The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper proposes a novel approach for machine fault diagnosis using industrial wireless sensor networks (IWSNs) and on-sensor calculation. In this paper, the induction motor and vibration signal are taken as an example of the monitored industrial equipment and signal due to their wide use. The discrete wavelet transform and wavelet energy-moment are used for on-sensor machine fault feature extraction,...
A new MATLAB toolbox DB-KIT was recently developed for the design and implementation of fault diagnosis systems. For the purpose of key performance indicator (KPI) oriented fault detection, over the past few years, a series of test statistics and the corresponding thresholds were derived based on the modified data structures originating from the existing multivariate statistical analysis tools. These...
The mass monitoring data collected by the on-line monitoring of the substation is stored in the Hadoop Distributed File System (HDFS), and the index table structure of the online monitoring data is optimized and stored in the distributed structured database (HBase) Quick access to monitoring data. Based on Hadoop 's online monitoring data processing experiment platform, a fast fault identification...
This paper proposes the design of various end effectors for first aid robots. There is a growing demand for special robots that perform rescue operations on behalf of people for rescue in dangerous areas such as disasters or wars. In addition, when injuries occur, first aid treatment is also necessary. In this paper, we design user and system requirements for robots performing first aid and propose...
The health degree of large distributed information system reflected from the business perspective is the core index to measure the stability of information system. It has significant meaning for the fault diagnosis of any information system. To solve the above problems, a knowledge representation method based on weighted fault diagnosis is proposed in this paper. Based on the knowledge representation...
Fault detection and isolation (FDI), which is a critical part of modern industrial systems, plays a key role in the maintainability, safety, and reliability of processes. Existing FDI approaches are dependent on varying degrees of knowledge of the process, limiting their implementation in practical industrial processes. Based on the least absolute shrinkage and selection operator (lasso), this paper...
Mechanical characteristics, including the displacement curves of the movable contacts and coil current curves are the most common routine monitoring objects of high voltage circuit breakers to evaluate the machines' condition. Generally, a high-performance mechanical characteristic tester has the ability to offer dozens of parameters consisting of stroke, speed, magnitude of current and so on. Besides,...
This paper designs a fault diagnosis model for circuit breaker based on power dispatching system. The model has three levels including data level, criterion level and judging level. The data level consists of data obtaining, data handling and fault database. The criterion level consists of operating time characteristics model, fault tree and repository. The judging level is logical judging method...
The realization of early detection of incipient faults makes great sense for the guarantee of system performance and security operation. Therefore, It is necessary to estimate the fault amplitude especially when the system security assessment is the main goal. Regarding the incipient fault with low Fault-Noise-ratio (FNR), in this paper, a practical online fault estimation method is presented for...
In process monitoring of batch process, Fisher discriminant analysis is a very popular method and has be widely applied. In this paper, a new kernel local Fisher discriminant analysis (KLFDA) algorithm is proposed for fault diagnosis. The main contributions of the presented approach are as follows: 1) the proposed algorithm can simultaneously extract the global European distribution of data and local...
In order to meet the needs of safety, durability and reliability for the battery management system, the data monitoring and diagnosis for the battery management system platform is researched and developed. The platform based on the CAN bus technology, in the VC++6.0 development environment, implement the battery management system running state monitoring, fault diagnosis, parameter configuration,...
In view of the shortcomings of traditional fault diagnosis system in accuracy, robustness and too complicated recognition algorithm, the distributed intelligent fault diagnosis system is presentation based on ZigBee technology and particle filter. Multi variable data's acquisition and centralized treatment is realized through the wireless sensor network, and the accurate estimation of the state of...
Condition monitoring (CM) of gearbox is a crucial activity due to its importance in power transmission for many industrial applications. Monitoring temperature is an effective mean to collect useful information about the healthy conditions of the gearbox. This study investigates the use of a novel wireless temperature node to monitor and diagnose different faults on a gearbox transmission system under...
Process monitoring of incipient faults, as opposed to abrupt faults, in an industrial process is increasingly becoming more important. These are slowly developing faults that may eventually lead to severe abnormal conditions, and ultimately, failure of a critical component. Data-driven multivariate statistical process monitoring (MSPM) methods are extensively studied and widely used for abrupt fault...
Process monitoring plays a vital role in order to sustain optimal operation and maintenance of the plant in process industry. As an essential stage in process monitoring, datadriven fault detection and diagnosis techniques have evolved quickly owing to the prosperity of multivariate feature extraction methods. In addition to the application of basic feature extraction methods, hybrid algorithms combining...
Vehicle Health Management Systems (VHMS) are used throughout commercial, military, and aerospace platforms to assess the current operational status of individual assets and entire fleets. One of the most common functions within most VHMS implementations is the collection and reporting of fault conditions and trouble codes. The management of this fault data, particularly its representation to a user,...
With the rapid development of Internet technologies such as cloud computing and big data, the scales of distributed information systems in big companies have grown to enormous sizes. Automatic detection and diagnosis of system faults in the large-scale information systems is complicated and important in both practice and research. In this paper, we propose a Graph-based Fault Diagnosis approach in...
The three-phase induction motor is one of the most employed equipment in industrial premisses. Despite of its reliability and robustness, these machines can present faults due to the operation time, harsh operating conditions, voltage unbalance, among other factors. In this work, a methodology for intelligent diagnose of multiple faults in induction motors by using a discretization of currents and...
Wind power has become the most important component of renewable energy with advances in technology in recent years. Reducing operations and maintenance cost effectively and detecting the fault timely for wind turbines are critical to expand wind power use. Due to difficult access and harsh environment, offshore wind turbines have more urgent need for reducing operations and maintenance costs. This...
This paper proposes a methodology to be used in the segmentation of infrared thermography images for the detection of bearing faults in induction motors. The proposed methodology can be a helpful tool for preventive and predictive maintenance of the induction motor. This methodology is based on manual threshold image processing to obtain a segmentation of an infrared thermal image, which is used for...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.