CN110045599A - A kind of electronic cigarette smog quality and flow control system and control method - Google Patents
A kind of electronic cigarette smog quality and flow control system and control method Download PDFInfo
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- CN110045599A CN110045599A CN201910467993.6A CN201910467993A CN110045599A CN 110045599 A CN110045599 A CN 110045599A CN 201910467993 A CN201910467993 A CN 201910467993A CN 110045599 A CN110045599 A CN 110045599A
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- 239000003571 electronic cigarette Substances 0.000 title claims abstract description 39
- 238000000034 method Methods 0.000 title claims abstract description 20
- 238000001514 detection method Methods 0.000 claims abstract description 41
- 230000036541 health Effects 0.000 claims abstract description 29
- 238000010438 heat treatment Methods 0.000 claims abstract description 28
- 238000012544 monitoring process Methods 0.000 claims abstract description 21
- 239000000779 smoke Substances 0.000 claims abstract description 13
- 238000013528 artificial neural network Methods 0.000 claims description 60
- 238000012549 training Methods 0.000 claims description 36
- 238000012360 testing method Methods 0.000 claims description 21
- 230000008569 process Effects 0.000 claims description 7
- 239000000446 fuel Substances 0.000 claims description 2
- 230000004044 response Effects 0.000 abstract description 5
- 230000008901 benefit Effects 0.000 abstract description 4
- 235000019659 mouth feeling Nutrition 0.000 abstract description 3
- 239000007789 gas Substances 0.000 description 26
- 241000208125 Nicotiana Species 0.000 description 16
- 235000002637 Nicotiana tabacum Nutrition 0.000 description 16
- 235000019504 cigarettes Nutrition 0.000 description 11
- 230000000391 smoking effect Effects 0.000 description 6
- 230000005611 electricity Effects 0.000 description 5
- 230000001276 controlling effect Effects 0.000 description 4
- 239000000443 aerosol Substances 0.000 description 3
- 239000000919 ceramic Substances 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- 239000003595 mist Substances 0.000 description 3
- 229920000742 Cotton Polymers 0.000 description 2
- 238000000889 atomisation Methods 0.000 description 2
- 238000009841 combustion method Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005265 energy consumption Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000012372 quality testing Methods 0.000 description 2
- 241000241602 Gossypianthus Species 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 239000000306 component Substances 0.000 description 1
- 239000008358 core component Substances 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000009123 feedback regulation Effects 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 239000003292 glue Substances 0.000 description 1
- 230000005802 health problem Effects 0.000 description 1
- 238000001727 in vivo Methods 0.000 description 1
- 230000006698 induction Effects 0.000 description 1
- 230000003434 inspiratory effect Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 210000005036 nerve Anatomy 0.000 description 1
- 230000000644 propagated effect Effects 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 238000011897 real-time detection Methods 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000000192 social effect Effects 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
- G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
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Abstract
The present invention provides a kind of electronic cigarette smog quality and flow control system and control method, including flow detection module, smog quality detection module, health monitoring module, active feeding means, smog generator, controller；Controller forms active feeding means voltage control signal according to acquisition data and smog generator adjusts operating voltage signal, and controls power management module and export relevant voltage to active feeding means and smog generator respectively.Present invention uses precision height, the MEMS flow sensor of fast-response, it can be quickly detected the actual air-breathing speed of user, the flow of gas in system is monitored in real time, real demand of the precise positioning to user, it is deployed by control circuit actively to oil mass and heating power come real-time control smoke generation, the mouth feeling experience preferably most met is brought to user, possesses very high economic benefits.
Description
Technical field
The present invention relates to electronic cigarette technical field, specifically a kind of electronic cigarette smog quality and flow control system and
Control method.
Background technique
Conditional electronic cigarette generally realizes the base of electronic cigarette using electret (ECM) diaphragm and control chip of induction negative pressure
This function.In existing structure, one negative pressure cavity is set in electret near modules, when people's air-breathing, close to the suction nozzle of negative pressure cavity
Negative pressure can be nearby generated, electret diaphragm passes through the generation for controlling chip controls smog after detecting this negative pressure.Except this it
Outside, there are also electronic cigarettes replaces traditional electret diaphragm, when the wearer inhales the air, electronics smoke chamber by using MEMS baroceptor
Pressure difference is formed with outside in vivo, MEMS baroceptor controls the generation of smog by detection draught head.
Electronic smoke atomizer is the core component of electronic cigarette, and tobacco tar is heated in this place, and it is molten to become misty gas
Glue is sucked by cigarette holder by smoker, to reach the process of simulation smoking, obtains the experience similar with cigarette is taken out.Existing quotient
There are mainly two types of atomization cores: the first be it is most common with circular metal heating wire or heating sheet in conjunction with cotton, cotton
Flower is directly contacted with liquid tobacco tar, when heater strip energization, the tobacco tar high-temperature atomizing that is adsorbed on cotton；Second by porous
Ceramics and heating-wire are combined into a ceramic heating element, are directly immersed in tobacco tar, and ceramic heating after energization and tobacco tar are atomized.
All there are some problems for the above structure:
1, for using the electronic cigarette of electret (ECM) diaphragm, smoke generation can not be controlled according to user's actual need
Speed is generated with smog, quantitative amount of smoke can only be provided according to fixed gear, product stability is inadequate, and power consumption is high, uses the registered permanent residence
Feel poor；For using the electronic cigarette of MEMS baroceptor, it at high cost, precision is low, and it is true can not accurately to react user
Real smog demand, poor controllability, response is slower, and power consumption is higher, and user experience is general.
2, conditional electronic cigarette can only regulate and control the amount of smoke of generation, can not detect the smog quality of smog generator generation,
The optimal smog of quality can not be generated, best mouthfeel can not be obtained so as to cause user, while also increasing energy consumption, be unfavorable for saving
The about energy.
3, it the heating power of smog generator and is unable to get to oil mass and is effectively matched control, it is possible that heating
Power is excessively high and the problem of oil supply dry combustion method problem not in time or heating power can not enough provide best in quality smog.
4, conditional electronic cigarette can only use the mode of passive oil supply, can not active control oil supply, oil supply rate limitation cigarette
The speed and quality that mist generates, can not bring best mouthfeel to user.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of electronic cigarette smog quality and flow control systems, realize electronics
The function of cigarette heating voltage, oil supply voltage real-time monitoring.
The present invention solves above-mentioned technical problem by the following technical programs:
A kind of electronic cigarette smog quality and flow control system, including
Flow detection module, for acquiring smog flow and exporting smog data on flows；
Smog quality detection module, for acquiring smog quality and exporting smog qualitative data；
Active feeding means is used for smog generator fuel feeding；
Smog generator carries out heating to oil smoke and generates smog；
Controller receives smog data on flows, smog qualitative data, and smog flow sum in the statistical unit time, right
Smog data on flows, smog qualitative data, smog flow sum is handled in the unit time, forms active feeding means voltage
Control signal and smog generator and adjust operating voltage signal, and control power management module respectively to active feeding means and
Smog generator exports relevant voltage；
Power management module is produced to flow detection module, smog quality detection module, active feeding means, smog respectively
Generating apparatus power supply.
Preferably, the flow detection module is MEMS flow sensor, is preset with single flow preset value；The MEMS
The smog data on flows currently acquired is compared by flow sensor with single flow preset value, and it is default to be greater than single flow
Value, then be sent to the controller for the smog data on flows.
Preferably, after the controller receives smog data on flows for the first time, power management module is controlled to smog matter
Measure detection module, active feeding means, smog generator power supply.
Preferably, the controller includes health monitoring module, and health monitoring module is preset with alarm preset value, health prison
It surveys module and is compared smog flow sum in the unit time with alarm preset value, if more than alarm preset value, then issue tune
Whole operating voltage signal and alarm signal, controller is according to adjustment operating voltage signal control power supply management module respectively to actively
Feeding means and smog generator output voltage.
Preferably, the controller is using target BP neural network trained in advance to smog data on flows, smog quality
Data, healthy data on flows are fitted, and obtain the control voltage of flow detection module and smog quality detection module.
Preferably, the training process of the target BP neural network are as follows: according to smog data on flows, smog qualitative data,
Healthy data on flows constructs sample set, and the sample set is divided into training set and test set；
The BP neural network constructed in advance using training set training, until convergence；And use test set test convergence
Whether the accuracy rate of BP neural network afterwards, the BP neural network after judging convergence is more than or equal to preset threshold, if so, will
BP neural network after the convergence is as target BP neural network；If it is not, the power that parameter in the BP neural network will be adjusted
Weight and hyper parameter, and return and execute the BP neural network constructed in advance using training set training, until convergence.
Present invention is alternatively directed to above-mentioned control systems to provide a kind of electronic cigarette smog quality and flow control methods, including following
Step:
Acquisition smog flow simultaneously exports smog data on flows；
Acquisition smog quality simultaneously exports smog qualitative data；
Smog flow sum forms healthy data on flows in the statistical unit time；
Smog data on flows, smog qualitative data, healthy data on flows are handled, active feeding means voltage is formed
Control signal and smog generator voltage control signal；
According to active feeding means voltage control signal and smog generator voltage control signal adjustment active oil supply dress
It sets with smog generator to piezoelectric voltage.
Preferably, the acquisition of smog data on flows is carried out using MEMS flow sensor, the MEMS flow sensor is pre-
Equipped with single flow preset value；The MEMS flow sensor is by the smog data on flows currently acquired and single flow preset value
It is compared, is greater than single flow preset value, then the smog data on flows is sent to the controller.
Preferably, controller using target BP neural network trained in advance to smog data on flows, smog qualitative data,
Healthy data on flows is fitted, and obtains the adjustment operating voltage signal of flow detection module and smog quality detection module.
Preferably, the training process of the target BP neural network are as follows: according to smog data on flows, smog qualitative data,
Healthy data on flows constructs sample set, and the sample set is divided into training set and test set；
The BP neural network constructed in advance using training set training, until convergence；And use test set test convergence
Whether the accuracy rate of BP neural network afterwards, the BP neural network after judging convergence is more than or equal to preset threshold, if so, will
BP neural network after the convergence is as target BP neural network；If it is not, the power that parameter in the BP neural network will be adjusted
Weight and hyper parameter, and return and execute the BP neural network constructed in advance using training set training, until convergence.
The present invention has the advantages that
1. the present invention is used cooperatively by flow detection module and smog quality detection module, control unit is realized
Heating power and active are automatically controlled with grade smog quality detection module testing result according to flow detection module testing result
To the function of oil mass, control circuit is truly realized to the real-time measure and control of system, is truly realized system intelligent, according to
Actual demand controls heating power and to oil mass, makes to can achieve optimal matching status between the two, avoids the occurrence of heating
Power is excessively high and oil supply dry combustion method problem not in time or heating power can not enough provide the key problem of best in quality smog, together
When it is of the invention low in energy consumption, cruising ability is strong, can be energy saving, there is good social effect.
2. the present invention realizes control unit and flexibly controls compared with conditional electronic cigarette can only use the mode of passive oil supply
Active oil supply, the amount of oil supply and time can accurately control according to the result that control circuit algorithm exports.
3. compared with traditional electronic cigarette, present invention uses precision high, fast-response MEMS flow sensor, it can be with
It is quickly detected the actual air-breathing speed of user, the flow of gas in system is monitored in real time, precise positioning to use
The real demand of person is deployed actively to oil mass and heating power come real-time control smoke generation by control circuit, is given
User brings the mouth feeling experience preferably most met, possesses very high economic benefits, and far superior to conditional electronic cigarette only has several grades
Fixed heating power, and can only hand shift working method.A flow threshold has also been devised simultaneously, avoids normal stream
Amount fluctuation bring error.
4. present invention uses smog quality detection sensors, it can generate dress to smog compared with conditional electronic cigarette
The aerosol gases for setting generation carry out quality testing, and control unit to heating power and can give oil mass according to this testing result
Feedback control is carried out, guarantee reaches optimal adaptation between the two, can export the smog of best in quality, guarantee user most
Good mouthfeel.
5. being previously written a neural network algorithm in the present invention, weighted value is according to sensor actual characteristic by not
Disconnected experiment obtains, and operation time is short, and fitting accuracy is high, can be under the premise of guaranteeing smog quality, and the fastest generation is most
Meet the smog of user's demand.
6. the present invention devises a health monitoring module, by being counted to the flow that user sucks, when a certain
When time statistic is more than reasonable value, which will export a respective handling as a result, regulating and controlling to system, maximum possible
Protection user health.
7. the present invention devises operating voltage feed circuit, can stable each section according to the actual situation operating voltage,
So that whole system has more stable heating atomization effect.
8. it is small in size, facilitate extension to design, manufacturing cost is low.
Detailed description of the invention
Fig. 1 is the overall structure block diagram of control system in the embodiment of the present invention 1；
Fig. 2 is the controling circuit structure figure of controller in the embodiment of the present invention 1；
Fig. 3 is the control principle block diagram of control system in the embodiment of the present invention 1；
Fig. 4 is target BP neural network structure chart in the embodiment of the present invention 1；
Fig. 5 is the structural schematic diagram of electronic cigarette in the embodiment of the present invention 2.
Specific embodiment
The effect of to make to structure feature of the invention and being reached, has a better understanding and awareness, to preferable
Examples and drawings cooperation detailed description, is described as follows:
Embodiment 1
As shown in Figure 1, a kind of electronic cigarette smog quality and flow control system, including
Flow detection module, the present embodiment uses MEMS flow sensor, for acquiring smog flow and exporting smog stream
Measure data；MEMS flow sensor is preset with single flow preset value；The smog flow that MEMS flow sensor will be acquired currently
Data are compared with single flow preset value, are greater than single flow preset value, then the smog data on flows are sent to control
Device, to screen the misinformation of data caused by the transient causes such as electronic cigarette weak vibrations.
The present embodiment has used MEMS flow sensor instead of traditional electret diaphragm and baroceptor.MEMS
Flow sensor can accurately measure the flow velocity of air in cavity.When the wearer inhales the air, the air in electronic cigarette cavity can produce
Raw flowing, the variation of air velocity can be perceived by MEMS flow sensor, and subsequent MEMS flow sensor can be subtle by these
Variation be converted to the electrical signal that can be identified by signal controller, and be transferred to signal controller.
Control system initial start stage, controller for the first time receive smog data on flows after, control power management module to
Smog quality detection module, active feeding means, smog generator power supply, control system formally enter working condition.
Smog quality detection module, the present embodiment uses MEMS gas sensor, for acquiring smog quality and exporting cigarette
Mist qualitative data.MEMS gas sensor is preset with quality preset value, and MEMS gas sensor is by the current smog quality of acquisition
Data are compared with quality preset value, when being less than preset value, then send the data to controller.When user starts to smoke
When, MEMS gas sensor passes through specific gas such as CO in detection gas2Concentration come detect generate aerosol gases quality,
And the concentration perceived is converted to the electrical signal that can be identified by signal controller, and be transferred to controller.
As shown in Fig. 2, controller includes control circuit and single-chip microcontroller.Control circuit includes:
Bridge measuring circuit is connect with MEMS flow sensor output end, the electricity for exporting MEMS flow sensor
Resistance variable signal is changed into analog voltage signal, specifically: R1, R2 and MEMS flow sensor constitute a bridge measurement electricity
Road forms a Hui Sidun bridge circuit by two fixed resistances and fixed voltage, and R5 constitutes MEMS gas sensor
Partial pressure measuring circuit.Filter circuit, R3, C1, R4, C2 and R6, C3 constitute three filter circuits, with bridge measuring circuit
Output end connection simply filters leading portion measurement output valve, avoids noise jamming.Output connection ADS1115 chip, carries out
For analog signal to the conversion of digital signal, last digital signal is transferred to single-chip microcontroller by iic bus.Have in power management module
Multiple low pressure difference linear voltage regulator chips are powered for cell voltage to be switched to suitable voltage to each section；Power management module
Voltage output is carried out according to MCU Instruction, gives MEMS flow sensor, MEMS gas sensor, smog generator, active
Feeding means power supply.Wherein in power management module in include an operational amplifier, and resistance R7, R8 constitute a voltage negative
Feed circuit, it is whether normal for detecting smog generator working condition, suitable heating power is maintained, and result is fed back
To control circuit.
Single-chip microcontroller is for controlling whole system, wherein be previously written a health monitoring module, when statistical unit
The smog flow sum of interior sucking is protected to the greatest extent for intervening the smoking capacity in user's stipulated time
The health of user.A target BP neural network algorithm is also written simultaneously, for according to smog data on flows, smog quality
Data, the smog flow sum of unit time are fitted, and obtain the control of flow detection module and smog quality detection module
Voltage is realized and carries out rationally effective control to system.
Health monitoring module is received for smog flow sum in the statistical unit time.Health monitoring module is preset with report
Smog flow sum in unit time is compared with alarm preset value, if more than alarm preset value, then issues by alert preset value
Operating voltage signal and alarm signal are adjusted, single-chip microcontroller is according to adjustment operating voltage signal control power supply management module respectively to master
The output voltage of dynamic feeding means and smog generator.For intervening the smoking capacity in user's stipulated time, most
The health of the protection user of big degree.
As shown in figure 4, the training process of target BP neural network are as follows: according to smog data on flows, smog qualitative data, be good for
Health data on flows constructs sample set, and sample set is divided into training set and test set；
The target BP neural network constructed in advance using training set training, until convergence；And use test set test convergence
Whether the accuracy rate of BP neural network afterwards, the BP neural network after judging convergence is more than or equal to preset threshold, if so, will
BP neural network after convergence is as target BP neural network；If it is not, the weight of parameter in BP neural network will be adjusted and surpassed
Parameter, and the BP neural network for executing and constructing in advance using training set training is returned, until convergence.
In the present embodiment, active feeding means 25 is micro- oil pump, is controlled circuit control and carries out active oil suction.Smog produces
Generating apparatus 26 is atomizer, and the oil suction chamber of atomizer is connected to micro- 25 oil outlet of oil pump.
As shown in figure 3, the control system control principle of the present embodiment are as follows: control system includes that there are three closed-loop controls:
First of all for the influence for avoiding air velocity from fluctuating, bad user experience is brought, only when MEMS flow sensing
When the smog data on flows that device 21 detects is greater than single flow preset value, just it is considered that user has begun air-breathing, avoids
Interference wrong report.Hereafter single-chip microcontroller perceives rapidly this variation, and control power management module 27 adjusts active feeding means, smog produces
The voltage of generating apparatus, while health monitoring module and smog mass sensor are started to work, other two closed-loop start-up.
For the closed loop of health monitoring module, control circuit, can be by discharge record to phase after recognizing effective discharge
The register answered, when certain time period user sucks the smog of too many flow, alarm system starting can input corresponding place
Reason mode regulates and controls operating voltage to single-chip microcontroller.
For the closed loop of smog quality testing, when there is smog generation, smog mass sensor will be measured in real time, when
When detected value is unsatisfactory for the requirement of best in quality, control circuit can to active feeding means and smog generator work electricity
Pressure is controlled.At the same time, MEMS flow sensor continues working, and is measured in real time to air mass flow in system, monolithic
Machine can carry out algorithm fitting with the output of in summary three closed loops, carry out precisely in real time to the operating voltage of system components
Control, so that system work in optimum state, under the premise of guaranteeing smog quality, generates rapidly the cigarette for meeting user's demand
Mist amount, while electricity and tobacco tar amount can be saved.
The target BP neural network algorithm being previously written in single-chip microcontroller is as shown in Figure 4:
In this algorithm, there are three signals to input: smog data on flows, smog qualitative data, healthy data on flows.3
After data input, neural network computing is carried out, L1 is input layer, and L2 to Ln is hidden layer, and algorithm first will be counted according to preset value
It is propagated forward to hidden layer according to from input layer, is fitted, obtains one two output as a result, hereafter again reversely being passed result
It broadcasts, calculates and obtain error with three input values, preset value is adjusted, is iterated, optimal output valve: active oil supply is obtained
Device voltage and smog generator voltage.In this algorithm, a typical two output nerves network algorithm has been used, it
Weight preset value needs constantly tested according to the actual characteristic of MEMS flow sensor and smog quality detection sensor
It is fitted to obtain, there is very strong specific aim, Riming time of algorithm can be reduced, improve processing result accuracy, nothing rapidly
Method replicates easily.
In specific works, when the first air-breathing of user, MEMS flow sensor 21 is responded rapidly to, and bridge measuring circuit is surveyed
The variation of MEMS flow sensor is measured, this analog voltage change transitions is to believe convenient for the number of transmission by ADS1115 chip
Number, subsequent single-chip microcontroller controls the tobacco tar that active feeding means actively draws matching result according to MEMS flow sensor response results
The tobacco tar accommodating chamber into smog generator is measured, subsequent to generate corresponding smog, MEMS gas sensor is started to work, and detection is originally
The secondary quality for generating smog, and by measuring circuit and signal conversion circuit, transfers data to single-chip microcontroller, first air-breathing with
System can be operated completely afterwards, MEMS flow sensor, MEMS gas sensor and the health prison being preset in control circuit
Module is surveyed to start to work at the same time.When user's air-breathing again, MEMS flow sensor can will be passed when the flow information of time air-breathing
Defeated to arrive single-chip microcontroller, single-chip microcontroller judges that this inspiratory flow reaches when being pre-designed threshold value rather than airwaves, will by this
Actual flow value is stored in specified registers, is overlapped to flow value, when the value does not meet presetting for health monitoring module
It is required that when, health monitoring module can generate respective handling signal.Meanwhile single-chip microcontroller ought time air-breathing MEMS flow sensor generation
Flow information, previous MEMS gas sensor generate quality information and health monitoring module processing signal be input to it is pre-
In the target BP neural network algorithm being first written, by being fitted three input values, obtain most accurately handling knot rapidly
Fruit, controller controls power management module according to algorithm response result and is adjusted to system rapidly later, such as when regulation
After interior flow summation value is more than the preset value of health monitoring module, in order to guarantee the health of user, single-chip microcontroller can be according to
Ratio carries out quantitative scaling to oil mass to heating voltage and unit time, and smog is reduced under the premise of guaranteeing smog quality and is produced
Raw amount, while will start LED light 13 and dodging different color lights, to remind user to pay attention to health problem；In addition to this, work as electricity
When sub- cigarette working condition meets the requirement of health monitoring module, electronic cigarette starts to work normally, if user increases air-breathing dynamics,
Then MEMS flow sensor can perceive rapidly this variation, while MEMS gas sensor can detect rapidly the matter for generating smog
Amount, single-chip microcontroller can be fitted according to this result, and heating voltage is accurately tuned up according to fitting result and to oil mass, is being guaranteed
The amount of smoke for meeting user's demand is generated rapidly under the premise of generating smog quality；When the unexpected osculum air-breathing of user,
MEMS flow sensor can perceive rapidly this variation, while MEMS gas sensor can detect rapidly the quality for generating smog,
Single-chip microcontroller can be fitted according to this result, accurately turned heating voltage down according to fitting result and to oil mass, guaranteed to produce
The amount of smoke for meeting user's demand is generated rapidly under the premise of raw smog quality, while can save electric energy and tobacco tar, institute
With due to having used MEMS flow sensor and MEMS gas sensor to carry out whole real-time detection to system simultaneously, and
The neural network algorithm that inside is previously written avoids so that heating power and actively giving oil mass available optimal matching
There is the insufficient interference problem of the excessively high oil supply of heating power and the problem of heating power can not enough provide quality best smog,
So that system is more intelligent, user can obtain optimal mouth feeling experience, while can save electric energy, tobacco tar, have very high
Social value and economic value.In addition to this, in order to guarantee that smog generator and active feeding means operating voltage are steady
Fixed, power management module carries out feedback regulation by a feed circuit, maintains stable operating voltage so that actively give oil mass with
Heating power reaches best match, generates the amount of smoke for being most able to satisfy user's demand rapidly.
The present embodiment also provides a kind of electronic cigarette smog quality and flow control methods, comprising the following steps:
The acquisition of smog data on flows is first carried out using MEMS flow sensor, MEMS flow sensor is preset with single stream
Measure preset value；The smog data on flows currently acquired is compared by MEMS flow sensor with single flow preset value, is greater than
The smog data on flows is then sent to controller by single flow preset value；
Controller for the first time receive smog data on flows after, control power management module to smog quality detection module,
Active feeding means, smog generator power supply, system formally start；
Smog quality is acquired using MEMS gas sensor and exports smog qualitative data, MEMS gas sensor can be examined
Survey the quality that smog generator generates smog.When user starts smoking, MEMS gas sensor passes through in detection gas
The concentration of specific gas such as CO2 generates the quality of aerosol gases to detect, and the concentration perceived is converted to can be by signal
The electrical signal of controller identification, and it is transferred to controller；
Controller includes control circuit and single-chip microcontroller.Control circuit includes bridge measuring circuit, with MEMS flow sensor
Output end connection, the resistance variations signal for exporting MEMS flow sensor are changed into analog voltage signal, specifically:
R1, R2 and MEMS flow sensor constitute a bridge measuring circuit, are made up of two fixed resistances and fixed voltage
One Hui Sidun bridge circuit, R5 constitute the partial pressure measuring circuit of MEMS gas sensor.Filter circuit, R3, C1, R4, C2
And R6, C3 constitute three filter circuits, connect with bridge measuring circuit output end, carry out to leading portion measurement output valve simple
Filtering, avoids noise jamming.Output connection ADS1115 chip carries out the conversion of analog signal to digital signal, last number letter
Number single-chip microcontroller is transferred to by iic bus.There are multiple low pressure difference linear voltage regulator chips in power management module, is used for battery
Voltage switchs to suitable voltage and powers to each section；Power management module carries out voltage output according to MCU Instruction, flows to MEMS
Quantity sensor, MEMS gas sensor, smog generator, the power supply of active feeding means.Wherein middle packet in power management module
An operational amplifier is included, constitutes a voltage negative feedback circuit with resistance R7, R8, for detecting smog generator work shape
Whether state is normal, maintains suitable heating power, and result is fed back to control circuit.
Single-chip microcontroller is for controlling whole system, wherein be previously written a health monitoring module, when statistical unit
The smog flow sum of interior sucking is protected to the greatest extent for intervening the smoking capacity in user's stipulated time
The health of user.A target BP neural network algorithm is also written simultaneously, for according to smog data on flows, smog quality
Data, the smog flow sum of unit time are fitted, and obtain the control of flow detection module and smog quality detection module
Voltage is realized and carries out rationally effective control to system.
Health monitoring module, for smog flow sum in the statistical unit time.It is pre- that health monitoring module is preset with alarm
If value, smog flow sum in the unit time is compared with alarm preset value, if more than alarm preset value, then issues adjustment
Operating voltage signal and alarm signal, single-chip microcontroller is according to adjustment operating voltage signal control power supply management module respectively to actively giving
The output voltage of oily device and smog generator.For intervening the smoking capacity in user's stipulated time, maximum journey
The health of the protection user of degree.
The training process of target BP neural network are as follows: according to smog data on flows, smog qualitative data, healthy flow number
According to, building sample set, and sample set is divided into training set and test set；
The target BP neural network constructed in advance using training set training, until convergence；And use test set test convergence
Whether the accuracy rate of BP neural network afterwards, the BP neural network after judging convergence is more than or equal to preset threshold, if so, will
BP neural network after convergence is as target BP neural network；If it is not, the weight of parameter in BP neural network will be adjusted and surpassed
Parameter, and the BP neural network for executing and constructing in advance using training set training is returned, until convergence.
Embodiment 2
As shown in figure 5, present embodiments providing a kind of electronic cigarette using above-mentioned control system, including a tobacco rod cavity
11, cigarette holder 12 is arranged in one end of the tobacco rod cavity 11, in the tobacco rod cavity 11 at the close cigarette holder 12 described in setting
MEMS flow sensor 21 and smog quality detection sensor 22.It wherein, include an active feeding means in tobacco rod cavity 11
25 1 smog generators 26 and circuit.Active feeding means 25 and smog generator 26 connect.
Further include LED indication device 13, is set to one end on the tobacco rod cavity 11 far from the cigarette holder 12.For showing
Show whether electronic cigarette is opened, while can be used for showing alarm.
In above-mentioned technical proposal, tobacco rod cavity 11 can be used with the connection type of cigarette holder 12 and be threadedly coupled, such good
It is in can more easily carry out the assembling of electronic cigarette and disassemble and maintain, time cost can be saved.
The basic principles, main features and advantages of the present invention have been shown and described above.The technology of the industry
Personnel are it should be appreciated that the present invention is not limited to the above embodiments, and what is described in the above embodiment and the description is only the present invention
Principle, various changes and improvements may be made to the invention without departing from the spirit and scope of the present invention, these variation and
Improvement is both fallen in the range of claimed invention.The present invention claims protection scope by appended claims and its
Equivalent defines.
Claims (10)
1. a kind of electronic cigarette smog quality and flow control system, it is characterised in that: including
Flow detection module, for acquiring smog flow and exporting smog data on flows；
Smog quality detection module, for acquiring smog quality and exporting smog qualitative data；
Active feeding means is used for smog generator fuel feeding；
Smog generator carries out heating to oil smoke and generates smog；
Controller receives smog data on flows, smog qualitative data, and smog flow sum in the statistical unit time, to smog
Data on flows, smog qualitative data, smog flow sum is handled in the unit time, forms the control of active feeding means voltage
Signal and smog generator adjust operating voltage signal, and control power management module respectively to active feeding means and smog
Generation device exports relevant voltage；
Power management module generates dress to flow detection module, smog quality detection module, active feeding means, smog respectively
Set power supply.
2. a kind of electronic cigarette smog quality according to claim 1 and flow control system, it is characterised in that: the flow
Detection module is MEMS flow sensor, is preset with single flow preset value；The MEMS flow sensor will be acquired currently
Smog data on flows is compared with single flow preset value, is greater than single flow preset value, then is sent out the smog data on flows
Give the controller.
3. a kind of electronic cigarette smog quality according to claim 2 and flow control system, it is characterised in that: the control
Device for the first time receive smog data on flows after, control power management module to smog quality detection module, active feeding means,
Smog generator power supply.
4. a kind of electronic cigarette smog quality according to claim 2 and flow control system, it is characterised in that: the control
Device includes health monitoring module, and health monitoring module is preset with alarm preset value, and health monitoring module is by smog in the unit time
Flow sum is compared with alarm preset value, if more than alarm preset value, then issues adjustment operating voltage signal and alarm signal
Number, controller is according to adjustment operating voltage signal control power supply management module respectively to active feeding means and smog generator
Output voltage.
5. a kind of electronic cigarette smog quality according to any one of claims 1 to 4 and flow control system, it is characterised in that:
The controller is using target BP neural network trained in advance to smog data on flows, smog qualitative data, healthy flow number
According to being fitted, the control voltage of flow detection module and smog quality detection module is obtained.
6. a kind of electronic cigarette smog quality according to claim 5 and flow control system, it is characterised in that: the target
The training process of BP neural network are as follows: according to smog data on flows, smog qualitative data, healthy data on flows, construct sample set
It closes, and the sample set is divided into training set and test set；
The BP neural network constructed in advance using training set training, until convergence；And after being restrained using test set test
Whether the accuracy rate of BP neural network, the BP neural network after judging convergence is more than or equal to preset threshold, if so, will be described
BP neural network after convergence is as target BP neural network；If it is not, by the weight for adjusting parameter in the BP neural network with
And hyper parameter, and return and execute the BP neural network constructed in advance using training set training, until convergence.
7. a kind of electronic cigarette smog quality and flow control methods, it is characterised in that: the following steps are included:
Acquisition smog flow simultaneously exports smog data on flows；
Acquisition smog quality simultaneously exports smog qualitative data；
Smog flow sum forms healthy data on flows in the statistical unit time；
Smog data on flows, smog qualitative data, healthy data on flows are handled, the control of active feeding means voltage is formed
Signal and smog generator voltage control signal；
According to active feeding means voltage control signal and smog generator voltage control signal adjustment active feeding means and
Smog generator gives piezoelectric voltage.
8. a kind of electronic cigarette smog quality according to claim 7 and flow control methods, it is characterised in that: use MEMS
Flow sensor carries out the acquisition of smog data on flows, and the MEMS flow sensor is preset with single flow preset value；It is described
The smog data on flows currently acquired is compared by MEMS flow sensor with single flow preset value, and it is pre- to be greater than single flow
If value, then be sent to the controller for the smog data on flows.
9. a kind of electronic cigarette smog quality according to claim 7 or 8 and flow control methods, it is characterised in that: control
Device intends smog data on flows, smog qualitative data, healthy data on flows using target BP neural network trained in advance
It closes, obtains the adjustment operating voltage signal of flow detection module and smog quality detection module.
10. a kind of electronic cigarette smog quality according to claim 9 and flow control methods, it is characterised in that: the mesh
Mark the training process of BP neural network are as follows: according to smog data on flows, smog qualitative data, healthy data on flows, construct sample
Set, and the sample set is divided into training set and test set；
The BP neural network constructed in advance using training set training, until convergence；And after being restrained using test set test
Whether the accuracy rate of BP neural network, the BP neural network after judging convergence is more than or equal to preset threshold, if so, will be described
BP neural network after convergence is as target BP neural network；If it is not, by the weight for adjusting parameter in the BP neural network with
And hyper parameter, and return and execute the BP neural network constructed in advance using training set training, until convergence.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110710728A (en) * | 2019-09-24 | 2020-01-21 | 河南中烟工业有限责任公司 | Tobacco product smelling equipment, heating and smoke discharging method of smelling equipment and using method |
| CN111406992A (en) * | 2019-09-26 | 2020-07-14 | 深圳市艾维普思科技有限公司 | Control method of electronic cigarette, storage medium and electronic cigarette |
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| CN113974231A (en) * | 2021-11-04 | 2022-01-28 | 歌尔微电子股份有限公司 | Electronic cigarette use control method and device and electronic cigarette |
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| CN115067576A (en) * | 2021-09-07 | 2022-09-20 | 深圳市驰泰电子科技有限公司 | Electronic cigarette based on MEMS |
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| WO2024021144A1 (en) * | 2022-07-26 | 2024-02-01 | 陈嘉豪 | Heating efficiency adjustment and control method and system based on vapor amount of electronic cigarette |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140332016A1 (en) * | 2011-10-28 | 2014-11-13 | Evolv, Llc | Electronic vaporizer that simulates smoking with power control |
| CN108135268A (en) * | 2015-09-28 | 2018-06-08 | 尼科创业控股有限公司 | Electronics steam provides system |
| CN207639684U (en) * | 2017-12-14 | 2018-07-24 | 深圳市中联华成数字技术有限公司 | A kind of new electronic cigarette device with flow sensor unit |
| US20180325183A1 (en) * | 2015-03-05 | 2018-11-15 | Wisenstech Ltd. | Smart Electronic Vaporizer |
| CN109259330A (en) * | 2018-11-07 | 2019-01-25 | 上海小魅科技有限公司 | Electronic cigarette system, control method, electronic cigarette and storage medium |
-
2019
- 2019-05-31 CN CN201910467993.6A patent/CN110045599A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140332016A1 (en) * | 2011-10-28 | 2014-11-13 | Evolv, Llc | Electronic vaporizer that simulates smoking with power control |
| US20180325183A1 (en) * | 2015-03-05 | 2018-11-15 | Wisenstech Ltd. | Smart Electronic Vaporizer |
| CN108135268A (en) * | 2015-09-28 | 2018-06-08 | 尼科创业控股有限公司 | Electronics steam provides system |
| CN207639684U (en) * | 2017-12-14 | 2018-07-24 | 深圳市中联华成数字技术有限公司 | A kind of new electronic cigarette device with flow sensor unit |
| CN109259330A (en) * | 2018-11-07 | 2019-01-25 | 上海小魅科技有限公司 | Electronic cigarette system, control method, electronic cigarette and storage medium |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110710728A (en) * | 2019-09-24 | 2020-01-21 | 河南中烟工业有限责任公司 | Tobacco product smelling equipment, heating and smoke discharging method of smelling equipment and using method |
| CN111406992A (en) * | 2019-09-26 | 2020-07-14 | 深圳市艾维普思科技有限公司 | Control method of electronic cigarette, storage medium and electronic cigarette |
| CN111406992B (en) * | 2019-09-26 | 2023-07-04 | 深圳市艾维普思科技有限公司 | Control method of electronic cigarette, storage medium and electronic cigarette |
| CN112906875B (en) * | 2021-04-29 | 2021-07-27 | 常州高凯电子有限公司 | Control system and method for precise gas flow valve |
| CN112906875A (en) * | 2021-04-29 | 2021-06-04 | 常州高凯电子有限公司 | Control system and method for precise gas flow valve |
| CN113287798A (en) * | 2021-06-25 | 2021-08-24 | 湖北中烟工业有限责任公司 | Method and device for adjusting smoking concentration of heating non-combustible cigarette and electronic equipment |
| CN115067576A (en) * | 2021-09-07 | 2022-09-20 | 深圳市驰泰电子科技有限公司 | Electronic cigarette based on MEMS |
| CN113974231A (en) * | 2021-11-04 | 2022-01-28 | 歌尔微电子股份有限公司 | Electronic cigarette use control method and device and electronic cigarette |
| CN114299688A (en) * | 2021-12-29 | 2022-04-08 | 张璇燕 | Tobacco tar component identification method and system based on electronic smoke detection |
| CN114299688B (en) * | 2021-12-29 | 2023-08-08 | 深圳市希格莱特科技有限公司 | Tobacco tar component identification method and system based on electronic smoke detection |
| CN114226955A (en) * | 2022-01-11 | 2022-03-25 | 武汉点金激光科技有限公司 | A laser processing robot control system with safety protection function |
| WO2024021144A1 (en) * | 2022-07-26 | 2024-02-01 | 陈嘉豪 | Heating efficiency adjustment and control method and system based on vapor amount of electronic cigarette |
| CN116542161A (en) * | 2023-05-22 | 2023-08-04 | 王从和 | Electronic cigarette atomizer service life analysis method |
| CN116542161B (en) * | 2023-05-22 | 2024-01-05 | 深圳市品锐科技有限公司 | Electronic cigarette atomizer service life analysis method |
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Application publication date: 20190723 |