Tachometric and thermal anemometers are two types of instruments mainly used in typical standard measurements in meteorology, ventilation, air conditioning, technical and industrial measurements. Both types of these instruments have many beneficial metrological properties, which causes their widespread use in many measurement issues. However, the sensors of mechanical anemometers have large dimensions

Laser trackers (LTs) are widely used for large-scale dimensional metrology. Periodic LT performance evaluation is a key aspect in ensuring measurement reliability. The existing documentary standards for LT performance evaluation require scale bars and special artifacts that are often unavailable for many LT users. A network-based method is considered in this paper as a simple and effective approach

Poor selection of footwear, underestimation of foot health, sedentary life, and lack of accessible foot screening can have significant long-term adverse effects on the health of lower limbs. Unobtrusive, pervasive methods for automated foot screening have the potential to allow for timely detection of foot abnormalities. In the present study, we describe a proof-of-concept where data collected through

Current strategies for quality-related process monitoring mainly focus on a single quality indicator. For multiple related indicators, traditional algorithms extract the same quality-related features from variable spaces while neglecting the specific features of each indicator. Considering the correlation among these quality indicators, essential information can be captured in common features without

We present a method for PPP adjustment based on Recursive Least Square Estimation (RLSE). This method estimates the stochastic model of GPS, GLONASS, Galileo and BeiDou observations by using RLS-Variance Components Estimation (RLS-VCE). The accuracy and the convergence time of horizontal, altitudinal and three-dimensional components is compared by using both nominal and RLS-VCE method so that the estimated

The fact that the calculation model and optimization method are critical to the optimization efficiency of ride comfort. To improve the reliability of this process for heavy vehicles, this article proposes a systematic modelling method that is based on the coupled nonlinear dynamics of suspension components and a hierarchical optimization method that considers passenger comfort, cargo safety, and parts

The interest in Ultra-High Concentrator Photovoltaic (UHCPV) devices has motivated the use of solar cells under ultra-high irradiance levels (+1000 suns). Temperature effects and variations in the spectrum of the incoming light on the solar cells need to be analysed to understand their performance under real operating conditions. In this work an experimental setup, based on an indoor multi-flash solar

In this paper, the effects of detection speed on eddy current testing (ECT) signals are studied, and the quantitative evaluation method of rail surface cracks at different speeds is proposed. According to the finite element simulation analysis, the excitation frequency and coil parameters are optimized. A high-speed ECT system is established for rail crack detection experiments in a lift-off range

Abstract This paper presented an efficient electronic nose (e-nose) system, named “NOS.E”, for odour analysis and assessment. In addition to the reliable hardware and software designs, an airflow intake system is implemented to ensure the precise odour analysis procedure in the NOS.E system. Besides, a particular control logic was introduced to improve the test efficiency of the NOS.E by reducing operation

The use of the magnetic flux density change as a diagnostic parameter in screw tightening torque of bolts is discussed in this study. The proposed methodology uses the inverse magnetostrictive effect, considering that the magnetic flux density changes according to the internal stress of the bolt. In the experiments, we measured the strain and magnetic flux density of the magnetostrictive material FeCo

Spherical detector (SD) is promising in the field of subsea pipeline defect detection because of low risk of blockage and quasi-real-time capacity. However, rolling stability has great influence on the detection performance of the SD. This paper proposes posture stabilization measures for enhancing performances of the SD in pipeline spanning inspections via analyzing the mathematical model of detection

Robust identification of bearing health states is closely linked to timely condition monitoring and downtime reducing for rotating machinery. Although many proposed algorithms achieve extraordinary performances on feature extraction, uncertainty still remains for the bearing fault identification. To address this problem, this paper introduces a two-stage framework for bearing fault detection using

An assessment of electromagnetic compatibility is important from a technical as well as legal point of view. The harmonized standards should provide detailed guidelines enabling assessment of electromagnetic compatibility for the typical application of devices in systems. This paper presents the specific issues accompanying measurements of conducted electromagnetic interference in multiconverter systems

Intelligent diagnosis algorithms can monitor faults with industrial production of a timely manner via their powerful learning ability. Multi-sensor diagnosis systems can more comprehensively describe the state of equipment and avoid the influence of incorrect data acquisition locations, which is beneficial to fault diagnosis. The fusion of the original data is a difficult problem, and it is hard to

A high-accuracy, large-scale measurement system of laser trackers is essential for aircraft assembly. The registration from a measurement coordinate system (MCS) to an assembly coordinate system (ACS) depends on an enhanced reference system (ERS). The usual method to construct a measurement system is the best-fit of single station (BFSS) method, which is highly sensitive to ERS deviation. In this paper

Vibration performances of planetary gears are greatly affected by the flexible ring gear and planet bearing faults. However, the previous works only considered single flexible ring gear, rigid planetary gear system or planet bearing fault in their models. To overcome this problem, a flexible-rigid coupling dynamic (FMBD) model for a planetary gear is presented. Both the flexible ring gear, flexible

Bearing faults account for approximately half of all electric machine failures. Bearing condition monitoring is of practical importance. Until now, there is not any complete research on application of frequency domain signal features on bearing natural fault prediction and also application of ANFIS fuzzy systems for natural bearing fault classification, especially using acoustic emission signals. So

For the first time, the electrochemical Brownian motion is considered in the context of discrete Chebyshev spectroscopy. The computer processing of output signal of analog-to-digital converter operating in the first-order sinc filter mode enables measuring the discrete Chebyshev spectrum of electrochemical analog of Brownian particle coordinate. It is shown that there is the Chebyshev power spectral

The rapid increase in the number of vehicles equipped with GPS devices has resulted in using automatic vehicle location (AVL) data as probes to identify traffic flow status as well as route travel speed on a very fine spatial-temporal scale. However, these traffic monitoring approaches heavily rely on the widely distributed probe vehicles in the network and the high frequency of these probe samples

A novel approach based on infrared spectrum analysis for early-warning of longitudinal tearing of the conveyor belt was proposed in the paper. Unlike most existing methods, the proposed method monitors the change process of the infrared radiation field of the longitudinal tearing through the infrared thermal imaging technology, and judges whether there is the risk of the longitudinal tearing of the

A large number of children die due to pneumonia every year worldwide. An estimated 1.2 million episodes of pneumonia were reported in children up to 5 years of age, of which 880,000 died in 2016. Hence, pneumonia is a major cause of death amongst children, with high prevalence rate in South Asia and Sub-Saharan Africa. Even in a developed country like the United States, pneumonia is among the top 10

Spherical detector (SD) is promising in the field of subsea pipeline defect detection because of low risk of blockage and quasi-real-time capacity. However, rolling stability has great influence on the detection performance of the SD. This paper proposes posture stabilization measures for enhancing performances of the SD in pipeline spanning inspections via analyzing the mathematical model of detection

Temperature monitoring is one of the easiest and frequent way to support maintenance procedures in the industry. In this paper, a procedure of long term temperature data processing for anomaly detection is proposed. The data obtained from a commercial SCADA (supervisory control and data acquisition system) covers a couple of months of gearbox operation. During that period, repair action has been performed

The introduction of Internet of Things (IoT) technologies, connected and synchronized devices, and smart solutions have brought tremendous technological advancements in global communication. The increasing demand for innovative measurement systems, smart sensing nodes and battery-less instruments is challenging instrumentation and measurement industries to improve communication, power budget and the

The article presents the monitoring potential of a simplified surface Time Domain Reflectometry (TDR) sensor design. Its basic element is a polyvinyl chloride (PVC) plate with two rods placed along the plate edges. The paper describes typical, invasive TDR sensors and the attempts to build a non-invasive TDR sensor for the dielectric moisture determination. The newly developed flat TDR sensor presented

Monitoring and diagnostics are vitally important in smart manufacturing systems since early detection can reduce downtime, protect environment, improve work efficiency, and save cost. The current work for monitoring and diagnostics mainly process the system condition data from multisensor by some mainstream machine learning and deep learning methods. However, these methods’ performance is limited by

Deep learning has been widely used nowadays to achieve an automated fault diagnosis of rolling bearings. However, most of deep learning based bearing fault diagnosis methods are based on the assumption that the recorded samples are labeled data, though most of field data are recorded without label information. To address this issue, an effective semi-supervised learning method based on the principle

Critical engineering components in the process of designing have employed fail-safe approaches and damage tolerance in industry optimization intelligent processing. Different types of geometrical intricacies were occurring in designing of pressure vessels while considering the parameters. The failures may be due to manufacturing defects or pre-existing flaws present in the cylinder. Even in the probabilistic

By considering railway track geometry as a fractal pattern, the irregularity of the track geometry can be expressed numerically with the help of fractal dimensions. In this study, a novel algorithm based on ruler method has been developed and a program was written to determine the fractal dimensions of railway track geometry graphs. Four different fractal dimensions of DR1, DR2, DR3, and DR4 were proposed

Abstract Degradation assessment (DA) is one of the most important technologies to implement the health management and predictive maintenance of rotating machinery. As the main task of DA, anomaly/degrade point detection and remaining useful life (RUL) prediction method of rolling element bearings is investigated in this paper. To detect the abnormal point more accurately, root mean square value is

This paper presents a novel Unmanned Aerial Vehicle (UAV) payload designed to perform semi-autonomous contact inspection tasks in vertical structures. The presented system includes on-board positioning capabilities to calculate the distance and angle between the structure and the UAV that support the navigation in the neighbourhood of the structure, considered a GPS-denied area. The collected navigation

In oil fields, multiphase flow meters (MPFMs) yield important data for proper reservoir management to maximize the oil-gas production throughput. MPFMs are also required in downstream industries such as refineries to monitor the quality of the end product and in power generation to estimate the amount of wet steam, which if its flow rate is high may damage the blade’s turbines. For decades, radioactive

The measurement data from an implemented device together with some reanalysis meteorological data were statistically analyzed via the evaluation of the mean, standard deviation (SD), mean bias error (MBE), root mean square error (RMSE), correlation coefficient (λ), normal distribution function (NDF), empirical cumulative distribution function (ECDF), scatter plot (SP), diurnal cycles (DC) and annual

To evaluate the mechanical properties of structures in service, a portable micro-indentation device was developed and built. The basic design principle of the indentation device, i.e. measurement of the indentation depth and the indentation force with sufficient accuracy, was discussed. To avoid using load cell to decrease the machine compliance, a new method that using the current through voice coil

Corrosion initiation time of embedded steel is an important service life parameter, which depends on concrete material make-up, exposure environment, and duration of exposure. The determination of corrosion initiation time in the laboratory is arduous due to the activities involving the data gathering process. This study leverages the capability of machine learning (ML) models to estimate corrosion

Structural Health Monitoring (SHM) is of great importance for the preventive protection of historical buildings. Real-time monitoring and early warning of the structural response have advantages of timeliness and early detection of abnormal structural conditions. Feiyun Wood Pavilion, a historical timber building in China, was taken as the object to study the early warning mechanism for real-time monitored

Complicated irradiation setup inside the water for intraoperative electron dosimetry suggests the plastic phantoms as an alternative medium. Depth scaling (cpl) and fluence scaling (hpl) factors for intraoperative electron dosimetry inside the PMMA phantom were measured in this study. cpl and hpl values were obtained at electron energies of 6, 8, 10 and 12 MeV through ionometric measurement. Results

Preceding researches proved that improper driving lead of tractor front wheels results in power circulation in transmission system, excessive wear of tires, premature rough ride, lower braking performance, and higher fuel consumption for mechanical front wheel drive (MFWD) tractor in rectilinear motion. For the first time, this study attempts to ascertain the driving lead dependency on draft force

Data acquisition plays a significant role in determining and optimizing maintenance actions for railway wheelsets, as small inaccuracies translate into decreasing useful life, unnecessary downtime and costs. In this study, a comparison between data acquired from three different inspection devices: i) manual (gauge device), ii) laser and iii) under-floor wheel lathe; is presented for three wheelset

Soil temperature (ST) as a vital variable of soil plays a key role in agriculture products, surface energy transactions, soil moisture balance, etc. In developing countries like Iran, access to the ST data may be limited. Hence, estimating this parameter by an appropriate alternative approach is of great importance. Two novel hybrid models are developed in this study based on Elman neural network (ENN)

Due to the complexity and harsh operating environment of planetary gear transmission system, compound fault may co-exist in the planetary gearbox, which results in different type faults coupling together and the weak fault impulse features being completely submerged by strong ambient noise, thus making it a great challenge to extract fault-related information from planetary gearbox. To address these

Recently, domain adaptation (DA) algorithms have been extensively employed in many fault diagnosis applications. Most prior researches perform well under a general assumption: the distributions of samples are balanced. Nevertheless, the unbalanced distributions of samples are common in practical applications which may cause the performances of these researches drop dramatically. To overcome this deficiency

Due to its excellent performance, composite materials are widely used in engineering structures. However, because of the velocity anisotropy, it is difficult to detect the damage accurately. In this paper, a novel velocity anisotropy probability imaging method is developed. Firstly, the velocity in all directions is obtained through numerical simulation technique. Secondly, the model of velocity anisotropy

This study focuses on the time stability of different metrological characteristics of quadrupole mass spectrometers (QMSs). Investigated parameters were the sensitivity, when using a Faraday cup as a detector, the peak position, the peak width, the gain of a secondary electron multiplier, and the minimum detectable partial pressure. Eight different commercial QMSs were investigated at seven national

To calibrate transcranial magnetic stimulation (TMS) devices before clinical trials, a 264-channel high-performance magnetic field detection system for TMS is proposed in this paper. The magnetic field detection system consists of three parts: 3D magnetic field measurement sensor (MFMS) array, 264-channel data acquisition (DAQ) card and monitor software. The 3D MFMS array is made of induction coils

The aim of this study was to compare the performance of FT-NIR spectroscopy and near-infrared hyperspectral imaging (NIR-HSI) in predicting the Corg and Nt contents in mine soils. The mine soil samples were measured for the Corg and Nt contents and their NIR spectra were recorded (1000–2500 nm). Predictive models were developed using 126 samples with partial least square regression (PLSR) or artificial