Papers by Keyword: Fault Diagnosis

Abstract: For the running situation of supercritical and ultra-supercritical steam turbine unit, a fault diagnosis method of steam turbine based on multiple parameters fusion is proposed. The association of the fault mode with the vibration parameters, the thermodynamic parameters and the operational parameters is built, according to fault development mechanism, equipment operation data and professional experience. The overall state evaluation of mechanical equipment is given, the reliability of fault diagnosis is improved, and the need of the steam turbine fault diagnosis is met, by means of comprehensive evaluation of multiple parameters. Example applications verify this method.

Abstract: For the low efficiency and poor accuracy of turbo-generator Unit s fault diagnosis, this paper divided the common 18 kinds of vibration fault into four categories, and took advantage of support vector machine to distinguish the fault cluster for early fault diagnosis according to the characteristics of vibration signal spectrum. For different fault cluster, different fault pattern recognition model was established. With the use of certain symptom group and weighted fuzzy logic, this article engaged in knowledge reasoning to obtain the specific fault recognition mode. Besides, the searching methods of fault cause, fault influence and troubleshooting measures in the knowledge base were proposed, which made the diagnosis process more meticulous and comprehensive. Case analysis shows that it is feasible to use this method to develop a system for intelligent fault diagnosis of turbo-generator unit, which is valuable for further study in more depth.

Abstract: Gearboxes are widely used in various kinds of applications. The normal operation of the gears contributes important roles on the machine performance. Due to harsh environment the rolling bearings are prone to failures. Hence, it is essential to detect the gear faults. However, the vibration signals of the gearbox are often contaminated, leading to deterioration of the fault diagnosis performance. To address this issue, a new approach is proposed based on the kernel independent component analysis (KICA) and BP neural network (BPNN). The KICA was used to extract sensitive signals to eliminate noise signals. Then a BPNN was adopted to detect the gear fault. To improve the fault identification, the Genetic Algorithm (GA) was adopted to optimize the BP parameters. Experiment tests using the gearbox fault simulator have been implemented. The test results show that the noise signals have been eliminated by the KICA and the GA-BPNN can detect the gear fault accurately. Moreover, through comparison with other existing methods, the proposed KICA-GA-BPNN produced the best detection rate of 93.7%.

Abstract: Hilbert-Huang transform is a new method of signal processing, which is very suitable for dealing with nonlinear and non-stationary signal. In this article, a gear fault diagnosis method based on Hilbert marginal spectrum is proposed in view of the non-stationary characteristics of gear vibration signal. First the original vibration signal is decomposed into several intrinsic mode functions (IMF) of different characteristic time scale smoothly by means of empirical mode decomposition (EMD) method. Then the Hilbert-Huang transform is carried out for IMF and the Hilbert marginal spectrum under different operating conditions are obtained. Gear faults can be judged through the analysis of the marginal spectrum. The experimental results show that this method can effectively diagnose the gear faults.

Abstract: In order to diagnosing new fault for hybrid system which is lack of experiential knowledge and historic knowledge, semi-quantitative fault diagnosis method based on graph theory and fuzzy theory combined with functional fault analysis (FFA) theories and Failure Mode and Effects Analysis (FMEA) is studied. And a multi-hierarchical functional directed graph modeling method is proposed for aircraft system fault diagnosis. Nacelle Anti-Ice subsystem of an aero engine is taken as a specific application to present the detailed MHFDG modeling method. The proposed modeling method is suitable for fault diagnosis of newly developed hybrid system.

Abstract: Many researchers dealt with single fault but in real life situations, combined action of two or more single faults are usually present. Multi-faults (two and three combinations) were studied by few researchers. Researchers have mostly studied the vibration behavior of a rotor with misalignment, unbalance and rub separately. This paper presents one such case, where multiple faults are considered together in a rotor system, i.e. misalignment, unbalance and rub. The objective of this paper is to experimentally investigate the vibration response of combined of three faults misalignment, unbalance and rub using Fast Fourier Transform (FFT). FFT spectrum of combination of three faults misalignment, unbalance and rub show 1 X and 2 X are predominant and many sub harmonics are generated.1X peak represent unbalance, 2X peak represents misalignment and sub harmonics shows rub fault.

Abstract: In order to collect the fault signal of slewing bearing, design and built up the slewing bearing test rig and the signal test system. Because slewing bearing fault signal is weak, the signal containing fault characteristics was resolved and reconstructed with the wavelet theory. With the application of the Hilbert transform in demodulation and detailed spectrum analysis, the fault characteristic frequency was extracted, and the slewing bearing fault was judged. All above work shows that Wavelet analysis combined with the Hilbert analysis is effective to the diagnosis of rotary bearing local fault.

Abstract: This paper was concerned with the fault diagnosis method based on the second-order sliding mode observer (SOSMO) for reconfigurable modular robot systems with joint friction. The residual signal between given threshold and output of the SOSMO are utilized to directly and effectively detect the fault of reconfigurable modular robot. The stability of the SOSMO is proved by using Lyapunov stability theory. In order to demonstrate the effectiveness of the proposed method, two different 2-DOF reconfigurable modular robots are employed for simulation.

Abstract: More and more problems emerged in integrated automation system such as data processing, database information integration, and decision supporting and fault diagnosis. Information fusion technology is currently a front research topic in the field of information processing. The application of information fusion in above four aspects suggests its an effective method to solve the problems in integrated automation system. Information fusion technology will get more widely applications in integrated automation system.

Abstract: Gear transmission system is as an important part of the armored vehicle, and its work reliability is directly related to the working performance of the armored vehicle. Based on introducing the need on condition monitoring and fault diagnosis of gear transmission system, the response methods on condition monitoring and fault diagnosis are expressed in the gear transmission system. Finally, an armored vehicle transmission system is as the research object, the test point selection, data acquisition and processing is studied. The paper shows how to use differ method such as the amplitude domain, frequency domain, demodulation analysis and wavelet analysis to extract fault characters and fault identification in the armored vehicle gear transmission system.