Evidence map›Paper›PMID 39275676›Full record

ArticleSensors (Basel, Switzerland)2024

Design of MEMS Pressure Sensor Anti-Interference System Based on Filtering and PID Compensation.

Baojie Li, Guiling Sun, Haicheng Zhang, Liang Dong, Yunlong Kong

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Baojie LiCollege of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China.
Guiling SunCollege of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China.
Haicheng ZhangCollege of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China.
Liang DongCollege of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China.
Yunlong KongCollege of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China.

Funding

Natural Science Foundation of Tianjin City 21JCZDJC00340
6 · The paper itself

Abstract

Due to the inherent temperature drift and lack of static stability in traditional pressure sensors, which make it difficult for them to meet the increasing demands of various industries, this paper designs a new system. The proposed system integrates temperature measurement and regulation circuits, signal processing, and communication circuits to accurately acquire and transmit pressure sensor data. The system designs a filtering algorithm to filter the original data and develops a data-fitting operation to achieve error compensation of the static characteristics. In order to eliminate the temperature drift problem of the sensor system, the system also adopts an improved PID thermostatic control algorithm to compensate for the temperature drift. Finally, it can also transmit the processed pressure data remotely. The experimental results show that the nonlinear error at 50 °C is reduced from the initial 1.82% to 0.24%; the hysteresis error is significantly reduced from 1.23% to 0.046%; and the repeatability error control is reduced from 3.79% to 0.89%. By compensating for thermal drift, the system's thermal sensitivity drift coefficient is reduced by 74.67%, the thermal zero drift coefficient is reduced by 66.24%, and the wireless communication range is up to 1km. The above significant optimization results fully validate the high accuracy and stability of the system, which is perfectly suited for demanding pressure measurement applications.

Indexed as

least squaresMEMS pressure sensorPID algorithmstatic characteristicstemperature drift

Identifiers

PMID39275676
PMCPMC11398226

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.