Author
Listed:
- WEI WANG
(School of Instrument and Electronics, North University of China, Taiyuan, Shanxi, P. R. China)
- DIMAH ALAHMADI
(��Information Systems Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia)
Abstract
In order to further explore the intelligent research of the pressure sensor in the pipeline, based on the existing pipeline detection methods of the Internet of Things (IoT), the signal processing method and correction research in the wireless sensor network of the IoT are explored. A multi-pressure sensor detection method of negative pressure wave is proposed. Scientific and intelligent means are used to explore the pipeline remote intelligent detection. The specific research results are as follows. In the simulation study, when the working condition of pump station 1# changes, the pressure wave first reaches A1 and B2 sensors, and finally reaches C1 and C2 sensors. If there is leakage in the pipeline, the simulation results show that when the pressure of pump station rises to 5MPa, the pressure of B1 and B2 test points decreases to about 4.9MPa, and the pressure of A1, A2, C1 and C2 test points is about 3MPa; when the pressure of the pump station drops to 3MPa, the pressure of all test points decreases. Generally speaking, the pressure of the front-end pressure sensor of the pump station is basically unchanged while the pressure of the back end increases when the pressure increases; when the pressure decreases, the pressure of the front-end pressure sensor of the pump station is basically unchanged while the pressure of all the back-end pressure sensor decreases. After correction, the signal data is obviously smooth and the error is obviously reduced. This study can provide scientific and effective reference for the pressure monitoring of IoT sensor network.
Suggested Citation
Wei Wang & Dimah Alahmadi, 2022.
"Dynamic Nonlinear Correction Processing Of Pressure Sensor Test Signal In Internet Of Things System,"
FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 30(02), pages 1-11, March.
Handle:
RePEc:wsi:fracta:v:30:y:2022:i:02:n:s0218348x22401041
DOI: 10.1142/S0218348X22401041
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wsi:fracta:v:30:y:2022:i:02:n:s0218348x22401041. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim (email available below). General contact details of provider: https://www.worldscientific.com/worldscinet/fractals .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.