Host PC Research Articles

A heterogeneous ultrasound open scanner for the real-time implementation of computationally demanding imaging methods.

Ultrasound open scanners have recently boosted the development and validation of novel imaging techniques. They are usually split into hardware- or software-oriented systems, depending on whether they process the echo data using embedded FPGAs/DSPs or a GPU on a host PC. The goal of this work was to realize a high-performance heterogeneous open scanner capable of leveraging the strengths of both hardware and software-oriented systems. The elaboration power of the 256-channel ultrasound advanced open platform (ULA-OP 256) was further enhanced by embedding a compact co-processing GPU system-on-module (SoM). By carefully avoiding latencies and overheads through low-level optimization work, an efficient PCIe communication interface was established between the GPU and the processing devices onboard the ULA-OP 256. As a proof of concept of the enhanced system, the high frame rate color flow mapping technique was implemented on the GPU SoM and tested. Compared to a previous DSP-based implementation, higher real-time frame rates were achieved together with unprecedented flexibility in setting crucial parameters such as the ensemble length (EL). For example, by setting EL=64 and a continuous-time high-pass filter, the flow was investigated with high temporal and spatial resolution in the femoral vein bifurcation (frame rate = 1.1 kHz) and carotid artery bulb (4.3 kHz), highlighting the flow disturbances due to valve aperture and secondary velocity components, respectively. The results of this work promote the development of other computational-expensive processing algorithms in real-time and may inspire the next generation of ultrasound high-performance heterogeneous scanners.

Wireless and battery-operatable IoT platform for cost-effective detection of fouling in industrial equipment

We present a novel internet of things (IoT) sensing platform that uses helical propagation paths of ultrasonic guided waves (UGWs) for structural health monitoring. This wireless sensor network comprises multiple identical sensor units that communicate with a host PC. The units have dedicated hardware to both generate and receive ultrasonic signals, as well as RF signals for use in triggering the sensors. The system was developed for monitoring and sensing pipelines and similar structures in real-time to facilitate interactive sensing. For accurate sensing with a limited number of arbitrarily scattered sensors, we obtain information from all sensor pairs and analyze helical propagation paths in addition to the commonly used shortest paths. UGWs can propagate long distances along the walls of pipelines, and their propagation velocity depends directly on the thickness of the waveguide, and is affected by energy leakage and mass loading. In this paper, we evaluated the network by utilizing it to detect fouling. The network could be adapted for further ultrasonic measurement tasks, e.g., measuring wall thicknesses or monitoring defects with pulse-echo methods.

Design and Implementation of Sensored Brushless DC Motor Control Using dsPIC30F4012 for CW/CCW Bidirectional Rotation

This paper presents the development of BLDC (Brushless DC) motor control based on dsPIC30F4012. The system is designed to control motor rotation in clockwise (CW) and counter clockwise (CCW) directions. There are 3 input pins used to facilitate the control interface, namely ground (GND) pin, control (CTRL) pin and enable (EN) pin. An analog input was assigned as command input for rotation in CW/CCW direction. The CTRL pin input has full-scale of analog input that comprises of three regions, namely CCW rotation input (0V~2.4V), CW rotation input (2.6V~5V), and neutral input (2.5±0.1)V as the deadband. The commutation sequences of six steps for direction of motor rotation, while P-I (Proportional-Integral) controller is used to control the motor current. The control law and commutation sequences are implemented in single chip dsPIC30F4012 microcontroller. To verify the system performance, we test the system implementation to drive BLDC motor and measured current are sent to the host PC through serial communication. From the experimental results it is shown that the realizing P-I controller is good performance in small frequency where the bldc motor current can follow the input commands. The bandwidth of motor control to characterize the performance of designed system is also presented.

A Low-Cost Test Platform for Performance Analysis of Phasor Measurement Units

In this paper, a customizable low-cost voltage waveform generator based on a real-time desktop PC and embedded data acquisition card synchronized with Coordinated Universal Time (UTC) is presented. A software approach to phase-locked loop synchronization with an external Global Positioning System (GPS) pulse signal is utilized to achieve a time uncertainty of ±1μs. This avoids expensive hardware modules for synchronization and timing purposes, which are commonly presented in literature. Besides the application for controlling the test platform, our own phasor data concentrator (PDC) application is running concurrently on the host PC. The latter is used for collecting and comparing the syncrophasor data from the test platform against the syncrophasor data measured by phasor measurement units (PMUs) under the test. The paper describes all procedures for generating reference test signals. Numerous case studies were performed, and experimental results for steady-state compliance as well as frequency ramp and phase modulation tests for dynamic compliance are presented in detail. All tests confirm that customizable test platform meets the requirements of IEEE/IEC standards. Compared to other calibrators, the cost as well as the specifications and point-by-point concept of data processing makes the described test platform suitable for performance analysis of PMU algorithms implemented on various development boards.

High Performance Software Architectures for Remote High-Speed Data Acquisition

There are various tools for real-time data acquisition and analysis of high-frequency signals. Usually, the tools for data acquisition and analysis are incompatible with each other, expensive, or require the utilization of various technologies. Designing a unique toolset for real-time data acquisition and analysis of high-frequency signals presents a large challenge, both in terms of hardware and software design. Some of the main challenges include fulfilling strict real-time performance requirements, using cost-effective hardware components, and designing a software architecture with minimal software latency for data sampling on an embedded platform and data analysis on a PC machine. This paper presents a software architecture design methodology for embedded platforms, including an RTOS and an Ethernet interface, along with the application architecture on the host side. To demonstrate the advantages of the proposed methodology, a prototype consisting of the STM32H747 microcontroller, FreeRTOS operating system, and a GUI application based on the Qt framework has been created. It has been shown that using the proposed architecture design methodology makes it possible to preserve the maximal hardware sampling rate utilizing a 100 Mbps Ethernet link. In the experiments, sampling rates up to 4.57 MSps for 10-bit resolution and real-time transfer of data over Ethernet link and visualization on host PC have been achieved with this specific MCU.

Convolution neural network and 77 ​GHz millimeter wave radar based intelligent liquid classification system

An intelligent liquid classification system based on 77 ​GHz ​millimeter wave radar and convolution neural network are proposed in this paper. The data are collected by the AWR1843 radar platform and processed by the neural network on the host PC in real-time. The doppler heatmap generated by radar signal processing is tried for the first time as the input of the system. The information carried by the heatmap in 2 dimensions is analyzed and the reason why the doppler heatmap could be used for classification is explained. The feasible experiment proved that the proposed method can successfully classify 8 kinds of common liquid with high accuracy. The result of the experiment is explained and the limitations of the experiment are discussed. It can be drawn that the combination of FMCW millimeter wave radar and convolution neural network is a method with great potential for liquid classification. The advantages of real time, non-invasive and unilateral measurement can also be used for the detection of dangerous liquids.

Security Risk and Preventive Measures of Multimedia Database System under Remote Control of Network Robot

The rapid development of network technology makes the world enter a new era, but it also brings a variety of severe information security problems, which makes the network security more and more important. Based on the existing literature and information, this paper expounds the current situation of database information system security. In view of the security risks of the media database information, this paper proposes to use the remote control system of the network robot, through sorting out the organizational structure characteristics and technology of multimedia data, establish the security defense system, and try to manage the multimedia data security. This system takes the mobile robot as the control object and adds the vision and ultrasonic transducer for the robot, so that it can carry on the semi-autonomous movement under the control of human. In addition, the host PC is used as the main control terminal to send instructions to the remote robot and receive the feedback data information. The simulation results show that the robot remote control system has good security, can ensure the establishment of database security defense technology system, and has the characteristics of convenient operation, easy to expand, and strong mobility. From the research point of view of this paper, the combination of robotics and multimedia information security is booming and will become a new application prospect.

Robot Gesture Control using Online Feedback Data with Multi-Tracking Capture System

This study employs a Vicon, high-speed and accurate marker-based motion capture system to develop a wireless low-latency gesture control method that requires no additional hardware components or onboard power sources. A novel control method is designed to track a rigid-body object's motion in the workspace and translate it into robot control signals. The system comprises five main components: a host PC with Vicon software named Tracker, a set of eight Vicon Vantage V8 infrared cameras, a client PC that receives Tracker's broadcasted data over Ethernet, a robot model named youBot provided by KUKA, and a rigid-body object that acts as the gesture controller. By using an Application Programming Interface (API) called DataStream, the rigid-body object's pose (position and orientation) can be estimated and used to remotely control the KUKA youBot robot with higher accuracy and an overall reduced latency of 0.3 seconds. In comparison to existing methods based on accelerometer-based and gyroscope-based controllers, the proposed gesture controller uses a set of retro-reflective markers for tracking purposes and requires no additional hardware systems. This proposed control method proves especially beneficial for the robotics prototyping development phase, where different control mechanisms can be easily replicated and tested within the motion capture system's operating range. Additionally, the robot's odometry can also be tracked during testing, making a motion capture system a valuable tool for evaluating motion control methods.

Design and Control of a Size-Adjustable Pediatric Lower-Limb Exoskeleton Based on Weight Shift

Lower-limb exoskeletons have been proven to be beneficial for motor function disability patients, in both clinical rehabilitation settings and daily activities. However, exoskeletons for the pediatric field are still very limited. In this paper, a novel lower-limb exoskeleton design for children is presented. Based on the anthropometric data of the target group, the size of the exoskeleton is designed adjustable to suit children from 8 to 12 years old. It employs six active joints on the knee and hip, actuated by Brushless DC motors and Harmonic Drive gears. The controller is based on a finite state machine model and the weight shift between two feet to generate the gait trajectory. An innovative automatic step-triggering mechanism is also proposed, based on the feedback from the ground reaction force sensor on the foot. Two user interfaces on the exoskeleton and the host PC are designed for easily operating the exoskeleton by clinicians and engineers. Experiments have been conducted with three healthy volunteers following the predesigned rehabilitation session protocol. Results show that the exoskeleton can well follow the gait trajectory generated by the control algorithm. All volunteers can fulfill all tasks in the test protocol with reduced efforts and the steps are automatically triggered by the presented controller.

High-Speed and Low-Latency 3D Fluorescence Imaging for Robotic Microscope

In this study, we propose a high-speed and low-latency 3D fluorescence imaging method for robotic microscopes. The prototype system consists of a focus-tunable lens called a TAG lens, which operates at several hundred kHz, an image intensifier (I.I.) that enhances faint light such as fluorescence, and a high-speed vision system that can transfer acquired images to the host PC in 500 Hz. The proposed method can acquire images at arbitrary focal lengths at frame rates on the order of 1 kHz by synchronizing the focal-length fluctuation of the TAG lens and the exposure timing of the I.I., whose duration is a few hundred nanoseconds. The low-latency we aim for in this paper is on the order of a few milliseconds. A prototype system was developed to validate the proposed method. High-speed 3D tracking of the Brownian motion of a fluorescent bead of 0.5 μm diameter was demonstrated to verify the feedback performance of the proposed low-latency 3D fluorescence imaging method.

Low-cost fabrication of flexible tactile sensor arrays

While for vision and audio the same mass-produced units can be embedded in many different systems from smartphones to robots, tactile sensors have to be built in application-specific shapes and sizes. To use a commercially available tactile sensor, it can be necessary to develop the entire system around an existing sensor model. We present a set of open-source solutions for designing, manufacturing, reading and integrating custom application-specific tactile matrix sensors. Our manufacturing process only requires an off-the-shelf cutting plotter and widely available plastic and metal foils. This allows creating sensors of diverse sizes, shapes, and layouts, which can be adapted to various specific use cases as demonstrated with exemplary robot integrations. For interfacing and readout, we develop an Arduino-like prototype board (Tacduino) with amplifier circuits to ensure good resolution and to suppress crosstalk. As an example, we give step-by-step instructions to build tactile fingertips for the RobotiQ 3-Finger Gripper, and we provide design files for the readout circuit board together with Arduino firmware and driver software. Both, wired and wireless communication between the sensors and a host PC are supported by this system. The hardware was originally presented and investigated in [1].

FPGA-based real-time implementation of a digital reactivity-meter

The aim of this paper is to present a Hardware/Software design approach for the real-time implementation of a digital reactivity meter on a Zynq SoC platform (FPGA: Field-Programmable Gate Array). As a primary design tool, the Xilinx System Generator (XSG) programming tool has been used. The elementary hardware digital processing units, used to solve the inverse kinetics equations, have been implemented inside the Programming Logic (PL) part of the Zynq platform. Other secondary tasks, such as communication with the host PC, data storage and display have been devoted to the software application running on the Processing System (PS) part. A dedicated Graphical User Interface (GUI) has been also developed on a remote host computer. This application will be essentially used to handle the communication with the embedded reactivity measurement system and to display the reactivity evolution curves through the time. The design has been validated by comparing the obtained results with those proposed in the literature. Real plant data, acquired from Es-salam research reactor, has been also used to confirm the online efficiency of the design. Experimental results demonstrate that the system works well for both negative and positive reactivity insertions.

TDLAS Tomography System for Online Imaging and Dynamic Process Playback of Temperature and Gas Mole Fraction

Tunable diode laser absorption spectroscopy (TDLAS) tomography enables online diagnosis of dynamic flames by imaging its temperature variations and exhaust gases, owing to its rapid response. Each tomographic image requires huge laser absorption spectrum data along multiple laser paths. For a high temporal resolution, the data sampling rate needs to be as high as possible which challenges the hardware implementation of parallel data acquisition of multiple channels. An online TDLAS tomography system was designed on field programmable gate array (FPGA) and PC for temperature and gas mole fraction distributions measurement. An on-chip parameter extraction module based on digital lock-in amplifier (DLIA) extracts absorption spectrum parameters at 1000 frames per second (FPS), and the framerate of real-time reconstruction on host PC can reach up to 302 FPS. A high-speed buffer on FPGA termed as transient spectrum recorder continuously records the latest five seconds of raw data. Both the playback of absorption spectrum parameters and raw data provide a way for detailed and in-depth understanding of the dynamic combustion process. Experiments were carried out by using an alcohol burner to evaluate the online monitoring and offline playback abilities of the system.

Hardware-Accelerated Real-Time Spectrum Analyzer With a Broadband Fast Sweep Feature Based on the Cost-Effective SDR Platform

Radio Frequency (RF) spectrum monitoring and broadband signal analysis have multiple application areas, especially in the era of a constantly growing number of wireless devices. One of the essential challenges for a spectrum sensor is to achieve an adequate measurement rate over a wide bandwidth to detect signals of short duration so that a low latency response can be provided. In procedures that require field measurements, and some compromise in accuracy is acceptable, low-cost Software Defined Radio (SDR) devices can be used instead of expensive and bulky professional spectrum analyzers. This paper introduces a real-time swept spectrum sensor based on LimeSDR-USB with custom embedded Field Programmable Gate Array (FPGA) firmware, designed to outperform similar software implementations. The Welch’s spectral density estimation is implemented in hardware to minimise the USB transfer rate and offload the host PC signal processing. Furthermore, the frequency tuning state machine and cache calibration memory are also managed by the FPGA to reduce the blind time during broadband sweep. The performance of the proposed solution indicates up to 96 MHz of real-time bandwidth along with a capability of less than millisecond cumulative sweep time per gigahertz. The characteristics of various design elements are investigated and refined during simulation and laboratory measurements, whereas the final prototype implementation is verified in real-world scenarios. The results demonstrate the effectiveness of the proposed device as a sensor for propagation studies, multiband spectrum utilisation monitoring, and spectral white spaces detection.

Demonstration of a novel multi-cameras light field rendering system and its application

Large scale light field rendering of real scene is very important for the area of image-based modeling and parallax-based 3D display. With this in mind, we tried to use simple cameras, lenses, motion platform and a host PC to capture the light field and render it for 3D display. It extends our ability to capture the 3D information of the real scene in an effective and compact way, elemental image array for 3D display can be generated without the need of any pixel interpolation or virtual view synthesis. Optical experiment verified the validity of the designed system.

IoT based Automated Plant Disease Classification using Support Vector Machine

Leaf - a significant part of the plant, produces food using the process called photosynthesis. Leaf disease can cause damage to the entire plant and eventually lowers crop production. Machine learning algorithm for classifying five types of diseases, such as Alternaria leaf diseases, Bacterial Blight, Gray Mildew, Leaf Curl and Myrothecium leaf diseases, is proposed in the proposed study. The classification of diseases needs front face of leafs. This paper proposes an automated image acquisition process using a USB camera interfaced with Raspberry PI SoC. The image is transmitted to host PC for classification of diseases using online web server. Pre-processing of the acquired image by host PC to obtain full leaf, and later classification model based on SVM is used to detect type diseases. Results were checked with a 97% accuracy for the collection of acquired images.

The GosipGUI Framework for Control and Benchmarking of Readout Electronics Front-Ends

The GOSIP (Gigabit Optical Serial Interface Protocol) provides communication via optical fibres between multiple kinds of front-end electronics and the KINPEX PCIe receiver board located in the readout host PC. In recent years a stack of device driver software has been developed to utilize this hardware for several scenarios of data acquisition. On top of this driver foundation, several graphical user interfaces (GUIs) have been created. These GUIs are based on the Qt graphics libraries and are designed in a modular way: All common functionalities, like generic I/O with the front-ends, handling of configuration files, and window settings, are treated by a framework class GosipGUI. In the Qt workspace of such GosipGUI frame, specific sub classes may implement additional windows dedicated to operate different GOSIP front-end modules. These readout modules developed by GSI Experiment Electronics department are for instance FEBEX sampling ADCs, TAMEX FPGA-TDCs, or POLAND QFWs. For each kind of front-end the GUIs allow to monitor specific register contents, to set up the working configuration, and to interactively change parameters like sampling thresholds during data acquisition. The latter is extremely useful when qualifying and tuning the front-ends in the electronics lab or detector cave. Moreover, some of these GosipGUI implementations have been equipped with features for mostly automatic testing of ASICs in a prototype mass production. This has been applied for the APFEL-ASIC component of the PANDA experiment currently under construction, and for the FAIR beam diagnostic readout system POLAND.

Design and Development of Flood Monitoring and Early Warning System

Flood is a natural disaster caused by the rise of water levels, typically in urban areas. This phenomenon can cause damages to properties such as buildings and landscapes. Moreover, it also can cause death among humans and animals. Malaysia is among the country that has rainfall throughout the years alongside monsoon seasons. Therefore, this country is prone to floods that are not predictable that causes the public to be unprepared to face potential floods. Although the authorities have taken some measures, such as the installation of the monitoring system, it is not efficient, expensive, and difficult to maintain. Hence, this study aims to design a low-cost flood monitoring system comprising a rainfall sensor, temperature sensor, humidity sensor, controller (Arduino), and GSM modem. The system will monitor the rainfall rates alongside temperature and humidity in deciding for the potential occurrence of flood. The data will be sent to a host PC with Graphical User Interface via GSM modem. The developed prototype aims to be installed at a selected location for monitoring and testing.

Water Quality Monitoring System Based on Microcontroller and LoRa

Water is essential for human and other lives such as marine and plants. However, water pollutions are a serious issue that needs to be solved. One of the actions that needs to be taken is to monitor the water quality regularly. However, many areas still used manual monitoring due to high cost of automatic monitoring system. Hence, this study aims to develop a low-cost and low-power water pollution monitoring system using a microcontroller and long-range wireless system (LoRa). The system monitors the water pollutions through pH and temperature sensor. Next, the data transmitted to a host PC wirelessly through LoRa communication. The data received will bs stored in a cloud with GUI. Moreover, the system equipped with a PV panel and Lithium-ion battery storage. This will allow the system to be deployed in remote areas with no power sources. The system performance on pollution detection and transmission distance were tested via several experiments. Several substances with different pH values were used simulate polluted water. Meanwhile, the data transmission was evaluated through several distance parameters. The results show the system successfully able to monitor polluted water with high accuracy and capable to transmit long-range data wireless. Hence, the system has efficient power usage through few numbers of sensors alongside LoRa that uses low power for communication.

Automatic Data Collecting and Application of the Touch Probing System on the CNC Machine Tool

For realizing automatic data collecting of the touch probing system on the CNC machine tool and practicing the application technology of big data from the CNC machining process, a special NC program was developed on the Siemens 840D SL controller to record data with a defined text format, and they were uploaded onto the host computer automatically. With the help of DB management software in the host PC, data obtained were sent into the MES database regularly, and then automatic data collecting of manufacturing process information was realized. With the big data technology, three applications based on big data technology have been listed. They are duo active error detection on the probing system, geometrical accuracy monitoring, and management of the cutting parameter and tool life. Tests of cutting on the platen of an injection molding machine with a PAMA SR3000 floor-type CNC boring-milling machine proved that the new technology achieves its design objectives.