800 publications from this institution
We applied wavelet transform method to analyze the deformation observation in Liaoning char-acteristics of the detailed part of signal variation after wavelet decomposition.The research results indicate that: the detailed decomposed signal characteristics of wavelet were different when the scale was differ-ent,it can identify and extract some anomalies from raw data before the earthquake.It is consideranly possible that moderate strong earthquake will occur in the range of about 250 km from the observation point when the annually periodic feature is broken or the detailed singnal variation exceeds the double mean square error and the scale is 3.
Man-made objects such as mechanical construction parts can typically be described as a composition of shape primitives like cylinders, planes, cones and spheres. We propose a robust method for the detection and pose estimation of such objects in 3D point clouds. Our main contribution is to enhance a probabilistic graph-matching approach that detects objects using 3D shape primitives with distinct 2D primitives such as circular contours. With this extension, our method copes with difficult occlusion situations and can be applied for object manipulation in complex scenarios such as grasping from a pile or bin-picking. We demonstrate the performance of our approach in a comparison with a state-of-the-art feature-based method for objects of generic shape and a primitive-based approach using only 3D shapes and no contours.
Volterra series is a promising technique with great potential for nonlinear system identification. The conventional Volterra series model computes the output responses by performing multiple convolutions between the input excitation and Volterra kernels function. However, the difficulty in acquiring the excitation forces of civil engineering structures under operating conditions greatly limits the application of using Volterra series-based method for system identification. This paper proposes an output-only-based approach using Volterra series model for nonlinear structural damage detection, by quantifying the nonlinear behavior of structures without the prior knowledge of external excitations. The proposed approach uses the structural responses measured at two different locations to identify the kernel function parameters and evaluate the contribution of nonlinear components in the measured responses. The ratio between the standard deviation of the nonlinear components and that of the overall structural response is adopted as damage-sensitive index to quantify the contributions from these two adjacent sensors for performing nonlinear structural damage detection. Numerical studies on a beam structure with a breathing crack under different levels of white noise excitations and experimental studies on a precast segmental concrete column subjected to ground motions with different peak ground acceleration (PGA) values are conducted to validate the capability and accuracy of using the proposed approach for nonlinear structural damage detection. The results demonstrate that the proposed approach is capable of performing nonlinearity quantification effectively and locating structural nonlinear damage. The increasing damage index value can also be used to register the increasing damage severity.
Aiming at the problem of a small parameter value range when a one-dimensional chaotic system presents a chaotic state, this paper proposes a new type of hybrid power exponential chaotic system (HPECS). HPECS combines the classic one-dimensional Sine chaotic system to form a new chaotic system (HPECS-SS). Experiments show that the obtained new chaotic system has better chaotic performance, a more extensive parameter value range, and higher sensitivity. Simultaneously, on the basis of HPECS-SS, a new image encryption algorithm is proposed. The algorithm uses the key generated by the SHA-512 algorithm and HPECS-SS to iteratively output the chaotic sequence, SFY algorithm combines the chaotic sequence to perform two rounds of scrambling on the plaintext sequence to obtain the scrambling sequence, and finally, through the modulus operation to diffuse the scrambling sequence to form the encryption matrix of the plaintext image, simulation experiment analysis shows that the algorithm has a large key space, good encryption effect, and security; the pixel change rate (NPCR) and the normalized average change intensity (UACI) are close to ideal values which can resist various cryptanalysis and attacks.
This paper proposes using the multi-type sensor vibration measurements, such as from a relative displacement sensors and a traditional accelerometer for the damage detection of shear connectors in composite bridge under moving loads. Hilbert-Huang Transform (HHT) spectra of these responses will be fused with a data fusion approach i.e., Dempster-Shafer method, to detect the damage of shear connectors. Experimental studies on a composite bridge model in the laboratory are conducted to demonstrate the effectiveness and performance of using the proposed approach in detecting the damage of shear connectors in composite bridges. Both undamaged and damaged scenarios are considered. The detection results with the data fusion of multi-type sensor measurements show a more reliable and robust performance and accuracy, avoiding the false identifications.
Vibration based structural health monitoring methods are usually dependent on the first several orders of modal information, such as natural frequencies, mode shapes and the related derived features. These information are usually in a low frequency range. These global vibration characteristics may not be sufficiently sensitive to minor structural damage. The alternative non-destructive testing method using piezoelectric transducers, called as electromechanical impedance (EMI) technique, has been developed for more than two decades. Numerous studies on the EMI based structural health monitoring have been carried out based on representing impedance signatures in frequency domain by statistical indicators, which can be used for damage detection. On the other hand, damage quantification and localization remain a great challenge for EMI based methods. Physics-based EMI methods have been developed for quantifying the structural damage, by using the impedance responses and an accurate numerical model. This article provides a comprehensive review of the exciting researches and sorts out these approaches into two categories: data-driven based and physics-based EMI techniques. The merits and limitations of these methods are discussed. In addition, practical issues and research gaps for EMI based structural health monitoring methods are summarized.
Fracture detection technique based on 3-D P-wave seismic dataset has been a powerful tool for fractured reservoir characterization in recent years. However, as the most economical method of fracture detection, the accuracy and resolution of this method has been doubted sometimes. The major aspect of this paper is to prove the effectivity of this method. Traditionally, fracture information comes from well data, in particular image log and core. The purpose of this article is to prove that P-wave azimuthal anisotropy technique not only can describe the fracture character in thin limestone reservoir to regions between the wells but also can get result with good accuracy and resolution. The results indicated that the final fracture orientation and intensity got from 3D P-wave azimuthal anisotropy are extremely consistent with FMI/CMI data from drilled wells.
This paper presents a new approach for damage detection based on swarm intelligence technique and a hybrid objective function. Damage identification is treated as an undetermined inverse problem, when a limited number of measurement information is available. Then a hybrid objective function is proposed, in which the Bayesian inference and sparse technique are used. An improved swarm intelligence technique, named K-means Jaya algorithm, is developed to optimize the defined hybrid objective function to identify structural damage locations and severities. The proposed approach can be used to obtain good identification results, even when high level noise is considered and incomplete modal data is used.
This paper proposes a structural damage identification approach based on model updating with electromechanical impedance sensitivity and the sparse regularization technique to identify the location and severity of minor damage in structures. The sensitivities of the resonance frequency shifts in the impedance responses with respect to the stiffness parameters of the host structure are calculated and used to identify the damage with a small number of resonance frequency shifts. Numerical verifications on a single lead zirconate titanate (PZT) transducer patch and a PZT on a narrow aluminum plate structure are conducted to validate the finite-element modeling technique to calculate the impedance. The effectiveness and performance of the proposed structural damage identification approach are demonstrated with numerical simulations on an aluminum plate model attached to a PZT transducer patch. The initial finite-element model and a limited number of resonance frequency shifts in the impedance responses are used for the identification. Sparse regularization, namely, the l1 regularization technique, is used for solving the inverse problem. Single and multiple damage scenarios are considered. The effects of noise in the measured impedance signals and the number of available frequency shifts on the performance of the proposed damage identification approach are investigated. The results demonstrate the performance and robustness of the proposed approach.
In 2020, the BeiDou-3 global navigation satellite system (BDS-3) was officially completed and put into service. Currently, network real-time kinematic (RTK) technology is considered the main means through which to improve the positioning accuracy of the BeiDou navigation satellite system (BDS). This paper proposes a long-range undifferenced network RTK (URTK) algorithm, based on multi-frequency observation data of the BDS. First, the multi-frequency phase integer ambiguity resolution (AR) model considering atmospheric error parameters is designed, and the multi-frequency phase integer ambiguity of the long-range BDS reference station is determined. Then, the undifferenced integer ambiguity of each reference station is obtained, using linear variation based on the accurately determined phase integer ambiguity between reference stations, and the undifferenced observation error of each reference station is calculated. Considering the weakening spatial correlation of the observation errors between long-range stations, undifferenced classification error corrections of a reference station network are separated, according to different error characteristics. Finally, the inverse distance weighting method is employed to calculate the classification undifferenced error correction of the rover station. The rover station corrects the observation error through applying the undifferenced error correction to achieve high-precision positioning. The measured data of a long-range continuous operation reference station (CORS) network are selected for an experiment. The results show that the proposed algorithm can quickly and accurately realize the resolution of the BDS integer ambiguity of a reference station network and establish an undifferenced area error correction model in order to achieve accurate classification of undifferenced error correction values for a rover station. In China, the BDS-3 is superior to the global positioning system (GPS) in terms of the satellite number, position dilution of precision (PDOP) value, AR success rate, stability, and convergence time. The results show that the AR success rate, stability, and convergence time increase with the operational frequency, and the BDS-3 can achieve centimeter-level positioning of single-system rover stations without relying on the GPS.
Cast-steel joint is a widely used type for long-span space structure.By forming finite element model and performing elastic-plastic analysis to special cast-steel joint of Chongqing Olympic stadium steel reticulated shells,the stress and strain distributing condition of cast-steel joint are get.And by full-scale experiment,the stress on test points of the cast-steel joint is obtained.Combining theoretical analysis with the experiment,stress distributing rule is gained and the carrying capacity of the joint is evaluated.Furthermore,some advice to design of large special cast-steel joint is given.
It is significant to apply the finite element analysis technology in the design,which can shorten the development cycle,improve product quality and reduce manufacturing cost.A finite element model for elbow-bar mechanism-main part that may influence press transmission precision and safety was established through the finite element analysis software Ansys Workbench,which strength in cycle of motion was analyzed,and then stress distribution law of the main transmission driving link in the whole cycle of motion was obtained.Finally,through displaying the position exceeding stress limit,the causes occurred was analyzed,thereby the structure was optimized and the safety of the mechanism was guaranteed.In one word,the finite element method provides security for the development and safe operation of the product.
