In this paper, the aero-engine test with inter-shaft bearing fault is carried out, and a dataset is proposed for the first time based on the vibration signal of rotors and casings. First, a test rig based on a real aero-engine is established, driven by motors and equipped with a lubricating system. Then, the aero-engine is disassembled and assembled following the specification process, and the inter-shaft bearing with artificial fault is replaced. Next, the aero-engine test is conducted at 28 groups of high and low pressure speeds. Six measuring points are arranged, including two displacement sensors to test the displacement vibration signals of the low pressure rotor and four acceleration sensors to test the acceleration vibration signals of the casing. The test results are integrated into an inter-shaft bearing fault dataset. Finally, based on the dataset in this paper, frequency spectrum, envelope spectrum, CNN, LSTM and TST are used for fault diagnosis, and the results are compared with those of CWRU and XJTU datasets. The results show that the characteristic fault frequency cannot be found directly in the spectrum and envelope spectrum corresponding to this paper's dataset but in CWRU and XJTU datasets. Using CNN, LSTM and TST for fault diagnosis of the dataset in this paper, the accuracy is 83.13%, 85.41% and 71.07%, respectively, much lower than the diagnosis results of CWRU and XJTU datasets. It can be seen that the dataset in this paper is closer to the actual fault diagnosis situation and is a more challenging dataset. This dataset provides a new benchmark for the validation of fault diagnosis methods. Mendeley data: https://github.com/HouLeiHIT/HIT-dataset. 

Inter-shaft Bearing Fault Diagnosis Based on Aero-engine System: A Benchmarking Dataset Study

Variational time–frequency adaptive decomposition of machine multi-impact vibration signals

The invention discloses an efficient and energy-saving welding electrode which comprises a clamping end and an arc end and is characterized in that filler wires, an insulating layer, a conductive metal tube and a coating are mutually wrapped from inside to outside to form a cylinder with small ends and a big middle part. According to the invention, only the conductive metal tube of the efficient and energy-saving welding electrode generates electric arcs, and part of electric arc heat is used for melting the filler wires, the insulating layer and the coating. Therefore, the amount of deposited metal in unit electricity and unit time is remarkably increased, and the purposes of increasing the welding fusion coefficient, saving electric energy, reducing welding heat input and improving performance of welded splices are achieved.

Efficient and energy-saving welding electrode

Impact time domain decomposition: An adaptive decomposition method for multi-source impact signals based on envelope energy gradient characteristics

This article develops a semianalytical model for characterizing the terminal responses of coated floating-ground multiconductor cables (FMCs) with arbitrarily routed wiring structures illuminated by a nonuniform electromagnetic field. In contrast to previous transmission line (TL) models, where only differential-mode (DM) coupling was considered, the proposed method decomposes the field-to-wire coupling effects in coated FMCs into common-mode (CM) coupling and DM coupling. First, for CM coupling, the coated FMCs are equivalent to a CM single conductor, and the CM current distribution along this conductor is obtained by full-wave simulations. Second, the equivalent coupled sources are decomposed into CM sources converted from the CM currents and DM sources induced by the electric and magnetic fields. The CM and DM sources are obtained separately by discretizing coated FMCs and sampling the incident electromagnetic field. Third, the combination model accounting for the comprehensive DM coupling is derived utilizing TL theory based on the equivalent coupled sources. The proposed method is validated through two application examples with good accuracy and higher computational efficiency compared with full-wave simulations.

Characterization of the Field-to-Wire Coupling in Coated Floating-Ground Multiconductor Cables

Modeling of catenary electromagnetic emission with electrified train passing through neutral section

This paper presents an approach for the time domain statistical simulation of field-to-wire coupling model with uncertain wire position in traverse direction. The parameters of governing equations of field-to-wire coupling model about the wire position are expanded to the augmented governing equations by using the generalized polynomial chaos technique with normalized orthogonal basis functions. And the coefficients of the polynomial chaos expansions are solved by combining with the stochastic Galerkin method. However, the solution of augmented governing equations is a complex problem. Therefore, a new finite-difference time-domain (FDTD) algorithm based on the implicit Wendroff difference format is proposed to solve the governing equations, and the general iterative equations are given in this paper. The proposed methods are verified by a field-to-wire coupling model. The effectiveness and advantages of the new FDTD algorithm and the uncertainty analysis method based on generalized polynomial chaos technique are verified, which are achieved by comparing with the conventional leapfrog fashion FDTD algorithm and the Monte Carlo technique, respectively.

Analysis on Uncertainty of Field-to-Wire Coupling Model in Time Domain

The utility model relates to simulation electric welding rod for an electric-arc welding simulation training machine, comprising a simulation electric welding rod body, a high-voltage lead and a joint connected with a high voltage output terminal of the electric-arc welding simulation training machine, wherein the simulation electric welding rod body comprises a welding core, a welding rod head and a resin shell; an insulating layer is arranged outside the welding core; the welding rod head is connected and fixed on the welding core by a soldering tin; the resin shell is covered outside the insulating layer; one end of the high-voltage lead is electrically connected with the welding core, and the other end is electrically connected with the joint. Compared with the prior art, the simulation electric welding rod can be used for simulating the appearance of the real welding rod, is environment-friendly and labor-saving, generate no gas and smoke when in work, can be repeatedly used, and reduces the consumption of material.

Simulation electric welding rod for electric-arc welding simulation training machine

The transient current pulse (TCP) caused by the traction network short-circuit fault (TNSF) will produce a high-strength transient electromagnetic field (TEMF). The electromagnetic field will interfere with nearby weak current equipment through the shielded cable. In this paper, a transient circuit model (TCM) for the short-circuit traction network is proposed to calculate the transient current. The short circuit is equivalent to a ring, and the TEMF transient electromagnetic field is calculated based on the magnetic dipole. The current response of the TEMF transient electromagnetic field on the shielded cable is deduced based on the transmission line theory and verified by experiments. The electromagnetic interference (EMI) of a TEMF transient electromagnetic field to the shielded cable terminal load were was studied under various incidence angles, azimuth angles, and polarization angles. The results demonstrate that the greater the incident angle and azimuth angle, the greater the EMI on the terminal load. The horizontal distance between the shielded cable head and the short-circuit point should be greater than 6 m, and the incident angle should be greater than 45∘. This method can provide a theoretical basis for the electromagnetic compatibility research of traction power supply systems and their nearby weak current equipment.

Research on EMI of Traction Network Transient Current Pulse on Shielded Cable Terminal Load

In order to overcome the difficulty of identifying multiple electromagnetic radiation sources (EMRS) of the same frequency and wideband EMRS, a deep neural network model based on blind source separation (BSS) and deep feature learning network (DFLN) is proposed. To separate the mixed signal of the unknown source number, a new BSS method based on convolutional neural network (CNN) and shallow neural network (SNN) is proposed. The spatial spectrum (SS), the number of EMRS, and the mixed matrix are estimated by CNN. The separation matrix is estimated by SNN. To effectively identify unknown wideband EMRS, a DFLN based on multiple feature representation learning (MFRL) and similarity metrics (SM) is proposed. The multiple feature representation of EMRS is obtained by two of the same CNNs, and the deep feature representation (DFR) is learned by SM. The classification layer is improved to identify unknown EMRS. To ensure generalization, both the simulated dataset and the measured dataset are used to train the proposed network. The experiment results show that the average identification accuracy of the proposed method for unknown EMRS reached 98% and about 97% for wideband EMRS.

Blind Source Separation and Deep Feature Learning Network-Based Identification of Multiple Electromagnetic Radiation Sources

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