Next Article in Journal
Microstrip Patch Sensor for Salinity Determination
Previous Article in Journal
Design and Performance Evaluation of an Electro-Hydraulic Camless Engine Valve Actuator for Future Vehicle Applications
Article Menu
Issue 12 (December) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(12), 2939; https://doi.org/10.3390/s17122939

Using the Kalman Algorithm to Correct Data Errors of a 24-Bit Visible Spectrometer

Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada
*
Author to whom correspondence should be addressed.
Received: 23 October 2017 / Revised: 12 December 2017 / Accepted: 14 December 2017 / Published: 18 December 2017
(This article belongs to the Section Intelligent Sensors)
View Full-Text   |   Download PDF [7610 KB, uploaded 19 December 2017]   |  

Abstract

To reduce cost, increase resolution, and reduce errors due to changing light intensity of the VIS SPEC, a new technique is proposed which applies the Kalman algorithm along with a simple hardware setup and implementation. In real time, the SPEC automatically corrects spectral data errors resulting from an unstable light source by adding a photodiode sensor to monitor the changes in light source intensity. The Kalman algorithm is applied on the data to correct the errors. The light intensity instability is one of the sources of error considered in this work. The change in light intensity is due to the remaining lifetime, working time and physical mechanism of the halogen lamp, and/or battery and regulator stability. Coefficients and parameters for the processing are determined from MATLAB simulations based on two real types of datasets, which are mono-changing and multi-changing datasets, collected from the prototype SPEC. From the saved datasets, and based on the Kalman algorithm and other computer algorithms such as divide-and-conquer algorithm and greedy technique, the simulation program implements the search for process noise covariance, the correction function and its correction coefficients. These components, which will be implemented in the processor of the SPEC, Kalman algorithm and the light-source-monitoring sensor are essential to build the Kalman corrector. Through experimental results, the corrector can reduce the total error in the spectra on the order of 10 times; for certain typical local spectral data, it can reduce the error by up to 60 times. The experimental results prove that accuracy of the SPEC increases considerably by using the proposed Kalman corrector in the case of changes in light source intensity. The proposed Kalman technique can be applied to other applications to correct the errors due to slow changes in certain system components. View Full-Text
Keywords: spectrometer; spectrum; Kalman; filter; noise reduction; corrector spectrometer; spectrum; Kalman; filter; noise reduction; corrector
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Pham, S.; Dinh, A. Using the Kalman Algorithm to Correct Data Errors of a 24-Bit Visible Spectrometer. Sensors 2017, 17, 2939.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top