Signal Conditioning Circuit Research Articles

Preparation and Characterization of BaTiO3–PbZrTiO3 Coating for Pyroelectric Energy Harvesting

Harvesting energy from waste heat is a promising field of research as there are significant energy recovery opportunities from various waste thermal energy sources. The present study reports pyroelectric energy harvesting using thick film prepared from a (x)BaTiO3–(1 − x)PbZr0.52Ti0.48O3 (BT–PZT) solid solution. The developed BT–PZT system is engineered to tune the ferro to paraelectric phase transition temperature of it in-between the phase transition temperature of BaTiO3 (393 K) and PbZrTiO3 (573 K) with higher pyroelectric figure-of-merit (FOM). The temperature-dependent dielectric behavior of the material has revealed the ferro- to paraelectric phase transition at 427 K with a maximum dielectric constant of 755. The room-temperature (298 K) pyroelectric coefficient (Pi) of the material was obtained as 738.63 μC/m2K which has yielded a significantly high FOM of 1745.8 J m−3 K−2. The enhancement in pyroelectric property is attributed to the morphotopic phase transition between tetragonal and rhombohedral PZT phases in the BT–PZT system. The developed BT–PZT system is capable of generating a power output of 1.3 mW/m2 near the Curie temperature with a constant rate (0.11 K/s) of heating. A signal conditioning circuit has been developed to rectify the time-varying current and voltage signals obtained from the harvester during heating cycles. The output voltage generated by the pyroelectric harvester has been stored in a capacitor for powering wearable electronics.

A User-Configurable Headstage for Multimodality Neuromonitoring in Freely Moving Rats.

Multimodal monitoring of brain activity, physiology, and neurochemistry is an important approach to gain insight into brain function, modulation, and pathology. With recent progress in micro- and nanotechnology, micro-nano-implants have become important catalysts in advancing brain research. However, to date, only a limited number of brain parameters have been measured simultaneously in awake animals in spite of significant recent progress in sensor technology. Here we have provided a cost and time effective approach to designing a headstage to conduct a multimodality brain monitoring in freely moving animals. To demonstrate this method, we have designed a user-configurable headstage for our micromachined multimodal neural probe. The headstage can reliably record direct-current electrocorticography (DC-ECoG), brain oxygen tension (PbrO2), cortical temperature, and regional cerebral blood flow (rCBF) simultaneously without significant signal crosstalk or movement artifacts for 72 h. Even in a noisy environment, it can record low-level neural signals with high quality. Moreover, it can easily interface with signal conditioning circuits that have high power consumption and are difficult to miniaturize. To the best of our knowledge, this is the first time where multiple physiological, biochemical, and electrophysiological cerebral variables have been simultaneously recorded from freely moving rats. We anticipate that the developed system will aid in gaining further insight into not only normal cerebral functioning but also pathophysiology of conditions such as epilepsy, stroke, and traumatic brain injury.

Passive Resistor Temperature Compensation for a High-Temperature Piezoresistive Pressure Sensor.

The main limitation of high-temperature piezoresistive pressure sensors is the variation of output voltage with operating temperature, which seriously reduces their measurement accuracy. This paper presents a passive resistor temperature compensation technique whose parameters are calculated using differential equations. Unlike traditional experiential arithmetic, the differential equations are independent of the parameter deviation among the piezoresistors of the microelectromechanical pressure sensor and the residual stress caused by the fabrication process or a mismatch in the thermal expansion coefficients. The differential equations are solved using calibration data from uncompensated high-temperature piezoresistive pressure sensors. Tests conducted on the calibrated equipment at various temperatures and pressures show that the passive resistor temperature compensation produces a remarkable effect. Additionally, a high-temperature signal-conditioning circuit is used to improve the output sensitivity of the sensor, which can be reduced by the temperature compensation. Compared to traditional experiential arithmetic, the proposed passive resistor temperature compensation technique exhibits less temperature drift and is expected to be highly applicable for pressure measurements in harsh environments with large temperature variations.

Wireless sensor nodes for generic signal conditioning: Application to Structural Health Monitoring of wind turbines

Condition monitoring, fault diagnosis and Structural Health Monitoring (SHM) are an essential part of predictive maintenance. In order to provide early warning of damage, wireless sensor nodes are located at structures, which are often in hostile and hard to access environments. Therefore, there is a need of using sensor nodes with low power signal conditioning electronics, wide range measurement, synchronous data acquisition and reliable signal transmission within large scale-networks.The sensor nodes developed in this work contain a transducer, a signal conditioning circuit and a signal processing software, and are powered by a small rechargeable lithium-ion polymer battery. The signal conditioning circuit is generic and configurable, enabling the conditioning of accelerometers and strain gages, and the signal acquisition of the nodes is performed through wireless synchronized communication.The performance of the presented device is demonstrated for SHM of wind turbines. The commonly used system for SHM of wind turbines is installed during the construction of the structure and consists of wired sensors connected to a central data acquisition unit via cables. In this respect, the system developed in this work, which forms a wireless sensor network (WSN) for SHM, is compared to the commonly used system for SHM of wind turbines. The developed WSN offers two main advantages with respect to commonly used systems for SHM: installation and maintenance cost, and time, high reduction.

A High-Temperature Piezoresistive Pressure Sensor with an Integrated Signal-Conditioning Circuit.

This paper focuses on the design and fabrication of a high-temperature piezoresistive pressure sensor with an integrated signal-conditioning circuit, which consists of an encapsulated pressure-sensitive chip, a temperature compensation circuit and a signal-conditioning circuit. A silicon on insulation (SOI) material and a standard MEMS process are used in the pressure-sensitive chip fabrication, and high-temperature electronic components are adopted in the temperature-compensation and signal-conditioning circuits. The entire pressure sensor achieves a hermetic seal and can be operated long-term in the range of −50 °C to 220 °C. Unlike traditional pressure sensor output voltage ranges (in the dozens to hundreds of millivolts), the output voltage of this sensor is from 0 V to 5 V, which can significantly improve the signal-to-noise ratio and measurement accuracy in practical applications of long-term transmission based on experimental verification. Furthermore, because this flexible sensor’s output voltage is adjustable, general follow-up pressure transmitter devices for voltage converters need not be used, which greatly reduces the cost of the test system. Thus, the proposed high-temperature piezoresistive pressure sensor with an integrated signal-conditioning circuit is expected to be highly applicable to pressure measurements in harsh environments.

Shape memory alloy wire for self-sensing servo actuation

This paper reports on the development of a straightforward approach to realise self-sensing shape memory alloy (SMA) wire actuated control. A differential electrical resistance measurement circuit (the sensorless signal conditioning (SSC) circuit) is designed; this sensing signal is directly used as the feedback for control. Antagonistic SMA wire actuators designed for servo actuation is realized in self-sensing actuation (SSA) mode for direct control with the differential electrical resistance feedback. The self-sensing scheme is established on a 1-DOF manipulator with the discrete time sliding mode controls which demonstrates good control performance, whatever be the disturbance and loading conditions. The uniqueness of this work is the design of the generic electronic SSC circuit for SMA actuated system, for measurement and control. With a concern to the implementation of self-sensing technique in SMA, this scheme retains the systematic control architecture by using the sensing signal (self-sensed, electrical resistance corresponding to the system position) for feedback, without requiring any processing as that of the methods adopted and reported previously for SSA techniques of SMA.

Development of an Intelligent Temperature Transducer

This paper presents the development of an intelligent temperature transducer to measure temperature in the range of 0 °C–100 °C using a negative temperature coefficient (NTC) thermistor. The NTC thermistor is connected in a timer circuit to convert the temperature change into frequency. The timer circuit acts as a signal conditioning circuit (SCC) for the NTC thermistor and exhibits a stable temperature-frequency characteristic with a reasonable error. The Levenberg-Marquardt training algorithm is used in a multilayer perceptron neural network to further reduce the nonlinearity error of the SCC. The trained artificial neural network (ANN) improved the linearity, sensitivity, and precision of the SCC to an appreciable range. A linearity of approximately ±0.8% and the sensitivity of about 5 kHz/°C are achieved. The intelligence of the trained ANN is embedded in a microcontroller unit, and the performance of the developed transducer is experimentally studied on a prototype board.

A CMOS temperature sensor and auto-zeroing circuit with inaccuracy of −1/+0.7 °C between −30 to 150 °C

An energy efficient complementary metal-oxide-semiconductor (CMOS) temperature sensor and signal conditioning circuit with auto zeroing technique has been enunciated in this paper. In the present study, a novel CMOS temperature sensor based on sub-threshold MOS operation has been presented, which is designed for Aerospace applications. The proposed sensor does not use bipolar junction transistor (BJT) for sensing; instead it utilizes the temperature dependency of the threshold voltage of MOSFET. The proposed temperature sensor is designed to sense −30 to 150 °C and its sensitivity is 1.4 mV/°C while the power consumption is 60 nW. The accuracy of sensor is mainly limited by offset and flicker noise (1/f) noise, which is cancel by the autozeroing circuit with the help of switch capacitor circuit. The sensor circuit is designed with biasing sub circuit for controlling the curvature correction. The proposed temperature sensor and signal conditioning are simulated in a Cadence Analog Design Environment with UMC90 nm library. The simulation result shows an inaccuracy of −1/+0.7 °C.

Design and modeling of an intelligent temperature to frequency converter

This paper presents the development of an intelligent temperature to frequency converter to measure the temperature using a negative temperature coefficient (NTC) thermistor. The signal conditioning circuit (SCC) of the NTC thermistor is a modified timer circuit whose control voltage is generated by a difference amplifier. The thermistor SCC acts as a temperature to frequency converter and exhibits a moderate linear temperature-frequency characteristic over a range of 0–100°C with a linearity error of ±3.5%. A multilayer perceptron (MLP) neural network with Levenberg–Marquardt (LM) algorithm is used for modeling and nonlinearity estimation of the converter. The LM algorithm effectively reduces the linearity error as compared to the Broyden–Fletcher–Goldfarb–Shanno (BFGS) and the scaled conjugate gradient (SCG) algorithms. Mean square error (MSE), regression coefficients, linearity, accuracy and dispersion spread are used to evaluate the performance of the proposed ANN-based modeling. The intelligence of the ANN-based modeling is embedded in a low cost microcontroller unit and the performance is experimentally verified on a prototype unit. The linearity error and sensitivity of the proposed unit are approximately ±0.35% and 5kHz/°C respectively.

Design of Smart Sensors for Real-Time Water Quality Monitoring

This paper describes work that has been done on design and development of a water quality monitoring system, with the objective of notifying the user of the real-time water quality parameters. The system is able to measure the physiochemical parameters of water quality, such as flow, temperature, pH, conductivity, and the oxidation reduction potential. These physiochemical parameters are used to detect water contaminants. The sensors, which are designed from first principles and implemented with signal conditioning circuits, are connected to a microcontroller-based measuring node, which processes and analyzes the data. In this design, ZigBee receiver and transmitter modules are used for communication between the measuring and notification nodes. The notification node presents the reading of the sensors and outputs an audio alert when water quality parameters reach unsafe levels. Various qualification tests are run to validate each aspect of the monitoring system. The sensors are shown to work within their intended accuracy ranges. The measurement node is able to transmit data by ZigBee to the notification node for audio and visual display. The results demonstrate that the system is capable of reading physiochemical parameters, and can successfully process, transmit, and display the readings.

Trajectory Tracking Control of a Real Redundant Manipulator of the SCARA Type

Modeling, control and implementation of a real redundant robot with five Degrees Freedom (DOF) of the SCARA (Selective Compliant Assembly Robot Arm) manipulator type is presented. Through geometric methods and structural and functional considerations, the inverse kinematics for redundant robot can be obtained. By means of a modification of the classical sliding mode control law through a hyperbolic function, we get a new algorithm which enables reducing the chattering effect of the real actuators, which together with the learning and adaptive controllers, is applied to the model and to the real robot. A simulation environment including the actuator dynamics is elaborated. A 5 DOF robot, a communication interface and a signal conditioning circuit are designed and implemented for feedback. Three control laws are executed in: a simulation structure (together with the dynamic model of the SCARA type redundant manipulator and the actuator dynamics) and a real redundant manipulator of the SCARA type carried out using MatLab/Simulink programming tools. The results, obtained through simulation and implementation, were represented by comparative curves and RMS indices of the joint errors, and they showed that the redundant manipulator, both in the simulation and the implementation, followed the test trajectory with less pronounced maximum errors using the adaptive controller than the other controllers, with more homogeneous motions of the manipulator.

A New Optical UWB Modulation Technique for 250Mbps Wireless Link in Implantable Biotelemetry Systems

We propose an optical UWB modulation based on a new pulsed coding technique for wireless implantable biotelemetry. The solution employs sub-nanosecond laser pulses allowing for both high data rates and reduction of the power consumption compared to the state-of-the-art. Thus, the proposed approach is suitable for upcoming biomedical systems like autonomous implantable neural devices. The developed architecture consists of a transmitter and a receiver employing a pulsed semiconductor laser and a small sensitive area photodiode, respectively, and includes coding and decoding digital systems, biasing and driving analogue circuits for laser pulse generation and photodiode signal conditioning. Experimental findings, obtained by employing discrete components prototype PCBs and FPGA implementations, validate the novel technique showing the capabilities to achieve a BER less than 10-9 with data rates up to 250Mbps and an estimated power consumption lower than 5mW. These results enable, for example, the transmission of a 1000-channel neural recording system sampled at 16 kHz with 16-bit resolution.

Noise modeling in a signal conditioning circuit for low power audio application using resistive sensor

Piezoresistive sensors convert a physical value into a resistance variation. Often four resistive elements are connected together in a Wheatstone bridge to provide electrical variations of sensors. When this structure is biased with a fixed voltage source or a current source the topology provides a differential output voltage. To exploit information a conditioning circuit is associated to the bridge. In most cases it consists of an instrumentation amplifier followed by a data converter to obtain very quickly a digital representation of information. Due to the high input impedance of the instrumentation amplifier, bridge sensitivity is preserved. A filter may be added to avoid aliasing or a continuous time sigma-delta modulator that includes filtering feature. This study is concerning the conditioning structure for piezoresistive sensors bridge especially fully integrated microphones for biomedical application. The bridge signal to noise ratio is set by biasing the amplifier stage by current. The noise performance becomes the limiting factor of the read-out circuit. Current mode topologies drive amplifiers design where inputs are the main noise contributor. Modeling noise contribution is a key point in the design of the conditioning circuit. The current consumption leads noise performances too. A proposed architecture was implemented in a 65nm CMOS standard technology for performance measurement and evaluation with nanowire based microphone dedicated to hearing aids application.

Performance Optimization of Healthcare Mobile Applications using Embedded System Design and Implementation

An Embedded device is an object that contains a special-purpose computing system. The system, which is completely enclosed by the object, may or may not be able to connect to the Internet. Embedded systems have extensive applications in consumer, commercial, automotive, industrial and healthcare markets. Generally, an embedded device's operating system will only run a single application which helps the device to do its job. The heart of electronics system and also coordinator in communication is embedded system managing biometric data from numerous stationary and on body. This simply means that the device's software does not have a user interface (UI). In such cases, an in-circuit emulator (ICE) is temporarily installed between the embedded device and an external computer to debug or update the software. Because embedded systems have limited computing resources and strict power requirements, writing software for embedded devices is very specialized field that requires knowledge of both hardware components and programming. This work describes the design of mobile medical system that can be used to monitor the human temperature and heart beat using a stand-alone microcontroller. The system hardware architecture consists of temperature and heart beat sensors, signal conditioning circuits (SCC), single chip microcontroller, LCD display and GSM modem. An embedded software algorithm acquires temperature, heart beat and pressure, processes, transmits, displays and stores it in the built-in EPROM of the microcontroller.

온도보상회로를 부착한 개방형 전류측정기의 특성

Open-type current sensors have been commonly used for DC motor controller, AC variable controller and Uninterruptible Power Supply. Recently they have begun to be used more widely, as the growth of renewable energy and smart-grid in power system. Considering most of the open-type current sensors are imported, developing the core technology needed to produce open-type current sensors is required. This paper describes the development and test results of open-type current sensors. Design of C type magnetic core, selection and test of a Hall sensor, design of current source circuit and signal conditioning circuit are described. 100A class DIP(Dual In-line Package) type and SMD(Surface Mount Devide) type open-type current sensors was made and tested. Test results show that the developed open-type current sensor satisfies the accuracy requirement of 2% and linearity requirement of 2% at 100 A of DC and AC current of 60Hz. Temperature compensation was carried out by using a temperature compensation circuit with NTC(Negative Temperature Coefficient) thermistor and the effect of the temperature compensation are described.

Development of an intelligent pressure measuring technique for bellows using radial basis function neural network

This paper presents the implementation of an intelligent pressure transmitter to measure pressure using a bellow sensor. In industrial applications, the deflection of the bellow due to applied pressure must be translated into an efficient electrical readout for monitoring, transmission and control. An inductive pick-up is used to convert the deflection of the bellow into the change in self-inductance of a coil. The signal conditioning circuit designed for the bellow sensor with the inductive coil is an inductance to voltage conversion circuit (ITVCC). The stray inductances, component tolerances and ambient factors introduce errors in the output of the ITVCC. The voltage–pressure relation exhibits a considerable nonlinearity and limits the measurement to local operations. In this aspect, we propose an artificial neural network (ANN) using a radial basis function to estimate and compensate the nonlinearity of the ITVCC. The intelligence of ANN modeling is incorporated into an embedded plug-in-module (EPIM). The output voltage of the EPIM is converted into a 4–20mA current signal for further processing. The performance of the proposed technique is experimentally verified. The nonlinearity expressed as maximum deviation from the desired response is within ±0.6% of full scale reading. The design aspects, simulation analysis and experimental results of the technique are reported.

Design and Implementation Model for Linearization Sensor Characteristic by FPAA

Linearization sensors characteristics becomes very interest field for researchers due to the importance in enhance the system performance, measurement accuracy, system design simplicity (hardware and software), reduce system cost, ..etc. in this paper, two approaches has been introduced in order to linearize the sensor characteristics; first is signal condition circuit based on lock up table (LUT) which this method performed for linearize NTC sensor characteristic. Second is ratiometric measurement equation which this method performed for linearize LVDT sensor characteristic. The proposed methods has been simulated by MATLAB, and then implemented by using Anadigm AN221E04 Field Programmable Analog Array (FPAA) development kit which several experiments performed in order to improve the performance of these approaches.

Labview Based ECG Patient Monitoring System for Cardiovascular Patient Using SMTP Technology

This paper leads to developing a Labview based ECG patient monitoring system for cardiovascular patient using Simple Mail Transfer Protocol technology. The designed device has been divided into three parts. First part is ECG amplifier circuit, built using instrumentation amplifier (AD620) followed by signal conditioning circuit with the operation amplifier (lm741). Secondly, the DAQ card is used to convert the analog signal into digital form for the further process. Furthermore, the data has been processed in Labview where the digital filter techniques have been implemented to remove the noise from the acquired signal. After processing, the algorithm was developed to calculate the heart rate and to analyze the arrhythmia condition. Finally, SMTP technology has been added in our work to make device more communicative and much more cost-effective solution in telemedicine technology which has been key-problem to realize the telediagnosis and monitoring of ECG signals. The technology also can be easily implemented over already existing Internet.

Design and Implementation Model for Linearization Sensor Characteristic by FPAA

Linearization sensors characteristics becomes very interest field for researchers due to the importance in enhance the system performance, measurement accuracy, system design simplicity (hardware and software), reduce system cost, ..etc. in this paper, two approaches has been introduced in order to linearize the sensor characteristics; first is signal condition circuit based on lock up table (LUT) which this method performed for linearize NTC sensor characteristic. Second is ratiometric measurement equation which this method performed for linearize LVDT sensor characteristic. The proposed methods has been simulated by MATLAB, and then implemented by using Anadigm AN221E04 Field Programmable Analog Array (FPAA) development kit which several experiments performed in order to improve the performance of these approaches.

Design and Uncertainty Evaluation of a Strain Measurement System

Strain measurement is very important in various industrial applications as well as different disciplines of science and technology for direct and indirect observations of certain parameters. Designing signal conditioning circuit is always a challenging and important task for satisfactory and reliable performance of a sensor as well as the system. The design and implementation details of a signal conditioning circuit of resistive sensor (strain gauge) for strain measurement are presented in this paper. Also the important aspects in designing a signal conditioning circuit for resistive sensor are presented and a novel method for the measurement of strain is discussed. Quarter bridge configuration with AC voltage excitation is used for the measurement along with the necessary circuitry to get a suitable and measurable output DC voltage. The measurement system is calibrated using a cantilever of stainless steel and the details of calibration are presented in the paper. The uncertainty associated with the measurement system is evaluated.