J. M. Dias Pereira

Fitting transducer characteristics to measured data

There are no rules to select the best curve-fitting method for a given set of data. This problem is of great importance in measurement applications. Optimizing analog and digital methods for a transducers characteristic interpolation or linearization is a field where constant research is being done, particularly since auto-calibration and self-test of intelligent transducers is a topic of major interest. We present an overview of classical methods for data interpolation and least mean squares regression. We make a comparative evaluation of the relative performance of polynomial and artificial neural networks approximations to measurement data with particular attention paid to the reduction of the required calibration set dimension to obtain a given accuracy.

A temperature-compensated system for magnetic field measurements based on artificial neural networks

This paper presents a personal-computer-controlled system, assembled mainly with IEEE 488 general purpose instruments and aimed at the measurement of magnetic field intensity. The main sensor element in the system is a magnetoresistive field sensor which includes four permalloy strips connected in a Wheatstone bridge configuration. The temperature dependence of this sensor can vary almost 25% in the experimental operating temperature range (20/spl deg/C-100/spl deg/C). In order to overcome this problem, a two-terminal integrated circuit temperature transducer is connected to the system, and its temperature information is used to correct the temperature drift error of the magnetic sensor. Artificial neural networks are used for data reduction and final results show an improvement in the systems accuracy from 20% to 2%.

Minimising temperature drift errors of conditioning circuits using artificial neural networks

Temperature drift errors are a problem that affect the accuracy of measurement systems. When small amplitude signals from transducers are considered and environmental conditions of conditioning circuits exhibit a large temperature range, the temperature drift errors have a real impact in systems accuracy. In this paper, a solution to overcome the problem of temperature drift errors of conditioning circuits is proposed. As an example, a thermocouple-based temperature measurement system is considered, and the stability of its conditioning circuit (AD595) is analyzed in two cases: with and without temperature drift error compensation. An Artificial Neural Network (ANN) is used for data optimization and a Virtual Instrument, using GPIB instrumentation, is used to collect experimental data. Final results show a significant improvement in the accuracy of the system when the proposed temperature drift error compensation technique is applied to compensate errors caused by temperature variations.

A fieldbus prototype for educational purposes

One of the problems with instrumentation systems is the interconnection between the multiple devices with different communication protocols. Exacerbating this problem are two typical requirements of interconnection: minimize cabling cost and avoid degradation of the signal during transmission. Cabling cost can be reduced through several multidrop communication systems: industrial local area networks or wireless communication. Reduction of signal to noise can restrict system performance and the quality of manufactured products, even if high-accuracy devices are used. Another problem in the field of manufacturing instrumentation networks is that industry uses multiple solutions to interconnect instrumentation with different communication protocols. This article presents the development of a prototype for an instrumentation network with the goal to study and analyze the characteristics of the different communication solutions. The overall system contains a large number of instrumentation devices, which is a great advantage for educational purposes and laboratory experiments. The students can configure, calibrate, and operate a large number of instruments connected to different segments of the DCS. We also connected some current-loop devices to the FF system to evaluate their performance when connected to a fully digital network. Results from the prototype DCS show that networking between different instrumentation devices and protocols can be successful and that a hybrid solution using conventional 4-20 mA current loop and fully digital instrumentation can work to leverage existing analogue systems. Future work will include the development of a fieldbus network analyzer to trace messages in the network and study the quality of FF service parameters, such as packet loss and delay measurement, as a function of network load.

Multi-usage of microwave Doppler radar in pervasive healthcare systems for elderly

Health assessment requirements for aging population have accentuated the need of ubiquitous and pervasive e-Health environments. Recently, new implemented embedded vital signs sensors were joined to ubiquitous computation in order to materialize Ubi-Health systems with lower price and augmented interoperability in comparison with traditional clinical instrumentation for in house health status monitoring needs. The work reports the utilization of the smart sensor based on 24GHz microwave FMCW (frequency modulated continuous wave) Doppler embedded in smart objects such as wheelchairs, walkers or crutches used by elderly, that perform cardiorespiratory signs and physical activity monitoring. According to the requirements of sensor identification and wireless data communication between the smart sensor and the advanced signal processing, data logging and web publishing unit, a combination between Bluetooth MAC based identification and Virtual Transducer Electronic Data Sheet was implemented. The system allows vital signs and motor activity monitoring, including gait characterization.

Real-Time Sensing Channel Modelling Based on an FPGA and Real-Time Controller

This paper presents the concept of reconfigurable sensing channel characteristics inverse model in auto-calibration measurement systems, particularly for water quality measuring systems. The inverse model implementation is supported on an advanced FPGA reconfigurable embedded control and acquisition system (CompactRIO). Model blocks, such as polynomial and neuronal, are on-line updated (reconfigured) in the cRIO real time controller using calibration data while the on-line processing of the measured physical quantities (e.g. water quality quantities: conductivity) are mainly processed by the RIO FPGA core

An ANN fault detection procedure applied in virtual measurement systems case

The prompt detection of anomalous conditions of the Virtual Measurement Systems (VMS) elements, as sensors or transducers, involve a specialised implementation of the VMS software part. One solution for this software implementation is based on the neural processing structures. The implemented Artificial Neural Networks (ANN) are supplied with the voltage signals delivered by the conditioning circuits of the VMS sensors. The signal acquisition was performed using a data acquisition board or a programmable voltmeter. For the acquired signals the ANN delivers the values which can be used for fault detection and localisation of faulty elements. Referring to ANN architectures a study concerning the number of layers, the number of processing neurons, the type of neuron activation functions and the possibilities to optimise those parameters is included in this paper. The performance of proposed ANN fault detection solution was experimentally evaluated in the particular case of a VMS based on a data acquisition board (DAQ) and on a GPIB controller.

Toward developing a smart wheelchair for user physiological stress and physical activity monitoring

The article presents a smart wheelchair characterized by embedded sensors and an acquisition, processing and communication platform based on a multifunction I/O module and an embedded PC for monitoring of physiological stress parameters and motion activity of the wheelchair user in unobtrusive way. The embedded sensors include E-textile electrodes attached to the wheelchair arms and a 3D MEMS accelerometer used to extract the motion activity information. Additional sensing channels, expressed by piezoresistive flexible force sensors are used to optimize the measurement of contact ECG and skin conductivity. A server application, developed in LabVIEW and hosted on the embedded computer, delivers information about the digital processed signals to the client application installed in mobile platforms such as tablet PC or smartphones. The mobile platform provides interface for nurses, physiotherapists or physicians as well as for the wheelchair user or informal caregivers.

Dithering performance of oversampled ADC systems affected by hysteresis

Abstract This paper addresses the problem of hysteresis in ADC systems and the improvement that can be obtained in the performance of such systems with the use of dithering and oversampling. The paper starts with an analysis of ADC hysteresis errors considering their effect on the quantization error and effective number of bits of an ADC system. It concludes with a study of the improvements obtained using dithering in over sampled ADC systems with hysteresis errors. Special attention is paid to the effect of different time sequences of a deterministic dither signal. Experimental results that validate theoretical predictions are also presented.

A low cost measurement system to extract kinematic parameters from walker devices

This paper presents a low cost measurement system that can be used to extract kinematic parameters from walker devices. The proposed measurement system can be easily integrated in any commercial non-smart walker device and includes mainly a set of six force sensing resistors and one 3D accelerometer, with the associated signal conditioning circuits, and the data acquisition and processing unit with wireless communication capabilities. The signals that are acquired from the sensors are used to obtain, in real time, the values of several variables related with strength, acceleration and tilt angles that are associated with the usage of walker devices. The proposed measurement system enables the detection of conditions that are related with a deficient usage of the walker device, such as, bad positioning of the walker legs during gait, amplitude and timing unbalances of the forces applied on the walker legs or on the walker hand grips, excessive values of mechanical oscillations or tilt angles of the walker device. Some calibration and experimental results are included in the paper.