Due to rapid advancement in technology, recently a significant amount of work has been carried out in the field of multi-mode sensor and multifunctional sensor. A single unit of multifunctional sensor provides multiple measurements, which eventually reduces the cost of multiple sensors and makes the system compact. Though the risk of sensor failure and reliability of the multifunctional sensor is always imminent, researchers are working out different methods to make the sensor fault tolerant. Multifunctional sensors are getting widespread acceptance in a variety of fields. This paper provides a review of recent advances in multifunctional sensor technology in the perspective of a multi-sensor system. Different aspects of design and implementation of multifunctional sensor technology have been addressed in this paper. This paper can serve as a basic reading material for students and researchers pursuing research on a multifunctional sensor.

Recent Advances in Multifunctional Sensing Technology on a Perspective of Multi-Sensor System: A Review

This research work regards the design and realization of an absorption spectrophotometer based on a LED light source in place of the usually employed Xenon lamp. The advantage of the use of LED technology resides in several factors such as the reducing of the analyte temperature variations and thus noise generation, which occur if a Xenon light source is used, beside of the high luminous efficiency, reliability, operating duration, lower maintenance and a lower power consumption. This last factor allows to supply the entire designed apparatus using a solar panel thus making the system easly portable for use even in places where the electricity network is absent. An optical filtering system was realized in order to detect the analyte absorption for each wavelength range selected by the optical filters. A PC-interfaced PIC-based control unit used to manage the different functionalities required by the spectophotometer was realized and tested. The control unit acquires and processes, via the developed firmware, the raw data provided by different sensors employed in the system. The sensors are used to monitor analyte temperature and humidity values, to control the analyte pressure and to acquire the luminous intensity value of the light beam before and after passing through the analyte. Finally, the realized electronic control unit actuates different mechanical sections (stepper motor, solenoid valve), sincronyzing and controlling the data exchange between hardware sections, microcontroller and the PC.

A solar-powered white led-based uv-vis spectrophotometric system managed by pc for air pollution detection in faraway and unfriendly locations

Digital twin for oil pipeline risk estimation using prognostic and machine learning techniques

Diabetes mellitus, commonly measured through an invasive process which although is accurate, has manifold drawbacks especially when multiple reading are required at regular intervals. Accordingly, there is a need to develop a dependable non-invasive diabetes detection technique. Recent studies have observed that other human serums such as tears, saliva, urine and breath indicate the presence of glucose in them. These parameters open quite a few ways for non-invasive blood glucose level prediction. The analysis of a persons breath poses as a good non-invasive technique to monitor the glucose levels. It is seen that in breath, there are many bio-markers and monitoring the levels of these bio-markers indicate the possibility of various chronic diseases. Among these bio-markers, acetone a volatile organic compound found in breath has shown a good correlation to the glucose levels present in blood. Therefore, by evaluating the acetone levels in breath samples it is possible to monitor diabetes non-invasively. This paper reviews the various approaches and sensory techniques used to monitor diabetes though human breath samples.

Recent Advancements and Future Prospects on E-Nose Sensors Technology and Machine Learning Approaches for Non-Invasive Diabetes Diagnosis: A Review

With the advantage of low cost and small size, a hall sensor has been exploited to detect motor position, and this strategy has attracted much attention. A challenge is that measurement model parameters vary with position and vary from motor to motor because of the machining errors of permanent magnets. While, most existing methods use other auxiliary displacement sensors to calibrate model parameters off-line, which require a lot of preliminary work and lose adaptation when they are applied in industry. In this paper, an on-line simultaneous computation of model parameters and position method is proposed to measure position for a permanent magnet synchronous linear motor. The measurement model with Fourier series is employed to approximate the mapping relationship between magnetic field strength and mover position. Based on the continuous variation characteristics of model parameters and position, a simultaneous computational algorithm is proposed to real-timely compute model parameters and position without other sensors. In the experiments of one-way and reciprocating motion, magnetic field information is detected by a self-designed hall sensor array. Experimental results indicate that the standard deviation of measurement error is less than $10~\mu \text{m}$ with the comparison of a reference optical encoder.

A Hall Sensor-Based Position Measurement With On-Line Model Parameters Computation for Permanent Magnet Synchronous Linear Motor

A rotameter is a variable-area-type flow rate measuring instrument in which the position of a metallic float in a transparent conical tube is taken as a flow rate indicator. It has the disadvantage that it is a local indicating type instrument and special type of transducer is used for its remote indication. In this paper, a noncontact flow rate measurement technique using Hall probe sensor and rotameter is designed, developed, and tested. In this design, a float carrying a thin circular permanent magnet is used, and a Hall probe sensor placed outside the rotameter tube has been used to sense the variation of magnetic field of the magnet with the variation of float position. A signal conditioner unit has been used to convert the Hall probe sensor output into 1–5 V dc signal. This dc signal output of the signal conditioner has been sent to a PC-based flow indicator through optoisolator and analog input channel of a data acquisition system (DAS) card. The PC-based flow indicator has been designed using the Lab Tech Note Book Pro software and the PC-based supervisory control and DAS. A theoretical equation has been derived to explain the operation of the system. The performance of the system has been tested experimentally, and the experimental results are reported in this paper. A very good repeatability and linearity of results has been observed.

Design and Implementation of Real-Time Flow Measurement System Using Hall Probe Sensor and PC-Based SCADA

This paper presents an intelligent flow transmitter using rotameter as a primary sensor. The float movement of the rotameter is converted into an electrical signal so that one can monitor it and control it at a remote location in industries. A Hall probe sensor is used to convert the float movement into Hall voltage, but various parameters like temperature, liquid density, viscosity etc., affect the Hall voltage measurement. The change of Hall voltage with respect to temperature is nonlinear in nature. In this respect, back propagation algorithm of the artificial neural network (ANN) is used to compensate the nonlinearity and inaccuracy of Hall probe sensor due to change in temperature. The proposed measurement system, experimental results, and testing results of the ANN are reported in this paper.

Design and Analysis of an Intelligent Flow Transmitter Using Artificial Neural Network

This paper presents a smart pressure transmitter using bellow as primary sensor. The deflection of bellow is converted into electrical output using hall probe sensor as secondary sensor. The output Hall voltage is affected by change in input parameters like temperature. So firstly the effect of temperature on Hall voltage is derived mathematically and then experimentally analyzed. This effect of temperature on output Hall voltage is then compensated using artificial neural network. The compensated output Hall voltage is then converted into (4–20) mA current signal using signal conditioning circuit. The proposed design, experimental and testing results are reported in this paper.

Design of a Smart Pressure Transmitter and Its Temperature Compensation Using Artificial Neural Network

A novel, cost- effective and efficient wireless pressure measurement system is modeled for transmission of the signal in harsh environment. The sensing part involves rubber bellows with a capacitive sensor made of copper plates. For remote transmission, monitoring and controlling the mechanical displacement of the bellows is converted into dc output voltage using differentiator and precision half wave rectifier. A linearization circuit is also designed, which linearized the output voltage with a value of percentage deviation from linearity of ±1.8%. For further FSK mode of transmission, the obtained linearized voltage is converted into 1 to 5 volt with a signal conditioning circuit. The transmitted output voltage is recovered using FSK demodulator circuit, LPF and a Decision circuit at receiving end. The full scale percentage error of the measurement system lies within 5% which is in an acceptable range. The proposed method is an economic and efficient transmission technique in hazardous areas where wired transmission is not feasible. The mathematical equations explaining the functioning of the proposed transmitter have been derived. The operation of the proposed pressure transmitter has been experimentally tested. The design approach, mathematical analysis and experimental results of the proposed model are reported in this paper.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-smt.2017.0545

Design and development of a capacitance-based wireless pressure transmitter

Rotameter is one of the most commonly used local indicating type flow measuring instrument. For remote indication and control a secondary transducer like Hall Probe sensor, LVDT etc. is incorporated with the conventional rotameter. In this paper, a modified rotameter with Hall Probe sensor is used as a measuring instrument. The output hall voltage is proportional to the flow rate of the fluid and the change in fluid density may also vary the hall voltage. So this kind of variation shows incorrect flow rate if the density of the float is not taken to a very high value compared to the density of the fluid. But the density float may affect the flow rate measurement and introduce error. In this respect firstly the variation of Hall voltage with respect to liquid density is analyzed and then the measuring system is calibrated using ANN. The ANN calculates the correction factor with respect to the change in liquid density, which results in obtaining the output close to the desired output. The simulation results show that the calibration technique is efficient.

Sunita Sinha

Papers

Design and Implementation of Real-Time Flow Measurement System Using Hall Probe Sensor and PC-Based SCADA

Design and Analysis of an Intelligent Flow Transmitter Using Artificial Neural Network

Design of a Smart Pressure Transmitter and Its Temperature Compensation Using Artificial Neural Network

Design and development of a capacitance-based wireless pressure transmitter

Optimization of modified rotameter using hall probe sensor with respect to liquid density and its calibration using artificial neural network