Resilient computation has been an emerging topic in the field of high-performance computing (HPC) for several years. In particular, studies show that tolerating faults on leadershipclass supercomputers (such as exascale supercomputers) is expected to be one of the main challenges. In this paper, we utilize dynamic binary instrumentation and virtual machine based fault injection to emulate soft ...

the running status of it can be more comprehensive judged through acquisition and analysis of vibration signal for water pump rotary machinery. Therefore, the collection of vibration signal is the key to monitor equipment running status and diagnose faults. This paper introduces water pump fault diagnosis system based on DSP and wavelet transform, and the system can realize water pump vibration...

This paper presents a novel analog circuit fault diagnosis approach using generalized multiple kernel learningsupport vector machine (GMKL-SVM) method and particle swarm optimization (PSO) algorithm. First, the wavelet coefficients’ energies of impulse responses are generated as features. Then, a diagnosis model is constructed by using GMKL-SVM method based on features. Meanwhile, the PSO algor...

Wireless sensor networks are resource-constrained self-organizing systems that are often deployed in inaccessible and inhospitable environments in order to collect data about some outside world phenomenon. For most sensor network applications, point-to-point reliability is not the main objective; instead, reliable event-of-interest delivery to the server needs to be guaranteed (possibly with a ...

Safety in dynamic processes is a concern of rising importance, especially if people would be endangered by serious system failure. Moreover, as the control devices which are now exploited to improve the overall performance of processes include both sophisticated control strategies and complex hardware (input-output sensors, actuators, components and processing units), there is an increased prob...

Received Jun 9, 2017 Revised Nov 20, 2017 Accepted Dec 11, 2017 Gears are important component of the rotational power transmission system and are largely used in variable load and speed applications. The faults on the gear generate excessive vibration which leads to breakdown of the machine. Sensor based methods could diagnose gear faults but proved to be expensive and have limited applications...

In this paper, we propose a method to diagnose the faults in the telecommunication networks by using the Realistic Abductive Reasoning Model 1]. This model uses abductive inference mechanism based on the parsimonious covering theory with some new features added to the general model of diagnostic problem solving. The fault diagnosis knowledge is assumed to be represented in the form of causal ch...

The paper introduces the concept of fault diagnosis using an observer bank of autoregressive time series models. The concept was applied experimentally to diagnose a number of induced faults in a rolling element bearing using the measured time series vibration signal. Three distinct techniques of autoregressive modeling were compared for their performance and reliability under conditions of var...

This paper presents work extending previous research in sensor fault tolerance, classification, and recovery from a single robot to a heterogeneous team of distributed robots. This approach allows teams of robots to share knowledge about the working environment, sensor and task state, to diagnose failures and also communicate to redistribute tasks in the event that a robot becomes inoperable. O...

Rotor crack detection method by using multi-vibration signals gathered at the basements is presented in this paper. The finite element software ANSYS is applied for analyzing the vibration response characteristics of the basement to determine sensor configuration. Feature fusion for time-domain statistics of multiple sensors is performed by using the support vector machine to diagnose the depth...