CN105388187B - The test method of the semiconductor gas sensor of controlled humidity - Google Patents
The test method of the semiconductor gas sensor of controlled humidity Download PDFInfo
- Publication number
- CN105388187B CN105388187B CN201510778949.9A CN201510778949A CN105388187B CN 105388187 B CN105388187 B CN 105388187B CN 201510778949 A CN201510778949 A CN 201510778949A CN 105388187 B CN105388187 B CN 105388187B
- Authority
- CN
- China
- Prior art keywords
- gas
- humidity
- sensor
- testing
- gas sensor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 239000004065 semiconductor Substances 0.000 title claims abstract description 50
- 238000010998 test method Methods 0.000 title abstract description 4
- 238000012360 testing method Methods 0.000 claims abstract description 126
- WSFSSNUMVMOOMR-UHFFFAOYSA-N Formaldehyde Chemical compound O=C WSFSSNUMVMOOMR-UHFFFAOYSA-N 0.000 claims abstract description 33
- 238000001514 detection method Methods 0.000 claims abstract description 24
- 239000007789 gas Substances 0.000 claims description 242
- 238000000034 method Methods 0.000 claims description 45
- 238000012545 processing Methods 0.000 claims description 34
- 230000004044 response Effects 0.000 claims description 27
- 238000013528 artificial neural network Methods 0.000 claims description 24
- 238000010438 heat treatment Methods 0.000 claims description 22
- UHOVQNZJYSORNB-UHFFFAOYSA-N Benzene Chemical compound C1=CC=CC=C1 UHOVQNZJYSORNB-UHFFFAOYSA-N 0.000 claims description 21
- 238000005070 sampling Methods 0.000 claims description 20
- 238000012549 training Methods 0.000 claims description 20
- 230000008569 process Effects 0.000 claims description 16
- 210000002569 neuron Anatomy 0.000 claims description 15
- 230000008859 change Effects 0.000 claims description 14
- 238000005259 measurement Methods 0.000 claims description 13
- 239000012159 carrier gas Substances 0.000 claims description 10
- QGZKDVFQNNGYKY-UHFFFAOYSA-N Ammonia Chemical compound N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 claims description 8
- 238000009826 distribution Methods 0.000 claims description 7
- 210000002364 input neuron Anatomy 0.000 claims description 6
- 238000010606 normalization Methods 0.000 claims description 6
- 210000004205 output neuron Anatomy 0.000 claims description 6
- 238000007619 statistical method Methods 0.000 claims description 6
- 238000001035 drying Methods 0.000 claims description 5
- 238000003491 array Methods 0.000 claims description 4
- 238000007405 data analysis Methods 0.000 claims description 4
- WSFSSNUMVMOOMR-NJFSPNSNSA-N methanone Chemical compound O=[14CH2] WSFSSNUMVMOOMR-NJFSPNSNSA-N 0.000 claims description 4
- 238000002156 mixing Methods 0.000 claims description 4
- 238000012544 monitoring process Methods 0.000 claims description 4
- 238000004451 qualitative analysis Methods 0.000 claims description 4
- 238000004868 gas analysis Methods 0.000 claims description 3
- 239000011521 glass Substances 0.000 claims description 3
- 238000004445 quantitative analysis Methods 0.000 claims description 3
- 238000007791 dehumidification Methods 0.000 description 11
- 230000006870 function Effects 0.000 description 11
- 238000010586 diagram Methods 0.000 description 9
- 238000005516 engineering process Methods 0.000 description 9
- 238000011160 research Methods 0.000 description 8
- 239000000919 ceramic Substances 0.000 description 7
- 230000035945 sensitivity Effects 0.000 description 7
- 230000001276 controlling effect Effects 0.000 description 6
- 238000011161 development Methods 0.000 description 6
- 238000004519 manufacturing process Methods 0.000 description 6
- 239000000463 material Substances 0.000 description 6
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 6
- 238000005273 aeration Methods 0.000 description 4
- 238000002474 experimental method Methods 0.000 description 4
- 230000003993 interaction Effects 0.000 description 4
- 230000008520 organization Effects 0.000 description 4
- 239000002244 precipitate Substances 0.000 description 4
- XOLBLPGZBRYERU-UHFFFAOYSA-N SnO2 Inorganic materials O=[Sn]=O XOLBLPGZBRYERU-UHFFFAOYSA-N 0.000 description 3
- 229910021627 Tin(IV) chloride Inorganic materials 0.000 description 3
- YXFVVABEGXRONW-UHFFFAOYSA-N Toluene Chemical compound CC1=CC=CC=C1 YXFVVABEGXRONW-UHFFFAOYSA-N 0.000 description 3
- 230000009471 action Effects 0.000 description 3
- KRKNYBCHXYNGOX-UHFFFAOYSA-N citric acid Chemical compound OC(=O)CC(O)(C(O)=O)CC(O)=O KRKNYBCHXYNGOX-UHFFFAOYSA-N 0.000 description 3
- 230000007547 defect Effects 0.000 description 3
- 238000002347 injection Methods 0.000 description 3
- 239000007924 injection Substances 0.000 description 3
- 229910052751 metal Inorganic materials 0.000 description 3
- 239000002184 metal Substances 0.000 description 3
- 239000002994 raw material Substances 0.000 description 3
- 230000001105 regulatory effect Effects 0.000 description 3
- VHUUQVKOLVNVRT-UHFFFAOYSA-N Ammonium hydroxide Chemical compound [NH4+].[OH-] VHUUQVKOLVNVRT-UHFFFAOYSA-N 0.000 description 2
- 235000011114 ammonium hydroxide Nutrition 0.000 description 2
- 238000004140 cleaning Methods 0.000 description 2
- 239000013256 coordination polymer Substances 0.000 description 2
- 238000013075 data extraction Methods 0.000 description 2
- 238000013500 data storage Methods 0.000 description 2
- 239000008367 deionised water Substances 0.000 description 2
- 229910021641 deionized water Inorganic materials 0.000 description 2
- 230000009699 differential effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000001704 evaporation Methods 0.000 description 2
- 230000008020 evaporation Effects 0.000 description 2
- 238000010304 firing Methods 0.000 description 2
- 238000003780 insertion Methods 0.000 description 2
- 230000037431 insertion Effects 0.000 description 2
- 238000007639 printing Methods 0.000 description 2
- 238000005057 refrigeration Methods 0.000 description 2
- 239000000243 solution Substances 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 238000003756 stirring Methods 0.000 description 2
- 239000000758 substrate Substances 0.000 description 2
- HPGGPRDJHPYFRM-UHFFFAOYSA-J tin(iv) chloride Chemical compound Cl[Sn](Cl)(Cl)Cl HPGGPRDJHPYFRM-UHFFFAOYSA-J 0.000 description 2
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 description 1
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 description 1
- 238000012356 Product development Methods 0.000 description 1
- 238000007605 air drying Methods 0.000 description 1
- 229910021529 ammonia Inorganic materials 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000009529 body temperature measurement Methods 0.000 description 1
- 229910002091 carbon monoxide Inorganic materials 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 230000008014 freezing Effects 0.000 description 1
- 238000007710 freezing Methods 0.000 description 1
- 238000000227 grinding Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000011031 large-scale manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 229910000623 nickel–chromium alloy Inorganic materials 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 238000001556 precipitation Methods 0.000 description 1
- 239000012716 precipitator Substances 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 239000000047 product Substances 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 238000007634 remodeling Methods 0.000 description 1
- 239000002002 slurry Substances 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 231100000331 toxic Toxicity 0.000 description 1
- 230000002588 toxic effect Effects 0.000 description 1
- 238000005303 weighing Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
- G01N27/04—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance
- G01N27/12—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance of a solid body in dependence upon absorption of a fluid; of a solid body in dependence upon reaction with a fluid, for detecting components in the fluid
- G01N27/125—Composition of the body, e.g. the composition of its sensitive layer
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
- G01N27/04—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance
- G01N27/12—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance of a solid body in dependence upon absorption of a fluid; of a solid body in dependence upon reaction with a fluid, for detecting components in the fluid
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F3/00—Air-conditioning systems in which conditioned primary air is supplied from one or more central stations to distributing units in the rooms or spaces where it may receive secondary treatment; Apparatus specially designed for such systems
- F24F3/12—Air-conditioning systems in which conditioned primary air is supplied from one or more central stations to distributing units in the rooms or spaces where it may receive secondary treatment; Apparatus specially designed for such systems characterised by the treatment of the air otherwise than by heating and cooling
- F24F3/14—Air-conditioning systems in which conditioned primary air is supplied from one or more central stations to distributing units in the rooms or spaces where it may receive secondary treatment; Apparatus specially designed for such systems characterised by the treatment of the air otherwise than by heating and cooling by humidification; by dehumidification
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D22/00—Control of humidity
- G05D22/02—Control of humidity characterised by the use of electric means
Landscapes
- Chemical & Material Sciences (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- Electrochemistry (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Health & Medical Sciences (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Investigating Or Analyzing Materials By The Use Of Fluid Adsorption Or Reactions (AREA)
- Investigating Or Analyzing Materials By The Use Of Electric Means (AREA)
Abstract
The test method of the semiconductor gas sensor of controlled humidity belongs to element test field, and the test method for solving the problems, such as existing formaldehyde gas sensor is incomplete, and the problem that humid control precision is low, technical essential are:Have:Semiconductor gas sensor tests the step of system buildup is with test, a kind of humidity control system has been used in the step, including master controller, moisture detection sensor, dehumidifier, ultrasonic humidifier and buzzer, wherein, moisture detection sensor, dehumidifier and ultrasonic humidifier are installed in gas chamber, and master controller is connect with moisture detection sensor, dehumidifier, ultrasonic humidifier, buzzer respectively.The invention enables the test for formaldehyde gas sensor is more perfect, and improve the controllability and control accuracy of humidity.
Description
Technical Field
The invention belongs to the field of element test, and particularly relates to a method for testing a humidity-controllable semiconductor gas-sensitive element.
Background
While the development of semiconductor gas sensor technology is well-established, the development of semiconductor gas sensor testing technology has not kept pace with the development of gas sensor technology. Human awareness and remodeling activities of the objective world are often based on testing efforts. The engineering test technology is an emerging technology which utilizes a modern test means to detect, test and analyze various signals in engineering, particularly dynamic physical signals changing along with time, and extracts useful information from the signals. The measured and analyzed results objectively describe the state, change and characteristics of the research object and provide reliable basis for further modification and control of the research object. Also, advances in sensor technology have not been made without any improvement in the means of testing. At present, an important factor limiting the research progress and the large-scale production of the semiconductor gas sensor is that the detection means is backward, the test environment is complex, the test efficiency and the precision are low, and meanwhile, complete parameters and curves of various characteristics of the gas sensor cannot be obtained due to the lack of perfect test equipment, and the further research and application of the semiconductor gas sensor are also limited, so that a perfect semiconductor gas sensor performance parameter test system is urgently needed for both production and scientific research.
Because of the practical significance of semiconductor gas sensors and the importance of gas sensor testing, researchers at home and abroad carry out a great deal of intensive research work on the testing systems of semiconductor gas sensors, and the researchers build the testing systems of semiconductor gas sensors with different functions in different modes, thereby playing an important role in the development of sensor performance testing and calibration technology. The automatic test system is designed by scholars of foreign L.Harvey, G.s.v., coles, Hildegard D.Jander, Wolfgang Gottler and the like, can test the gas sensor in pure air, single gas and mixed gas, and simultaneously considers the influence of environmental temperature and humidity on performance parameters, but a plurality of operations need to be carried out manually, so that a tester cannot be far away from a toxic test environment, the automation degree of the tester needs to be further improved, the types of parameters capable of being tested are few, and the shape of the tested semiconductor gas sensor is limited; the domestic scholars such as Tuoyu, Pengzhi and Lin Yongbing also develop a set of automatic test system in turn, integrate a test chamber and a detection system into a whole, and provide reliable data for new product development, but the degree of automation is not high enough, the acquired parameters are single, the used hardware is excessive, the reliability is not high, various pure gases are difficult to mix in the high dynamic and low concentration range, and the required concentration and precision requirements are difficult to meet. There are also difficulties in achieving inspection and grading of gas sensors. Many manufacturers mainly use manual testing, have low testing efficiency and low precision, and are far from meeting the requirements of production development, and more importantly, the manual testing cannot realize dynamic measurement, so that some parameters of the gas sensitive element, such as a response time curve, a recovery time curve and the like, cannot be accurately measured. The defect that complete parameters of various characteristics of the gas sensor cannot be obtained limits further research and application of the gas sensor. In order to meet the requirements of enterprise production and research, the development of the gas sensor needs a complete set of complete testing system.
In the process of developing the semiconductor gas sensor, the gas response characteristics of the sensor under different environments and working conditions need to be researched, the quality of the sensor is measured, and the optimal working state is found out in summary, so that good testing equipment cannot be used.
At present, two test modes of static state and gas flow are used for researching the gas response characteristics of a semiconductor gas sensor, the sensor is installed in a gas chamber, certain gas with known concentration is injected into the gas chamber, and the gas-sensitive response characteristics of the sensor to the gas can be obtained by collecting the response signals of the sensor. In general, a system for performing static tests adopts a closed large-capacity gas chamber, and sample gas is injected and uniformly mixed in a container to form test gas with a certain volume. The gas flow mode is that gas flow with constant flow is introduced into a gas chamber with smaller capacity, sample gas with certain concentration is passed through in a time period, and sensor response data in the time period is collected. In the mode, because the gas chamber is small, the time for cleaning residual gas is short, the sensor device can be quickly recovered to the initial state, repeated experiments can be quickly carried out, and the method is particularly favorable for researching the gas-sensitive characteristic of the sensor array.
Disclosure of Invention
In order to solve the technical problems and accurately control the humidity in the testing process, the invention provides a testing method of a humidity-controllable semiconductor gas sensitive element.
The technical scheme adopted by the invention is as follows: a method for testing a humidity-controllable semiconductor gas sensor comprises:
the method comprises the steps of constructing and testing a semiconductor gas sensor testing system, and analyzing the performance of the semiconductor gas sensor testing system and a semiconductor gas sensitive element; wherein,
the step of building and testing the gas sensor testing system is provided with a step of controlling the humidity of the gas chamber, a humidity control system is used in the step, and the humidity control system comprises a main controller, a humidity detection sensor, a dehumidifier, an ultrasonic humidifier and a buzzer, wherein the humidity detection sensor, the dehumidifier and the ultrasonic humidifier are installed in the gas chamber, and the main controller is respectively connected with the humidity detection sensor, the dehumidifier, the ultrasonic humidifier and the buzzer.
Furthermore, in the step of building and testing the semiconductor gas sensor test system, the semiconductor gas sensor test system is used for dynamically distributing different gases under given concentration and enabling the multiple sensor arrays to monitor the change of the surface conductivity of the gas sensitive element in real time when the gases are introduced;
the semiconductor gas sensor test system includes: the system comprises a sample feeding device for automatically carrying out sample gas concentration proportioning, a gas sensor heating and temperature measuring device, a signal measuring and data collecting circuit for coordinating with the sample feeding device and automatically collecting 4-6 paths of gas sensor measuring signals under different gas sample environments, and a data processing circuit for carrying out data processing on the collected measuring signals; and a temperature compensation circuit for compensating for temperature variations caused by changes in the intake process and room temperature;
the gas sensor array is arranged in the gas chamber, the change of the gas concentration measured by the gas sensor is the change of the gas in the gas chamber, and the gas chamber is a dry organic glass chamber with a smooth inner cavity and a square approximate shape;
the gas sensor heating and temperature measuring device heats the gas sensitive element and measures the working temperature of the gas sensor in real time; when the working temperature of the sensor changes due to the influence of the ambient temperature or the airflow, the temperature compensation circuit carries out temperature compensation control in real time so as to keep the working temperature of the sensor unchanged; the signal measurement and data acquisition circuit is used for adjusting and AD sampling signals, the signal adjustment is used for converting the response of the gas sensor to a test gas sample into an electric signal, the AD sampling is used for converting an analog signal into a digital signal through the data processing circuit, and the acquired 4-6 paths of sensor signals are converted into standard signals required by a BP neural network through normalization processing;
the standard gas sample output is divided into two paths or multiple paths, each path is controlled by a mass flow controller and is connected into a testing device, carrier gas and gas to be tested enter a drying tank to be fully mixed under the control of the mass flow controller respectively to prepare a target testing gas sample and enter a testing cavity in the testing device, a gas sensor testing system distributes gas with set target concentration under the control of a computer, one or more target gas samples with standard concentration and standard carrier gas are proportioned according to the proportion and are introduced into a mixing channel to be fully mixed under the control of the mass flow controller, when the mixed testing gas sample is introduced into the testing cavity, 4-6 paths of response signals of a gas sensor array in a gas chamber are collected, and the obtained response information of the gas sensor array to the sample gas is transmitted to the computer for data processing and data analysis, carrying out test gas inlet, response signal acquisition and data processing in sequence; when the temperature monitoring system finds that the working temperature of the semiconductor gas sensitive element changes, the temperature compensation circuit compensates the working temperature of the element in real time, and adjusts the heating voltage of the resistance wire to keep the working temperature of the element unchanged;
the humidity detection sensor detects a humidity signal in the air chamber in real time and transmits the signal to the main controller, the main controller compares the humidity signal with a set value of the controller based on a constant humidity set value or a set humidity range in the air chamber, and the controller outputs a split-range control signal; when the humidity in the air chamber is lower than 10% RH and the humidifier is opened to the maximum, the system can not continue to humidify, or the humidity in the air chamber is higher than 60% RH and the dehumidifier is opened to the maximum, the main controller controls the buzzer to sound, calls the main controller to interrupt, stops signal output to the dehumidifier and the ultrasonic humidifier, and automatically cuts off the power supply and stops testing when the humidity exceeds 60% RH.
Further, the software part of the gas sensor testing system comprises a gas path control module, a voltage sampling module, a temperature compensation module, a data processing module and a display function module, wherein:
the gas circuit control module sets control parameters, wherein the parameters comprise pre-aeration time, post-aeration time, data sampling time interval, mixed gas types, various gas concentrations and carrier gas control voltage;
the voltage sampling module correspondingly controls the start of voltage sampling, the interruption of sampling and the end of sampling;
the data processing module is used for carrying out data acquisition, data storage, image printing and historical data extraction processing.
Further, the data acquisition module finishes data tracking acquisition in a sampling time interval, provided experimental data are automatically stored into six files with two formats after the experiment is finished, the six files are respectively the voltage, the resistance, the response sensitivity digital quantity and the dynamic change curve of a 4-6-path sensor, and simultaneously, the stored image is printed instantly and historical data is extracted according to time; and in the data acquisition process, displaying the dynamic change curves of the standard voltage, the resistance and the response sensitivity of the 4-6 sensors along with time in a display module according to different requirements in real time.
5. The method for testing a humidity-controlled semiconductor gas sensor as recited in claim 4, wherein the step of analyzing the gas sensor test system and the gas sensor performance comprises analyzing various errors of the gas sensor test system, analyzing sensitivity of a measuring resistor, a temperature characteristic of the resistor, a sensitivity-temperature characteristic, a sensitivity-concentration characteristic, and an influence of doping on the element performance.
Further, 4-6 road standard signals adopted by the sensor are subjected to data normalization processing, the data are processed into a BP neural network to obtain a required standard data source, and the BP neural network gas analysis is carried out according to the following steps:
quantitative analysis:
selecting a single formaldehyde gas to detect a sample, carrying out quantitative detection, forming a sensor array by 4-6 sensors to carry out quantitative identification on formaldehyde gas, ammonia gas, benzene and other mixed gases, wherein the number of input neurons of a neural network is 6, the number of output neurons of the neural network is 1, dynamically changing the number of hidden layers, and solving the corresponding training errors of the hidden layers to determine the optimal number of hidden layer neurons;
creating a two-layer network by using a newff function, setting the number of hidden layer neurons of the network as S (i), setting the range of S (i) to be 3-13, setting a training function of the network as Trainbr, setting the weight and the threshold of the network as random variables with special distribution, estimating the weight and the threshold of the network by using a statistical method, taking an input vector P as the input of the trained neural network, training the network by using a train function, and quantitatively detecting 30 groups of formaldehyde gases with different concentrations as the input to obtain the output result of quantitative detection and corresponding experimental errors;
and (3) qualitative analysis:
the method comprises the following steps that a sensor array consisting of 4-6 sensors qualitatively identifies characteristic quantities of formaldehyde, ammonia gas and benzene, the number of input neurons of a network is 6, the number of output neurons of the network is 3, the optimal hidden layer number is determined through error comparison, and the hidden layer number is dynamically changed;
creating a three-layer network by using a newff function, setting the neuron number of a hidden layer of the network as a dynamic variable S (i) with the range of 3-13, obtaining a group of neuron numbers with the minimum training error as the optimal neuron number through 10 times of training, setting the weight and threshold of the network as random variables with special distribution, and estimating the weight and threshold of the network by using a statistical method; training is stopped until experimental errors meet requirements; the odd group is used as the input of the trained neural network.
Further, humidity control system, still include the host computer, the host computer has man-machine interaction interface to human-machine interaction operation shows humidity set value and humidity measurement value in real time, main control unit is PLC, and uses PLC's PID adjusting module to carry out closed-loop control to the humidity in the air chamber.
Further, the method for controlling humidity by using the STEP 7 software comprises the following STEPs:
creating items and hardware configuration: firstly, entering a STEP 7 software interface, clicking a menu, creating a new item, clicking an item name on the left menu of a right button, clicking and inserting an S7-300 site, double clicking to open the inserted S7-300 site, double clicking to hardware of a right window, and performing hardware configuration on a popped hardware window;
configuration:
and finding the rack in the right frame, clicking the slot 2 after double-clicking the set rack, finding the CPU with the corresponding model in the right frame, and inserting the CPU into the slot 2 after double-clicking. Then double clicking the CPU, setting a corresponding subnet MPI in a pop-up window, and inserting the analog input module into the No. 4 slot in the same operation as inserting the CPU;
after all the hardware is inserted into the corresponding slots, clicking a shortcut key of 'save and compile' of the upper menu bar to complete the hardware configuration, and returning to the STEP 7 main interface to perform the next programming;
an OB1 organization block appears on a main interface after hardware configuration is completed, other needed organization blocks and logic blocks are added in a blank position, the insertion of an upper menu bar is clicked, an S7 module is clicked in a popped pull-down menu, and the module needed to be added is selected;
the programming method needed by each part control is as follows: the automatic control system comprises a manual automatic switch, a manual dehumidification start-stop, a manual humidification start-stop and a manual operation output, wherein an intermediate relay is used for simulating the opening and closing of a normally open and normally closed contact so as to achieve the purposes of control and self-locking, when the humidity is lower than 20% RH and higher than 40% RH, an alarm is given, an output coil is arranged with 1, a buzzer is enabled to whistle, a main program is interrupted, and all pulses sent to an external solid-state relay are stopped, namely, the dehumidification or humidification of a dehumidifier and an ultrasonic humidifier are realized;
the PID regulating module is used for carrying out closed-loop regulation on the humidity, and the closed-loop regulation is FB58 'TCONT _ CP', and is used for controlling a continuous humidity processing process or a humidity processing process with a pulse signal; calling the module can generate a background data block DB58, double-clicking a DB58 background data block of a main interface, clicking a viewing parameter, and observing data on a popped interface;
the method for setting the parameters of the FB58 module is as follows:
(1) PV _ IN is a set value of a controlled variable;
(2) SP _ INT is the actual value of the controlled variable and needs to input a humidity measured value;
(3) QPULSE is output pulse and is connected with an external solid-state relay;
the internal variable setting method comprises the following steps:
(1) the GAIN of the dehumidification calling module is set to be negative, the GAIN is set to be-4.0, and the GAIN value is positive in the humidifying part and the GAIN initial value is 2;
(2) PULSE _ ON turns ON the PULSE generator, which is activated when this value is changed from FALSE to true;
(3) TI integral action reset time, the initial value is 4.0S;
(4) the reset time of TD differential action is 1.0S as the initial value;
(5) TUN _ ON self-adjusts open, here changing the initial value FALSE to TURE;
(6) TUN _ ST initiates self-adjustment, where the initial value FALSE is changed to TURE.
Has the advantages that:
1. the invention can realize the distribution of common test gas in the conventional test concentration range with high precision; multiple sensors or gas sensor arrays can be tested simultaneously.
2. The invention can realize multi-parameter measurement: because the test system is modularized, a plurality of measurement modules can be connected at the same time, and each measurement module can realize multi-channel measurement, the simultaneous test of a plurality of kinds of parameters is easy to realize.
3. The invention prepares and tests the sensitive elements of various doping technologies, and makes the semiconductor gas sensitive element have progress in detecting volatile organic gases.
4. The invention realizes qualitative identification of various gases and quantitative identification of single gas by combining the gas sensor array with the artificial neural network technology and based on the BP algorithm.
5. The humidity control system provided by the invention can effectively perform control such as humidity sensing, dehumidification, humidification, humidity display, humidity alarm and the like on a humidity environment. The humidity can be effectively monitored and controlled, the test process is smoothly carried out, the humidity control in a closed environment within the humidity range of 10-60% RH is realized, the dehumidification effect is obvious, and the requirement on the humidity control during the test of the gas sensitive element is effectively met. And the invention sets the system to be powered off when the humidity of the air chamber exceeds 60% RH, aiming at ensuring that the test is carried out in a safe environment, and when the humidity exceeds 60% RH, the test system is in a dangerous state and is not suitable for the test experiment.
Drawings
FIG. 1 is a flowchart of a method of example 1 of the present invention;
FIG. 2 is a schematic diagram of a closed loop process of a semiconductor gas sensor test system according to embodiment 2 of the present invention;
fig. 3 is a block diagram showing the structure of a semiconductor gas sensor test system according to embodiment 2 of the present invention; (humidity control system has been added)
FIG. 4 is a software functional block diagram of embodiment 3 of the present invention;
FIG. 5 is a measurement circuit of a semiconductor gas sensor test system in embodiment 5 of the present invention;
FIG. 6.1 is a schematic diagram of the structure of the quantitatively identified BP neural network in embodiment 6 of the present invention;
FIG. 6.2 is a schematic diagram of the training process of the quantitative gas detection in example 6 of the present invention;
FIG. 6.3 is a diagram showing the structure of a qualitatively identified BP neural network in embodiment 6 of the present invention;
FIG. 6.4 is a diagram showing the result of the qualitative analysis training in example 6 of the present invention;
FIG. 7 is a schematic block diagram of a humidity control system according to the present invention;
FIG. 8 is a block diagram of a closed loop control system for the humidity control system of the present invention.
Detailed Description
Example 1:
a method for testing a humidity-controllable semiconductor gas sensor comprises: SnO2The method comprises the steps of preparing a gas sensitive material, manufacturing a gas sensitive element, building and testing a semiconductor gas sensor testing system, and analyzing the performance of the semiconductor gas sensor testing system and the semiconductor gas sensitive element.
The step of building and testing the gas sensor testing system is provided with a step of controlling the humidity of the gas chamber, a humidity control system is used in the step, and the humidity control system comprises a main controller, a humidity detection sensor, a dehumidifier, an ultrasonic humidifier and a buzzer, wherein the humidity detection sensor, the dehumidifier and the ultrasonic humidifier are installed in the gas chamber, and the main controller is respectively connected with the humidity detection sensor, the dehumidifier, the ultrasonic humidifier and the buzzer.
Example 2:
the technical scheme is the same as that of the embodiment 1, and more specifically comprises the following steps: SnO2The preparation method of the gas sensitive material comprises the following steps: with SnCl4·5H2Taking O as raw material and dilute ammonia water as precipitator, weighing a certain amount of SnCl4·5H2Dissolving O raw material in a proper amount of deionized water, adding a small amount of citric acid, stirring to completely dissolve the O raw material, and heating to boil for reaction; slowly dripping prepared diluted ammonia water into SnCl4Stirring in water solution, and heating until precipitation is completeWashing with water, centrifugally cleaning for many times to remove Cl & lt- & gt in the precipitate, drying the precipitate at 60-100 ℃, grinding the precipitate, and firing the ground precipitate in a muffle furnace at about 700 ℃ for 2-4 hours to obtain SnO2A gas sensitive material.
Example 3:
the technical scheme is the same as that of the embodiment 1 or 2, and more specifically comprises the following steps: in the manufacturing step of the gas sensor, the tube core of the sensor is provided with a capillary ceramic tube, a heating wire penetrates into the ceramic tube, a metal electrode is coated outside the ceramic tube to be used as a signal electrode for measuring the resistance of the sensor, and a gas-sensitive material SnO is coated outside the metal electrode2And firing to obtain the product;
the manufacturing steps are as follows: the ceramic tube substrate coated with metal electrodes at two ends is sequentially cleaned by toluene, alcohol and deionized water in an ultrasonic mode, ground slurry is coated on the surface of the ceramic tube after being dried under an infrared lamp, the ceramic tube substrate is dried under the infrared lamp and then sintered in a tubular resistance furnace, finally a heating wire with a proper resistance value penetrates into a burnt tube core, an electrode lead and a heating wire lead are welded on a tube seat of an element, a gas sensor is manufactured, and the gas sensor is manufactured by using the gas sensor.
The structure overcomes the defects of a direct heating element, avoids mutual interference between a measuring loop and a heating loop because the heating wire is not contacted with the gas sensitive material, greatly improves the consistency of the element performance and greatly improves the mechanical strength.
Example 4:
the technical scheme is the same as that of the embodiment 1, 2 or 3, and more specifically is as follows: in the step of building and testing the semiconductor gas sensor testing system, the semiconductor gas sensor testing system is used for dynamically distributing different gases under given concentration and enabling a plurality of sensor arrays to monitor the change of the surface conductivity of the gas sensitive element in real time when the gases are introduced;
the semiconductor gas sensor test system includes: the system comprises a sample feeding device for automatically carrying out sample gas concentration proportioning, a gas sensor heating and temperature measuring device, a signal measuring and data collecting circuit for coordinating with the sample feeding device and automatically collecting 4-6 paths of gas sensor measuring signals under different gas sample environments, and a data processing circuit for carrying out data processing on the collected measuring signals; and a temperature compensation circuit for compensating for temperature variations caused by changes in the intake process and room temperature; the coordination action with the sample injection device means that the signal acquisition and the sample injection are synchronous or corresponding, so that the coordination of the sample injection and the acquisition in time sequence can be realized.
The gas sensor array is arranged in the gas chamber, the change of the gas concentration measured by the gas sensor is the change of the gas in the gas chamber, and the gas chamber is a dry organic glass chamber with a smooth inner cavity and a square approximate shape;
the gas sensor heating and temperature measuring device heats the gas sensitive element and measures the working temperature of the gas sensor in real time; when the working temperature of the sensor changes due to the influence of the ambient temperature or the airflow, the temperature compensation circuit carries out temperature compensation control in real time so as to keep the working temperature of the sensor unchanged; the signal measurement and data acquisition circuit is used for adjusting and AD sampling signals, the signal adjustment is used for converting the response of the gas sensor to a test gas sample into an electric signal, the AD sampling is used for converting an analog signal into a digital signal through the data processing circuit, and the acquired 4-6 paths of sensor signals are converted into standard signals required by a BP neural network through normalization processing;
the humidity detection sensor detects a humidity signal in the air chamber in real time and transmits the signal to the main controller, the main controller compares the humidity signal with a set value of the controller based on a constant humidity set value or a set humidity range in the air chamber, and the controller outputs a split-range control signal; when the humidity in the air chamber is lower than 10% RH and the humidifier is opened to the maximum, the system can not continue to humidify, or the humidity in the air chamber is higher than 60% RH and the dehumidifier is opened to the maximum, the main controller controls the buzzer to sound, calls the main controller to interrupt, stops signal output to the dehumidifier and the ultrasonic humidifier, and automatically cuts off the power supply and stops testing when the humidity exceeds 60% RH.
Humidity control system, still include the host computer, the host computer has man-machine interaction interface to human-machine interaction operation shows humidity set value and humidity measurement value in real time, main control unit is PLC, and uses PLC's PID regulating module to carry out closed-loop control to the humidity in the air chamber.
Wherein: a Programmable Controller (Programmable Controller) is a member of the computer family, and is manufactured for industrial control applications, and an early Programmable Controller is called a Programmable Logic Controller (PLC), which is called PLC for short, and is mainly used to replace a relay to realize logic control. Although today's PLCs have long been able to perform more than just the task of logic control, they are still called PLCs by their habit, but they are called programmable controllers (PLC) by the name of Chinese. The embodiment uses the S7-300 PLC manufactured by Siemens company, belongs to a medium PLC, adopts a modular structure and has wide application range.
The humidity sensitive element is the simplest humidity sensor, the humidity sensitive element mainly comprises a resistance type humidity sensor and a capacitance type humidity sensor, the embodiment adopts an HM1500 humidity sensor, which belongs to the capacitance type humidity sensor, and particularly, the humidity sensitive element is a linear voltage output type integrated humidity sensor.
The methods of dehumidification are quite abundant, the most common being through-air drying. The more effective way of indoor dehumidification is to select different types of dehumidifiers, which are classified into a freezing dehumidifier, a rotary dehumidifier and an electro-osmotic dehumidifier due to different working principles. Most of household dehumidifiers are refrigeration type dehumidifiers, and the dehumidification method adopted by the embodiment belongs to the refrigeration type dehumidifier category.
The humidification mode is very abundant, and traditional humidification is sprayed water on the ground, utilizes the natural evaporation of moisture in order to reach the purpose that increases air humidity. Modern times mainly utilize humidifiers for humidification. The humidifier can be classified into an industrial use, a commercial use and a household use through different use ranges. Heat evaporation type humidifiers are commonly used in industry, and ultrasonic humidifiers are generally used commercially. Many home humidifiers choose pure type humidifiers. The embodiment adopts an ultrasonic humidifier, and the humidifying module mainly comprises a power supply unit (the same as the humidifying unit), an ultrasonic transducer, a water pool and a fan.
The method for controlling humidity by using STEP 7 software in this embodiment is as follows:
creating items and hardware configuration: firstly, entering a STEP 7 software interface, clicking a menu, creating a new item, clicking an item name on the left menu of a right button, clicking and inserting an S7-300 site, double clicking to open the inserted S7-300 site, double clicking to hardware of a right window, and performing hardware configuration on a popped hardware window;
configuration:
and finding the rack in the right frame, clicking the slot 2 after double-clicking the set rack, finding the CPU with the corresponding model in the right frame, and inserting the CPU into the slot 2 after double-clicking. Then double clicking the CPU, setting a corresponding subnet MPI in a pop-up window, and inserting the analog input module into the No. 4 slot in the same operation as inserting the CPU;
after all the hardware is inserted into the corresponding slots, clicking a shortcut key of 'save and compile' of the upper menu bar to complete the hardware configuration, and returning to the STEP 7 main interface to perform the next programming;
an OB1 organization block appears on a main interface after hardware configuration is completed, other needed organization blocks and logic blocks are added in a blank position, the insertion of an upper menu bar is clicked, an S7 module is clicked in a popped pull-down menu, and the module needed to be added is selected;
the programming method needed by each part control is as follows: the automatic control system comprises a manual automatic switch, a manual dehumidification start-stop, a manual humidification start-stop and a manual operation output, wherein an intermediate relay is used for simulating the opening and closing of a normally open and normally closed contact so as to achieve the purposes of control and self-locking, when the humidity is lower than 20% RH and higher than 40% RH, an alarm is given, an output coil is arranged with 1, a buzzer is enabled to whistle, a main program is interrupted, and all pulses sent to an external solid-state relay are stopped, namely, the dehumidification or humidification of a dehumidifier and an ultrasonic humidifier are realized;
the PID regulating module is used for carrying out closed-loop regulation on the humidity, and the closed-loop regulation is FB58 'TCONT _ CP', and is used for controlling a continuous humidity processing process or a humidity processing process with a pulse signal; calling the module can generate a background data block DB58, double-clicking a DB58 background data block of a main interface, clicking a viewing parameter, and observing data on a popped interface;
the method for setting the parameters of the FB58 module is as follows:
(1) PV _ IN is a set value of a controlled variable;
(2) SP _ INT is the actual value of the controlled variable and needs to input a humidity measured value;
(3) QPULSE is output pulse and is connected with an external solid-state relay;
the internal variable setting method comprises the following steps:
(7) the GAIN of the dehumidification calling module is set to be negative, the GAIN is set to be-4.0, and the GAIN value is positive in the humidifying part and the GAIN initial value is 2;
(8) PULSE _ ON turns ON the PULSE generator, which is activated when this value is changed from FALSE to true;
(9) TI integral action reset time, the initial value is 4.0S;
(10) the reset time of TD differential action is 1.0S as the initial value;
(11) TUN _ ON self-adjusts open, here changing the initial value FALSE to TURE;
(12) TUN _ ST initiates self-adjustment, where the initial value FALSE is changed to TURE.
During the testing process of the semiconductor gas sensitive element: the standard gas sample output is divided into two paths or multiple paths, each path is controlled by a mass flow controller and is connected into a testing device, carrier gas and gas to be tested enter a drying tank to be fully mixed under the control of the mass flow controller respectively to prepare a target testing gas sample and enter a testing cavity in the testing device, a gas sensor testing system distributes gas with set target concentration under the control of a computer, one or more target gas samples with standard concentration and standard carrier gas are proportioned according to the proportion and are introduced into a mixing channel to be fully mixed under the control of the mass flow controller, when the mixed testing gas sample is introduced into the testing cavity, 4-6 paths of response signals of a gas sensor array in a gas chamber are collected, and the obtained response information of the gas sensor array to the sample gas is transmitted to the computer for data processing and data analysis, carrying out test gas inlet, response signal acquisition and data processing in sequence; when the temperature monitoring system finds that the working temperature of the semiconductor gas sensitive element changes, the temperature compensation circuit compensates the working temperature of the element in real time, and the heating voltage of the resistance wire is adjusted to keep the working temperature of the element unchanged.
Wherein: because the working characteristics of the semiconductor gas sensitive element are related to the temperature, the semiconductor gas sensitive element needs to be heated, the working temperature of the gas sensitive element directly influences the sensitivity of the sensor, and meanwhile, the temperature sensor is needed to measure the working temperature of the gas sensor in real time, so that the testing system in the embodiment is provided with a gas sensor heating and temperature measuring device and a working temperature compensation circuit.
In the test, the heating resistance wire is selected to be nickel-chromium alloy, the resistance is 30 ohms, and the heating voltage is controlled by adopting a direct current power supply, so that the working temperature of the gas sensitive element is controlled. The thermocouple temperature sensor for measuring temperature detects the temperature of the surface of the ceramic tube, but the temperature is obtained by directly detecting the surface of the element through the thermocouple, the surface of the contact element has small surface area, the surface material is extremely easy to damage after being contacted, and the surface temperature of the element is reduced during temperature measurement, so that certain deviation is brought to measurement.
Heating voltage | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
Temperature (. degree.C.) | 26 | 55 | 89 | 137 | 179 | 225 | 268 | 302 | 343 | 377 | 416 |
The output of the standard gas sample is divided into two paths or multiple paths, each path is controlled by a mass flow controller and is connected into a testing device, carrier gas and gas to be tested (such as formaldehyde, ammonia, benzene, carbon monoxide, oxygen and the like) respectively enter a drying tank to be fully mixed under the control of the mass flow controller to be prepared into a testing gas sample and enter a testing cavity in the testing device, a gas sensor testing system distributes gas with set target concentration under the control of a computer, the target gas sample with one or more standard concentrations and the standard carrier gas are proportioned according to the proportion and are introduced into a mixing channel to be fully mixed under the control of the mass flow controller, when the mixed testing gas sample is introduced into a gas chamber, response signals of a gas sensor array in the gas chamber are collected, and the obtained response information of the gas sensor array to the sample gas is transmitted to the computer for data analysis, carrying out test gas inlet, response signal acquisition and data processing in sequence; when the temperature monitoring system finds that the working temperature of the semiconductor gas sensitive element changes, the temperature compensation circuit compensates the working temperature of the element in real time, and the heating voltage of the resistance wire is adjusted to keep the working temperature of the element unchanged. The method overcomes the defects that the traditional test method not only consumes excessive manpower, but also has a plurality of unstable factors due to manual operation, so that a large deviation value is added to the measurement.
In order to observe the response process visually, the corresponding application software on the computer is provided with a graphical interface and can display the response curve of the sensor array in real time.
Example 5:
the method has the same technical scheme as that of the embodiment 1, 2, 3 or 4, and more specifically comprises the following steps: the software part of the gas sensor testing system comprises a gas path control module, a voltage sampling module, a temperature compensation module, a data processing module and a display function module, wherein:
the gas circuit control module sets control parameters, wherein the parameters comprise pre-aeration time, post-aeration time, data sampling time interval, mixed gas types, various gas concentrations and carrier gas control voltage;
the voltage sampling module correspondingly controls the start of voltage sampling, the interruption of sampling and the end of sampling;
the data processing module is used for carrying out data acquisition, data storage, image printing and historical data extraction processing.
Example 6:
the method has the same technical scheme as that of the embodiment 1, 2, 3, 4 or 5, and more specifically comprises the following steps: the data acquisition module finishes data tracking acquisition in a sampling time interval, provided experimental data are automatically stored into six files with two formats after the experiment is finished, the six files are respectively the voltage, the resistance, the response sensitivity digital quantity and the dynamic change curve of a 4-6-path sensor, and simultaneously, the stored image is printed immediately and historical data is extracted in time; and in the data acquisition process, displaying the dynamic change curves of the standard voltage, the resistance and the response sensitivity of the 4-6 sensors along with time in a display module according to different requirements in real time.
Example 7:
the method has the same technical scheme as that of the embodiment 1, 2, 3, 4, 5 or 6, and more specifically comprises the following steps: the step of analyzing the performance of the gas sensor testing system and the gas sensitive element comprises the steps of analyzing various errors of the gas sensor testing system, analyzing the sensitivity, the resistance temperature characteristic, the sensitivity-temperature characteristic and the sensitivity-concentration characteristic of the measuring resistor and analyzing the influence of doping on the element performance.
Example 8:
the method has the same technical scheme as that of the embodiment 1, 2, 3, 4, 5, 6 or 7, and more specifically comprises the following steps: carrying out data normalization processing on 4-6 road standard signals adopted by the sensor, processing the data into a BP neural network to obtain a required standard data source, and carrying out BP neural network gas analysis according to the following steps:
quantitative analysis:
selecting a single formaldehyde gas to detect a sample, carrying out quantitative detection, forming a sensor array by 4-6 sensors to carry out quantitative identification on formaldehyde gas, ammonia gas, benzene and other mixed gases, wherein the number of input neurons of a neural network is 6, the number of output neurons of the neural network is 1, dynamically changing the number of hidden layers, and solving the corresponding training errors of the hidden layers to determine the optimal number of hidden layer neurons;
creating a two-layer network by using a newff function, setting the number of hidden layer neurons of the network as S (i), setting the range of S (i) to be 3-13, setting a training function of the network as Trainbr, setting the weight and the threshold of the network as random variables with special distribution, estimating the weight and the threshold of the network by using a statistical method, taking an input vector P as the input of the trained neural network, training the network by using a train function, and quantitatively detecting 30 groups of formaldehyde gases with different concentrations as the input to obtain the output result of quantitative detection and corresponding experimental errors;
and (3) qualitative analysis:
the method comprises the following steps that a sensor array consisting of 4-6 sensors qualitatively identifies characteristic quantities of formaldehyde, ammonia gas and benzene, the number of input neurons of a network is 6, the number of output neurons of the network is 3, the optimal hidden layer number is determined through error comparison, and the hidden layer number is dynamically changed;
creating a three-layer network by using a newff function, setting the neuron number of a hidden layer of the network as a dynamic variable S (i) with the range of 3-13, obtaining a group of neuron numbers with the minimum training error as the optimal neuron number through 10 times of training, setting the weight and threshold of the network as random variables with special distribution, and estimating the weight and threshold of the network by using a statistical method; training is stopped until experimental errors meet requirements; the odd group is used as the input of the trained neural network.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be able to cover the technical solutions and the inventive concepts of the present invention within the technical scope of the present invention.
Claims (1)
1. A method for testing a humidity-controllable semiconductor gas sensor, comprising:
the method comprises the steps of constructing and testing a semiconductor gas sensor testing system, and analyzing the performance of the semiconductor gas sensor testing system and a semiconductor gas sensitive element; wherein,
the step of building and testing the gas sensor testing system is provided with a step of controlling the humidity of the gas chamber, and a humidity control system is used in the step and comprises a main controller, a humidity detection sensor, a dehumidifier, an ultrasonic humidifier and a buzzer, wherein the humidity detection sensor, the dehumidifier and the ultrasonic humidifier are arranged in the gas chamber, and the main controller is respectively connected with the humidity detection sensor, the dehumidifier, the ultrasonic humidifier and the buzzer;
in the step of building and testing the semiconductor gas sensor testing system, the semiconductor gas sensor testing system is used for dynamically distributing different gases under given concentration and enabling a plurality of sensor arrays to monitor the change of the surface conductivity of the gas sensitive element in real time when the gases are introduced;
the semiconductor gas sensor test system includes: the system comprises a sample feeding device for automatically carrying out sample gas concentration proportioning, a gas sensor heating and temperature measuring device, a signal measuring and data collecting circuit for coordinating with the sample feeding device and automatically collecting 4-6 paths of gas sensor measuring signals under different gas sample environments, and a data processing circuit for carrying out data processing on the collected measuring signals; and a temperature compensation circuit for compensating for temperature variations caused by changes in the intake process and room temperature;
the gas sensor array is arranged in the gas chamber, the change of the gas concentration measured by the gas sensor is the change of the gas in the gas chamber, and the gas chamber is a dry organic glass chamber with a smooth inner cavity and a square approximate shape;
the gas sensor heating and temperature measuring device heats the gas sensitive element and measures the working temperature of the gas sensor in real time; when the working temperature of the sensor changes due to the influence of the ambient temperature or the airflow, the temperature compensation circuit carries out temperature compensation control in real time so as to keep the working temperature of the sensor unchanged; the signal measurement and data acquisition circuit is used for adjusting and AD sampling signals, the signal adjustment is used for converting the response of the gas sensor to a test gas sample into an electric signal, the AD sampling is used for converting an analog signal into a digital signal through the data processing circuit, and the acquired 4-6 paths of sensor signals are converted into standard signals required by a BP neural network through normalization processing;
the standard gas sample output is divided into two paths or multiple paths, each path is controlled by a mass flow controller and is connected into a testing device, carrier gas and gas to be tested enter a drying tank to be fully mixed under the control of the mass flow controller respectively to prepare a target testing gas sample and enter a testing cavity in the testing device, a gas sensor testing system distributes gas with set target concentration under the control of a computer, one or more target gas samples with standard concentration and standard carrier gas are proportioned according to the proportion and are introduced into a mixing channel to be fully mixed under the control of the mass flow controller, when the mixed testing gas sample is introduced into the testing cavity, 4-6 paths of response signals of a gas sensor array in a gas chamber are collected, and the obtained response information of the gas sensor array to the sample gas is transmitted to the computer for data processing and data analysis, carrying out test gas inlet, response signal acquisition and data processing in sequence; when the temperature monitoring system finds that the working temperature of the semiconductor gas sensitive element changes, the temperature compensation circuit compensates the working temperature of the element in real time, and adjusts the heating voltage of the resistance wire to keep the working temperature of the element unchanged;
the humidity detection sensor detects a humidity signal in the air chamber in real time and transmits the signal to the main controller, the main controller compares the humidity signal with a set value of the controller based on a constant humidity set value or a set humidity range in the air chamber, and the controller outputs a split-range control signal; when the humidity in the air chamber is lower than 10% RH, the humidifier is opened to the maximum, the system cannot continue humidifying, or the humidity in the air chamber is higher than 60% RH, and the dehumidifier is opened to the maximum, the main controller controls the buzzer to sound, calls the main controller to interrupt, stops signal output to the dehumidifier and the ultrasonic humidifier, and automatically cuts off the power of the system and stops testing when the humidity exceeds 60% RH;
carrying out data normalization processing on 4-6 road standard signals adopted by the sensor, processing the data into a BP neural network to obtain a required standard data source, and carrying out BP neural network gas analysis according to the following steps:
quantitative analysis:
selecting a single formaldehyde gas to detect a sample, carrying out quantitative detection, forming a sensor array by 4-6 sensors to carry out quantitative identification on formaldehyde gas, ammonia gas, benzene and other mixed gases, wherein the number of input neurons of a neural network is 6, the number of output neurons of the neural network is 1, dynamically changing the number of hidden layers, and solving the corresponding training errors of the hidden layers to determine the optimal number of hidden layer neurons;
creating a two-layer network by using a newff function, setting the number of hidden layer neurons of the network as S (i), setting the range of S (i) to be 3-13, setting a training function of the network as Trainbr, setting the weight and the threshold of the network as random variables with special distribution, estimating the weight and the threshold of the network by using a statistical method, taking an input vector P as the input of the trained neural network, training the network by using a train function, and quantitatively detecting 30 groups of formaldehyde gases with different concentrations as the input to obtain the output result of quantitative detection and corresponding experimental errors;
and (3) qualitative analysis:
the method comprises the following steps that a sensor array consisting of 4-6 sensors qualitatively identifies characteristic quantities of formaldehyde, ammonia gas and benzene, the number of input neurons of a network is 6, the number of output neurons of the network is 3, the optimal hidden layer number is determined through error comparison, and the hidden layer number is dynamically changed;
creating a three-layer network by using a newff function, setting the neuron number of a hidden layer of the network as a dynamic variable S (i) with the range of 3-13, obtaining a group of neuron numbers with the minimum training error as the optimal neuron number through 10 times of training, setting the weight and threshold of the network as random variables with special distribution, and estimating the weight and threshold of the network by using a statistical method; training is stopped until experimental errors meet requirements; the odd group is used as the input of the trained neural network.
Priority Applications (7)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710890243.0A CN107677709B (en) | 2015-11-13 | 2015-11-13 | Method for testing semiconductor gas sensitive element with gas sensitive material preparation step |
CN201710890876.1A CN107677710A (en) | 2015-11-13 | 2015-11-13 | The test system of the semiconductor gas sensor of controlled humidity |
CN201710890245.XA CN107807152A (en) | 2015-11-13 | 2015-11-13 | SnO2The method of testing of gas sensitive preparation method and semiconductor gas sensor |
CN201710890870.4A CN107807154A (en) | 2015-11-13 | 2015-11-13 | The method of testing of the semiconductor gas sensor of controlled humidity with gas sensor making step |
CN201710890627.2A CN107807153A (en) | 2015-11-13 | 2015-11-13 | Humidity control method in the semiconductor gas sensor test of controlled humidity |
CN201710890877.6A CN107817270A (en) | 2015-11-13 | 2015-11-13 | The method of testing of gas sensor preparation method and semiconductor gas sensor |
CN201510778949.9A CN105388187B (en) | 2015-11-13 | 2015-11-13 | The test method of the semiconductor gas sensor of controlled humidity |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510778949.9A CN105388187B (en) | 2015-11-13 | 2015-11-13 | The test method of the semiconductor gas sensor of controlled humidity |
Related Child Applications (6)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201710890876.1A Division CN107677710A (en) | 2015-11-13 | 2015-11-13 | The test system of the semiconductor gas sensor of controlled humidity |
CN201710890870.4A Division CN107807154A (en) | 2015-11-13 | 2015-11-13 | The method of testing of the semiconductor gas sensor of controlled humidity with gas sensor making step |
CN201710890627.2A Division CN107807153A (en) | 2015-11-13 | 2015-11-13 | Humidity control method in the semiconductor gas sensor test of controlled humidity |
CN201710890877.6A Division CN107817270A (en) | 2015-11-13 | 2015-11-13 | The method of testing of gas sensor preparation method and semiconductor gas sensor |
CN201710890245.XA Division CN107807152A (en) | 2015-11-13 | 2015-11-13 | SnO2The method of testing of gas sensitive preparation method and semiconductor gas sensor |
CN201710890243.0A Division CN107677709B (en) | 2015-11-13 | 2015-11-13 | Method for testing semiconductor gas sensitive element with gas sensitive material preparation step |
Publications (2)
Publication Number | Publication Date |
---|---|
CN105388187A CN105388187A (en) | 2016-03-09 |
CN105388187B true CN105388187B (en) | 2018-09-14 |
Family
ID=55420712
Family Applications (7)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201710890876.1A Withdrawn CN107677710A (en) | 2015-11-13 | 2015-11-13 | The test system of the semiconductor gas sensor of controlled humidity |
CN201710890627.2A Withdrawn CN107807153A (en) | 2015-11-13 | 2015-11-13 | Humidity control method in the semiconductor gas sensor test of controlled humidity |
CN201710890870.4A Withdrawn CN107807154A (en) | 2015-11-13 | 2015-11-13 | The method of testing of the semiconductor gas sensor of controlled humidity with gas sensor making step |
CN201710890243.0A Active CN107677709B (en) | 2015-11-13 | 2015-11-13 | Method for testing semiconductor gas sensitive element with gas sensitive material preparation step |
CN201710890245.XA Withdrawn CN107807152A (en) | 2015-11-13 | 2015-11-13 | SnO2The method of testing of gas sensitive preparation method and semiconductor gas sensor |
CN201710890877.6A Withdrawn CN107817270A (en) | 2015-11-13 | 2015-11-13 | The method of testing of gas sensor preparation method and semiconductor gas sensor |
CN201510778949.9A Expired - Fee Related CN105388187B (en) | 2015-11-13 | 2015-11-13 | The test method of the semiconductor gas sensor of controlled humidity |
Family Applications Before (6)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201710890876.1A Withdrawn CN107677710A (en) | 2015-11-13 | 2015-11-13 | The test system of the semiconductor gas sensor of controlled humidity |
CN201710890627.2A Withdrawn CN107807153A (en) | 2015-11-13 | 2015-11-13 | Humidity control method in the semiconductor gas sensor test of controlled humidity |
CN201710890870.4A Withdrawn CN107807154A (en) | 2015-11-13 | 2015-11-13 | The method of testing of the semiconductor gas sensor of controlled humidity with gas sensor making step |
CN201710890243.0A Active CN107677709B (en) | 2015-11-13 | 2015-11-13 | Method for testing semiconductor gas sensitive element with gas sensitive material preparation step |
CN201710890245.XA Withdrawn CN107807152A (en) | 2015-11-13 | 2015-11-13 | SnO2The method of testing of gas sensitive preparation method and semiconductor gas sensor |
CN201710890877.6A Withdrawn CN107817270A (en) | 2015-11-13 | 2015-11-13 | The method of testing of gas sensor preparation method and semiconductor gas sensor |
Country Status (1)
Country | Link |
---|---|
CN (7) | CN107677710A (en) |
Families Citing this family (18)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105954323B (en) * | 2016-06-02 | 2020-12-01 | 中国石油大学(华东) | Ultralow concentration intelligent monitoring device for gaseous pollutants discharged from thermal power plant |
CN106053551A (en) * | 2016-07-31 | 2016-10-26 | 河北工业大学 | Multi-channel multi-type sensor capability test system |
CN106404839A (en) * | 2016-08-19 | 2017-02-15 | 北京艾立特科技有限公司 | An intelligent gas-sensitive analytical device used for an indirectly heated gas sensor |
CN106646086B (en) * | 2017-02-25 | 2019-05-28 | 郑州畅威物联网科技有限公司 | A kind of detection method of semiconductor gas sensor heater strip fracture of wire |
CN108562697A (en) * | 2018-03-30 | 2018-09-21 | 歌尔股份有限公司 | A kind of indoor harmful gas monitoring device |
CN108645894A (en) * | 2018-04-25 | 2018-10-12 | 北京交通大学 | Monitor NAPLs migration process and test method of phase transformation in unsaturated soil |
CN108982396A (en) * | 2018-05-30 | 2018-12-11 | 南京信息工程大学 | A kind of infrared CO2Gas sensor and its calibration system and humiture compensation method |
CN108828010B (en) * | 2018-08-22 | 2021-03-02 | 云南大学 | Sensitive material for detecting formaldehyde gas, preparation method and application |
EP3699582A1 (en) * | 2019-02-25 | 2020-08-26 | Infineon Technologies AG | Gas sensing device and method for operating a gas sensing device |
CN110220945B (en) * | 2019-04-23 | 2021-12-07 | 金卡智能集团股份有限公司 | Full-range temperature compensation method of semiconductor gas sensor |
CN112540150A (en) * | 2019-09-20 | 2021-03-23 | 中国石油化工股份有限公司 | Sensor performance evaluation device, method and system |
CN112578133B (en) * | 2019-09-27 | 2024-07-05 | 深圳迈瑞生物医疗电子股份有限公司 | Sample analysis system and test management method of analysis equipment |
DE102021109438A1 (en) * | 2020-04-21 | 2021-10-21 | The University Of Tokyo | Field effect transistor, gas sensor, and manufacturing method of the same |
CN112730530A (en) * | 2020-12-24 | 2021-04-30 | 中国科学技术大学 | Aviation kerosene concentration detection method and device based on composite sensor |
CN113138210B (en) * | 2021-06-22 | 2021-09-24 | 电子科技大学 | Self-adaptive local Gaussian temperature and humidity compensation method for intelligent gas sensor |
CN113514621A (en) * | 2021-09-14 | 2021-10-19 | 成都千嘉科技有限公司 | Method for testing dynamic performance of gas sensor |
CN113970578B (en) * | 2021-10-21 | 2023-05-02 | 西安交通大学 | Universal data normalization calibration method for resistance type micro gas sensor |
CN114646680B (en) * | 2022-05-18 | 2022-09-13 | 深圳市瑞达同生科技发展有限公司 | Automatic test system of gas sensor |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101241093A (en) * | 2007-02-07 | 2008-08-13 | 中国科学院微电子研究所 | Gas sensor calibration and reliability test system |
CN102507650A (en) * | 2011-09-30 | 2012-06-20 | 郑州炜盛电子科技有限公司 | Method and system for testing parameters of gas-sensitive element |
CN103293199A (en) * | 2013-05-21 | 2013-09-11 | 重庆大学 | Experimental device and method for testing gas-sensitive characteristics of titanium dioxide nanotube sensor |
CN105021777A (en) * | 2015-07-31 | 2015-11-04 | 湖北大学 | Multifunctional gas sensor testing system |
Family Cites Families (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8898633B2 (en) * | 2006-08-24 | 2014-11-25 | Siemens Industry, Inc. | Devices, systems, and methods for configuring a programmable logic controller |
CN101881761B (en) * | 2010-03-11 | 2012-11-21 | 大连理工大学 | Humidity adjustable high precision closed loop gas distribution system |
CN102331481B (en) * | 2010-07-12 | 2015-11-25 | 上海航天汽车机电股份有限公司 | The oxygen sensor performance measuring system of multichannel distribution simulated automotive tail gas environment |
CN102384962B (en) * | 2011-11-09 | 2015-04-15 | 上海交通大学 | Gas sensor performance testing device |
CN102495110A (en) * | 2011-11-18 | 2012-06-13 | 南京工业大学 | Gas sensor test system |
CN102608277B (en) * | 2012-04-10 | 2014-05-07 | 无锡隆盛科技股份有限公司 | Detection method of detection system for oxynitride sensor |
CN102866179B (en) * | 2012-09-13 | 2014-06-18 | 重庆大学 | Online recognition and inhibition method based on non-target interference smell in electronic nose of artificial intelligent learning machine |
-
2015
- 2015-11-13 CN CN201710890876.1A patent/CN107677710A/en not_active Withdrawn
- 2015-11-13 CN CN201710890627.2A patent/CN107807153A/en not_active Withdrawn
- 2015-11-13 CN CN201710890870.4A patent/CN107807154A/en not_active Withdrawn
- 2015-11-13 CN CN201710890243.0A patent/CN107677709B/en active Active
- 2015-11-13 CN CN201710890245.XA patent/CN107807152A/en not_active Withdrawn
- 2015-11-13 CN CN201710890877.6A patent/CN107817270A/en not_active Withdrawn
- 2015-11-13 CN CN201510778949.9A patent/CN105388187B/en not_active Expired - Fee Related
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101241093A (en) * | 2007-02-07 | 2008-08-13 | 中国科学院微电子研究所 | Gas sensor calibration and reliability test system |
CN102507650A (en) * | 2011-09-30 | 2012-06-20 | 郑州炜盛电子科技有限公司 | Method and system for testing parameters of gas-sensitive element |
CN103293199A (en) * | 2013-05-21 | 2013-09-11 | 重庆大学 | Experimental device and method for testing gas-sensitive characteristics of titanium dioxide nanotube sensor |
CN105021777A (en) * | 2015-07-31 | 2015-11-04 | 湖北大学 | Multifunctional gas sensor testing system |
Non-Patent Citations (4)
Title |
---|
《Classifying inventory using an artificial neural network approach》;Fariborz Y P et al.;《Computer&I ndust rial Engineering》;20021231;第389-404页 * |
《基于BP 网络的气敏传感器阵列测试分析》;周东祥 等.;《华中科技大学学报(自然科学版)》;20070430;第35卷(第4期);第51-53页 * |
《基于人工神经网络的甲醛气敏元件自动测试系统》;杜海英 等.;《扬州大学学报(自然科学版)》;20090228;第12卷(第1期);第45页第2-4段 * |
《气敏元件自动测试系统的设计》;杜海英 等.;《工业仪表与自动化装置》;20051231(第6期);第30页右栏倒数第2段到第32页右栏第2段,图2 * |
Also Published As
Publication number | Publication date |
---|---|
CN107677710A (en) | 2018-02-09 |
CN107677709B (en) | 2020-07-21 |
CN107807153A (en) | 2018-03-16 |
CN107807152A (en) | 2018-03-16 |
CN107677709A (en) | 2018-02-09 |
CN107817270A (en) | 2018-03-20 |
CN105388187A (en) | 2016-03-09 |
CN107807154A (en) | 2018-03-16 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN105388187B (en) | The test method of the semiconductor gas sensor of controlled humidity | |
CN108896706B (en) | The foul gas multiple spot centralization electronic nose instrument on-line analysis of big data driving | |
CN105259215B (en) | The method of testing of semiconductor gas sensor | |
CN207396402U (en) | High-precision gas sensor dynamic checkout unit under a kind of multi-parameters test environment | |
CN101000318A (en) | Sensor array based on temperature control and gas detection method | |
CN105445321B (en) | The detection means of combustible material hot property under the conditions of a kind of programmable temperature control | |
CN104407073B (en) | A kind of control system of gas chromatograph and control method | |
Ni et al. | Air quality monitoring and on-site computer system for livestock and poultry environment studies | |
CN1453584A (en) | Fast non-destructive detection method and device of food smell based on gas sensor array technology | |
CN201255729Y (en) | Wood material moisture percentage intelligent detecting device based on multi-sensor data fusion | |
CN104569056A (en) | Portable liquor identification equipment based on electronic nose technology | |
CN112387208A (en) | Medicinal fluidized bed control system based on near infrared and distributed predictive control | |
Guterman et al. | Automatic on‐line growth estimation method for outdoor algal biomass production | |
CN206074625U (en) | Bionic olfactory detection and analysis device based on dynamic air-distributing | |
CN106443031B (en) | Bionic olfactory detection and analysis device and its determination method based on dynamic air-distributing | |
CN107976469A (en) | A kind of soil nutrient device for fast detecting based on Artificial Olfactory | |
CN106404839A (en) | An intelligent gas-sensitive analytical device used for an indirectly heated gas sensor | |
CN109612919B (en) | Method for detecting galvanic couple type atmospheric corrosion sensor | |
CN103336026A (en) | Polymer piezoelectric gas sensor system for detecting gases | |
CN106918626B (en) | Dangerous atmosphere comprehensive state fingerprint identification method | |
CN110993994B (en) | Fuel cell test system based on Internet of things | |
CN114549995A (en) | Method and system for identifying raw materials running in kiln | |
CN113267533A (en) | Device and method for dynamically monitoring VOCs (volatile organic chemicals) on line by self-calibration gas sensor array | |
CN207164022U (en) | A kind of debirs treatment facility foul gas detection device | |
CN101246139A (en) | Zirconium oxide analyzer |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
CB03 | Change of inventor or designer information | ||
CB03 | Change of inventor or designer information |
Inventor after: Sun Yanhui Inventor after: Du Haiying Inventor after: Li Zheng Inventor after: Wang Shugang Inventor before: Du Haiying Inventor before: Sun Yanhui Inventor before: Li Zheng Inventor before: Wang Shugang |
|
GR01 | Patent grant | ||
GR01 | Patent grant | ||
CF01 | Termination of patent right due to non-payment of annual fee | ||
CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20180914 Termination date: 20201113 |