Showing papers in "Measurement in 2017"

TL;DR: Developing a convolutional neural network to learn features directly from frequency data of vibration signals and testing the different performance of feature learning from raw data, frequency spectrum and combined time-frequency data demonstrate that the proposed method is able to learning features adaptively from frequencyData and achieve higher diagnosis accuracy than other comparative methods.

TL;DR: In this paper, the influence of the number of ground control points used for georeferencing on Digital Surface Model and orthoimage accuracies obtained with UAV-photogrammetry is analyzed.

TL;DR: A novel technique of automatic classification of single and hybrid PQDs using a novel technique PNN-ABC based optimal feature selection and parameter optimization for improving the performance of the classification system.

TL;DR: An improved algorithm to detect QRS complex features based on the multiresolution wavelet transform to classify four types of ECG beats and classification accuracy of SVM approach proves superior for the proposed method to that of the NN classifier with extracted parameter in detecting ECG arrhythmia beats.

TL;DR: In this paper, a noncontact vision-based sensor is proposed as an accurate and cost-effective alternative for the determination of cable tension forces in cable-supported bridges and roof structures.

TL;DR: In this article, the authors investigated the mechanical properties of AA 6082 composites reinforced with tungsten carbide particles and found that the tensile strength of the composites increased initially and then tends to decrease.

TL;DR: In this paper, the authors quantified the influence of rain in different LiDAR parameters: range, intensity, and number of detected points, and found that the intensity returned from pavement is not specially influenced by rain.

TL;DR: In this paper, a hybrid method that incorporates empirical mode decomposition (EMD) and support vector regression (SVR) algorithms is proposed to forecast the electricity load demand using a hybrid approach.

TL;DR: It was found that the constructed ANFIS model exhibited relatively high prediction performance of UCS than the MR and the ANN models, and revealed that soft computing is a good approach for minimizing the uncertainties and inconsistency of correlations in geotechnical engineering.

TL;DR: A novel hybrid fusion algorithm is proposed to provide a pseudo position information to assist the integrated navigation system during GPS outages and achieves better performance in the prediction of GPS position information than the normal artificial neural network (ANN) trained by Bayesian Regularization.

TL;DR: A review of the literature on the ranking of data envelopment analysis (DEA) in order to increase the discrimination power of this analytical technique can be found in this paper, where the authors classified DEA ranking methods into 10 categories based on their structure, and they include those approaches published up to 2016.

TL;DR: In this paper, the effect of three operational parameters (CO 2 pressure, temperature and water-to-solid ratio) on the rate and efficiency of the mineral carbonation reaction of steel-making slag at laboratory-scale was examined.

TL;DR: In this article, the authors provide a comprehensive review of current research and development activities in sensor validation methodology for structural health monitoring (SHM) systems, which mainly focusses on the detection, isolation and reconstruction of sensor faults.

TL;DR: An integrated multi-objective optimization method with GRA, radial basis function (RBF) neural network, and particle swarm optimization (PSO) algorithm is proposed and proved to be feasible and can be generalized for other multi- objective optimization problem in manufacturing industry.

TL;DR: The present study focused on the determination of parameters like uniaxial compressive strength, tensile strength, point load index and Young’s modulus from very easily determinable physical parameters viz. density, porosity, and compressional wave velocity using multiple variable regression analysis and adaptive neuro-fuzzy inference system.

TL;DR: In this paper, a novel diagnosis scheme based on envelope analysis and wavelet de-noising with sigmoid function based thresholding is used to extract the fault related symptoms from noisy vibration signatures of defective ball bearings operating at slow speed.

TL;DR: In this article, a robust automated signal processing algorithm is proposed for defect identification in the centrifugal pump, where features sensitive to defective conditions are extracted from raw signal and scale marginal integration graph.

TL;DR: In this paper, a series of (75-x) B 2 O 3 -xBi 2O 3 -10Na 2 O-10CaO-5Al 2 O3 glasses, (0,≤ ǫ −1 and 200,850,nm, respectively, were prepared and density and molar volume were measured.

TL;DR: This paper presents a systematic review on sparse signal representation, especially on two key topics, i.e. atomic decomposition algorithms and dictionary design methods reported in more than 70 representative articles published since 1990.

TL;DR: In this paper, the machinability of a hand-laminated uni-directional carbon fiber reinforced polymer (CFRP) was investigated in the case of using a special diamond coated twist drill and a solid carbide end mill (helical milling) with a view to analysing and optimising referent machining parameters.

TL;DR: In this paper, the authors focused on the determination of the optimum cutting conditions leading to minimum surface roughness as well as cutting force, cutting power and maximum productivity, in the case of the turning of the polyoxymethylene polymer POM C using cemented carbide cutting tool.

TL;DR: In this article, the authors proposed a method for the reduction of forces and the improvement of efficiency during finish ball end milling of hardened 55NiCrMoV6 steel, which enables simultaneous minimisation of cutting force values and increased process efficiency.

TL;DR: In this paper, the authors investigated the machinability characteristics of end milling operation to yield the minimum surface roughness, cutting force, tool wear with the maximum material removal rate using RSM based grey relational analysis.

TL;DR: In this paper, the authors developed a model to quantify wilting point with respect to the deterministic factors such as soil clay content, soil organic matter, slope of soil water characteristic curve at inflection point (i.e., s index) and fractal dimension.

TL;DR: A quaternion singular spectrum analysis method based on the convex optimization leads to a better solution to extract the feature frequency in mechanical fault diagnosis.

TL;DR: The developed DAQS was found to be very supportive for research and educational purposes and the performance of the proposed system is tested when integrated with small size PV system.

TL;DR: In this paper, the importance of pipeline inspection is firstly emphasized and the studies about the inspection of pipelines at literature are examined, in addition, the usage purposes of PIGs, the basics of Non-destructive Evaluation technologies and the samples of applications at pipelines are examined.

TL;DR: In this article, the quality of rapeseed during 31 days of storage was studied using an electronic nose (Agrinose) built of 8 metaloxide semiconductor sensors and one representing the Micro Electro Mechanical Systems technology (MEMS).

TL;DR: In this article, a comparative study between the thermocouples and fiber sensors response for the monitoring of temperature variations occurring in three different locations of a lithium battery is presented, where the battery is submitted to constant current charge and different discharge rates, under normal and abusive operating conditions.

TL;DR: In this article, the authors deal with quality characteristics such as cutting force, surface roughness and specific cutting energy in internal cryogenic cooling assisted milling of hardened steel vis-a-vis mathematical modeling and multiple attributes optimization by using response surface methodology.