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.
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
High density wireless sensor networks (HDWSNs) are emerging as promising techniques in a variety of fields such as target detection and tracking, military surveillance, intelligent family, preventing forest fire loss, building monitoring and control, medical diagnostic, etc. HDWSNs composed of a large number of sensors with wireless communication, computation, information acquisition, and self-adaptation...
Characteristic energy analysis of the wavelet transform (CEAWT) method is introduced for the detection of metallic particle signal in the presence of strong noise. Starting point, ending point and amplitude of sinusoidal wave of metallic particle signal is identified in characteristic energy analysis. When employing the CEAWT method, the amplitude of metallic particle signal is highlighted and the...
Optimal slip rate identifier based on BP neural network has some bugs such that it is easy to fall into local minimum. In order to improve the aircraft's braking efficiency, this paper presents a new method for optimal slip rate identification based on firefly algorithm optimization. The proposed algorithm is used to optimize the weight value of BP neural network and the result shows that the algorithm...
Rolling bearing's running state has an important influence on the health condition of rotate machinery. This work focuses on the remaining useful life prediction of the rolling bearing. An auxiliary particle filter-based predictor for rolling bearing is presented. The energy spectrum feature of vibration signal is selected as the representation of system degraded states. The wavelet packet decomposition...
Evaluating architecture of aircraft power supply system precisely is the basis of optimizing aircraft architecture design. The multi-index evaluation of its architecture involves reliability, expense, maintainability, weight and power quality, which provides designers with the optimal decision information, including two steps: normalize individual evaluation index and export each single-index result;...
Typical matching parts of servo valve have high precision requirement and strict fit tolerance, which reduces the matching quality and practical performance. The traditional fit quality control method of the matching parts is based on expert experience and tolerance analysis, which is subjective and indirect. In this paper, a novel method was proposed to determine the matching quality before precision...
Acoustic signals reflect the health status of machinery, and therefore can be used for fault diagnosis. It is necessary to understand acoustic characteristics for planetary gearbox fault diagnosis via acoustic signal analysis. Based on the generating mechanism of structural noise, planetary gearbox acoustic signal model is developed, and the acoustic characteristics in Fourier spectrum and envelope...
The efficiency of current aero-engine remaining life prediction methods has room for improvement. This paper focuses on analysis of aero-engine exhaust gas temperature margin (EGTM) time-series data and introduces a pattern mining method of aero-engine performance degradation based on Empirical Mode Decomposition (EMD) and k-nearest neighbors optimized clustering by fast search and find of density...
Bearings are one of the most omnipresent and vulnerable components in rotary machinery such as motors, generators, gearboxes, or wind turbines. The consequences of a bearing fault range from production losses to critical safety issues. To mitigate these consequences condition based maintenance is gaining momentum. This is based on a variety of fault diagnosis techniques where fuzzy clustering plays...
The accuracy of bearing health prognostics highly depends on the constructed health indicator. This paper presents a health indicator construction method based on distance metric learning (DML). First, multiple features are extracted from the raw monitoring vibration signals, including a designed feature named as average energy of fault frequency band (AEFFB). Then, the optimal features are selected...
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.