Improving calibration accuracy of a vibration sensor through a closed loop measurement system


A sensor is a transducer whose purpose is to sense (that is, to detect) some characteristic of its environments. It detects events or changes in quantities and provides a corresponding output, usually as an electrical or optical signal. It has been widely employed in mechanical engineering, aeronautics and astronautics engineering, industrial control, etc. Sensors play important roles in industries like producing, where all require the sensor to act as a reliable unit [one], [2]. In practical engineering applications, a sensor is usually used for measuring vibrations, as well as acceleration, velocity, and displacement. It is the first link in achieving conversion, processing, recording, and storage of data. So, its performance directly influences the reliability and accuracy of the entire system. The calibration for vibration sensors, that want to establish sensitivity, frequency response characteristics, amplitude linearity, etc., are needed before the measurement is made [3], [4]. Traditionally, an open loop device (in that the excitation signal is adjusted manually and the parameters are recorded manually) is used for sensor calibration. This sort of manual calibration generates a massive amount of work and active jamming, that ends up in errors. If a closed loop calibration system will be designed (i.e., the excitation signals are adjusted automatically by devices, and the important time data are sampled and analyzed), it will supply abundant measurement info and analysis methods which will facilitate improve calibration accuracy and potency. In this article, we tend to introduce such a closed loop calibration system for vibration sensors.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Improving I/O Complexity of Triangle Enumeration ABSTRACT: Many graph algorithms are now required to operate in external memory and deliver performance that does not significantly degrade with the scale of the
PROJECT TITLE : Improving Speech Emotion Recognition With Adversarial Data Augmentation Network ABSTRACT: When there aren't many training data to work with, it can be difficult to train a deep neural network without triggering
PROJECT TITLE : A Time-Series Feature-Based Recursive Classification Model to Optimize Treatment Strategies for Improving Outcomes and Resource Allocations of COVID-19 Patients ABSTRACT: This paper presents a novel Lasso Logistic
PROJECT TITLE : Recommender Systems and Scratch An integrated approach for enhancing computer programming learning ABSTRACT: Learning computer programming is a difficult task. Visual programming languages (VPLs), such as Scratch,
PROJECT TITLE : Using Cost-Sensitive Learning and Feature Selection Algorithms to Improve the Performance of Imbalanced Classification ABSTRACT: The problem of unbalanced data is common in network intrusion detection, spam filtering,

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry