It is well recognized that strain and deflection data are important indexes to judge the safety of truss structures. Specifically, the shape sensing technology can estimate the deformation of a ...structure by exploiting the discrete strain data without considering the material property conditions. To fill the gap in which most of the methods in SHM (structural health monitoring) cannot be directly used to predict the displacement field, this paper proposed a novel inverse finite element method (iFEM) algorithm based on the equivalent stiffness theory. A deflection sensor is fabricated to focus on predicting the distributed deflection variation of the truss structure. The performance of the deflection sensor was evaluated by a calibration test and a stability test. Finally, it was applied to distributed deflection monitoring in the testing of truss structures. Results of all tests verify that the deflection sensor based on the i-FEM algorithm can predict the distributed deflection variation of the truss structure accurately, in real time, and dynamically.
Conditional Random Fields as Recurrent Neural Networks Shuai Zheng; Jayasumana, Sadeep; Romera-Paredes, Bernardino ...
2015 IEEE International Conference on Computer Vision (ICCV),
12/2015
Conference Proceeding, Journal Article
Odprti dostop
Pixel-level labelling tasks, such as semantic segmentation, play a central role in image understanding. Recent approaches have attempted to harness the capabilities of deep learning techniques for ...image recognition to tackle pixel-level labelling tasks. One central issue in this methodology is the limited capacity of deep learning techniques to delineate visual objects. To solve this problem, we introduce a new form of convolutional neural network that combines the strengths of Convolutional Neural Networks (CNNs) and Conditional Random Fields (CRFs)-based probabilistic graphical modelling. To this end, we formulate Conditional Random Fields with Gaussian pairwise potentials and mean-field approximate inference as Recurrent Neural Networks. This network, called CRF-RNN, is then plugged in as a part of a CNN to obtain a deep network that has desirable properties of both CNNs and CRFs. Importantly, our system fully integrates CRF modelling with CNNs, making it possible to train the whole deep network end-to-end with the usual back-propagation algorithm, avoiding offline post-processing methods for object delineation. We apply the proposed method to the problem of semantic image segmentation, obtaining top results on the challenging Pascal VOC 2012 segmentation benchmark.
To improve the accuracy of earth faults feeder selection in full cable networks under different fault conditions, an improved K‐means algorithm for earth faults feeder selection in full cable ...networks is proposed. Firstly, the transient zero‐sequence network for earth faults in full cable networks is built using the rich fault information contained in its transient current, which per feeder under different fault conditions is decomposed by Fourier transform, active power method, and wavelet packet transform to obtain four features: fundamental wave amplitude, fifth harmonic amplitude, average active power component, and wavelet energy value. Then, the four features are fused by principal component analysis, the principal component components are extracted, and the feature database is established. Eighty per cent and 20% of the database data are used as training sets and test sets, respectively. The feature database is trained by the improved K‐means method to realize fault feeder selection. The proposed method is validated in a full cable network model with five feeders. The findings demonstrate that the suggested technique has high accuracy in feeder selection and is not affected by fault conditions.
Aiming at overcoming the drawbacks of bus voltage deviation and current sharing accuracy degradation caused by conventional v-i droop control in primary control of DC microgrid, a distributed ...cooperative secondary control strategy is proposed in this paper. The strategy includes voltage restoration control and current sharing control. Discrete consensus is applied in the proposed method which considers the discrete nature of measurement, controller implementation, and communication. The controller on each converter exchanges data with only its neighbors on a sparse network of communication across the DC microgrid, further dynamically tracking the output voltage and current. In addition, the proposed control strategy can reduce the impact of communication noise on consensus convergence and accuracy by introducing the consistency gain function. The effectiveness of the proposed method is verified by a grid-connected DC microgrid system based on the MATLAB/Simulink.
Minisci-type alkylation of electron-deficient heteroarenes has been a pivotal technique for medicinal chemists in the synthesis of drug-like molecules. However, such transformations usually require ...harsh conditions (
, strong acids, stoichiometric amount of oxidants, elevated temperatures,
). Herein, by utilizing photoredox catalysis, a highly-selective alkylation method using heteroaryl sulfones has been developed that can be carried out under acid-free and redox-neutral conditions. Because of these mild conditions, challenging yet privileged structures, such as monosaccharides and unprotected secondary amines, can be installed.
Tobacco bacterial wilt (TBW) and tobacco black shank (TBS) are two of the most devastating tobacco soil-borne diseases worldwide. In this study, Pseudomonas aeruginosa NXHG29 exhibited dually ...antagonistic activities against TBW and TBS in vitro assays. Pot experiments were performed to evaluate the capability of a novel bio-organic fertilizer (BOF) consisting of organic fertilizer with NXHG29 to control TBW and TBS. The results showed that application of BOF could more effectively decrease the disease incidence of TBW and TBS than the direct application of NXHG29. Higher amounts of BOF application (0.5% and 1% amendment) resulted in the more suppressive effects on tested pathogens when compared with a low amount of BOF application (0.1% amendment). To determine the antagonistic mechanism of NXHG29, we investigated the colonization pattern of NXHG29 on tobacco roots in a sand system and a natural soil system by tagging NXHG29 with a GFP-marked plasmid. Similar observations were obtained in the two systems. The results indicated that GFP-tagged NXHG29 colonized first the differentiation zones followed by the elongation and maturation zones of the primary roots and subsequently around the junctions of primary and lateral roots. The population dynamics of GFP-tagged NXHG29 on tobacco roots and in the rhizosphere were also monitored. The development of the BOF using dually antagonistic bacteria might provide new options for control strategies, especially with respect to managing both diseases simultaneously in the host plant, which should be more effective in the long term.
This paper proposes a thermal network parameter estimation method for insulated-gate bipolar transistor (IGBT) modules using the junction temperature cooling curve. The proposed method finds the RC ...parameters of a fourth-order Cauer network by establishing a relationship between RC parameters and time constants of junction temperature response curves. Experimental tests are performed to validate the accuracy of the developed method. Results show that the difference of total thermal resistance between the proposed method and IEC standard is below 2%. Advantages of the proposed method over the existing methods are that the proposed method does not need 1) to know the power loss information of IGBT and 2) to heat the IGBT module up to thermal steady state. In addition, we show that the identified RC parameters can be used for condition monitoring and junction temperature estimation.
As a particular two degree of freedom generating method, skiving is effective to manufacture the periodically distributed internal and external profiles, and its cutting edge design is a foundational ...problem. In order to avoid the singularity in analytical methods, this paper studied a discrete surface assisted universal method to identify the cutting edge of skiving cutter and simulate the machining process by discrete cutting points. Firstly, the kinematic model of skiving was constructed in aspects of the parametrical modeling of the cutter and workpiece as well as the machining configuration. The principle of cutting edge identification was investigated based on the conjugation process of skiving in the following. Then, the entire procedure for cutting edge calculation was presented in detail. Therefrom, according to the profile generation during cutting action, the skiving spatial contacts were analyzed through reasonable coordinate frame transformation. At last, an external skiving for involute gear was taken, the cutting edges for two kinds of rake flank were calculated, and the machining error between the machined profile and desired profile was compared to proof the correctness of calculated cutting edges. Besides, the analysis of the spatial contact motions for these cases validated the effectiveness and the practicality of the proposed method.
An efficient and simple synthetic approach has been developed for the synthesis of bis-1,3-dicarbonyl compounds via visible light-mediated oxidation of tertiary amines in the presence of CsPbBr3 ...perovskite. The perovskite photocatalyst exhibited high catalytic performance and recyclability.
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•Preparation of a perovskite material.•The perovskite material exhibits high photocatalytic activity for the synthesis of bis-1,3-dicarbonyl compounds.•The photocatalyst can be recycled and reused.
An efficient and simple synthetic approach has been developed for the synthesis of bis-1,3-dicarbonyl compounds via visible light-mediated oxidation of tertiary amines in the presence of CsPbBr3 perovskite. This heterogeneous photocatalyst exhibits highly catalytic activity and broad applicability to a variety of substrates. It can be recycled by simple centrifugal filtration and reused several times without obvious decrease of activity.
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