PUBLICATIONS
1. S. BISWAS, K. BISWAS, P. MANDAL, "IMPEDIMETRIC OSCILLATOR CIRCUIT: DESIGN AND IMPLEMENTATION", COMMUNICATED TO IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I: REGULAR PAPERS
In peer review, March 20, 2022
A novel oscillator structure has been proposed for impedimetric application. The oscillator structure is simulated in LTspice and validated by bread-board level hardware implementation.
2. PATENT (FILED): IMPEDIMETRIC OSCILLATOR CIRCUIT SYSTEM; APPLICATION NUMBER: 202231003118
January 19, 2022
The present invention relates to an oscillator-based circuit structure that can measure characterizing parameters of the circuit element. More specifically, the present invention is directed to develop an impedimetric oscillator circuit system for measuring the impedance phase of any generalized impedimetric structure. In the present impedimetric oscillator circuit system, the output oscillation is proportional to the ratio of two impedances which advantageously fulfills two purposes viz. (i) any multiplicative non-idealities of the impedances or multiplicative interfering factors for impedance measurement are eliminated, and (ii) separate measurement for reference is eliminated.
3. DETERMINATION OF FAT, SNF AND PROTEIN CONTENT IN COW MILK FROM THE VOLTAGE OUTPUT OF ‘MILKTESTER’
May 17, 2021
Authors:
Suman Biswas, Ajoy Mandal, Moupali Chakraborty, Karabi Biswas
Conference:
2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
Description: In this work, we report estimation of fat, protein and solid not fat (SNF) of cow milk using the output voltage obtained from the `MilkTester', developed by the authors at Indian Institute of Technology Kharagpur (IIT Kharagpur). The estimation is carried out in three phases named as “Training”, “Interrelation”, and “Validation”. In the “Training Phase”, output voltage from the “MilkTester” is expressed as multivariate equation of fat, SNF and protein. The data sets of fat, SNF and protein are collected using the commercial instrument, “MilkoScreen” (from FOSS, Denmark). This instrument is installed in National Dairy Research Institute Kalyani, India to measure the constituents of milk. Interrelations between “protein & SNF” and “SNF & fat” are estimated by linear regression analysis using the software, OriginPro 8.5, which return the value of the coefficients of the equations. Finally, relation between output voltage and fat is obtained. Once the value of fat percentage is known, the other two parameters can be found out by using the interrelation equations. In the `Validation Phase', fat, SNF and protein are regarded as unknown components and estimated using voltage data (from the `MilkTester'). The error between the estimated value (from regression analysis) and true value (obtained from the “MilkoScreen') is also evaluated for all the three parameters for randomly chosen samples. The maximum error, 12.21%, is found for estimation of protein. But the difference of absolute value is only 0.59. Maximum error for fat estimation is 10.01%, where absolute difference is 0.63. The SNF estimation shows error of 4.61% with absolute error of 0.45.
May 25, 2020
Authors:
Suman Biswas, Moupali Chakraborty, Karabi Biswas
Conference:
2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
Description: In this work, a novel copper-based sensor, coated with RGO (reduced graphene oxide) and PMMA (polymethyl methacrylate) is proposed to detect the presence of formaldehyde in milk and water. The phase angle of the proposed sensor changes, when dipped in pure milk and formaldehyde adulterated milk. In water, both phase and magnitude of the sensor impedance change. Milk and water, adulterated with different concentrations of formaldehyde are considered for evaluating the performance of the proposed sensor.