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In rotating machinery, the malfunctions of rolling bearings are one of the most common faults. To prevent machine breakdown, the pattern recognition of rolling bearing faults has been a pivotal issue for fault identification and classification. This study proposes a new feature extraction method based on ensemble empirical mode decomposition (EEMD) and singular value decomposition (SVD) for fault classification. The proposed E–S method (EEMD combined with SVD using feature parameters) intends to enhance the faults identification capability in different working conditions, including various fault types (FT), fault severities (FS), and fault loads (FL). In this study, the E–S method is adopted to analyze the simulated signals. And the experiment further discusses three cases of different FT, FS, and FL separately under six different classifiers. The experimental results show that different fault classes can be effectively distinguished by the proposed E–S in comparison with other traditional feature extraction methods. Hence, the proposed method is verified to have an effective and excellent performance in bearing fault classification. [ABSTRACT FROM AUTHOR]

There are still some remaining issues for time–frequency distribution application in rolling bearing fault diagnosis, such as noise suppression and resolution improvement. In this paper, we proposed a novel time–frequency correlation matching and reconstruction method to enhance the ability of rolling bearing fault identification. Firstly, we use the optimal simulated bearing fault signal to obtain the matching template through time–frequency distribution. Then, correlation matching operation is conducted between the obtained matching template and the original time–frequency distribution of analyzed signal. Finally, the original time–frequency distribution is reconstructed with the correlation coefficients and matching template using the template reconstruction algorithm. The reconstructed time–frequency distribution has inherited the capability of matching template in noise suppression, and can reveal the fault impulses of interest in a unified scale. The effectiveness of the proposed method has been proved by experimental result. [ABSTRACT FROM AUTHOR]

Hydraulic units often come across condition changes such as start-up, normal stop and load rejection. Load rejection transient process (LRTP) is one of the running conditions which make the unit and water diversion system in worst operation state. It has great influence on the safety and stability of hydraulic units. A new method called SE-ICNA which is based on Internal Characteristic Numerical Algorithm (ICNA) and static efficiency (SE) iteration is proposed. The analysis of rotating speed rising ratio (RS-RR) and pressure rising ratio (P-RR) in LRTP is mainly discussed for hydraulic unit security assessment. The correctness and rationality of SE-ICNA can be verified by means of Transient Process (TP) analysis on medium and small units within the scope of different water levels. Verification examples proved that this method has an excellent performance for hydraulic unit security assessment in low water level conditions. A conclusion is made that the proposed SE-ICNA method can well assess the security of small hydraulic units in low head conditions. [ABSTRACT FROM AUTHOR]

An energy analyzing method called the Impact Energy Model (IEM) is introduced to assess and diagnose the rub–impact fault of a rotor system. The main purpose of the model is to indicate the probability of rub–impact or the severity level of the fault. Utilizing the nonlinear predictive energy, an effective quantitative evaluation index IEM is obtained from the model. Some work has been done elsewhere to partly demonstrate the IEM through experiments. In this paper we mainly discuss the variation of the IEM index with the speed ratio Ω at different levels of damping ratio ξ. The stagnation point is discussed in detail which is important to the assessment for the probability or severity of a rub–impact fault. The influence of dynamic stiffness is discussed which may affect the assessment result of the IEM. Furthermore, a sensitive area of the rotor operating system is presented. The result shows that this sensitive area provides a reference for the operation and design of a rotor system. [ABSTRACT FROM PUBLISHER]