查看更多>>摘要：A typical method for real-time and unpolluted measurement of chemical oxygen demand (COD) is UV-Vis absorption spectroscopy, however, contamination of the measuring system's optical window surface affects the measurement accuracy during long-term monitoring. This study proposes an optical window surface contamination (OWSC) compensation method, and a multi-wavelength smart sensor for long-term accurate COD measurement was developed. This study uses equivalent absorption spectrum (EAS) to describe OWSC, and explores its spectral characteristics. Therefore, we can predict the EAS of OWSC between 250 and 380 nm based on the measured absorption spectrum between 380 and 440 nm, and subtract the EAS of OWSC to get the absorbance of COD to complete the spectrum compensation. Furthermore, we designed a smart COD sensor which has the advantages of real-time warning and maintenance-free. We proved that the OWSC compensation has excellent applicability through experiments using the COD sensor, and long-term accurate COD measurement can be achieved.
查看更多>>摘要：Chatter has been the most significant factor affecting grinding quality and efficiency in the camshaft high-speed grinding process, which is complex and difficult to detect. Consequently, this paper proposes a novel approach to detect the chatter for high-speed grinding process of camshaft based on variational mode decomposition (VMD) parametric optimization. In this method, recorded chatter signal has been pretreatment using fast local mean empirical mode decomposition (FLMEMD). The number of modes is estimated according to the similarity coefficient criterion, and the quadratic penalty is optimized based on comprehensive evaluation factor method. The energy entropy is used to detect the chatter frequency bands automatically. The vibration signal containing chatter frequency is simulated and the high-speed grinding experiments with different conditions are performed to evaluate the effectiveness of the proposed method. The results show that the proposed method is suitable for detecting chatter in the high-speed grinding process of camshaft.
查看更多>>摘要：Anisotropic Magneto-Resistive (AMR) sensing is one of the most burgeoning techniques for traffic volume measurement to support effective traffic management. This is because of its small size, low power consumption and environmental resilience. This paper presents a vehicle detection algorithm based on a new type of AMR sensor called Smart Road Stud (SRS), which can detect the Magnetic Field Intensity (MFI) disturbance generated by passing vehicles. The proposed two-step process can extract the disturbance signal from MFI time series with a simple determination of threshold and a more widespread applicability. However, when vehicle temporal headway is short, an extracted signal may be generated by more than one vehicle. For this case, a method to recognize the number of vehicles the signal corresponds to is proposed also. The results show that the accuracy of traffic volume measurement is higher than 97% when detecting traffic volume in two adjacent lanes.
查看更多>>摘要：An axial inductive displacement sensor, which can be fixed on radial direction to measure axial displacement of the suspended rotor, is proposed in this paper. Based on Schwarz-Christoffel transformation, 3D inductance of the proposed sensor is calculated. The novel approach for 3D inductance calculation is compared with 3D FEM results, showing the feasibility for practical applications. Static and dynamic characteristics are evaluated on a magnetic bearing platform. Sensitivity and linearity are 2.63 V/mm and 0.46%, respectively. Static noise result shows that the proposed sensor can reach a resolution of 5 mu m. Dynamic characteristics tests, including vibrating and shocking experiments show that the displacement detection capability of the proposed sensor is similar to that of an eddy current sensor, showing the potential of the proposed sensor used in other fields where eddy current sensors have already be applied.
查看更多>>摘要：The detection and accurate location of metal components surface defects are the basis of automatic laser cladding/laser additive manufacturing repair. Most deep-learning methods utilize regression networks trained with non-maximum suppression and loss function to correct the offset. However, these methods are unable to implement sufficient punishment for accidental offset, resulting in an inaccurate offset prediction. In this investigation, we proposed a reweighting offset bin classification network to solve this issue. The network discretizes the offset values into multiple offset bins by its probability distribution and corrects the offset of the bounding box by predicting the probability of these bins. In addition, the offset bins are classified into different balance groups for parallel training to ensure that all bins have relatively balanced weight norms. Comparative experiments conducted on the advanced detection network and defect datasets demonstrate that our method can locate defects accurately.
查看更多>>摘要：This paper proposes an improved double-dictionary K-singular value decomposition (IDDK-SVD) algorithm for the compound fault diagnosis of rolling element bearings under complex industrial environments. In the framework, a double-dictionary is first designed for respectively identifying and distinguishing compound-fault features. In addition, an atom selection strategy based on fault information is constructed by combining the Gini index with envelope periodic modulation intensity, which can simultaneously take the periodicity and impulsivity into consideration to find a set of atoms most related to fault for the update of double-dictionary. Finally, an estimation method for calculating the residual error in the sparse coding stage is also presented to meet a better result. Benefitting from these improvements, the proposed IDDK-SVD is effective in the application of compound-fault diagnosis, which is verified by both simulation signals and real signals collected from the locomotive bearing test rig.
查看更多>>摘要：In order to solve the problems that it's difficult in installing a sensor in a narrow space and identifying microdisplacement direction in micro-displacement measurement. A three-dimensional micro-displacement measurement method based on capacitance-grating sensor was proposed by highlighting the idea of combining several groups of capacitance grids and the theory of displacement coordinate decomposition. The sensor structure was optimized and a three-dimensional micro-displacement test system was also established. By taking into consideration the positional relationship of the sensors in measurement model, a micro-displacement measurement model of sphere eccentricity was established to deduce the relationship between the displacement in the x,y and z directions and capacitance change. The relationship between the displacement direction and the capacitance change trend was also analyzed, based on which, a three-dimensional spatial microdisplacement decoupling mathematical model was established to measure displacement and judge the specific direction. BP neural network was also used to realize the decoupling of three-dimensional spatial microdisplacement and verification of decoupling accuracy. Under the ideal simulation conditions, the decoupling errors in x,y and z directions are less than 4 mu m. The experimental results show that decoupling errors are all less than 8 mu m. According to the results, the three-dimensional micro-displacement measurement method based on capacitance-grating sensor could measure the three-dimensional micro-displacement and identify the direction. The accuracy could reach 1.6% over the full range of sensor.
查看更多>>摘要：Today, due to the widespread utilization of Induction Motors (IMs) in different industries, their condition monitoring is of great importance. Concentrating on the failures of IMs, it has been acknowledged that the stator inter-turn faults (SITFs) are the most frequent electrical failures. This paper puts forward an algorithm for SITF detection founded on Kalman Filter (KF). More specifically, the proposed algorithm employs KF to extract motor current signatures (MCS) and motor voltage signatures (MVS). Afterward, a statistical SITF index is used, based on the standard deviation of the extracted signatures. The proposed SITF index is technically robust against nonfault conditions including voltage quality problems and heavy load changes as well as has a significant performance in the presence of high measured noise-impregnated signals due to utilization of KF algorithm-based. Moreover, during source harmonic pollutions, the proposed algorithm has a very robust performance. Also, due to straightforward and low-computational mathematical basis, the proposed method is computationally efficient. The performance of the proposed method is validated with numerous simulation and experimental scenarios. The results indicate the proposed SITF index has robust performance, promising accuracy and good speed of convergence.
查看更多>>摘要：The soil layer is a common issue for energy systems as solar panels or prime mover and driven turbomachines. This phenomenon is usually known as fouling, and it consists of a microscopic layer (usually lower than 1 mm) that wraps the surface of these machines and devices. The presence of a deposited layer determines the modification of the surface characteristics as transparency or roughness with the consequent performance and efficiency reduction. In the present paper, a detailed investigation is carried out on seven measurement methods used for estimating the sand layer morphology and thickness. Each method has been applied for measuring similar soil layers, giving the possibility to compare the methodologies and show the capability of each method to obtain different information from the same specimen. Several guidelines and suggestions about technology, cost, and usefulness of each method are also included.
查看更多>>摘要：Microdrill machining is in high demand and is widely applied in various industries where the structural design and material properties of the microdrill are critical components in machining. A composite microdrill composed of cemented carbide and polycrystalline diamond balances the wear resistance, toughness, and hardness properties of the cutting tool. Nevertheless, the tool geometry error must be examined because of complex technique involved in the tool fabrication process. The investigated microdrill is fabricated through a brazing technique that connects the shank and drill body of different material compositions. A computer vision algorithm was developed specifically for measuring the axial straightness error and radial runout of the microdrill. Accordingly, the ability of the developed measurement techniques to perform precise and accurate tool geometry error measurements is evaluated in this study.
NSTL
Elsevier