Search results for "Detection"
showing 10 items of 2543 documents
Fault detection for nonlinear networked systems based on quantization and dropout compensation: An interval type-2 fuzzy-model method
2016
Abstract This paper investigates the problem of filter-based fault detection for a class of nonlinear networked systems subject to parameter uncertainties in the framework of the interval type-2 (IT2) T–S fuzzy model-based approach. The Bernoulli random distribution process and logarithm quantizer are used to describe the measurement loss and signals quantization, respectively. In the framework of the IT2 T–S fuzzy model, the parameter uncertainty is handled by the membership functions with lower and upper bounds. A novel IT2 fault detection filter is designed to guarantee the residual system to be stochastically stable and satisfy the predefined H ∞ performance. It should be mentioned that…
Multi-band identification for enhancing bearing fault detection in variable speed conditions
2020
Abstract Rolling element bearings are crucial components in rotating machinery, and avoiding unexpected breakdowns using fault detection methods is an increased demand in industry today. Variable speed conditions render a challenge for vibration-based fault diagnosis due to the non-stationary impact frequency. Computed order tracking transforms the vibration signal from time domain to the shaft-angle domain, allowing order analysis with the envelope spectrum. To enhance fault detection, the bearing resonance frequency region is isolated in the raw signal prior to order tracking. Identification of this region is not trivial but may be estimated using kurtosis-based methods reported in the li…
Food tray sealing fault detection using hyperspectral imaging and PCANet
2020
Abstract Food trays are very common in shops and supermarkets. Fresh food packaged in trays must be correctly sealed to protect the internal atmosphere and avoid contamination or deterioration. Due to the speed of production, it is not possible to have human quality inspection. Thus, automatic fault detection is a must to reach high production volume. This work describes a deep neural network based on Principal Component Analysis Network (PCANet) for food tray sealing fault detection. The input data come from hyperspectral cameras, showing more characteristics than regular industrial cameras or the human eye as they capture the spectral properties for each pixel. The proposed classification…
Scale invariant line matching on the sphere
2013
International audience; This paper proposes a novel approach of line matching across images captured by different types of cameras, from perspective to omnidirectional ones. Based on the spherical mapping, this method utilizes spherical SIFT point features to boost line matching and searches line correspondences using an affine invariant measure of similarity. It permits to unify the commonest cameras and to process heterogeneous images with the least distortion of visual information.
Collision detection for 3D rigid body motion planning with narrow passages
2017
In sampling-based 3D rigid body motion planning one of the major subroutines is collision detection. Especially for problems with narrow passages many samples have to be checked by a collision detection algorithm. In this application, the runtime of the motion planning algorithm is dominated by collision detection and the samples have the very specific characteristic that many of them are in collision and have small penetration volumes. In our work, we introduce a data structure and an algorithm that makes use of this characteristic by combining well-known data structures like a distance field and an octree with the swap algorithm by Llanas et al. For 3D rigid body motion planning with narr…
Gradient-based time to contact on paracatadioptric camera
2013
International audience; The problem of time to contact or time to collision (TTC) estimation is largely discussed in perspective images. However, a few works have dealt with images of catadioptric sensors despite of their utility in robotics applications. The objective of this paper is to develop a novel model for estimating TTC with catadioptric images relative to a planar surface, and to demonstrate that TTC can be estimated only with derivative brightness and image coordinates. This model, called "gradient based time to contact", does not need high processing such as explicit estimation of optical flow and feature detection/or tracking. The proposed method allows to estimate TTC and give…
Tolerating malicious monitors in detecting misbehaving robots
2008
This paper considers a multi–agent system and focuses on the detection of motion misbehavior. Previous work by the authors proposed a solution, where agents act as local monitors of their neighbors and use locally sensed information as well as data received from other monitors. In this work, we consider possible failure of monitors that may send incorrect information to their neighbors due to spontaneous or even malicious malfunctioning. In this context, we propose a distributed software architecture that is able to tolerate such failures. Effectiveness of the proposed solution is shown through preliminary simulation results.
Automatic Acoustic Target Detecting and Tracking on the Azimuth Recording Diagram with Image Processing Methods
2019
International audience; Passive acoustic target detection has been a hot research topic for a few decades. Azimuth recording diagram is one of the most promising techniques to estimate the arrival direction of the interested signal by visualizing the sound wave information. However, this method is challenged by the random ambient noise, resulting in low reliability and short effective distance. This paper presents a real-time postprocessing framework for passive acoustic target detection modalities by using a sonar array, in which image processing methods are used to automate the target detecting and tracking on the azimuth recording diagram. The simulation results demonstrate that the prop…
Secure and efficient verification for data aggregation in wireless sensor networks
2017
Summary The Internet of Things (IoT) concept is, and will be, one of the most interesting topics in the field of Information and Communications Technology. Covering a wide range of applications, wireless sensor networks (WSNs) can play an important role in IoT by seamless integration among thousands of sensors. The benefits of using WSN in IoT include the integrity, scalability, robustness, and easiness in deployment. In WSNs, data aggregation is a famous technique, which, on one hand, plays an essential role in energy preservation and, on the other hand, makes the network prone to different kinds of attacks. The detection of false data injection and impersonation attacks is one of the majo…
On Detection of Network-Based Co-residence Verification Attacks in SDN-Driven Clouds
2017
Modern cloud environments allow users to consume computational and storage resources in the form of virtual machines. Even though machines running on the same cloud server are logically isolated from each other, a malicious customer can create various side channels to obtain sensitive information from co-located machines. In this study, we concentrate on timely detection of intentional co-residence attempts in cloud environments that utilize software-defined networking. SDN enables global visibility of the network state which allows the cloud provider to monitor and extract necessary information from each flow in every virtual network in online mode. We analyze the extracted statistics on d…