Acoustic-based damage detection method

Most of the structural health monitoring (SHM) methods is either based on vibration-based and contact acoustic emission (AE) techniques. Both vibration-based and acoustic emission techniques require attaching transducers to structure. In many applications, such as those involving hot structural materials for thermal protection purposes or in rotating machines, non-contact measurements would be preferred because the operating environment is prohibitive leading to potential damage in contact sensors or their attachments. In this paper, a new non-contact, acoustic-based damage detection method is proposed and tested with an objective that the proposed method is able to detect the location and extend of damage accurately. The proposed acoustic-based damage detection method is a direct method. In this proposed method, changes in vibro-acoustics flexibility matrices of the damage and health structure are used to predict the location and extend of damage in the structure. A case study involving actual measured date for the case of a fixed–fixed plate structure is used to evaluate the effectiveness of the proposed method. The results have shown that the proposed acoustic-based damage detection method can be used to detect the location and extend of the damage accurately.     

Object location fire precision test technology by using intersecting photoelectric detection target

To improve four across screens system measurement precision on flying projectile location, the new method that adds two incline screens to four intersecting screens system to form six intersecting screens was put forward and the flying object coordinate test model was set up. This method not only gains object coordinate but also measures object's pitching and azimuth angle that can amend coordinates and improve measurement precision. The differential methods were used to analyze their measure errors, which came from the angle of intersection screen, the thick of screen, the time and distance of measuring, and give out measure errors distributing. The experimental result shows the new measure method can improve measurement precision that meets test demand.     

Research on photoelectronics properties of array emitting diode and its light energy distribution in detection screen

According to the principle of multi-screen intersection target measure flying projectile parameters, the photoelectronics properties of array emitting diode that form detection screen in multi-screen intersection target and its light energy distributing were studied. The form of detection screen using array emitting diode and the measure principle of four screens intersection were analyzed. The properties of emitting diode were analyzed based on its compound emitting mechanism and P–N ties internal current carrier. The light energy superposition principle was applied to set up light energy distributing model and give out its arithmetic. Through calculation and analysis, the light energy distributing is asymmetric when being close to diode position and the output variation range of light energy is large relatively. When test position is far from diode, the light energy distributing is uniformity, but the energy is relatively feebleness in edge of screen. Detection screen light energy distribution is trapezoidal in whole screen. The variety of emitting diode luminous flux is very distinct when projectile close to pointing light source, the output signal in received detective circuit is very high which is propitious to improve acquirement rate.     

Detection H2S mixed with natural gas using hollow-core photonic bandgap fiber

An optical fiber gas sensor using hollow-core photonic bandgap fiber as a gas cell is proposed to detect H₂S mixed with natural gas. This sensor is advantageous for eliminating instability of light source, impact of thermal zero drift, and zero shift of photoelectric device. The gas sensing probe of configuration is using two shorter pieces of hollow-core photonic bandgap fiber (HC-PBF) with the same overall length instead of one long piece of HC-PBF to improve the system response. The experimental dates indicate that a minimum detectivity of 10 ppm for the system configuration was estimated.     

Evaluation of single virus detection through optical biosensor based on microsphere resonator

Shift of resonance frequency in microsphere optical resonator due to attachment of a desirable particle is obtained. Our 3-D finite element numerical method (FEM) simulations’ results show the path of light through microsphere and its variation due to attachment of particle. It is apparent that after attachment of particle to microsphere's surface, light is inclined to pass through the particle. Subsequently, the path of light becomes longer than previous. Because of this phenomenon, the resonance wavelength shifts to longer wavelengths. It is shown that microsphere optical resonator is a prominent biosensor for single virus detection since we applied characteristics of virus for particle in our simulations. Response of this biosensor depends on the characteristics of particle like its radius as we show in this article. Transmission spectrum of fiber which reveals a selected resonance frequency, have been studied in the frequency range of 106.3 to 107 THz under three different sizes of particles. The results show that the amount of frequency shift rises by enhancement of particle's size.     

A robust edge detection method with sub-pixel accuracy

In this paper, a new edge detection approach combining gray-moments operator with smoothing spline algorithm is proposed, which is invariant to additive and multiplicative noises in the image. This approach consists of two steps: firstly, a continuous blurred edge model is obtained using the smoothing spline algorithm in the edge region detected by Sobel operator; then a gray-moment solution is derived for both the one- and two-dimensional situations using the blurred edge model. Testing of this new detection approach demonstrates more robustness against the white Gaussian noise and speckle noise, and run time very close to the gray-moment and space-moment operators. The above advantages indicate this approach is very suitable for on-line accurate detection.     

Abnormal crowd behavior detection by using the particle entropy

The crowd distribution information is the crucial information for abnormal behaviors detection in the crowd scenes. In this paper, we firstly refer to the definition of the entropy and propose an algorithm effectively and accurately representing the crowd distribution information in the crowd scenes. The proposed algorithm not only avoids unstable foreground extraction, but also owns low computational complexity. To detect the abnormal crowd behaviors, we use the Gaussian Mixture Model (GMM) over the normal crowd behaviors to predict the abnormal crowd behaviors since GMM usually can deal well with the unbalanced problem. In this paper we simultaneously use the crowd distribution information and the crowd speed information to estimate the parameters of GMM over the normal crowd behaviors and predict abnormal crowd behaviors. Experiment conducted on publicly available dataset consisting of gathering and dispersion events validates that the proposed approach can preeminently reflect the crowd distribution information. In addition, experiments conducted on publicly UMN dataset demonstrate that the proposed abnormal crowd behavior detection method has an excellent performance and outperforms the state-of-the-art methods.     

Detection and tracking strategy for license plate detection in video

In this paper, we present a novel method to detect license plates in video sequences automatically. The framework mainly integrates the cascade detectors method and the Tracking Learning Detection (TLD) algorithm. The cascade detectors are used to detect license plates, and the TLD algorithm is adopted to track the license plate regions. The license plates in the first frame image are detected by the cascade detectors to build the original tracking list, the tracking results and the detection results in following frames will be compared, and the newly appearing license plate information will be added to the tracking list. Meanwhile, the tracking results existing in the current tracking list would be replaced by the corresponding detection results with higher degree of confidence. We demonstrate the effectiveness of our algorithm for license plate detection task on a road intersection dataset, and the experimental evaluation shows the detection performance has been greatly improved by synthetically using the detection and tracking strategy.