Dynamic Detection System Research Articles

Design of dynamic error detection system for grating scale

Grating scale is a closed-loop detection and control tool for precision machine tools, and its accuracy detection needs a higher precision detection platform. There are two kinds of commonly used detection platform guideways: sliding guideway and rolling guideway. Because of the contact of points or lines, the error caused by the guideway itself is obvious. In order to reduce the error of the platform itself, the air-floating guideway with small friction resistance and no vibration relative to the motion is used as the support mode, and the air pressure is debugged according to the smoothness of sliding. The static accuracy detection method of grating sensor is comparatively mature, but there is no effective solution for its dynamic accuracy detection. To solve this problem, we developed a dynamic error detection system of grating scale based on high-precision grating scale. The experimental results show that the system can detect the dynamic accuracy of grating scale, and has high detection efficiency. It is suitable for mass rapid measurement in practical work.

Protective performance test and safety risk evaluation of a powered air-purifying suit

The positive pressure biological protective suit is the highest degree of personal protective equipment, and its performance directly impacts the health and safety of the wearer. Protection factor is the most critical measure of the performance of a positive pressure bio-protective suit. This study establishes a dynamic detection system for the positive pressure bio-protective suit, to evaluate its safety risks, and explores methods to reduce these risks. A manikin was used to perform human actions, such as raising the arms, sitting, and walking, that were simulated at different levels. Integrity breaches of different shapes and sizes were made to different parts of the suit for evaluation. The aerosol concentration and the pressure of the suit were detected. Positive-pressure suits provide exceptionally good protection even in accident scenarios and provide a greater flexibility and more ergonomic benefits. However, sufficiently large (>3 cm) breaches caused a negative-pressure and an inward airflow during vigorous activities. The location of the breach site on the suit also had a significant effect on bio-aerosol leakage. Studies have shown that effective methods to avoid the risk of damage include increasing the air supply flow and performing gentle movements while wearing the suit. The dynamic detection method and the results obtained in this study are a significant advance to predict and avoid the risks associated with powered air-purifying suits.

Fast Dynamic Vehicle Detection in Road Scenarios Based on Pose Estimation with Convex-Hull Model.

Dynamic vehicle detection is of great significance for the safety of autonomous vehicles and the formulation of subsequent driving strategies. A pose-estimation algorithm, namely, the pose estimation with convex-hull model (PE-CHM), is proposed in this paper, and introduced in the dynamic vehicle detection system. In PE-CHM, the convex hull of the object’s point-clouds is first extracted and the most fitted bounding box is determined by a multifactor objective function. Next, the center position of the target is inferred according to the location and direction of the target. With the obtained bounding box and the position inference, the pose of the target is determined, which reduces the interference of the missing contour on pose estimation. Finally, three experiments were performed to validate the performance of the proposed PE-CHM method. Compared with several typical model-based methods, PE-CHM can implement dynamic vehicle detection faster, which reduces the amount of calculation on the basis of ensuring detection efficiency.

Mechanical fault diagnosis based on digital image processing technology

Modern mechanical equipment continues to generate high productivity, at the same time, it has brought many new challenges and new problems. It is of great importance to detect and diagnose mechanical fault diagnosis in time and then provide alarm messages. Therefore, in this paper, we aim to propose a novel mechanical fault diagnosis with the digital image processing technology. Firstly, overall structure of mechanical equipment fault dynamic motion detection system is illustrated and the infrared image segmentation is the key part this system. Secondly, we convert the infrared image segmentation problem to a cluster problem and then, provide a novel immune neural network cluster algorithm. Finally, a representative region for a specific machinery condition is selected according to the largest dispersion degree criterion. Experimental results demonstrate that the proposed algorithm can detect mechanical faults with high accuracy.

Mechanical fault diagnosis based on digital image processing technology

Modern mechanical equipment continues to generate high productivity, at the same time, it has brought many new challenges and new problems. It is of great importance to detect and diagnose mechanical fault diagnosis in time and then provide alarm messages. Therefore, in this paper, we aim to propose a novel mechanical fault diagnosis with the digital image processing technology. Firstly, overall structure of mechanical equipment fault dynamic motion detection system is illustrated and the infrared image segmentation is the key part this system. Secondly, we convert the infrared image segmentation problem to a cluster problem and then, provide a novel immune neural network cluster algorithm. Finally, a representative region for a specific machinery condition is selected according to the largest dispersion degree criterion. Experimental results demonstrate that the proposed algorithm can detect mechanical faults with high accuracy.

Dynamic Fuzzy Rule Interpolation and Its Application to Intrusion Detection

Fuzzy rule interpolation (FRI) offers an effective approach for making inference possible in sparse rule-based systems (and also for reducing the complexity of fuzzy models). However, requirements of fuzzy systems may change over time and hence, the use of a static rule base may affect the accuracy of FRI applications. Fortunately, an FRI system in action will produce interpolated rules in abundance during the interpolative reasoning process. While such interpolated results are discarded in existing FRI systems, they can be utilized to facilitate the development of a dynamic rule base in supporting subsequent inference. This is because the otherwise relinquished interpolated rules may contain possibly valuable information, covering regions that were uncovered by the original sparse rule base. This paper presents a dynamic fuzzy rule interpolation (D-FRI) approach by exploiting such interpolated rules in order to improve the overall system's coverage and efficacy. The resulting D-FRI system is able to select, combine, and generalize informative, frequently used interpolated rules for merging with the existing rule base while performing interpolative reasoning. Systematic experimental investigations demonstrate that D-FRI outperforms conventional FRI techniques, with increased accuracy and robustness. Furthermore, D-FRI is herein applied for network security analysis, in devising a dynamic intrusion detection system (IDS) through integration with the Snort software, one of the most popular open source IDSs. This integration, denoted as D-FRI-Snort hereafter, delivers an extra amount of intelligence to predict the level of potential threats. Experimental results show that with the inclusion of a dynamic rule base, by generalising newly interpolated rules based on the current network traffic conditions, D-FRI-Snort helps reduce both false positives and false negatives in intrusion detection.

Methodologies for the Exploitation of Existing Energy Corridors. GIS Analysis and DTR Applications

The exploitation of power lines currently in operation has now become a common practice among electric system operators. The construction of new power lines requires taking economic, political and social problems into consideration. This paper considers two methodologies adopted by the Italian Transmission System Operator (TSO), Terna S.p.A.: Dynamic Thermal Rating (DTR) and Laser Imaging Detection and Ranging-Geographic Information System (L-GIS). DTR systems dynamically calculate the real transport capacity of a power line. The L-GIS system allows, after the geo-referencing of the power line, the management of any interference between the line and the nearby obstacles, permitting the optimization of the high voltage line operation. In this paper, after a brief illustration of the two methods, the authors report the results of some applications in the Sicilian electrical power High Voltage (HV) system.

A Fiber Bragg Grating-Based Dynamic Tension Detection System for Overhead Transmission Line Galloping.

Galloping of overhead transmission lines (OHTLs) may induce conductor breakage and tower collapse, and there is no effective method for long distance distribution on-line galloping monitoring. To overcome the drawbacks of the conventional galloping monitoring systems, such as sensitivity to electromagnetic interference, the need for onsite power, and short lifetimes, a novel optical remote passive measuring system is proposed in the paper. Firstly, to solve the hysteresis and eccentric load problem in tension sensing, and to extent the dynamic response range, an ‘S’ type elastic element structure with flanges was proposed. Then, a tension experiment was carried out to demonstrate the dynamic response characteristics. Moreover, the designed tension sensor was stretched continuously for 30 min to observe its long time stability. Last but not the least, the sensor was mounted on a 70 m conductor model, and the conductor was oscillated at different frequencies to investigate the dynamic performance of the sensor. The experimental results demonstrate the sensor is suitable for the OHTL galloping detection. Compared with the conventional sensors for OHTL monitoring, the system has many advantages, such as easy installation, no flashover risk, distribution monitoring, better bandwidth, improved accuracy and higher reliability.

Influence of Human Body Static Elimination Technology on Human Electrostatic Potential

Abstract To research the impact of human body electrostatic potential caused by diverse static elimination technologies and the result of static elimination technologies influenced by different human movements, we carry out a series of experiments to test this phenomenon by EST405 static dynamic computer detection and alarm system. According to the analysis of consequence, wearing grounding bracelet, which is the greatest method to make human electrostatic potential reduced in any movement states, could prevent fire caused by static. However, wearing anti-static shoes and suit making human electrostatic potential declined cannot meet safe requirement. What’s more, anti-static wrist strap hardly has function of eliminating static. And accordingly, various static elimination technologies could have different effects. To be more specific, the more acute human movements are, the poorer effect from static elimination technologies is.

Dynamic resolution detection system design of CCD aerial camera

Dynamic resolution detection system design of CCD aerial camera

An Accurate and Fast Method to Inspect Rail Wear Based on Revised Global Registration

Rail wear inspection is vitally important in the railway industry. Conventional methods mainly use manual or static measurements to detect rail wear, which are inefficient, imprecise, and unreliable. To improve the accuracy and efficiency of rail wear inspection, a dynamic detection system based on a revised fast global registration (RFGR) algorithm was employed. First, the framework for online detection of rail wear with multi-profile was put forward to reduce the influence of vibrations of individual sections. Second, the RFGR method was proposed by using a robust weight function to convert the non-convex registration model to a convex problem, and the Levenberg–Marquardt method was used to solve nonlinear least-squares systems robustly. Finally, the Hausdorff distance was introduced to visualize the distance between the wear profile and the reference profile after alignment. The experimental results demonstrated that the RFGR algorithm was more accurate, robust, and effective than iterative closest point (ICP), sparse ICP, Yi’s sparse ICP, and the fast global registration algorithm. For actual wear detection, the proposed method was more efficient and robust for the online dynamic detection of rail wear when compared with the single-profile-section-based inspection method.

Dynamic video anomaly detection and localization using sparse denoising autoencoders

The emergence of novel techniques for automatic anomaly detection in surveillance videos has significantly reduced the burden of manual processing of large, continuous video streams. However, existing anomaly detection systems suffer from a high false-positive rate and also, are not real-time, which makes them practically redundant. Furthermore, their predefined feature selection techniques limit their application to specific cases. To overcome these shortcomings, a dynamic anomaly detection and localization system is proposed, which uses deep learning to automatically learn relevant features. In this technique, each video is represented as a group of cubic patches for identifying local and global anomalies. A unique sparse denoising autoencoder architecture is used, that significantly reduced the computation time and the number of false positives in frame-level anomaly detection by more than 2.5%. Experimental analysis on two benchmark data sets - UMN dataset and UCSD Pedestrian dataset, show that our algorithm outperforms the state-of-the-art models in terms of false positive rate, while also showing a significant reduction in computation time.

Database Implementation and Testing of Dynamic Credit Card Fraud Detection System

Database Implementation and Testing of Dynamic Credit Card Fraud Detection System

A Dynamic Survival Detection and Analysis System for Mosquito Larvae Viability in Drug Assays.

Bioinformatics studies have emerged in the domain of larval behavior analysis in recent years. A dynamic survival detection and analysis system for automatically monitoring a large amount of mosquito larvae in bioassays with multiwell plates by acquiring and processing videos is proposed in this article. In our system, equipment is designed for acquiring the video of the mosquito larvae in several multiwell plates simultaneously by a camera, and a video analysis module is developed for detecting the survival states of larvae in each well in real time. Also, a novel model and a new image registration algorithm are proposed to accurately obtain the survival state by analyzing the larval motion activities and the weights of larvae in each well. In our experiments, several spinosad bioassays against 2-instar Aedes aegypti with 96-well plates are used to evaluate the proposed system, and the accuracy of the larval survival state in our system is more than 85%. Moreover, this investigation has indicated that the developed system not only can be used in the mosquito larval bioassays but also can be suitable to detect and analyze the behaviors of large amount of other larvae.

Dynamic detection system design of fraud simbox to improve quality service of international incoming call

Dynamic detection system design of fraud simbox to improve quality service of international incoming call

A Dynamic Instability Detection and Prediction System for High Clearance Tractor

Abstract: High clearance tractors are often operated on rough terrain with high rollover risk, which would result in operator injury. This paper introduces a high clearance tractor rollover detection and risk prediction system, developed with multi-sensing technologies and embedded device. Mathematical model was firstly established and coded to calculate the stability index of tested machine. GPS and inertial sensors were utilized to obtain the machine parameters for index calculation. Mobile software was developed with the function of image and sound warning for machine operator. Experiments were conducted to indentify the effect of velocity, slope angle, rotation velocities on tractor stability. Obtained results indicated the validity of developed model and prediction system.

Detection of (1,3)-β-D-glucan for diagnosis of invasive fungal infection in premature infants

Objective To evaluate the diagnostic value of (1, 3)-β-D-glucan assay (G test) in the plasma of premature infants with invasive fungal infection (IFI) and determinate the best diagnostic value of G test. Methods The premature infants who were at risk of IFI from NICU were enrolled in Shengjing Hospital of China Medical University from July 2010 to September 2011. The concentration of (1, 3)-β-D-glucan were detected by GKT-5MSet microbial dynamic detection system, and the fungal and bacterial culture were performed in the same samples of blood. We used to perform statistic analysis for sensitivity, specificity, positive predictive value and negative predictive value at different cutoff values, and draw receiver operating characteristic curve for G test. Results Forty-four infants were eligible for the study, of 17 permature infants with IFI, and of 27 ones with non IFI, in whom bacterial culture was positive in 12 cases and culture was negative in 15 cases. The concentration of (1, 3)-β-D-glucan in IFI group[5~3 117 pg/ml, median (Q75-25) 190.60 (501.44) pg/ml] was higher than that in non IFI group[5.0~434.3 pg/ml, median (Q75-25) 5.86 (5.62) pg/ml], the difference was significant (Z=-3.77, P<0.01).15 pg/ml was the best cutoff value, and the area under curve was 0.839, 95%CI (0.697, 0.980). Conclusion G test is useful in the diagnosis of IFI in premature infants with high sensitivity and specificity. G test can be used for the screening of high-risk patients with high risk of fungal infection ratio. Key words: (1, 3)-β-D-glucan; Invasive fungal infection; Premature infant

Research on target photoelectricity track method and improved image processing arithmetic in dynamic targets detection system

To solve the problem that the complexity background affects the dynamic target detection performance, which causes detection performance instability in dynamic target track system, this paper is to study target photoelectricity track method based on revolving image sensor, analyze dynamic targets track principle and track geometry relation on optical image track instrument, put forward the improved Mean Shift target track arithmetic and the improved difference image processing arithmetic to eliminate the background effect; research the positive and negative difference image processing algorithm and image target region extraction, analyze the flow of image processing arithmetic and derivate their calculation method by gathering target image in track detection system. Through experimentation gathering and processing target sequence image, the results show the target track method and processing arithmetic are accurate and feasible.

Control Algorithm of Control of Start and Stop of Data Collection of Dynamic Detection of Airport Flight Aid Light

To the problem of control of start and stop position of data collection of airport flight aid light light intensity dynamic detection system, control algorithm based on weight sum function was proposed. The algorithm uses weight sum functions constructed to control the start and stop of detection of light intensity dynamically according to the position of vehicle and illumination values detected, which ensures the full collection of data using to draw isocandela diagram and calculate average light intensity. Experiments showed that this algorithm makes airport flight aid light light intensity dynamic detection system can control start and stop position of data collection reliably, which ensures the integrality of isocandela diagram generated.

The Design of the Dynamic Detection System for the Screw’s Lead Precision Testing

For the screw’s lead precision dynamic testing needs, the hardware of the design includes two parts: the motion control card and the data acquisition card. We use the motion control card (GT200-SV) as the circular grating and long grating motor controller, and the data acquisition card is consist of FPGA and DSP. FPGA is the core device to realize the synchronous dynamic grating signal and inductive signal data acquisition and DSP is used to realize the function of decoding and communicating to PC by the USB bus protocol. Finally data are evaluated by the software on the computer. The acquisition speed of Screw’s lead precision dynamic detection system can reach 20 KHZ, and it has been successfully applied to a certain type of screw’s lead precision dynamic detection device in a company.