Acquisition Board Research Articles

Development of a Didactic Educational Tool for Learning Fuzzy Control Systems

This paper presents the development of a virtual didactic tool for students of mechatronic engineering taking an intelligent system course. The objective of the tool is for students to learn the structures for fuzzy control systems. This tool makes it easier for students to understand the behavior of the membership functions of input and output variables, the evaluation of the set of fuzzy rules, and the method of defuzzification, giving the students the possibility of applying a fuzzy controller in industrial processes using a data acquisition board. The proposed tool was developed with the virtual instrumentation software LabVIEW. It has the advantage that students can manipulate the internal structure of the fuzzy logic control system in a unique window where students can analyze the behavior of internal signals by looking at the response graphs. The fuzzy controller can be easily translated to a real application by using LabVIEW compatible hardware. To have feedback from students on the use of the tool and to understand if this tool allows an improvement in their academic performance, a 2-hour workshop on the proposed application was given to a group of 93 students. At the end of the workshop, a knowledge assessment and a perception survey were applied to the participants. The academic performance achieved by students who were given the workshop using the proposed teaching tool was compared with the academic performance of students who witnessed the workshop using Matlab tools. The statistical analysis of the results obtained for the knowledge assessment shows that the students that had taken the workshop using the proposed teaching tool had better compression of the topic compared to the students that had taken the workshop using the Fuzzy Logic Toolbox provided by Matlab MathWorks. The students that had taken the workshop using the proposed teaching tool obtained a mean grade of 89.63/100, while students that had taken the workshop using Matlab’s tools obtained a mean grade of 69.85/100. Also, the students’ perception of the proposed tool was that it allowed the design of fuzzy control systems in a simple and intuitive way.

A Comprehensive Design of Six-Axis Force/Moment Sensor.

Strain gage type six-axis force/moment (F/M) sensors have been largely studied and implemented in industrial applications by using an external data acquisition board (DAQ). The use of external DAQs will ill-affect accuracy and crosstalk due to the possibility of voltage drop through the wire length. The most recent research incorporated DAQ within a relatively small F/M sensor, but only for sensors of the capacitance and optical types. This research establishes the integration of a high-efficiency DAQ on six-axis F/M sensor with a revolutionary arrangement of 32 strain gages. The updated structural design was optimized using the sequential quadratic programming method and validated using Finite Element Analysis (FEA). A new, integrated DAQ system was designed, tested, and compared to commercial DAQ systems. The proposed six-axis F/M sensor was examined with the calibrated jig. The results show that the measurement error and crosstalk have been significantly reduced to 1.15% and 0.68%, respectively, the best published combination at this moment.

Design of prototype readout electronics system for gamma-gamma collider

The γγ collider is proposed in China to observe γγ scattering and the Breit Wheeler (BW) pairs production.This paper presents a prototype readout electronics system that is intended to provide a suitable readout solution for the γγ collider. The paper analyzes the readout requirements of electronics such as implementation of 1426 electronical channels in a limited space, stability in vacuum working environment and incident particle discrimination. To meet the requirements, the paper proposes a high-density, low-power and high-sampling-rate (1 GHz) prototype readout electronics system using waveform digitization technology based on switch capacitor array (SCA) DRS4 chips and analog-to-digital converters (ADC). The prototype readout system is composed of 8 front-end electronics (FEE) boards and a data acquisition (DAQ) board. The FEE board can digitize 180-channel signals from the collider and send packaged data to the DAQ board via high-speed optical fiber. The paper proves the particle discrimination ability and the stability of the prototype electronics system in the joint-test with other detectors, which provides a strong guarantee for the subsequent development of the γγ collider.

An IoT optical sensor for photometric determination of oxalate in infusions

A new device exploiting an optical sensor and a remote-controlled IoT-Bluetooth acquisition board has been proposed for photometric measurements. A visible light-to-digital sensor (TSL2591) was connected to a microcontroller and the response signals were sent wirelessly over the Bluetooth connection. A LED was used as a light source for absorbance measurements. The point-of-care device was designed and fabricated using an FDM-based 3D printer with ABS thermoplastic filament, providing low-cost housing for the optoelectronics and the sample cell. To demonstrate the applicability effectiveness of our new device, an oxalate photometric smart sensor has been development. The quantification method exploited the reaction between oxalate and the red-colored complex Zr(IV)–SPADNS, leading to the decrease of color intensity associated with 590 nm. The analytical performance of the optical sensor obtained a linear range of 0.3–10 mg L−1, with limit of detection (LOD) and limit of quantification (LOQ) values of 0.2 mg L−1 and 0.7 mg L−1, respectively. The method was applied for the determination of oxalate in some infusions samples with satisfactory results and recoveries in the range of 96.6–109.7%. Miniaturized LED-based photometer approaches for oxalate determination presented an analytical performance similar to those obtained with the commercial spectrophotometer. However, the marriage of LED-based photometer with optical sensor enables the development of powerful IoT platforms for many important applications including food samples.

A Portable Waterproof EEG Acquisition Device for Dolphins.

The acquisition and analysis of EEG signals of dolphins, a highly intelligent creature, has always been a focus of the research of bioelectric signals. Prevailing cable-connected devices cannot be adapted to data acquisition very well when dolphins are in motion. Therefore, this study designs a novel, light-weighted, and portable EEG acquisition device aimed at relatively unrestricted EEG acquisition. An embedded main control board and an acquisition board were designed, and all modules are encapsulated in a 162 × 94 × 60 mm3 waterproof device box, which can be tied to the dolphin’s body by a silicon belt. The acquisition device uses customized suction cups with embedded electrodes and adopts a Bluetooth module for wireless communication with the ground station. The sampled signals are written to the memory card on board when the Bluetooth communication is blocked. A limited experiment was designed to verify the effectiveness of the device functionality onshore and underwater. However, more rigorous long-term tests on dolphins in various states with our device are expected in future to further prove its capability and study the movement-related artifacts.

Evaluation of thickness‐dependent temperature coefficient in a thin film thermocouple and its in vivo test using a porcine model

A micromachined thin film thermocouple (TFTC), that is, a contact-type temperature sensor, was fabricated to diagnose the physiological state. The TFTC involved two metal films (copper and constantan) with considerably different Seebeck coefficients. Six types of TFTCs with different film thickness values were fabricated and experimentally characterized to determine the thickness-dependent temperature coefficient attesting to a high sensitivity of the sensors. The performance of each TFTC was evaluated by measuring the induced thermal electric motive force and temperature in the temporal and spatial domains by using a data acquisition board and an infrared camera, respectively. Moreover, an in vivo experiment of the proposed TFTC with the highest temperature coefficient (38.9 µV/°C) was conducted by measuring the body temperature difference of an anesthetized porcine model during its euthanasia process to evaluate the device performance.

Development and Initial Results of a Brain PET Insert for Simultaneous 7-Tesla PET/MRI Using an FPGA-Only Signal Digitization Method.

In study, we developed a positron emission tomography (PET) insert for simultaneous brain imaging within 7-Tesla (7T) magnetic resonance (MR) imaging scanners. The PET insert has 18 sectors, and each sector is assembled with two-layer depth-of-interaction (DOI)-capable high-resolution block detectors. The PET scanner features a 16.7-cm-long axial field-of-view (FOV) to provide entire human brain images without bed movement. The PET scanner early digitizes a large number of block detector signals at a front-end data acquisition (DAQ) board using a novel field-programmable gate array (FPGA)-only signal digitization method. All the digitized PET data from the front-end DAQ boards are transferred using gigabit transceivers via non-magnetic high-definition multimedia interface (HDMI) cables. A back-end DAQ system provides a common clock and synchronization signal for FPGAs over the HDMI cables. An active cooling system using copper heat pipes is applied for thermal regulation. All the 2.17-mm-pitch crystals with two-layer DOI information were clearly identified in the block detectors, exhibiting a system-level energy resolution of 12.6%. The PET scanner yielded clear hot-rod and Hoffman brain phantom images and demonstrated 3D PET imaging capability without bed movement. We also performed a pilot simultaneous PET/MR imaging study of a brain phantom. The PET scanner achieved a spatial resolution of 2.5 mm at the center FOV (NU 4) and a sensitivity of 18.9 kcps/MBq (NU 2) and 6.19% (NU 4) in accordance with the National Electrical Manufacturers Association (NEMA) standards.

Arduino: a Novel Solution to the Problem of High-Cost Experimental Equipment in Higher Education

The acquisition of experimental equipment has become a problem, due to its high costs. To partially solve this problem, the scientific community has used the Arduino data acquisition board (DAB). This board has a low-cost and allows the automation of equipment in a simple and practical way. However, using only the Arduino board is no longer enough, it is now necessary to combine it with the implementation of an user-friendly interface. Through this combination, it is possible to develop sophisticated laboratory equipment. The aim of this work is to describe step by step and in a simple way the development and implementation of a low-cost experimental equipment based on Arduino for use in higher education. Also, this work tries to encourage users to develop their own laboratory equipment, and solve their equipment needs. The novelty of this work pretends to be that any user without a deep knowledge of electronics and programming can easily assemble their own lab equipment, avoiding high equipment fees. In this work, three simple examples are shown, and any teacher, researcher, or student can easily reproduce them. With the combination of three previous examples, it is possible to develop sophisticated laboratory equipment, for example a Ph Meter with temperature sensor and stirring setup. The commercial cost of this lab equipment is approximately 600 USD, but with this homemade setup, the total cost drops to 75 USD.

Research on speed estimation of hub-motor vehicle based on multi-sensor information fusion

Accurate acquisition of longitudinal and lateral velocity of the vehicle plays an important role in the modern automobile control system. In this paper, the vehicle speed test system is composed of multiple sensors, data acquisition board (NI cDAQ9137) and LabVIEW software. The real-time acquisition of front-wheel angle, wheel speed, longitudinal acceleration, lateral acceleration, and yaw velocity of the hub-motor vehicle is completed by using the speed measuring system. Based on the real road test results, the vehicle speed estimation is obtained by Kalman filter technology and compared with the reference vehicle dynamics model. The comparison results show that the vehicle speed estimation has high accuracy and can meet the requirements of state parameter estimation. The algorithm has the advantages of simple structure, small computation and easy implementation and can provide more information for the automobile control system.

Electromagnetic Induction Imaging at Multiple Depths With a Single Coil

Electromagnetic induction imaging (EII) is an attractive imaging modality due to its contactless operation, low cost, and good penetration depth. To implement real-time imaging, in applications such as object tracking or functional biomedical imaging, fast data acquisition is required. To proceed toward this goal, in this article, we propose the use of a single coil for 3-D EII along with a fast inversion approach. To collect sufficient data that allow 3-D imaging, we propose two approaches: collecting data at multiple coil’s drive current levels and collecting data with multiple tank circuit’s capacitor values. We show that the use of such data when using a single coil allows for 3-D EII. For proof-of-concept experiments, we use a commercial data acquisition board, that is, LDC1614EVM module, and multilayer planar coils made by Texas Instruments.

Calling songs of Neotropical katydids (Orthoptera: Tettigoniidae) from Panama

Understanding the ecology and evolution of animal communication systems requires detailed data on signal structure and variation across species. Here, we describe the male acoustic signals of 50 species of Neotropical katydids (Orthoptera: Tettigoniidae) from Panama, with the goal of providing data and recordings for future research on katydid communication, evolution, ecology, and conservation. Male katydids were recorded individually using an ultrasound-sensitive microphone and high-sampling rate data acquisition board to capture both audible and ultrasonic components of calls. Calls varied enormously in duration, temporal patterning, peak frequency, and bandwidth both across and within subfamilies. We confirm previous studies showing that katydid species within the subfamily Pseudophyllinae produced short calls (<250 ms) at long intervals and we confirm that this is true for species in the subfamily Phaneropterinae as well. Species in the Conocephalinae, on the other hand, typically produced highly repetitive calls over longer periods of time. However, there were exceptions to this pattern, with a few species in the Conocephalinae producing very short calls at long intervals, and some species in the Phaneropterinae producing relatively long calls (1–6 s) or calling frequently. Our results also confirm previous studies showing a relationship between katydid size and the peak frequency of the call, with smaller katydids producing higher frequency calls, but the slope of this relationship differed with subfamily. We discuss the value of documenting the diversity in katydid calls for both basic studies on the ecology, evolution, and behavior of these species as well as the potential conservation benefits for bioacoustics monitoring programs.

Design of a downlink algorithm for rotary steering (logging while drilling) systems

For logging while drilling (LWD) systems, it is necessary to adjust the working state of the downhole tools in real-time according to different operating conditions. In this paper, on the basis of the characteristics of LWD systems, a mud pressure-apperceived downlink system was examined. For the design of this system, a signal acquisition and processing board was created based on a piezoelectric ceramic sensor to acquire the mud pressure signal. The error sources of the downlink command sending process were analyzed, and an error accumulation compensation processing algorithm was proposed to improve the recognition success rate of the downhole system. Moreover, to reduce noise interference on the characteristics of the mud impulse signal, a filtering algorithm was proposed based on the empirical mode decomposition method, and the success rate of instruction issuance was determined by identifying feedback instructions. Field tests were conducted to further improve the system, the results of which suggested that the system had good mud adaptability, high recognition success rate, and a certain application value.

Wireless, miniaturized, semi-implantable electrocorticography microsystem validated in vivo

This paper reports on the design, development, and test of a multi-channel wireless micro-electrocorticography (µECoG) system. The system consists of a semi-implantable, ultra-compact recording unit and an external unit, interfaced through a 2.4 GHz radio frequency data telemetry link with 2 Mbps (partially used) data transfer rate. Encased in a 3D-printed 2.9 cm × 2.9 cm × 2.5 cm cubic package, the semi-implantable recording unit consists of a microelectrode array, a vertically-stacked PCB platform containing off-the-shelf components, and commercially-available small-size 3.7-V, 50 mAh lithium-ion batteries. Two versions of microelectrode array were developed for the recording unit: a rigid 4 × 2 microelectrode array, and a flexible 12 × 6 microelectrode array, 36 of which routed to bonding pads for actual recording. The external unit comprises a transceiver board, a data acquisition board, and a host computer, on which reconstruction of the received signals is performed. After development, assembly, and integration, the system was tested and validated in vivo on anesthetized rats. The system successfully recorded both spontaneous and evoked activities from the brain of the subject.

A Densely-Deployed, High Sampling Rate, Open-Source Air Pollution Monitoring WSN

Air quality, especially particulate matter, has recently attracted a lot of attention from governments, industry, and academia, motivating the use of denser air quality monitoring networks based on low-cost sensing strategies. However, low-cost sensors are frequently sensitive to aging, environmental conditions, and pollutant cross-sensitivities. These issues have been only partially addressed, limiting their usage. In this study, we develop a low-cost particulate matter monitoring system based on special-purpose acquisition boards, deployed for monitoring air quality on both stationary and mobile sensor platforms. We explore the influence of all model variables, the quality of different calibration strategies, the accuracy across different concentration ranges, and the usefulness of redundant sensors placed in each station. The collected sensor data amounts to about 50GB of data, gathered in six months during the winter season. Tests of statically immovable stations include an analysis of accuracy and sensors’ reliability made by comparing our results with more accurate and expensive standard $\beta$ -radiation sensors. Tests on mobile stations have been designed to analyze the reactivity of our system to unexpected and abrupt events. These experiments embrace traffic analysis, pollution investigation using different means of transport and pollution analysis during peculiar events. With respect to other approaches, our methodology has been proved to be extremely easy to calibrate, to offer a very high sample rate (one sample per second), and to be based on an open-source software architecture. Database and software are available as open source in [1] .

Data processing from electrical signals acquired by an E-nose system used for quality control of cocoa

This research consists of the implementation of different pattern recognition methods applied to discriminate and classify the physical signals (electrical) acquired by an artificial electronic nose system composed of a gas sensor array of 10 units coupled with a data acquisition board that were used to perform a sensor chamber that receives the electrical information from volatile organic compounds generated by cacao beans. A concentration chamber for samples conditioning of fermented beans was used and the samples were fermented around 72 and 144 hours while the cacao samples infected with monilia were over-fermented. For obtaining the temperature inside of the sensor chamber, a digital temperature sensor was implemented by using a Peltier Cell mechanism which was controlled through a classical algorithm. At the design stage, a data acquisition system composed of an Arduino card and a graphical interface made in LabView was developed for data storing, controlling, and signals monitoring. For the electrical signals treatment and data analysis, two pattern recognition models were applied by using Python software where two signals pre-processing methods such as Euclidean normalization and Roboust Scaling were used afterward with data processing techniques as principal component analysis and clusters analysis, obtaining a 96.51% of variance in the two first components.

I4.0 Pilot Project on a Semiconductor Industry: Implementation and Lessons Learned.

Industry 4.0 considers the combinations of Internet of Things, computing and communication infrastructure, sensors, and artificial intelligence (AI) to provide predictive maintenance and process optimization. These benefits are very relevant to the semiconductor industry, where high reliability and low operating costs are critical for a business’ success. Analyzing the state-of-the-art of the projects that present the implementation of the fourth industrial revolution in semiconductor companies, we noticed mainly two branches of initiatives: (i) articles that explain the final achievements, not detailing how they were assembled and structured; (ii) articles that detail a part of the industry ecosystem, for example, approaching only the communication system or AI algorithms. In this context, this article proposes an I4.0 Pilot as a compilation of lessons learned during an end-to-end development of a reference design applied to a semiconductor packaging and test company. We explore the requirements of clean rooms and information related to sensors and data acquisition boards, in addition to performance details and configurations pertaining to visualization tools and warning notifications. The main contribution appears in presenting the advantages of adopting flexible decisions in the pilot to enable the best characteristics for a final expandable solution. Our final idea is to emphasize the importance of having a pilot project without significant expenses, presenting the reader with the acquired knowledge, and how they can benefit from it.

Wearable Physiological Monitoring System Based on Electrocardiography and Electromyography for Upper Limb Rehabilitation Training.

Secondary injuries are common during upper limb rehabilitation training because of uncontrollable physical force and overexciting activities, and long-time training may cause fatigue and reduce the training effect. This study proposes a wearable monitoring device for upper limb rehabilitation by integrating electrocardiogram and electromyogram (ECG/EMG) sensors and using data acquisition boards to obtain accurate signals during robotic glove assisting training. The collected ECG/EMG signals were filtered, amplified, digitized, and then transmitted to a remote receiver (smart phone or laptop) via a low-energy Bluetooth module. A software platform was developed for data analysis to visualize ECG/EMG information, and integrated into the robotic glove control module. In the training progress, various hand activities (i.e., hand closing, forearm pronation, finger flexion, and wrist extension) were monitored by the EMG sensor, and the changes in the physiological status of people (from excited to fatigue) were monitored by the ECG sensor. The functionality and feasibility of the developed physiological monitoring system was demonstrated by the assisting robotic glove with an adaptive strategy for upper limb rehabilitation training improvement. The feasible results provided a novel technique to monitor individual ECG and EMG information holistically and practically, and a technical reference to improve upper limb rehabilitation according to specific treatment conditions and the users’ demands. On the basis of this wearable monitoring system prototype for upper limb rehabilitation, many ECG-/EMG-based mobile healthcare applications could be built avoiding some complicated implementation issues such as sensors management and feature extraction.

A Low-Cost, Small-Size, and Bluetooth-Connected Module to Detect Faults in Rolling Bearings

Condition monitoring techniques have been successfully applied to detect damaged bearings. However, the signal acquisition and the subsequent processing are typically outsourced to expensive data acquisition boards and complex software, resulting in expensive solutions. As a side effect, the integration of condition monitoring systems in wireless sensor networks can be tough to achieve. Aiming to overcome such issues, a low-cost and small-size electronic module to be placed in the proximity of the bearing to be monitored was developed. The acoustic signal delivered by the bearing is acquired, and the corresponding frequency spectrum is evaluated on-board. Based on that, the developed module automatically detects the presence of defects and notifies the remote controller via a wireless connection only when a fault is detected, thus avoiding the use of data cables whilst minimizing the amount of transferred data. Experimental tests carried out on the proposed system assessed the accuracy of the evaluated frequency spectrum, resulting in an amplitude error within ±0.6%, as well as the fault detection capability in the presence of environmental acoustic noise.

Low-cost experimental apparatus for motion tracking based on image processing and camera calibration techniques

The present work focuses on the use of a low-cost equipment to monitor static and dynamic tests as an alternative to expensive commercial devices. First, we describe a procedure for cameras calibration and image processing in order to establish a less invasive (than other common instrumentation, such as strain gauges) and much cheaper motion capture method (than commercial tracking systems). Following, two cameras and one personal computer (with an image acquisition board) are used as the monitoring apparatus for tracking the movements of a flexible cable under harmonic excitation at its top end. The experimental results are then compared with numerical simulations, showing a fairly good agreement and the same level of precision as that obtained with one of the most used motion capture system in laboratories. The proposed experimental methodology correctly identifies the displacements, frequencies, and dynamic geometric behavior of the flexible model in all directions. Although commercial solutions are faster, since data processing and cameras calibration take place in real time, the acquisition cost of the suggested equipment is most affordable for small industries, educational institutions and projects with restrict budget on kinesiology, physiology, dentistry, facial recognition and mechanics, among others.

Design and Research on the detection system of controllable distance measuring device

In view of the defects of the existing hand-held Multimeter in measurement, such as difficult to operate and low measurement accuracy, a new type of component measurement device based on controllable distance expansion is proposed, and its detection system is designed and studied based on the device. By using LabVIEW programming software as the development environment and calling DAQ assistant function to configure the relevant voltage and current parameters, the DAQ acquisition board module integrated in the measurement device realizes the interactive communication between the data, and realizes the voltage and current acquisition of the system control. The experimental results show that the system can detect the voltage, current or resistance of components quickly, and the system has strong readability and high data precision.