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High-precision humidity sensor

A humidity sensor, high-precision technology, applied in the field of sensors, can solve problems such as large errors, and achieve the effects of high accuracy, improved accuracy and stable properties

Inactive Publication Date: 2016-12-07
CHENGDU PEACE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since the measuring part of the sensor is always exposed to the air, the change of temperature will affect the change of the dielectric constant of the dielectric, causing the humidity sensor to produce a certain temperature drift, resulting in the data measured by the humidity sensor being different from the relative humidity value of the standard Compared with the relative humidity, the error is relatively large, so corresponding measures must be taken to compensate the temperature of the humidity sensor, so that the compensated result meets the error requirements of relative humidity measurement

Method used

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Experimental program
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Effect test

Embodiment 1

[0043] Such as figure 1 As shown, a high-precision humidity sensor includes a sequentially connected data acquisition unit and a segment compensation unit. The data acquisition unit collects humidity change data acquisition, and the segment compensation unit includes PSO-BP neural network error compensation.

[0044] PSO-BP neural network error compensation includes the following steps,

[0045] Step 1, set the relevant parameters of the PSO-BP neural network, 2 input and output nodes, 1 output node, 5 hidden layer nodes, the maximum number of iterations is 1500, and the target error is 1×10 -6 , the learning rate is 0.01, the population size is 40, and the inertia weight is 1. The total number of weight thresholds to be optimized by the PSO algorithm is: N=(m+1)×n+(n+1)×t, m is the input neuron The number of units, n is the number of neurons in the hidden layer, t is the number of neurons in the output layer, and the speed and position of the particles are randomly initializ...

Embodiment 2

[0052] Such as Figure 2 to Figure 3 As shown, the data acquisition unit includes a humidity sensing device, the humidity sensing device includes a substrate 1, the thickness of the substrate 1 is 400 μm, the lower surface of the substrate 1 is covered with a substrate layer 7, the upper surface of the substrate 1 is provided with a heater 2, and the upper surface of the heater 2 is An output layer 6 is provided, and the upper surface of the output layer is covered with a moisture-sensitive layer 3 . The heater 2 is a serpentine heater, and the heater 2 includes three heating units, which are sequentially connected to the heating unit 1, heating unit 2 and heating unit 3 from left to right; one end of the heating unit 1 and the heating unit 3 are connected with electrodes 5. The other end is connected to both ends of heating unit two; heating unit one is arranged horizontally, heating unit one is mirror-symmetrical to heating unit three, heating unit two is arranged vertically...

Embodiment 3

[0057] Silane-alkyne block resins are prepared by:

[0058] Magnesium powder (6g, 0.25mol) and tetrahydrofuran (40ml) were added to a four-necked flask, and ethyl bromide (25.92g, 0.24mol) was added dropwise under a nitrogen atmosphere. Add m-diethynylbenzene (15.12g, 0.12mol) dropwise in an ice-water bath, reflux at 67°C for 1h, add dichloropolysiloxane (0.08mol) dropwise in an ice-water bath, and reflux for 2h to obtain the macromonomer Grignard Reagent P 1 . Magnesium powder (2.16g, 0.09mol) and tetrahydrofuran (40ml) were added into a four-necked flask, and bromoethane (8.64g, 0.08mol) was added dropwise under a nitrogen atmosphere. m-diethynylbenzene (5.04g, 0.04mol) was added dropwise in an ice-water bath, refluxed for 1h, dimethyldichlorosilane (7.74g, 0.06mol) was added dropwise in an ice-water bath, and refluxed for 2h to obtain a macromonomer Chlorosilane P 2 .

[0059] Will P 2 slowly drop to P 1 in the reaction system. After dripping, heat to reflux for abo...

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Abstract

The invention discloses a high-precision humidity sensor and belongs to the field of sensors. The high-precision humidity sensor comprises a data collecting unit and a subsection compensation unit which are sequentially connected, wherein the data collecting unit collects humidity change data, and the subsection compensation unit comprises PSO-BP neural network error compensation. The high-precision humidity sensor has the advantages that the global searching ability of a PSO algorithm is utilized to optimize the initial weight threshold of a BP neural network so as to optimize the structure of the BP neural network, and the humidity sensor temperature compensation model of the PSO-BP neural network is built to compensate temperature's influence on the measuring result of the humidity sensor.

Description

technical field [0001] The invention relates to a sensor, in particular to a high-precision humidity sensor. Background technique [0002] Humidity sensors are widely used in many fields, such as industrial control, pharmaceutical production, agricultural planting, weather detection, and food storage. It is of great significance to realize fast and accurate measurement of humidity in these fields. [0003] However, since the moisture-sensitive film is a dielectric with moisture-sensitive characteristics, its dielectric constant changes with the change of relative humidity, so as to complete the measurement of humidity. Since the measuring part of the sensor is always exposed to the air, the change of temperature will affect the change of the dielectric constant of the dielectric, causing the humidity sensor to produce a certain temperature drift, resulting in the data measured by the humidity sensor being different from the relative humidity value of the standard Compared ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N27/22G01D3/036
CPCG01N27/223G01D3/036G01N27/226
Inventor 潘犁
Owner CHENGDU PEACE TECH CO LTD
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