Felipe-Sese, L.Molina-Viedma, A. J.Pastor-Cintas, M.Lopez-Alba, E....
11页
查看更多>>摘要：Phase-Based Motion Magnification (PBMM) is an effective methodology to visualise imperceptible phenomena based on magnifying periodic subtle movements on image sequences. Moreover, the integration of the optical techniques Fringe Projection and 2D Digital Image Correlation (FP + 2D-DIC) make it possible to obtain 3D displacement maps employing a single camera.In this study, the integration of PBMM with FP + 2D-DIC is exploited for the determination of subtle 3D displacements. An initial solid-rigid test validates of the combination of those techniques. A later test, employing a cantilever beam, demonstrates its correct performing in the determining of Operational Deflection Shapes. In both cases, the results are compared with those obtained with 3D-DIC and Scanning Laser Doppler Vibrometer (SLDV) to evaluate the relation between the magnification factor and the result obtained. Finally, the potential of the proposed integration for the determination of complex mode shapes is demonstrated by obtaining the ODSs of an industrial component.
查看更多>>摘要：Pseudomonas aeruginosa is a waterborne ubiquitous opportunistic pathogen that can be fatal for immunocompromised patients. Here, we report the use of paper-based screen-printed sensors for the electrochemical detection of P. aeruginosa in water sources in only 14 s. P. aeruginosa is identifiable by its unique biomarker pyocyanin, which is redox-active and therefore suitable for direct electrochemical detection without sample pretreatment. The detection method was applied to detect pyocyanin directly in spiked lake water, tap water, sea water and groundwater. The electrochemical response was linearly proportional to the pyocyanin concentration with R2 values between 0.9918 and 0.9991. Additionally, we demonstrated the direct detection of P. aeruginosa in water in concentrations ranging from 5 to 50 colonies/mL. The results are a step towards utilizing simple electrochemical sensing to rapidly determine if water sources are infected with P. aeruginosa prior to bathing, consumption or other use.
查看更多>>摘要：The domain-adaptation technique has been proven to be able to resolve the fault diagnosis under various working conditions. Most research presumes that the health states in the source domain are consistent with the target domain. However, open-set domain adaptation problem that contains the unknown states in testing process remains unexplored. Here we propose an interactive dual adversarial neural network (IDANN) for this problem. First, a closed-set domain adversarial network is trained to obtain the weight of each target instance. Then, an open-set domain adversarial network is trained by importing the weighted unknown classification items and entropy minimization techniques. Through a series of interactive training, the IDANN can not only distinguish the unknown instances but also assign known instances to corresponding classes. Two experiment cases validate the effectiveness of the proposed IDANN method. The comparison results suggest that the proposed method can achieve superior performance in open-set domain adaptation problems.
查看更多>>摘要：In this work, a reconfigurable dual-band multiple-input-multiple-output (MIMO) antenna (RDMA) for the fifth generation (5G) 3.5 GHz and industrial, scientific and medical (ISM) 5.2 GHz has been reported. The reported antenna uses the partial ground plane defected ground structure (PGP-DGS) technique and the integration of the pin diode integrated branch lines (BLs) to obtain dual-band operation. Also, the intermediate structure, without DGS operates in wideband to narrowband reconfigurable mode. The operating frequency of the antenna can be tuned to other frequencies by changing the DGS and BLs design attributes. A novel mushroom inspired dual-band electronics bandgap structure is developed and characterized using a dispersion diagram. The proposed EBG is then placed between RDMA to obtain isolation better than -25 dB between closely packed (at A5G/17.14) antenna elements. The proposed antenna has an acceptable realized gain above 2.5 dBi and a stable end-fire radiation pattern with the main lobe at -45 degrees.
查看更多>>摘要：To increase efficiency of transformers, iron (hysteresis and Fuko losses), copper and abnormal losses must be prevented. Hysteresis loss may be significantly reduced by adding silicon to iron, and Fuko loss may be significantly reduced by using cold-rolled grain-oriented steel (CRGO) in the form of thin sheets with high resistance. To reduce abnormal losses, it is necessary not to use CRGO with ferromagnetic features including cracks in the core sequence. In line with this, currently, the magnetic flux leakage (MFL) method is commonly used to research cracks in ferromagnetic materials. Generally, literature studies researched the variation characteristics of MFL signals collected with magnetic sensors and size of amplitude values according to the physical properties (crack width, crack depth, etc.) of the crack in the ferromagnetic material. Different to the literature, our primary aim in this study is to determine this variation according to the type and geometric features of an artificial full crack with known physical properties created in MOH CRGO steel. The secondary aim of our study is to develop an artificial neural network predicting the type and geometric features of a full crack with unknown geometric features using the data obtained. In line with this, our study first produced an MFL measurement system. Then, artificial full crack samples were prepared with different types and geometric features using MOH CRGO steel. These artificial full crack samples were magnetized by being placed in the core of an electromagnet with 50 kHz AC signal and the surface of the material was scanned in a single dimension with a location-controlled fluxgate sensor. Harmonics of signals obtained from the fluxgate sensor were investigated with DSP lock-in amplifier and the amplitude values for the harmonics with greatest variation were uploaded to the computer. Finally, 3 different Bayesian regularized artificial neural networks (BRANN) were developed and trained using the harmonic amplitude values for full crack samples with known geometric features and used to predict the type and geometric features of full cracks with unknown geometric features. The first of these BRANN was used to identify the fixed or variable width of the full crack type, while the others were used to find the geometric features according to the full crack type. For the BRANNs trained with the K-fold cross-validation method, accuracy degrees of R = 0.99934, R = 0.99999 and R = 0.91654 were obtained, respectively. The trained BRANNs provided results compatible with reality for artificial full crack models with unknown crack type and geometric properties.
查看更多>>摘要：Eddy current testing (ECT) technology is currently one of the effective methods for non-destructive testing of aviation materials. In the application of ECT technology, a lower operating frequency is generally used for aviation metal materials, while carbon fiber reinforced plastics (CFRP) often require higher operating frequencies due to the low conductivity characteristic. However, multiple materials are often used simultaneously in aircraft manufacturing, including metallic materials and CFRP. Therefore, due to the difference in materials, the traditional ECT technology needs to be carried out in the ultra-large frequency range (1 kHz to 100 MHz) during the ECT inspection process of the aircraft, which will bring great difficulties to instrument development and actual operation. Concerning this issue, a self-frequency-conversion ECT method is proposed in this paper, and the corresponding ECT system was developed. The proposed method has two detection signals simultaneously, the current signal and the frequency signal, which are used to characterize the defects of CFRP and metal materials, respectively. Experimental studies on CFRP and aluminum alloys were carried out using the proposed method. The experimental results show that the proposed method can realize the defect detection of metal materials and CFRP in the conventional frequency range of 1 kHz to 1 MHz. Compared with the traditional ECT technique, the proposed method greatly reduces the operating frequency range and can provide better detection sensitivity, which is an ECT technology with great engineering application value.
查看更多>>摘要：The aim of this study was to develop a method for airplane ground roll distance measurement. This method is based on measurements of aircraft accelerations, magnetic field vector, as well as Global Positioning System (GPS) position. A convolution neural network was developed in this study and it recognizes characteristic mo-ments of flight during takeoff: longitudinal acceleration, nose wheel up (rotation), and liftoff, as well as during landing: approach, touchdown, rollout, and stop. The developed neural network includes two filters that enable collection of input data from both the total dataset as well as from data portions for information about the occurrence of a peak at the time of touchdown and the change of acceleration at the time of takeoff.The distance traveled by the plane on the ground during takeoff or landing is then calculated using the GPS coordinates, measured simultaneously. The method uses a sensor system consisting of accelerometers, magne-tometers, and a GPS receiver; a prototype hardware was based on a single-board miniature computer. The hardware is small in size and fits anywhere in the aircraft cockpit. The method has been practically examined by means of flight tests and it was concluded that it performs well: the mean difference in the measured take-off and landing distances from the results obtained with the reference method was 2,92 % and 6,31 % respectively. The method was not sensitive to airplane design type: low wing vs. high wing. Also, the method has been tested for two different pilots and no significant difference in the results of measurement was observed.
查看更多>>摘要：As a result of the rapid development of intelligent equipment, the importance of intelligent sensing technology for use in structural health monitoring applications is increasing. Among the emerging intelligent structure monitoring methods, microstrip antenna sensing technology is attracting considerable attention. The working environments for mechanical equipment are often harsh and highly differentiated. Multiple environmental jamming factors, including water, dust, ice, and other foreign bodies, will reduce the parameter monitoring reliability of microstrip antenna sensors. In this paper, an anti-interfering method for these environmental foreign bodies based on antenna cladding technology is presented. First, a multi-physical numerical model is established to study the mechanism by which the environmental foreign bodies affect the resonant frequency of the antenna sensor. The effects of the foreign bodies on the sensor's resonant frequency are analyzed via simulations. The anti-interfering cladding design method for environmental bodies is then studied. The structure,a shape, and size of the environmental anti-interfering cladding are designed using an FR4 epoxy plate with good heat and moisture resistance, largely causing the fluctuation level of the sensor's resonant frequency with changes in the environment to be reduced by more than 95%. The simulation and experimental results show that the proposed anti-interfering method for environmental foreign bodies using antenna cladding technology greatly improves the reliability of the microstrip antenna sensor and has considerable engineering application value.
查看更多>>摘要：In the DC system of electric ships, insulation drops and grounding will pose a threat to stable ship operation and personal safety. Therefore, it is necessary to monitor the insulation status of the battery pack between high voltage and ground in real time. However, traditional measurement methods have problems such as low accuracy, long measurement time, and poor reliability. In this paper, an insulation detection method based on an unbalanced bridge was proposed and the principle of insulation resistance detection was analyzed. The influence of different resistance values of insulation detection circuits on the measurement error of insulation resistance was studied by simulation analysis and experimental tests to obtain the optimal set of bridge resistance matching designs. Digital filter and Kalman filter were used to filter out noise in the voltage signal. The results show that measurement error of insulation resistance after optimization was less than 3% and drops to approximately 0.46% after processing by the Kalman filter algorithm, which proves that the insulation detection method designed in this paper has high measurement accuracy.
查看更多>>摘要：With the completion of the BeiDou Global Navigation Satellite System (BDS-3), more available frequencies have brought opportunities for precise point positioning ambiguity resolution (PPP-AR). This research theoretically deduced the multi-frequency PPP-AR model and the rule of observable-specific signal bias (OSBs) transformation. Then 34 International GNSS Service stations were selected to investigate the multi-frequency BDS-3 and multi-GNSS PPP-AR. The results suggested that the OSBs products provided by Centre National D'Etudes Spatiales (CNES) have absorbed the impact of inter-frequency clock bias and could be directly added to the original observations to restore the integer characteristics of the multi-frequency ambiguity. Meanwhile, the antenna phase center correction should keep consistent when using the CNES OSBs to restore the Melbourne-Wiibbena ambiguity. The BDS-3 quad-frequency ambiguity-fixed convergence time was 39.0 and 25.1 min for kinematic and static PPP, which was shortened by nearly 15.0 and 3.4 min than the dual-frequency ambiguityfixed solution. The quad-system multi-frequency PPP-AR showed the optimal state, which was 0.66, 0.76 and 2.66 cm for kinematic mode while 0.31, 0.31 and 1.02 cm for static mode in east, north, and up directions, respectively.
NSTL
Elsevier