amplifier U1, the non-inverting input terminal of integrated transporting discharging U1 are also connected with one end of resistance R3, and the other end of resistance R3 connects
The grid of pipe M1 should be imitated by connecing field, and the other end of resistance R3 is also connected with the output end of integrated transporting discharging U1, and the reverse phase of integrated transporting discharging U1 is defeated
Enter REG-OUT end of the end through resistance R6 connection ADP509X collection module, the inverting input terminal of integrated transporting discharging U1 also connects through resistance R7
Ground, the end REG-OUT of the power supply termination ADP509X collection module of integrated transporting discharging, the ground terminal ground connection of integrated transporting discharging；
The end VIN of ADP509X collection module is also connected with one end of resistance R8, and the other end connection ADP509X of resistance R8 is received
Collect the end MPPT of module；The other end of resistance R8 is also grounded through resistance R9, and the end VID of ADP509X collection module connects through resistance R10
The end CBP on ground, ADP509X collection module is grounded through capacitor C2, and the end MINOP of ADP509X collection module is grounded through capacitor C3；
The anode of the end the BACK-UP connection super capacitor of ADP509X collection module, the cathode ground connection of super capacitor；
The anode of the end the BAT connection rechargeable battery of ADP509X collection module, the cathode ground connection of rechargeable battery；
The end REG-OUT of ADP509X power module is also connected with one end of resistance R11, the other end connection of resistance R11
The end REG-FB of ADP509X power module, the other end of resistance R11 are also grounded through resistance R21；
One end of the end the REF connection resistance R12 of ADP509X power module, the other end connection ADP509X electricity of resistance R12
The end SETSD of source module, the other end of resistance R12 are also grounded through resistance R13；
The end REF of ADP509X power module is also connected with one end of resistance R14, and the other end of resistance R14 connects ADP509X
The end SETPG of power module, the other end of resistance R14 are also connected with one end of resistance R15, the other end connection of resistance R15
The end SETHYST of ADP509X power module, the other end of resistance R15 are also grounded through resistance R16；
The end REF of ADP509X power module is also connected with one end of resistance R17, and the other end of resistance R17 connects ADP509X
The end SETBK of power module, the other end of resistance R17 are also grounded through resistance R18；
The end REF of ADP509X power module is also connected with one end of resistance R19, and the other end of resistance R19 connects ADP509X
The end TERM of power module, the other end of resistance R19 are also grounded through resistance R20；
The end SYS of ADP509X power module and the power end of MCU Main Processing Unit 1 are connected as its power supply；
The present invention collects the electric energy of solar panel S1 using ADP509X collection module, charges for rechargeable battery, can
Charge efficiency is improved, the service life of rechargeable battery is conducive to extend, ADP509X collection module power consumption itself is low, in high current,
Field should imitate pipe M1 conducting, and in low current, field should imitate pipe M1 cut-off, since field should imitate the control action of pipe M1, in low current
It can be realized trickle charge.ADP509X power module is directly connected to power for it with MCU Main Processing Unit 1.
ADP509X collection module is connected with super capacitor, when electric quantity of rechargeable battery is low, can supply for flame detector
Electricity.
The Power Management Unit 81 uses RC5T619 management module, and the MCU Main Processing Unit 1 is provided with power management
End group, MCU Main Processing Unit 1 connect the RC5T619 management module by power management end group；The anode of rechargeable battery is through resistance
The anode of R35 connection diode D3, the cathode of diode D3 are grounded through capacitor C31, and the cathode of diode D3 is also connected with RC5T619
The end VINP1 of management module, the end VINP1 of RC5T619 management module also and connect RC5T619 management module the end VINP2,
The end VINP3, the end VINL1, the end VINL2, the end VINL3；The ground terminal AGND of RC5T619 management module is grounded；
The anode of rechargeable battery is also connected with one end of resistance R31, and the other end of resistance R31 is grounded through resistance R32, resistance
The other end of R31 is also connected with the inverting input terminal of integrated transporting discharging U3, and the non-inverting input terminal of integrated transporting discharging U3 is super through resistance R33 connection
The anode of grade capacitor, the non-inverting input terminal of integrated transporting discharging U3 are also grounded through resistance R34, and the anode of super capacitor is also connected with field-effect
The source level of pipe M3, the end VINP1 of the drain connection RC5T619 management module of field-effect tube M3, the output end of integrated transporting discharging U3 connect
Connect the grid of field-effect tube M3, grid of the source level of field-effect tube M3 also through resistance R36 connection field-effect tube M3；
RC5T619 management module is also connected with the first output power supply circuit, and RC5T619 management module is supplied by the first output
Circuit is the power supply of ultraviolet Acquisition Circuit 3, and the first output power supply circuit includes inductance L31, one end of inductance L31 with
The end LX1 of RC5T619 management module connects, and one end of the other end connection resistance R37 of inductance L31, the other end of resistance R37 connects
The end FB1 of RC5T619 management module is connect, the other end of resistance R37 also connects the end GND1 of RC5T619 management module through R38；Inductance
The other end of L31 also connects the end GND1 of RC5T619 management module through capacitor C32, and the capacitor C32 is parallel with capacitor C33, inductance
The other end of L31 connects ultraviolet Acquisition Circuit 3 and powers for it；
RC5T619 management module is also connected with the second output power supply circuit, and RC5T619 management module is supplied by the second output
Circuit is the power supply of NB-IoT wireless communication unit 7, and the second output power supply circuit is identical as the first output structure of power supply circuit；
RC5T619 management module is also connected with third output power supply circuit, and RC5T619 management module is exported by third and supplied
Circuit is that visible light image sensor 61, infrared image sensor array 62 are powered, and third exports power supply circuit and first defeated
The structure of power supply circuit is identical out；
The end LDOVOUT1 of RC5T619 management module and integrated infra red flame sensor 2 are connected as its power supply；RC5T619
The end LDOVOUT2 of management module and environment parameter sensing unit 5 are connected as its power supply；The LDOVOUT3 of RC5T619 management module
End is connected as its power supply with image identification unit 6.
Power Management Unit 81 of the present invention uses RC5T619 management module, and MCU Main Processing Unit 1 passes through power management end group
Controlling RC5T619 management module is integrated infra red flame sensor 2, ultraviolet Acquisition Circuit 3, environment parameter sensing unit 5, image
Recognition unit 6, visible light image sensor 61, infrared image sensor array 62, NB-IoT wireless communication unit 7 are powered.
RC5T619 management module is easy to control, and power consumption is lower.
By the control action of integrated transporting discharging U3 and field-effect tube M3, when electric quantity of rechargeable battery is low, using super capacitor
Power supply.
The environment parameter sensing unit 5 includes that Temperature Humidity Sensor 51 and atmosphere light shine Ultraviolet sensor 52, the temperature
Humidity sensor 51 uses SI702X sensor, and the atmosphere light uses SI113X sensor according to Ultraviolet sensor 52.Above-mentioned two
Kind sensor belongs to mature modules, and internal circuit is omited.
It is convenient that temperature-humidity signal is acquired by SI702X sensor by above-mentioned structure setting, it is sensed by SI113X
The illuminance and uitraviolet intensity signal of device acquisition environment.
The ultraviolet Acquisition Circuit 3 includes Ultraviolet sensor circuit and interference cancellation circuit 31, Ultraviolet sensor circuit warp
Interference cancellation circuit 31 is connected with MCU Main Processing Unit 1.
Ultraviolet flame sensor 4 in the prior art is transmitted directly to MCU Main Processing Unit 1, does not eliminate electricity by interference
Ambient ultraviolet interference signal is eliminated on road 31 can eliminate ambient ultraviolet interference signal by the setting of interference cancellation circuit 31.
The Ultraviolet sensor circuit is provided with TPS65552A module, and the end Vcc of TPS65552A module simultaneously meets its VBAT
Power Management Unit 81 is connected behind end, the end Vcc of TPS65552A module is also grounded through capacitor C61, TPS65552A module
The end PGND ground connection, Vcc end of the end CHG of TPS65552A module also through resistance R64 connection TPS65552A module；TPS65552A
Vcc end of the end I-PEAK of module through upper divider resistance R61 connection TPS65552A module, the end I-PEAK of TPS65552A module
Also it is grounded through lower divider resistance R62；Vcc end of the end F-ON of TPS65552A module through resistance R63 connection TPS65552A module；
The end XIFULL of TPS65552A module is successively grounded through resistance R66, resistance R67 and adjustable resistance RSEL；
TPS65552A module the end SW connection transformer TR1 input coil one end, transformer TR1 input coil it is another
One end connects one end of resistance R65, and the other end of resistance R65 is grounded through capacitor C62；One end of transformer TR1 output winding connects
The anode of diode D61, the anode of the cathode connection electrolytic capacitor C63 of diode D61 are connect, the cathode of electrolytic capacitor C63 is grounded,
The other end of transformer TR1 output winding is grounded；The anode of electrolytic capacitor C63 is also connected with one end of ultraviolet flame sensor 4, purple
The other end of outer flame sensor 4 is grounded through resistance R70；
The anode of electrolytic capacitor C63 is also connected with one end of resistance R68, and the other end of resistance R68 is through capacitor C64 connection transformation
One end of device TR2 input coil, one end of the other end connection transformer TR2 output winding of transformer TR2 input coil, transformation
The other end of the other end connection ultraviolet flame sensor 4 of device TR2 output winding；
The other end of resistance R68 is also connected with the collector of switch transistor T 61, the emitter ground connection of switch transistor T 61, switching tube
The base stage of T61 connects the end G-IGBT of TPS65552A module, and the other end of ultraviolet flame sensor 4 is being also connected with diode D62 just
Pole, the collector of the cathode connection switch pipe T61 of diode D62, the other end of ultraviolet flame sensor 4 are also connected with capacitor C65
One end, the other end of capacitor C65 is through the cathode of resistance R69 connection diode D62；
The other end of ultraviolet flame sensor 4 is also connected with the non-inverting input terminal of integrated transporting discharging U8, the same phase of integrated transporting discharging U8
Input terminal is also grounded through capacitor C66, and the inverting input terminal of integrated transporting discharging U8 is connected through resistance R71 with Power Management Unit 81, collection
It is also grounded through resistance R72 at the inverting input terminal of amplifier U8, the output end of integrated transporting discharging U8 is connected with interference cancellation circuit 31；
The interference cancellation circuit 31 includes CD4017 counter, output end and the CD4017 counter of integrated transporting discharging U8
The end CLOCK is connected, and the end Q2 of CD4017 counter is connected with the base stage of switch transistor T 64, and the collector of switch transistor T 64 connects MCU
The ultraviolet collection terminal of the first of main control unit 1, the emitter ground connection of switch transistor T 64；
The end Q5 of CD4017 counter is connected with the base stage of switch transistor T 63, and the collector of switch transistor T 63 connects MCU master control
The ultraviolet collection terminal of the second of unit 1, the emitter ground connection of switch transistor T 63；The end Q5 of CD4017 counter is also counted with CD4017
The end CLOCK-IN of device is connected.
It is counted by the pulse that CD4017 counter generates ultraviolet flame sensor 4.
Thus, it is possible to according to the selection of sensitivity, i.e. the pulse number that generates of ultraviolet flame sensor 4 can filter out
The pulse signal that some low frequency UV lights in environment generate.
Specific implementation: single-chip microcontroller issues three in the pulse of acquisition CD4017 output, actually ultraviolet flame sensor 4
A or six pulsed flame signals, single-chip microcontroller just receive one, thus can effectively exclude the interference of environment light source.
A kind of control method of flame detector, it is critical that include the following steps,
Step A1, MCU Main Processing Unit 1 controls integrated infra red flame sensor 2 and is powered；
Step A2, MCU Main Processing Unit 1 enters dormant state；
Step A3, the interrupt signal that MCU Main Processing Unit 1 obtains integrated infra red flame sensor 2 wakes up；
Step A4, MCU Main Processing Unit 1 obtains the number of the first flame infrared sensor cell of integrated infra red flame sensor 2
According to Ch_fire1 [i], the data Ch_fire2 [i] of the second flame infrared sensor cell, human-body infrared sensing unit data Ch_
Interference [i] and the infrared data Ch_background [i] with reference to sensing unit of background；I is the signal number of acquisition
Mesh, i=1~128；
Step A5, MCU Main Processing Unit 1 obtains illuminance information Light [n] by environment parameter sensing unit (5), and n is
The illuminance information number of acquisition, n=1~3；
Step A6, MCU Main Processing Unit 1 is respectively by the data Ch_fire1 [i] of the first flame infrared sensor cell, the second fire
The data Ch_fire2 [i] of flame infrared sensor cell carries out Fourier transform, respectively obtains Fourier transform results FFt_fire1
And FFt_fire2, Fourier transform results FFt_fire1 and FFt_fire2 are carried out respectively using frequency domain distribution statistical function
Statistics, respectively obtains statistical result Sta_fire1 and Sta_fire2；
Step A7, MCU Main Processing Unit 1 judges whether statistical result Sta_fire1 and Sta_fire2 have the basic of flame
Frequecy characteristic, if do not had, return step A2；A8 is entered step if had；
Step A8, MCU Main Processing Unit 1 determines infrared channel correlation coefficient threshold y by illuminance information Light [n]3；
Step A9, MCU Main Processing Unit 1 acquires the correlation coefficient ρ of Ch_fire1 [i] Yu Ch_interference [i]1,
The correlation coefficient ρ of Ch_fire1 [i] and Ch_background [i]2, the phase of Ch_fire2 [i] and Ch_interference [i]
Relationship number ρ3, the correlation coefficient ρ of Ch_fire2 [i] and Ch_background [i]4；
If step A10, MCU Main Processing Unit 1 judges correlation coefficient ρ1, correlation coefficient ρ2, correlation coefficient ρ3, correlation coefficient ρ4
It is less than infrared correlation coefficient threshold y entirely3；Then first flame identification result is flare up fire, and first flame identification result is passed through
NB-IoT wireless communication unit 7 uploads or further takes the ultraviolet identification of flame, otherwise return step A2.
The present embodiment also further takes the ultraviolet identification of flame.
Step B1, MCU Main Processing Unit 1 obtains the UV intensity UV of environment by environment parameter sensing unit 5；
Step B2, MCU Main Processing Unit 1 determines the recognition threshold UV_ of flame Ultraviolet sensor 4 according to UV intensity UV
Threshold；
Step B3, MCU Main Processing Unit 1 opens flame Ultraviolet sensor 4, obtains ultraviolet pulse frequency UV_Count；
If step B4, MCU Main Processing Unit 1 judges that ultraviolet pulse frequency UV_Count is higher than recognition threshold UV_
Then secondary flame confirmation result is flare up fire to Threshold, and secondary flame is confirmed that result wirelessly communicates list by NB-IoT
Member 7 uploads or further takes image recognition, otherwise return step A2.
The present embodiment also further takes image recognition, and image recognition includes the following steps；
Step C1, MCU Main Processing Unit 1 opens image identification unit 6 and acquires visible light image data VisablePic [m]；
Step C2, MCU Main Processing Unit 1 is it will be seen that light image data VisablePic [m] is converted to grayscale image
VisablePic_Gray [m], and convolution is done with convolution kernel, the grayscale image VisablePic_Gray_Conv after obtaining convolution
Grayscale image VisablePic_Gray_Conv [m] after convolution is sought peak-to-peak value, obtains seeking the image data after peak-to-peak value by [m]
VisablePic_Gray_Peek simultaneously carries out binaryzation, obtains binarization result picture VisablePic_Bool；
Step C3, binarization result picture VisablePic_Bool is carried out morphological erosion, filter by MCU Main Processing Unit 1
Wave, expansion, reduction obtain filtering two-value picture VisablePic_Bool_Reduce；
Step C4,1 couple of filtering two-value picture VisablePic_Bool_Reduce of MCU Main Processing Unit is filtered, and is obtained
Doubtful flame characteristic picture VisablePic_Final；
Step C5, MCU Main Processing Unit 1 acquires infrared thermal imaging picture IrPic and each pixel of infrared thermal imaging picture
Temperature value；Binary conversion treatment is carried out to infrared thermal imaging picture IrPic and obtains binaryzation infrared thermal imaging picture IrPic_Bool；
Step C6, MCU Main Processing Unit 1 calculates doubtful flame characteristic picture VisablePic_Final and the infrared heat of binaryzation
The picture related coefficient Count_Fire of picture IrPic_Bool is imaged；
Step C7, MCU Main Processing Unit 1 judges that picture related coefficient Count_Fire is higher than empirical value and is then finally identified as
Flame pre-warning signal, enters step C8；Otherwise return step A2；
Step C8, MCU Main Processing Unit 1 is by fire behavior warning information, visible light image data VisablePic [m] and infrared heat
Picture IrPic is imaged, cloud platform 9 is uploaded by NB-IoT communication module 7；
Fire behavior warning information includes the number of flame detector, position etc..
As shown in figure 11, the control method of the cloud platform 9 includes the following steps:
Step D1: the fire behavior warning information of the reception NB-IoT communication module 7 of cloud platform 9；
Step D2: cloud platform 9 judges whether the reception of fire behavior warning information succeeds, if so, under NB-IoT communication module 7
Hair receives successful information, enters step D3；Otherwise request NB-IoT communication module 7 is retransmitted, return step D1；
Step D3: cloud platform 9 parses fire behavior warning information；Step D4: cloud platform 9 calls Short Message Service Gateway interface 91 to user
Terminal push note fire behavior early warning；Step D5: cloud platform 9 positions early warning position and is shown in GIS map；
Step D6: cloud platform 9 receive NB-IoT communication module 7 send visible light image data VisablePic [m] with
Infrared thermal imaging picture IrPic；
Step D7: cloud platform 9 judges that visible light image data VisablePic [m] is with infrared thermal imaging picture IrPic
It is no to receive successfully, if not provided, request NB-IoT communication module 7 is retransmitted, return step D6；If it is successful, being communicated to NB-IoT
Module 7 issues reception successful information, enters step D8；
Step D8: cloud platform 9 parses visible light image data VisablePic [m] and infrared thermal imaging picture IrPic；Step
Rapid D9: cloud platform 9 carries out image with infrared thermal imaging picture IrPic by visible light image data VisablePic [m] and synthesizes
Operation obtains synthesis operation image；
Step D10: cloud platform 9 pushes interface 92 by image and is pushed to user terminal for operation image is synthesized；
Step D11: cloud platform 9 uploads to operation image is synthesized in GIS map；
Step D12: cloud platform 9 waits the alert order that disappears.Short Message Service Gateway interface 91 and image push interface 92 belong to API and connect
Mouthful, SMS platform is connected to user terminal pushed information and image.
It is arranged by above-mentioned control method, MCU Main Processing Unit 1 is acquired a variety of red using integrated infra red flame sensor 2
External signal carries out flame infrared identification, carries out secondary-confirmation by the flame UV signal that ultraviolet flame sensor 4 acquires, finally
Visible light picture combination infrared thermal imaging picture is acquired by visible light image sensor 61 and infrared image sensor array 62
Finally confirmed, improves the recognition accuracy of flame.
Wherein the first flame infrared sensor cell, the second flame infrared sensor cell are respectively used to two kinds of different wave lengths of acquisition
Flame infrared signal, human-body infrared sensing unit is for acquiring human body infrared interference signal, i.e., for acquiring human or animal's hair
The infrared infrared wavelength signal for being used to acquire background environment sending with reference to sensing unit of interference infrared signal and background out；
Fourier transform is carried out by the signal to the first flame infrared sensor cell, the acquisition of the second flame infrared sensor cell, if sentencing
It is disconnected that there is flare up fire feature, then seek respectively infrared with reference to the related of sensing unit to human-body infrared sensing unit and background
Coefficient is identified as flare up fire if related coefficient meets flame characteristic for the first time.Ultraviolet flame sensor 4 is for acquiring fire
The UV signal of the UV signal combining environmental parameter sensing unit 5 of flame carries out secondary-confirmation.
Due to only being easy to be influenced by live illumination with visible light picture recognition, the present invention passes through acquisition visible light picture
It is handled in conjunction with infrared thermal imaging picture, seeks its related coefficient, finally confirmed.
MCU Main Processing Unit 1 acquires infrared data by integrated infra red flame sensor 2, passes through environment parameter sensing unit 5
It acquires environmental data and flare up fire is identified using cross validation's algorithm:
First flame infrared sensor cell, the second flame infrared sensor cell, human-body infrared sensing unit and background are red
External Reference sensing unit acquires data respectively, for reflecting the Wave data of each infrared unit during this period.Four infrared lists
Metadata definition is as follows, respectively indicates the array comprising 128 numerical value:
Ch_fire1 [i] indicates the data of the first flame infrared sensor cell acquisition；Ch_fire2 [i] indicates the second flame
The data of infrared sensor cell acquisition；Ch_interference [i] indicates the data of human-body infrared sensing unit acquisition；Ch_
Background [i] indicates the infrared data acquired with reference to sensing unit of background；I=1~128.Acquiring four infrared units
While data, illuminance data, i.e. illuminance information are acquired by environment parameter sensing unit 5, obtaining includes n numerical value
Array: Light [n], n=1~3.
Use Fourier transform function y1=FFt (x1) (1)
Function is common Fourier transform function, and by Ch_fire1 [i], Ch_fire2 [i] is used as variable x1Input Fu
Vertical leaf transformation function；
Acquire two passage of flame Ch_fire1 [i], the result data FFt_ after the Fourier transform of Ch_fire2 [i]
Fire1 and FFt_fire2.Result data after Fourier transform, illustrate the infrared unit during data collection, waveform
In the distribution of different frequency.FFt_fire1 and FFt_fire2 is the frequency of Ch_fire1 [i] and Ch_fire2 [i] in 0~20Hz
Rate distribution.
Use frequency domain distribution statistical function
In above-mentioned formula, the data FFt_fire1 after inputting the first flame infrared sensor cell Fourier transform and the
Data FFt_fire2 after two flame infrared sensor cell Fourier transforms is substituted into carry out operation respectively；Sum in above-mentioned formula
() is summing function；
Function has counted the array x of input2, i.e. Fourier transform results, in formula (2), molecule acquires it in 3~5Hz
The summation of distribution, denominator acquire the distribution summation of all frequencies, then return to the former the ratio y than upper the latter2, y2Return value
Range is (0.0~1)；
Using FFt_fire1 and FFt_fire2 as x2Frequency domain distribution statistical function is substituted into, FFt_fire1 and FFt_ are acquired
The function implementing result of fire2 obtains frequency domain distribution Sta_fire1 and Sta_fire2.If the value of the two is both less than empirical parameter
0.5, then it is judged as the infrared triggering of interference, stops recognizer.If one of them is greater than empirical parameter 0.5, has flame
Basic frequency feature.
Function, which is obtained, using infrared correlation coefficient threshold obtains infrared correlation coefficient threshold；
In above-mentioned formula, the illuminance data Light [n] of input environment parameter sensing unit (5) acquisition, by Light [n]
As variable x3It substitutes into formula and carries out operation；
Tanh () can use y in above-mentioned formula (3)6It indicates,
E is the nature truth of a matter；
Average () function returns to the average value of input array in above-mentioned formula (3)；Peak () function in above-mentioned formula
Return to the peak-to-peak value of input array；This formula is obtained by the fitting of actual experiment data；
Light [n] is converted to last result y by above-mentioned formula3, as infrared correlation coefficient threshold.Light
The range of each numerical value of [n] array is (0~3000), and the range of results by Average () is (0~3000), by Peak
The range of results of () is (0~3000), so byRange of results be (0~4).And
Tanh () function curve of function is as shown below, and returning the result numberical range is (0.0~1.0).In summary, numerical value
Range is (0.3~0.7).
Function is obtained using cross-correlation coefficient:
In above-mentioned formula (6), a (i) is any group in two groups of passage of flame data, and b (i) is interference or background channel
Any group in data；
N in above-mentioned formula: being fixed value 128 in this programme for the length of array；I=1~128；
Average () in above-mentioned formula: the average value of input array is returned；
Using above-mentioned formula (6), the related coefficient of Ch_fire1 and Ch_interference are acquired, which uses
ρ1It indicates, the related coefficient of Ch_fire1 and Ch_background, related coefficient ρ2It indicates, Ch_fire2 and Ch_
The related coefficient of interference, related coefficient ρ3It indicates, the related coefficient of Ch_fire1 and Ch_background,
Related coefficient ρ4It indicates.
Correlation coefficient ρ1、ρ2、ρ3、ρ4It is less than infrared correlation coefficient threshold entirely；Then first recognition result is flame；Then this calculation
Method identifies successfully.
Ultraviolet pulse number and ambient ultraviolet intensity weighted algorithm:
MCU Main Processing Unit (1) acquires current environment UV intensity UV by environment parameter sensing unit 5；
The umber of pulse UV_Count that ultraviolet flame sensor 4 exports in 3 seconds is obtained by ultraviolet Acquisition Circuit 3；UV_
Count is ultraviolet pulse frequency；
UV_Threshold is obtained using formula (7):
In above-mentioned formula (7), x7For current environment UV intensity UV, value range is (0~3000)；
In above-mentioned formula int () be bracket function, for take the parameter in bracket integer part numerical value；
Using above-mentioned formula, UV intensity UV is inputted, result y is obtained7, as UV_Threshold, UV_Threshold
The as recognition threshold of flame Ultraviolet sensor (4).UV_Count is greater than UV_Threshold, then secondary recognition result is flame
Signal then meets flame condition.
Visible light picture flame characteristic extraction algorithm: MCU Main Processing Unit (1) by visible light image sensor 61 every
200ms acquires a visible light picture, obtains visible light image data；Visible light image data is indicated with VisablePic [m]；
M is the number of visible light image data, m=1~5；
VisablePic [m] is color image；Grayscale image VisablePic_Gray is converted it into psychology formula
[m]；
Psychology formula: Gray=0.3 × R+0.59 × G+0.11 × B； (8)
In formula (8), R, G, B are the value in the corresponding channel of three colors of red, green, blue respectively；
Same article appears in the position in 5 pictures of VisablePic_Gray [m] may be different, in picture
There may be drifts for absolute position.So by grayscale image VisablePic_Gray [m] and convolution kernelConvolution is done, is reduced
Drift, the grayscale image VisablePic_Gray_Conv [m] after obtaining convolution；
For a certain pixel in VisablePic_Gray_Conv [m], the maximum value in 5 pictures is subtracted most
The small obtained value of value is the corresponding peak-to-peak value of the pixel.To each of VisablePic_Gray_Conv [m] point
Its peak-to-peak value is sought, an image data VisablePic_Gray_Peek asked after peak-to-peak value is obtained；
The segmentation threshold for obtaining VisablePic_Gray_Peek with maximum entropy threshold method is obtained then by its binaryzation
To binarization result picture VisablePic_Bool；
Maximum entropy threshold method: pixel point value range is 0~255 in picture, probability of the statistical pixel o'clock in 0~255 range
Distribution.Such as be worth and occur in picture 10 times for 125 pixel, a total of 100 pixels, then on 125 point
Cloth is 10%；
The definition of digital picture medium entropy:
H=- Σ p (g) × log (p (g)) (9)
Entropy is the H in formula (9).P (g) indicates the distribution on g, and g is the value of pixel.P (g) be value be g this
The number of pixel；If the probability distribution for the pixel that value is 125 is 10%, p (125)=10%=0.1；log(p
(g)) what is represented is the corresponding logarithm of the distribution, and usually taking 2 is bottom.
Find an optimal partition point X so that the entropy summation H1 of the 0~X and entropy summation H2 of X~255, have H1+H2 its
Value is maximum.Then point X is max-thresholds cut-point.
Use structural elementMorphological erosion VisablePic_Bool is carried out, to filter, then morphology again
It expands, go back original image, obtain filtering two-value picture VisablePic_Bool_Reduce；
White area in VisablePic_Bool_Reducel image checks the region in original image
Distribution of color in VisablePic [m], filters out the region for being unsatisfactory for flame color, obtains final doubtful flame characteristic figure
Piece VisablePic_Final；
The region that pixel point value in VisablePic_Final is 1 is flame characteristic.
The flame characteristic and infrared thermal imaging picture of doubtful flame characteristic picture overlap flame characteristic algorithm:
Each pixel storage in infrared thermal imaging picture IrPic, IrPic is obtained by infrared image sensor array 62
It is temperature value；IrPic binary conversion treatment is converted into binaryzation infrared thermal imaging by the threshold value using 300 ° of temperature as segmented image
Picture IrPic_Bool；VisablePic_Final is done and operation with each corresponding pixel of IrPic_Bool, obtains figure
Piece FirePic；
It (is indicated with operation with symbol &): 1&1=1,0&0=0,1&0=0
The pixel sum that the pixel value in FirePic is 1 is counted, Count_Fire is obtained；I.e. doubtful flame characteristic figure
The picture related coefficient of piece and binaryzation infrared thermal imaging picture.Count_Fire is greater than empirical value and is then identified as flame.Through
The 10% of pixel sum of a picture can be taken by testing threshold value.
After cloud platform 9 receives fire alarm text information, fire alarm notice is pushed to user at the first time, calls short message
Gateway interface 91 sends warning information to user terminal, and believes according to reporting information to position the fire behavior band of position in GIS map
Breath executes 9 early warning of cloud platform.After cloud platform 9 has received image data, defers to specific protocol and carry out data parsing, carry out visible
The superposition of light image and infrared thermal imaging, complete on visible images mark flare shape, size, flame zone temperature,
The arithmetic operations such as fire location, and image is called to push interface 92, pictorial information is pushed into client terminal, while being shown in cloud
Alarm detector position in the GIS map of platform 9.Finally it should be noted that: those skilled in the art can be to this
Invention is modified and modification, if these modifications and variations belong to the claims in the present invention and its equivalent technologies range it
It is interior, it is considered as protection scope of the present invention.
Claims (3)
1. a kind of flame detector, it is characterised in that: including MCU Main Processing Unit (1), which is connected with integrated
Infra red flame sensor (2), the integrated infra red flame sensor (2) are integrated with the first flame infrared sensor cell, the second fire
Flame infrared sensor cell, human-body infrared sensing unit and background are infrared with reference to sensing unit；
The MCU Main Processing Unit (1) is also connected with environment parameter sensing unit (5), and the environment parameter sensing unit (5) is used for
Acquire Atmosphere temp.and RH, illuminance and uitraviolet intensity signal；
MCU Main Processing Unit (1) obtains the infra red flame signal of integrated infra red flame sensor (2), and combining environmental parameter sensing is single
The illuminance signal of first (5) carries out flame infrared identification；MCU Main Processing Unit (1) is also connected with NB-IoT wireless communication unit
(7)；
The MCU Main Processing Unit (1) is also connected with ultraviolet flame sensor (4) through ultraviolet Acquisition Circuit (3)；MCU Main Processing Unit
(1) the uitraviolet intensity signal for obtaining the signal combining environmental parameter sensing unit (5) of ultraviolet flame sensor (4) carries out flame
Signal confirmation；
Further include light energy collection unit (8), is directly MCU Main Processing Unit after light energy collection unit (8) converts light energy into electric energy
(1) it powers, light energy collection unit (8) is integrated infra red flame sensor (2), ultraviolet Acquisition Circuit by Power Management Unit (81)
(3), environment parameter sensing unit (5), NB-IoT wireless communication unit (7) power supply；
MCU Main Processing Unit (1) controls Power Management Unit (81) power supply；
The ultraviolet Acquisition Circuit (3) includes Ultraviolet sensor circuit and interference cancellation circuit (31), Ultraviolet sensor circuit warp
Interference cancellation circuit (31) is connected with MCU Main Processing Unit (1)；
The Ultraviolet sensor circuit is provided with TPS65552A module, the end Vcc of TPS65552A module and after connecing its end VBAT
It connects Power Management Unit (81), the end the PGND ground connection of TPS65552A module, the end CHG of TPS65552A module is also through resistance
The end Vcc of R64 connection TPS65552A module；The end I-PEAK of TPS65552A module is through upper divider resistance R61 connection
The end Vcc of TPS65552A module, the end I-PEAK of TPS65552A module are also grounded through lower divider resistance R62；TPS65552A mould
Vcc end of the end F-ON of block through resistance R63 connection TPS65552A module；
The end XIFULL of TPS65552A module is successively grounded through resistance R66, resistance R67 and adjustable resistance RSEL；
One end of the end the SW connection transformer TR1 input coil of TPS65552A module, the other end of transformer TR1 input coil
One end of resistance R65 is connected, the other end of resistance R65 is grounded through capacitor C62；One end connection two of transformer TR1 output winding
The anode of pole pipe D61, the anode of the cathode connection electrolytic capacitor C63 of diode D61, the cathode of electrolytic capacitor C63 simultaneously connect transformation
It is grounded after the other end of device TR1 output winding；The anode of electrolytic capacitor C63 is also connected with one end of ultraviolet flame sensor (4), purple
The other end of outer flame sensor (4) is grounded through resistance R70；
The anode of electrolytic capacitor C63 is also connected with one end of resistance R68, and the other end of resistance R68 is through capacitor C64 connection transformer
One end of TR2 input coil, one end of the other end connection transformer TR2 output winding of transformer TR2 input coil, transformer
The other end of other end connection ultraviolet flame sensor (4) of TR2 output winding；
The other end of resistance R68 is also connected with the collector of switch transistor T 61, and the emitter of switch transistor T 61 is grounded, switch transistor T 61
Base stage connects the end G-IGBT of TPS65552A module, and the other end of ultraviolet flame sensor (4) is also connected with the anode of diode D62,
The collector of the cathode connection switch pipe T61 of diode D62, the other end of ultraviolet flame sensor (4) are also connected with capacitor C65's
One end, the other end of capacitor C65 is through the cathode of resistance R69 connection diode D62；
The other end of ultraviolet flame sensor (4) is also connected with the non-inverting input terminal of integrated transporting discharging U8, and integrated transporting discharging U8's is same mutually defeated
Enter end to be also grounded through capacitor C66, the inverting input terminal of integrated transporting discharging U8 is connected through resistance R71 with Power Management Unit (81), collection
It is also grounded through resistance R72 at the inverting input terminal of amplifier U8, the output end of integrated transporting discharging U8 is connected with interference cancellation circuit (31)；
The interference cancellation circuit (31) includes CD4017 counter, output end and the CD4017 counter of integrated transporting discharging U8
The end CLOCK is connected, and the end Q2 of CD4017 counter is connected with the base stage of switch transistor T 64, and the collector of switch transistor T 64 connects MCU
First ultraviolet collection terminal of main control unit (1), the emitter ground connection of switch transistor T 64；
The end Q5 of CD4017 counter is connected with the base stage of switch transistor T 63, and the collector of switch transistor T 63 connects MCU Main Processing Unit
(1) the ultraviolet collection terminal of second, the emitter ground connection of switch transistor T 63；The end Q5 of CD4017 counter also with CD4017 counter
The end CLOCK-IN be connected.
2. a kind of recognition methods of flame detector is used for flame detector described in claim 1, which is characterized in that including
Following steps,
Step A1, MCU Main Processing Unit (1) controls integrated infra red flame sensor (2) and is powered；
Step A2, MCU Main Processing Unit (1) enters dormant state；
Step A3, the interrupt signal that MCU Main Processing Unit (1) obtains integrated infra red flame sensor (2) wakes up；
Step A4, MCU Main Processing Unit (1) obtains the number of the first flame infrared sensor cell of integrated infra red flame sensor (2)
According to Ch_fire1 [i], the data Ch_fire2 [i] of the second flame infrared sensor cell, human-body infrared sensing unit data Ch_
Interference [i] and the infrared data Ch_background [i] with reference to sensing unit of background；
Step A5, MCU Main Processing Unit (1) obtains illuminance information Light [n] by environment parameter sensing unit (5)；
Step A6, MCU Main Processing Unit (1) is respectively by data Ch_fire1 [i], the second flame of the first flame infrared sensor cell
The data Ch_fire2 [i] of infrared sensor cell carries out Fourier transform, respectively obtain Fourier transform results FFt_fire1 and
FFt_fire2 respectively unites to Fourier transform results FFt_fire1 and FFt_fire2 using frequency domain distribution statistical function
Meter, respectively obtains statistical result Sta_fire1 and Sta_fire2；
Step A7, MCU Main Processing Unit (1) judges whether statistical result Sta_fire1 and Sta_fire2 have the basic frequency of flame
Rate feature, if do not had, return step A2；A8 is entered step if had；
Step A8, MCU Main Processing Unit (1) determines infrared channel correlation coefficient threshold y by illuminance information Light [n]3；
Step A9, MCU Main Processing Unit (1) acquires the correlation coefficient ρ of Ch_fire1 [i] Yu Ch_interference [i]1, Ch_
The correlation coefficient ρ of fire1 [i] and Ch_background [i]2, Ch_fire2 [i] is related to Ch_interference's [i]
Coefficient ρ3, the correlation coefficient ρ of Ch_fire2 [i] and Ch_background [i]4；
Step A10, MCU Main Processing Unit (1) is if judgement correlation coefficient ρ1, correlation coefficient ρ2, correlation coefficient ρ3, correlation coefficient ρ4It is complete small
In infrared correlation coefficient threshold y3；Then first flame identification result is flare up fire, and first flame identification result is passed through NB-
IoT wireless communication unit (7) uploads or further takes the ultraviolet identification of flame, otherwise return step A2.
3. a kind of recognition methods of flame detector according to claim 2, which is characterized in that flame it is ultraviolet identification include
Following steps:
Step B1, MCU Main Processing Unit (1) obtains the UV intensity UV of environment by environment parameter sensing unit (5)；
Step B2, MCU Main Processing Unit (1) determines the recognition threshold UV_ of flame Ultraviolet sensor (4) according to UV intensity UV
Threshold；
Step B3, MCU Main Processing Unit (1) opens flame Ultraviolet sensor (4), obtains ultraviolet pulse frequency UV_Count；
Step B4, MCU Main Processing Unit (1) is if judgement ultraviolet pulse frequency UV_Count is higher than recognition threshold UV_Threshold
Then secondary flame confirmation result is flare up fire, and secondary flame is confirmed that result is uploaded by NB-IoT wireless communication unit (7),
Otherwise return step A2.
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| CN113570810A (en) * | 2021-07-16 | 2021-10-29 | 无锡格林通安全装备有限公司 | Hydrogen flame detection method and device |
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| CN102426753B (en) * | 2011-11-21 | 2013-07-17 | 上海大学 | Infrared multiparameter fire and gas detector |
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