Complex Coupling System Research Articles

Multi-Fault Feature Extraction and Diagnosis of Gear Transmission System Using Time-Frequency Analysis and Wavelet Threshold De-Noising Based on EMD

gear transmission system is a complex non-stationary and nonlinear time-varying coupling system. When faults occur on gear system, it is difficult to extract the fault feature. This paper researches the threshold principle in the process of using the wavelet transform to de-noise the system, and combines EMD (empirical mode decomposition) with wavelet threshold de-noising to solve the problem. The wavelet threshold de-noising is acts on the high-frequency IMF (Intrinsic Mode Function) component of the signal, and does overcome the defect by simply highlighting the fault feature. On this basis, the pre-processed signal is analyzed by the method of time-frequency analysis to extract the feature of the signal. The result shows that the SNR (signal-noise ratio) of the signal was largely improved, and the fault feature of the signal can therefore be effectively extracted. Combined with time-frequency analyses in the different running conditions (300 rpm, 900 rpm), various faults such as tooth root crack, tooth wear and multi-fault can be identified effectively. Based on this theory and combining the merits of MATLAB and VC++, a multi-functional gear fault diagnosis software system is successfully exploited.

Multi-Fault Feature Extraction and Diagnosis of Gear Transmission System Using Time-Frequency Analysis and Wavelet Threshold De-Noising Based on EMD

gear transmission system is a complex non-stationary and nonlinear time-varying coupling system. When faults occur on gear system, it is difficult to extract the fault feature. This paper researches the threshold principle in the process of using the wavelet transform to de-noise the system, and combines EMD (empirical mode decomposition) with wavelet threshold de-noising to solve the problem. The wavelet threshold de-noising is acts on the high-frequency IMF (Intrinsic Mode Function) component of the signal, and does overcome the defect by simply highlighting the fault feature. On this basis, the pre-processed signal is analyzed by the method of time-frequency analysis to extract the feature of the signal. The result shows that the SNR (signal-noise ratio) of the signal was largely improved, and the fault feature of the signal can therefore be effectively extracted. Combined with time-frequency analyses in the different running conditions (300 rpm, 900 rpm), various faults such as tooth root crack, tooth wear and multi-fault can be identified effectively. Based on this theory and combining the merits of MATLAB and VC

Control of Multivariable Coupling System Based on Improved PID Neural Networks

The paper analyzes the characteristics and the situation of the control of multivariable coupling system, combining improved PID neural networks with PSO algorithm, and finally designs a suitable controller model. To achieve a controller model, an initial structure of PID neural networks is established in the first place. Then weights in the network is initialized by PSO algorithm and optimized by improved gradient descent algorithm. A simulation, MIMO coupling system, prove this controller has such characteristics with short time and high precision. The research of the paper provides a new idea and approach for control of complex coupling system.

City Optimal Allocation of Water Resources Research Based on Sustainable Development

The water resources is a complex coupling system,combined with the human social development and living environment. Water resources optimal allocation plays an important role in supporting the whole sustainable development of national economy in Weinan city as the solution about the shortage of urban water resources .In this paper, we take the urban water supply and the water resources system in Weinan city as the research object, through the analysis of the actual data, analyzing the elements and relationships between systems of urban water supply in Weinan city and the characteristics of the water resources project, adopting optimization theory of dynamic programming principle to build the Weinan city water resources optimization allocation model, and puts forward the method of benefit function to obtain the strategy plan for optimal allocation of water resources in the city.

City Optimal Allocation of Water Resources Research Based on Sustainable Development

The water resources is a complex coupling system,combined with the human social development and living environment. Water resources optimal allocation plays an important role in supporting the whole sustainable development of national economy in Weinan city as the solution about the shortage of urban water resources .In this paper, we take the urban water supply and the water resources system in Weinan city as the research object, through the analysis of the actual data, analyzing the elements and relationships between systems of urban water supply in Weinan city and the characteristics of the water resources project, adopting optimization theory of dynamic programming principle to build the Weinan city water resources optimization allocation model, and puts forward the method of benefit function to obtain the strategy plan for optimal allocation of water resources in the city.

Fuzzy PID Control To Feed Servo System of CNC Machine Tool

The feed servo system of CNC machine tool is a complex electromechanical coupling system. Due to the characteristics of time-varying parameters, load disturbances and motor nonlinear, it is difficult to model for the control system accurately. An approach is presented that a fuzzy adaptive PID controller is designed by the PID controller combined with the fuzzy controller based on the mathematical model of the CNC machine tool feed servo system. The controller is applied to control the feed servo system and gained better control performance. The simulation results show that this method not only has no static distortion, but also has a fast response with little overshoot. This fuzzy adaptive PID controller has high stability and accuracy.

Break through the limits of vibroseis data quality

ABSTRACTThe vibroseis method has become the principal data acquisition method in land seismic exploration. It seems that this method has been extended to its limits as the search for energy resources continues. Many practical issues arising from field operations have remained theoretically unexplained, for example, variations in wavelet arrival time, inaccurate wavelet estimation and harmonics in the wavelet itself. The focus of this paper is the proposal of a new model, which is referred to as the vibrator‐coupled ground model, to simulate the filtering effects of a complex coupling system consisting of the coupling between the baseplate and the ground as well as the coupling between the captured ground mass near the vibrator baseplate and the surrounding earth. With this vibrator‐coupled ground model many of the practical issues mentioned above were reasonably addressed. Furthermore, it was demonstrated from experimental tests that both the pilot sweep and the weighted‐sum groundforce, when filtered by the vibrator‐coupled ground model, are proportional to the far‐field particle velocity whereas the unfiltered signals are not. The harmonics on the filtered weighted‐sum groundforce successfully maintain a proportional relationship with the harmonics seen in the far‐field signal.

An Intelligent Bi-Cooperative Decoupling Control Approach Based on Modulation Mechanism of Internal Environment in Body

In order to develop more effective decoupling control methods for complex coupling system, we present an intelligent bi-cooperative decoupling controller (IBCDC) inspired from the modulation mechanism of internal environment in body. The IBCDC consists of a coordination control unit (CCU), a model identification unit (MIU), a decoupling control evaluation unit (DEU), and two control units. The DEU includes a reinforcing decoupling control block (RDCB) and a suppression decoupling control block (SDCB). Every control unit or block including an original control block (OCB) and a decoupling compensation block (DCB) is designed according to different physiological organs or systems. Under the coordination of the CCU, all the control units or blocks communicate with each other to exchange the control or decoupling control information. Through adjusting the actuators harmoniously, the coupling influences among different control loops can be reduced or almost eliminated. The simulation results demonstrate that the IBCDC can almost eliminate the coupling influence with better control performance. Compared with other decoupling control methods, the IBCDC can be implemented more easily and practically, and be easily generalized to the multiple-input-multiple-output systems.

Adaptive fuzzy sliding mode control in PH neutralization process

In chemical industry process, PH neutralization process consists of a complex and multi-variable nonlinear coupling system. This paper combines the fuzzy control and sliding mode control, and fully using the system state information to simplify the fuzzy control rules. This paper gives the adaptive fuzzy sliding mode control algorithm as well as the stability-state analysis. The quantification scale factor changing adaptively adjusts the universe of fuzzy control system, makes system control signals soften and reduces the chattering of sliding mode control. Designed control system has strong robustness and good adaptive ability. Simulation results show that even a major change in operating point or suffer greater interference, the systems still have good anti-disturbance and strong robustness.

Experimental MHD – flow analyses in a mock-up of a test blanket module for ITER

Magnetohydrodynamic experiments in a scaled mock-up of a helium-cooled lead lithium test blanket module designed for being tested in ITER have been performed in the MEKKA liquid metal laboratory at the Forschungszentrum Karlsruhe. The mock-up consists of four breeder units connected by feeding and draining manifolds. Each breeder unit contains five internal walls simulating the helium-cooled plates which remove in the original design the heat from the breeding zone. Due to the electric conductance of all walls the whole structure represents a complex coupled system, since currents induced by the motion of the fluid under the influence of the strong plasma-confining magnetic field can cross the walls and couple electrically neighboring fluid domains. The present work is focussed on the experimental study of flow partitioning in subchannels of breeder units, depending on flow rate and strength of the applied magnetic field. For strong magnetic fields one can observe that the flow distribution is similar as assumed in the design. In accordance with theoretical predictions the outer subchannels of breeder units show higher velocities than those in central ducts. This is a consequence of the established strong coupling of flow domains inside breeder units and by the fact of a weak coupling of neighboring breeder units. With increasing flow rate or decreasing magnetic field uneven flow distributions and even flow reversal are observed. Such unfavorable flow regimes, however, occur only at parameters that are out of scope of normal ITER operation.

Generative Programming in Scientific Computing

AbstractThe complexity of simulation software increases because the simulated phenomena get more complex and massively parallel machines have to be used. Other reasons are the consideration of new technologies like the computational Grid and the integration of simulation programs into more complex applications. Therefore the development of future scientific software requires implicitly a step towards separation of concerns beyond the possibilities of classical programming techniques. An important integration problem in the context of scientific computing is the coupling of independently simulated phenomena, where different programs simulate only a part of a more complex coupled system. Numerical methods for the coupling of simulators like Lagrangian–multipliers based or staggered methods are in common use. Many problems which appear in practice of simulator coupling are not mathematical, but of more technical nature. That results in the current situation where code for the coupling of simulations is not implemented in a reusable way. New approaches to separation of concerns like aspect oriented and generative techniques may help to overcome these issues. As our vision we discuss the idea of a domain specific language (DSL) for coupled simulations. We present a review on methods, paradigms, theories and tools which aim at the development of coupled simulations with a generative approach. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Coevolutionary Architecture for Distributed Optimization of Complex Coupled Systems

A coevolutionary architecture for distributed optimization of complex coupled systems is presented. This architecture is inspired by the phenomena of coevolutionary adaptation occurring in ecological systems. The focus of this research is to develop flexible design architectures for addressing the organizational and computational challenges involved in optimization of large-scale multidisciplinary systems. In the proposed design architecture the optimization procedure is modeled as the process of coadaptation between sympatric species in an ecosystem. Each species is entrusted with the task of improving subdomain specific objectives and the satisfaction of subdomain constraints. Coupling compatibility constraints are accommodated via implicit generalized Jacobi iteration, which enables the application of the proposed architecture to systems with arbitrary coupling bandwidth between the disciplines, without an increase in the problem size. A domain decomposition approach is presented for distributed structural optimization to construct a class of test problems. Numerical studies are presented to demonstrate that convergence to an optimal solution satisfying the subdomain and coupling compatibility constraints can be readily achieved.

Dynamic structural–acoustic–piezoelectric finite-element analysis of a sonar array for a supercavitating high-speed underwater vehicle

Three-dimensional nonlinear dynamic finite-element analysis (FEA) is utilized herein in order to examine the coupled structural, acoustic, and piezoelectric noise propagation physics within a high-frequency sonar array for a supercavitating underwater research vehicle. Specifically, steady-state dynamic simulations of the sonar array’s coupled performance are carried out that model both (a) the acoustic radiation field resulting from electrically actuated ceramic array elements, and (b) the ceramic array element electrical response due to incident structure-borne excitation; fluid-borne excitation is being examined presently and may also be presented if completed in time. This paper focuses primarily on the interesting issues related to accurately modeling such a complex coupled system. For example, the frequency-dependent properties of a nonlinear elastomer absorption material within the array must be carefully characterized at very high frequencies in order to gain accurate results. Additionally, determining electrical properties of the piezoelectric ceramic material can pose a significant problem. Finally, performing a three-dimensional simulation at high frequencies with coupled physics analyses is not a trivial undertaking.. Laboratory shaker experiments performed in order to validate the modeling will also be presented.