Data Acquisition Equipment Research Articles

Intelligent Operation of Wheel Loader Based on Electrohydraulic Proportional Control

In this paper, the wheel loader with electrohydraulic proportional control technology is used as the carrier. For the first time, the dual-angle sensor is used for intelligent operation, which allows the wheel loader working device to be precisely controlled. First, the theoretical analysis of the electrohydraulic proportional control technology on the wheel loader studied in this paper is carried out. Next, according to the feedback of the boom and bucket angle sensor signals, the electrohydraulic proportional control technology is used to initially realize the boom memory and bucket automatic levelling function of the wheel loader working device. Finally, the data acquisition equipment is connected to provide experimental verification, although the test results did not achieve precise control of the working device. After analysis, the detected problems were solved by constructing a neural network algorithm model, which successfully realizes the intelligent and precise operation of the wheel loader, reducing unnecessary energy loss.

Possible detection of solar gamma-rays by ground-level detectors in solar flares on 2011 March 7

Abstract On 2011 March 7, the Solar Neutron Telescope located at Mt. Sierra Negra, Mexico (4600 m) observed enhancements of the counting rate from 19:57 to 20:04 UT with statistical significance 6.8σ and from 20:36 to 21:03 UT with 5.8σ. One plausible physical explanation for the observation enhancements is that they were produced by solar gamma-rays. The intensities were estimated to be (0.16 ± 0.03) photons cm−2 s−1 for the first flare and (0.22 ± 0.04) photons cm−2 s−1 for the second one at the top of the atmosphere. As far as we know, this is the first report on the detection of solar gamma-rays with a ground-based detector. In association with these events, the solar neutron detector Space Environment Data Acquisition Equipment on board the International Space Station registered two solar neutrons with statistical significances of 7.3σ and 6.6σ. The Large Area Telescope on board the Fermi observatory also observed high-energy gamma-rays from this flare with a statistical significance of 6.7σ. In this paper we propose a unified model to explain the production mechanism of high-energy gamma-rays and neutrons in association with this flare.

Cement Grout Nonlinear Flow Behavior through the Rough-Walled Fractures: An Experimental Study

This research experimentally studied the effects of various fracture roughness (characterized by the fractal dimension D) and normal stress (normal loads FN) applied to fracture on ultrafine cement grout nonlinear flow behavior through rough-walled plexiglass fractured sample. A high-precision and effective sealing self-made apparatus was developed to perform the stress-dependent grout flow tests on the plexiglass sample containing rough-walled fracture (fracture apertures of arbitrary variation were created by high-strength springs and normal loads according to design requirements). The real-time data acquisition equipment and high-precision self-made electronic balance were developed to collect the real-time grouting pressure P and volumetric flow rate Q, respectively. At each D, the grouting pressure P ranged from 0 to 0.9 MPa, and the normal loads FN varied from 1124.3 to 1467.8 N. The experimental results show that (i) the Forchheimer equation was fitted very well to the results of grout nonlinear flow through rough-walled fractures. Besides, both nonlinear coefficient (a) and linear coefficient (b) in Forchheimer’s equation increased with increase of D and FN, and the larger the FN was, the larger the amplitude was. (ii) For normalized transmissivity, with the increase of Re, the decline of the T/T0−β curves mainly went through three stages: viscous regime, weak inertia regime, and finally strong inertia regime. For a certain D, as the normal load FN increased, the T/T0−β curves generally shifted downward, which shows good agreement with the single-phase flow test results conducted by Zimmerman. Moreover, with the increase of D, the Forchheimer coefficient β decreased. However, within smaller FN, β decreased gradually with increasing D and eventually approached constant values. (iii) At a given FN, Jc increased with increasing D.

Autonomous Detection for Traffic Flow Parameters of a Vehicle-Mounted Sensing Device Based on Symmetrical Difference

Based on the research and analysis of traffic detectors, it is found that the existing vehicle detection equipment is generally vulnerable to environmental interference and the detection effect cannot meet the current traffic demand. Therefore, an automatic detection method of traffic flow parameters based on symmetrical difference was put forward. This method collects the traffic flow parameters through wireless sensor nodes. Since the safety transmission protocol of VANET (Vehicular Ad Hoc Networks) can maximize the safety channel capacity, it transmits the traffic flow parameters to the data acquisition and control equipment of the upper computer through the cross layer pre-balanced safety transmission protocol of VANET in the wireless communication unit. The data acquisition and control equipment of the upper computer uses the traffic flow detection method based on the symmetrical difference to obtain the details of the moving objects in the traffic flow so as to realize the independent detection of the traffic flow parameters of the vehicle-borne sensor equipment. Experimental results show that the designed method has anti-interference abilities for the noise and light changes. Meanwhile, this method can completely extract moving objects from the traffic flow and can improve the detection effect of the moving objects in the traffic flow. Thus, the effectiveness of the proposed method can be fully verified.

Preliminary Concept of an Unmanned Aerial Vehicle for Patrolling of Water Basins

The paper presents a preliminary concept of an unmanned aerial vehicle (UAV) designed with a form of the Kasper wing (known in Polish as the ‘Kasprzyk wing’) and intended for aerial patrolling and monitoring of large water basins, mass gatherings, ground traffic, state borders, and other applications. Considering the potential uses resulting from the applications, the UAV defined in this preliminary concept would have to operate with high-value onboard data acquisition equipment. This is why this paper focus specifically on the problems of security and protection of the onboard data acquisition equipment the purchase costs of which can be several times higher than the costs of building the UAV airframe. This problem brought the authors to the main assumption of the work presented herein: to develop an UAV design which would provide maximum security and protection of the onboard mission loadout even in conditions of complete loss of propulsion and guidance control. The capability of safe emergency unpowered landing of the UAV enabled the application of an reflex airfoil based on the Kasper wing design. In the event of a propulsion power loss, the UAV could automatically begin a low advance velocity flight to reduce the risk of UAV failure upon touchdown. This was how the objective of this work was identified: to study the design criteria and select the materials for the fabrication of the UAV. The fabrication materials were selected to minimise the risk of failure or sinking of the UAV and its high-value onboard loadout in the event of emergency alighting on water. The behaviour of an UAV model at various loads which simulate real-life flight conditions required a multi-faceted analysis; the second part of the work discusses a selection of experimental methods (including an optically active layer method and a digital image correlation method) which will enable testing the strength properties of the fabricated structural elements of the UAV.

An interpretable model for short term traffic flow prediction

Predicting short term traffic flow to improve traffic control is a research problem attracting increased attention over the past 30 years. With increasing number of traffic data acquisition equipments coming into usage, it provides an opportunity to use deep neural network (DNN) to predict short-term traffic flow. Behind its considerable success, the DNN is weighed down by some problems, and here we focus on: 1. how to justify the number of input nodes employed by DNN; 2. how to explain the causality between the historical spatiotemporal information and the future traffic condition. In this paper, we propose a deep polynomial neural network combined with a seasonal autoregressive integrated moving average model. The new model has superior predicting accuracy as well as enhanced clarity on the spatiotemporal relationship in its deep architecture. Experimental results indicate that the proposed model has better explanation power and higher accuracy compared with the LSTM based model.

Design of simple refrigerating device for multiparametric analysis of the thermoacoustic cooling phenomenon

Although the widespread introduction of numerical tools and the CFD models have improved the design methodology of thermoacoustic coolers and eased optimization of such units, high computational costs vitally limit their application in parametric analyses of thermoacoustic devices. Thus, experimental investigation remains essential field of research, considering design of such units. In the paper, the design and construction of an experimental setup, dedicated to perform an extensive multiparametric analyses on compact thermoacoustic devices with varying characteristic parameters, is discussed in detail. A complete design path, beginning with general consideration, with further detailed dimensioning and selection of market-available parts, ending with installation of control and data acquisition equipment, is described. Initial testing of the device, performed both computationally at the design stage and experimentally after the final setup assembling, is discussed as well. The results of the tests demonstrated ability to observe the variability in the operational parameters of the cooler following change in number of environmental and constructional parameters. The data acquired indicated vital importance of the stack porosity and frequency of the acoustic wave on performance of the thermoacoustic device, which corresponds to the data presented in the literature.

Quantitative assessment of lower limbs gross motor function in children with cerebral palsy based on surface EMG and inertial sensors.

Taking advantage of motion sensing technology, a quantitative assessment method for lower limbs motor function of cerebral palsy (CP) based on the gross motor function measurement (GMFM)-24 scale was explored in this study. According to the motion analysis on GMFM-24 scale, we translated the assessment problem of GMFM-24 scale into a detection problem of different motion modes including static state, fall, step, turning, alternating gait, walking, running, lifting legs, kicking balls, and jumping. The surface electromyography (sEMG) electrodes and inertial sensors were adopted to capture motion data, and a framework integrating a series of detection algorithms was presented for the assessment of lower limbs gross motor function. Two groups of participants including 8 healthy adults and 14 CP children were recruited. A self-developed data acquisition equipment integrating 24 sEMG electrodes and 9 inertial units was adopted for data acquisition. A platform based on two laser beam sensors was used to perform cross-border detection. The parameters/thresholds of motion detection algorithms were determined by the data from healthy adults, and the lower limbs gross motor function evaluation was conducted on 14 CP children. The experimental results verified the feasibility and effectiveness of the proposed quantitative assessment method. Compared to the clinical assessment score based on GMFM-24 scale, 90.1% accuracy was obtained for evaluation of 303 tasks in 14 CP children. The objective motor function assessment method proposed has potential application value for the quantitative assessment of lower limbs motor function of CP children in clinical practice. Graphical abstract The algorithm framework for the assessment of lower limbs gross motor function. Using the GMFM-24 scale as the evaluation standard, a quantitative evaluation program for the lower limbs gross motor function of CP children based on motion sensing technology was proposed.

Unsupervised depth estimation from monocular videos with hybrid geometric-refined loss and contextual attention

Most existing methods based on convolutional neural networks (CNNs) are supervised, which require a large amount of ground-truth data for training. Recently, some unsupervised methods utilize stereo image pairs as input by transforming depth estimation into a view synthesis problem, but need stereo camera as an additional equipment for data acquisition. Therefore, we use more available monocular videos captured from monocular camera as our input, and propose an unsupervised learning framework to predict scene depth maps from monocular video frames. First, we design a novel unsupervised hybrid geometric-refined loss, which can explicitly explore more accurate geometric relationship between the input color image and the predicted depth map, and preserve depth boundaries and fine structures in depth maps. Then, we design a contextual attention module to capture nonlocal dependencies along the spatial and channel dimensions in a dual path, which can improve the ability of feature representation and further preserve fine depth details. In addition, we also utilize an adversarial loss to discriminate synthetic or realistic color images by training a discriminator so as to produce realistic results. Experimental results demonstrate that the proposed framework achieves comparable or even better results than those trained with monocular videos or stereo image pairs.

Performance-based Piezoelectric Material Applied in Health Inspection of Civil Engineering Structures

The application of piezoelectric impedance principle in health monitoring of civil engineering structures has attracted more and more attention. In this paper, the application of piezoelectric materials in health detection of civil engineering structures is reviewed. The basic principles, research progress, advantages and problems of impedance method and wave method are analyzed. Civil engineering structures, such as dams, bridges, high-rise buildings, etc., will inevitably suffer some damage during their service. Sometimes it is caused by natural factors of force majeure, or due to long-term accumulation damage, these damages will directly cause structural resistance to decay, and in severe cases may lead to catastrophic accidents. The support role of structural monitoring technology is needed to provide early warning of these disasters. Piezoelectric materials, piezoelectric impedance principles, interaction models of piezoelectric materials with monitored structures, and monitoring techniques based on impedance information. The research results of piezoelectric material size selection, scanning frequency selection, sensing range, binder influence, data acquisition equipment development and data processing methods are summarized.

A Survey on Optical Technologies for IoT, Smart Industry, and Smart Infrastructures

In the Internet of Things (IoT), a huge number of sensors, actuators and other equipment for data acquisition and processing will be interconnected by means of an omnipresent communication network able to efficiently support heterogeneous transmission technologies and applications. On the one hand, advanced optical communication systems, which already play a significant role in modern networks, are currently evolving to meet very high requirements of modern applications. On the other hand, there are already many ways to utilize optical components and effects for building precise, efficient, and reliable sensors. Thus, optical technologies have the potential to greatly help in realizing future smart infrastructures and systems. This paper gives an overview of currently available and emerging optical technologies for sensing and communication applications and reviews their possible application in the context of the IoT for realizing smart systems and infrastructures.

Vehicle load updating of roadway bridges based on Bayesian method and Monte Carlo simulation

For the life-cycle design of bridges, it is of significance to establish and update the probabilistic model. However, for the current situation of practical engineering, popularizing data acquisition equipments to collect long-term data could not meet the facts. The Monte Carlo simulation is utilized to simulate the prior samples and expand the sample size. The Bayesian method is adopted to update the sectional distribution. A mathematical example based on self programming is given to illustrate the method. The results show that: the cooperation of the Bayesian method and Monte Carlo simulation could update the short-term vehicle load model. The method is of good reliability and serviceability which could be references for further studies.

Vibration–Based online Tool Wear Monitoring Using Piezo Film Sensor Analyzed by I-kaz Multilevel Signal Feature

Wear in cutting tool is a normal phenomenon in machining process. Problems such as dimensional precision, surface finish quality and defect cost is due to the wear. The wear also can cause unexpected stop time and lower down the manufacturing productivity. Therefore, a system to monitor the progression of the tool wear is needed to predict the wear status and stop machining operation once the wear reach the allowed limit. In this study, the monitoring system was designed by utilizing 2 units of piezoelectric film sensors which are capable of detecting and analyzing signals related to tool holder vibration during the machining process in both feed and tangential axes. The sensors were stacked on x axis and z axis surfaces of the tool holder and signals were channeled to a charge amplifier and then to the digital data acquisition equipment which then display the vibration signal in time domain on the computer screen. A total of 8 experiments were carried out using CNC turning machine. Vibration signal and wear measurement were recorded for each run in the experiment. The experiment were stopped once the wear reach approximately 0.3mm. I-kaz multilevel signal features were extracted from the vibration signal recorded and then correlated with the flank wear status. There is a solid or substantial correlation between the cutting tool wear condition and I-kaz multilevel coefficient value, with average of 0.87 for I-kaz x coefficient (tangential direction) and 0.910 for I-kaz z coefficient (feed direction). This affirm that I-kaz multilevel signal feature can be assigned as the input criterion for the tool condition monitoring system that can estimate the current status of the flank wear on the cutting tools which can prevent defect in the machining process.

Verification of reliability of numerical analysis by comparison with actual crash impact test of rotorcraft fuel tank

The general function of a fuel tank is to store fuel. However, the structural soundness of a fuel has a great influence on the survival of the crew in an emergency situation such as an aircraft crash. For this reason, countries with advanced aviation technology have developed crashworthy fuel tank for decades. The crashworthiness performance of fuel tank is demonstrated by the crash impact test, which has high risk of failure due to the high impact loads, so much effort has been made to minimize the possibility of failure in the actual test. Numerical analysis performed before the actual test is a part of such efforts. However, for the results of numerical analysis to be reflected in the design, a certain level of reliability of the numerical analysis is required. In this study, the results of a numerical analysis and actual crash impact test data were compared to verify the reliability of the numerical analysis. Crash analysis software (LS-DYNA) was used and the arbitrary Lagrangian–Eulerian (ALE) technique was applied as the analysis method. To obtain actual test data, strain gages were installed on the metal fittings of the fuel tank and linked to the data acquisition equipment. As a result of the numerical analysis, strain and stress of the fuel tank fittings were calculated. And, the reliability of the numerical analysis was enhanced by assessing the error between the strain measurement of the upper fittings obtained from an actual fuel tank test and the strain calculated from the numerical analysis.

A comparative evaluation of vertical fractures using different azimuthal electrical resistivity survey arrays

ABSTRACTThe identification of geological discontinuities such as fractures and faults is fundamental to geotechnical and hydrogeological characterization of rock masses. It is difficult to characterize these discontinuities, even by means of drill cores. Electrical resistivity has been historically employed as an alternative tool for the characterization of discontinuities, and new equipment for data acquisition and modern interpretation techniques have increased this possibility. However, when the characterization of vertical discontinuities is to be carried out in small areas, such as urban zones or for engineering works, traditional surveying may be impracticable, because it requires larger areas for proper acquisition. In these situations, azimuthal electrical resistivity surveying can be a good option, thanks to faster data acquisition and the possibility of reaching greater depths of investigation. There are several types of azimuthal arrays, but comparative analyses of their efficiency are still scarce. The objective of this study is to compare the applicability of several types of azimuthal resistivity surveys to identify vertical discontinuities in rock masses. The study was carried out in the laboratory using a scale model (tank), where boundary conditions could be well‐defined. We tried to replicate the natural conditions of a karstic area in Brazil, known to have hydrogeological and geotechnical problems associated with subvertical discontinuities. The simulations involved a limestone rock mass crosscut by a set of discontinuities with varied apertures. The selected arrays (square, equatorial dipole–dipole, Wenner and Schlumberger) encompassed varied inter‐electrode spacings and three different thicknesses of a saturated isotropic overburden, so as to represent field conditions. The azimuthal resistivity surveys, especially the Wenner array, proved to be promising in order to detect vertical discontinuities. The non‐collinear arrays are preferable when it comes to discerning the depth of investigation (square) and detecting electric anisotropy (equatorial dipole–dipole), despite small azimuthal distortions that were observed in relation to the strike of the discontinuities.

Pros and Cons in Helicopter-Borne GPR Data Acquisition on Rugged Mountainous Areas: Critical Analysis and Practical Guidelines

We critically discuss both advantages and limitations of helicopter-borne GPR surveys in rugged mountainous areas by analyzing a pseudo 3D data set acquired over the Marmolada Glacier, which constitutes the largest ice body in the Dolomites (Eastern Alps) and contains several peculiar features both in terms of the internal structures and the surrounding topography. In this paper we analyze several possible issues that can be encountered when performing airborne surveys in mountain regions, related to both the local conditions in the particular survey areas, and the general performance of the data acquisition equipment, which includes the GPR device, the GPS system, and the helicopter itself. Based on our analyses and observations, we propose a few guidelines and optimization strategies in order to address several issues, including the choice of various data acquisition parameters, interpretation problems related to curvilinear or irregular flight paths, and trace positioning errors caused by GPS malfunctioning or oscillating antennas. Such results have general validity and can be used for helicopter-borne survey planning, as well as for data analysis and interpretation.

Multichannel Inductive Sensor Based on Phase Division Multiplexing for Wear Debris Detection.

Inductive wear debris sensor has been widely used in real time machine lubricant oil condition monitoring and fault forecasting. However, the small sensing zone, which is designed for high sensitivity, of the existing sensors leads to low throughput. In order to improve the throughput, a novel multichannel wear debris sensor that is based on phase division multiplexing is presented. By introducing the phase shift circuit into the system, multiple sensing coils could work at different initial phases. Multiple signals of sensing coils could be combined into one output without information loss. Synchronized sampling is used for data recording, and output signals of multiple sensing coils are extracted from the recorded data. A four-channel wear debris sensor system was designed to demonstrate our method. Subsequently, crosstalk analysis, pseudo-dynamic testing and dynamic testing were conducted to check the sensing system. Results show that signals of four sensing coils could be simultaneously detected and the detection limit for ferrous wear debris is 33 μm. Using the presented method, real time wear debris detection in multiple channels could be achieved without increasing the number of excitation source and data acquisition equipment.

Development of a novel system for linear displacement sensor calibration

This paper presents the development of semi-autonomous metrological devices, capable of calibrating variety of linear displacement sensors, like Linear Variable Differential Transformers (LVDT), string potentiometers, laser displacement sensors and other. Data acquisition equipment that could be used for measuring objects of various shapes and sizes are already available; however, devices specifically tailored for the calibration of displacement sensors are not currently offered. Advantages of this new technology, that we are investigating and developing, include reduction of time, costs and human resources required to perform calibration. In addition to that, the advantages of an affordable calibration device will allow calibrations to be carried out internally, as opposed to outsourcing to dedicated facilities. The scope of the project encompasses research into the device’s compliance with ISO/IEC 17025 to obtain NATA accreditation, research into design, and selection of material and manufacturing processes to ensure an acceptable measurement of uncertainty is achievable across all varieties of linear displacement sensors. The sensors are used to measure suspension displacement, steered angle and various other geometries on vehicles and test equipment. Outcomes of this research project offer experimental evidence that proves the feasibility of developing and manufacturing devices that produce an acceptable uncertainty that meets testing standards requirements at a fraction of the cost of comparable measuring devices.

Multi-fidelity validation algorithm for next generation hybrid-electric vehicle system design

With the evolution of increasingly complex hybrid-electric vehicle powertrains, the process of creating validated system models has become progressively more difficult to achieve. Increasing levels of confidence in how instantaneous vehicle energy states are captured is needed to take full advantage of the fuel consumption and emissions reduction potential of the vehicle to move towards more sustainable transportation systems. While many strategies for model validation exist, the majority rely on ascertaining comparisons with global system characteristics, for instance, total fuel consumption over a fixed driving event. However, these methods do not necessarily account for the rapidly fluctuating energy states which need to be understood to optimise the vehicle’s energy management strategy. The current work proposes a new validation approach which captures these instantaneous characteristics taking advantage of the high signal sampling rates available from modern data acquisition equipment rather than relying on drive cycle average or cumulative global behaviours. The method proposed provides a holistic view of the behaviours demonstrated by the vehicle model and identifies regions of poor system validation targeting areas for further model refinement. The algorithm is demonstrated on a new post-transmission, parallel mild-hybrid-electric bus. The model was developed in the MATLAB Simulink modelling environment. The validation algorithm is tested against vehicle dynamometer and test track data. With an increasing volume of mild and full hybrid vehicle configurations emerging, validation strategies such as the one proposed here are increasingly important for the design of energy management strategies to deliver the full potential benefits of the vehicle. The algorithm is proposed in a step by step method which can be automated to limit required user input.

Study on Air Characteristics of the U-shaped Sail

Sail-assisted technology is an effective mean to reduce the carbon emission of shipping industry. In order to research the air characteristics of u-shaped sails, we select more than 20 attack angles to conduct wind blowing tests on u-shaped sails and ordinary laminar sails. The air characteristic parameters such as lift-drag coefficient, lift-drag ratio, resultant force coefficient and torque, as well as the thrust coefficient and lateral force coefficient influencing the propulsion effect of the two models were obtained by data acquisition equipment. The results show that the u-shaped’s maximum lift coefficient is 2.199 when the attack angle is +18°and significantly higher than control group. The thrust coefficient of the u-shaped sail is approximately twice that of the conventional laminar wind sail, which can obtain greater propulsion power.