Study of Failure Diagnostic Methods and Intelligent Diagnostic System for Reciprocating Compressors

Three categories of failure diagnostic methods for reciprocating compressors are classified according to the signals adopted by the diagnosis.They are parameter method,vibration method,and oil analysis method.In this paper,the applicable range and operational difficulties of these methods are discussed on the basis of analysis and induction upon normal failure.It is proposed that a compressor‘s normal failure can be divided into thermodynamical property failure and mechanical function failure.As to the former,the parameter method that takes a cylinder pressure signal as the main diagnostic signal may be applied;and as to the latter,the vibration signal frequency spectrum can be used to diagnose.At the same time,the structure of an intelligent diagnostic system based on neural networks is introduced,and its schematic is given.     

Modelling a Job-Shop Plant Using Queuing Networks Techniques

This article illustrates the use of open queuing networks for the planning of discrete production systems of the job-shop type. For this purpose, it is assumed that the system can be modelled by a set of workstations. The mathematical and numerical procedures, related to the definition of the model that is used to characterize the system operations, are analyzed first. For this purpose, an ideal situation of a system with only two workstations and four products is used. Next, the application of the model to a real case study, corresponding to a metalworking company, is illustrated. In this case, the parameters that can be used to characterize the efficiency of the system are also introduced. The performance diagnostics involves the analysis of the work-in-process and the production lead-times. The optimization of the system involves the probabilistic characterization of the demand and the characterization of the probability of transference of products among workstations. Among other alternatives, a waiting-cost function, which is evaluated using the queuing parameters, can be used to compare alternative solutions.     

The Prediction of Dynamic Coefficients for Tilting-Pad Journal Bearings Based on an AGA-BP Neural Network

To provide real-time dynamic coefficients of tilting-pad journal bearings( TPJBs) for the dynamic analysis of a rotor-bearing system accurately,an improved error back propagation( BP) neural network model is built in this paper.First,the samples are gained by solving the Reynolds equation with the finite differential method based on hydrodynamic lubrication theory.Secondly,the adaptive genetic algorithm( AGA) is applied to optimize the initial weights and thresholds of the BP neural network before training.Then,with a number of trial calculations,the optimum parameters for the neural network are obtained.Finally,an application case of the neural network is given as well as the results analysis.The results show that the AGA can efficiently prevent the training of the neural network from falling into a local minimum,and the AGA-BP neural network of dynamic coefficients for TPJBs built in this paper can meet the demand of engineering.     

Synchronizing the Parameter Non—matching Chaotic Systems

It is shown that synchronization,in a weak sense,can be achieved between two-parameter non-matching systems by using the adaptive control method.In essence,this requires just a scalar signal transmitted from the drive to the response system.Two typical chaotic systems,i.e.Lorenz and Roessler system ,are taken as examples of applications in this paper.     

Load Allocation Research in a Manufacturing System

Based on queuing theory, a nonlinear optimization model is proposed in this paper, which has the service load as its objective function and includes three inequality constraints of Work In Progress （WIP）. A novel transformation of optimization variables is also devised and the constraints are properly combined so as to make this model into a convex one from which the Lagrangian function and the Karurh Kuhn Tucker （KKT） conditions are derived. The interior-point method for convex optimization is presented here as a computationaUy efficient tool. Finally, this model is evaluated on a real example, from which such conclusions are reached that the optimum result can ensure the full utilization of machines and the least amount of WIP in manufacturing systems; the interior-point method needs fewer iterations with significant computational savings and it is possible to make nonlinear and complicated optimization problems convexified so as to obtain the optimum.     

Fault Diagnosis of a Turbo—unit Based on Wavelet Packet Theory

In this paper we studied the fault feature of the generator set and the characteristics of wavelet packet theory for signal de-noising.The vibration signal of the generator set in different states is ana-lyzed by using the signal re-construction technique of the wavelet packet theory.The time domain method is given for the generator set fault diagnosis.The experiment results show that the wavelet packet theory can be used to directly identify the state of the generator set and provide a credible new idea for complex machinery fault diagnosis.     

Control strategies and hardware-in-the-loop simulation for bus signal priority

It is considered to be an important and effective means to give priority to the development of public transport which can improve the efficiency of using traffic resources and alleviate traffic jams , public transit signal priority belongs to the "time priority" among right-of-way priorities .In the review of existing bus priority signal control strategies and the progress of related technologies at home and abroad, this article analysis the condition of our country for the bus signal priority and a breakthrough in optimizing the design direction, then propose hardware and software systems and modules for the bus priority signal control system. Finally, the hardware-in-the-loop simulation is introduced to evaluate and demonstrate bus priority signal control programs, which can better develop and optimize the control strategy.     

Design of Variable Structure Control by Using the L_2 Gain Method

The robust stabilization problem for a family of nonlinear plants with mismatch uncertainties is addressed,and a solution is presented based on variable structure control theory and H∞ control theory.A kind of boundary layer is built near the ideal switch surface which can eliminate chattering in the switch surface.The proposed control method with L2 gain can guarantee exponential stability of a system state with no parameter uncertainty and external disturbance,while it can guarantee state ultimate boundness if parameter uncertainty and external disturbance exist.In the proposed design method,stability of the closed-loop system is analyzed by adopting the Lyapunov function approach.Finally the numerical simulation results show that the proposed smooth variable structure controller has good performance without chattering in the switch surface.     

Visualizing nonlinear resonance in nanomechanical systems via single-electron tunneling

Numerous reports have elucidated the importance of mechanical resonators comprising quantum-dot-embedded carbon nanotubes(CNTs)for studying the effects of single-electron transport.However,there is a need to investigate the single-electron transport that drives a large amplitude into a nonlinear regime.Herein,a CNT hybrid device has been investigated,which comprises a gate-defined quantum dot that is embedded into a mechanical resonator under strong actuation conditions.The Coulomb peak positions synchronously oscillate with the mechanical vibrations,enabling a single-electron Chopper*1 mode.Conversely,the vibration amplitude of the CNT versus its frequency can be directly visualized via detecting the time-averaged single-electron tunneling current.To understand this phenomenon,a general formula is derived for this time-averaged single-electron tunneling current,which agrees well with the experimental results.By using this visualization method,a variety of nonlinear motions of a CNT mechanical oscillator have been directly recorded,such as Duffing nonlinearity,parametric resonance,and double-,fractional-,mixed-frequency excitations.This approach opens up burgeoning opportunities for investigating and understanding the nonlinear motion of a nanomechanical system and its interactions with electron transport in quantum regimes.     

Dynamics of a Dual Power-split Transmission Based on Loaded Tooth Contact Analysis

In order to implement the dynamic characteristic of a dual power-split transmission,a dynamic mechanics model is built. Firstly,according to the method of theoretical analysis of the tooth contact analysis ( TCA) and loaded tooth contact analysis ( LTCA) ,the actual meshing process of each gear pairs is simulated, and the time-varying mesh stiffness excitations are obtained,which can improve the numerical precision. Secondly,by using the lumped mass method,the bending-torsional coupling three dimensional dynamic model of the dual power-split transmission is established,and the identical dimensionless equations are deduced by eliminating the effect of rigid displacement and the method of dimensional normalization. Finally,by the method of the fourth order Runge-Kutta algorithm with variable step lengths,the responses of this system in a frequency domain and time domain are obtained,and the dynamic load change characteristics of each gear pairs are analyzed. The results show that the establishment,solution and analysis of the system dynamics model could provide a basis for the dynamic design,and have an important significance for the dynamic efficiency analysis and dynamic performance optimization design of the dual power-split transmission.     

Increasing the Resolution and SNR of an ADC＇s Measurement with a Method of OverSampling and Averaging

By analyzing the theory of over-sampling and averaging, the conclusion is educed that white noise accompanies the signal and the addition of each bit of resolution can be achieved via a fourfold sampling frequency. The addition of each bit will approximately increase the SNR （signal to noise ratio） to 6dB.     

Data based model free hysteresis identification for a nonlinear structure

In the last two decades, the damage detection for civil engineering structures has been widely treated as a modal analysis problem and most of the currently available vibration-based system identification approaches are based on modal parameters, namely the natural frequencies, mode shapes and damping ratios, and/or their derivations, which are suitable for linear systems. Nonlinearity is generic in engineering structures. For example, the initiation and development of cracks in civil engineering structures as typical structural damages are nonlinear process. One of the major challenges in damage detection, early warning and damage prognosis is to obtain reasonably accurate identification of nonlinear performance such as hysteresis which is the direct indicator of damage initiation and development under dynamic excitations. In this study, a general data-based identification approach for hysteretic performance in form of nonlinear restoring force using structural dynamic responses and complete and incomplete excitation measurement time series was proposed and validated with a 4-story frame structure equipped with smart devices of magneto-rheological (MR) damper to simulate nonlinear performance. Firstly, as an optimization method, the least-squares technique was employed to identify the system matrices of an equivalent linear system of the nonlinear structure model basing on the excitation force and the corresponding vibration measurements with impact test when complete and incomplete excitations; and secondly, the nonlinear restoring force of the structure was identified and compared with the test measurements finally. Results show that the proposed data-based approach is capable of identifying the nonlinear behavior of engineering structures and can be employed to evaluate the damage initiation and development of different structure under dynamic loads.     

Research of a Response Precise Algorithm on a System with a Pseudo-viscous Frictional Energy Dissipator

The pseudo-viscous frictional energy dissipator(PVFED) is a new energy dissipator. This dissipator can be widely used in engineering for not only the friction is in direct ratio to velocity, but also the problem of viscous energy dissipator mucilage easily leaked has been overcome. The problem of how to get response of the PVFED system need to be solved before this dissipator can be used widely in engineering. The response calculation methods of the PVFED system on sina load was researched. Wilson-θ,Newmark-β and a precise integration algorithm was used separately to solve the system response and the calculation result in a different time step was compared. It was found from comparison that three calculation results were almost equivalent in a small time step. Calculation precision of Newmark-β and Wilson-θ was reduced and high calculation precision of a precise integration algorithm was kept in a large time step. The results show that it is an effective way to solve the response of a PVFED system by a precise integration method.     

Variable Parameters PD Control and Stability of a High Rate Rigid Rotor-Journal Active Magnetic Bearing System

Stability is a key problem that means whether a high rate rotor-active magnetic bearings system works reliably or not. Aiming at a bearings system described with nonlinear equations, this paper built a linear model according to the system behavior. Considering realization of the control system and behavior of a high rate rotor system (magnetic force is far smaller than input force produced by mass eccentricity) this paper proposes a design method of variable parameters PD control algorithm that can be used universally. The control system was simplified and a mass of adjusting work of control parameters was reduced. Analysis and simulation indicated that the bearings system could get a wider stable region of harmonic motion, and proved that the algorithm is robust and advanced. The control system can be realized because the winding electric currents are positive. The method is convenient for operation and can easily be used for engineering practice.     

Detection and Diagnosis of Gear Fault By the Single Gear Tooth Analysis Technique

This paper, presents a procedure of single gear tooth analysis for early detection and diagnosis of gear faults. The objective of this procedure is to develop a method for more sensitive detection of the incipient faults and locating the faults in the gear. The main idea of the single gear tooth analysis is that the vibration signals collected with a high sampling rate are divided into a number of segments with the same time interval. The number of signal segments is equal to that of the gear teeth. The analysis of individual segments reveals more sensitively the changes of the vibration signals in both time and frequency domain caused by gear faults. In addition, the location of a failed tooth can be indicated in terms of the position of the segment that deviates from the normal segments. An experimental investigation verified the advantages of the single gear tooth analysis.     

A Study on a Remote Monitoring and Diagnosis System and Its Application

Remote monitoring and diagnosis （RMD） is a new kind of monitoring and diagnosis technology that combines computer science, communication technology and fault diagnosis technology. Via the Internet a remote monitoring and diagnosis system can be established. In this paper, the model of an Internet based remote monitoring and diagnosis system is presented; the function of every part of the RMD system is discussed. Then, we introduce a practical example of a remote monitoring and diagnosis system that we established in a factory; its traits and functions are described.     

Application of General Fractal Dimension to Coupling Fault Diagnosis

This paper presents the coucept of general and sensitive dimension,and also proposes the calculation formula of the general dimension least squares method.By calculating and analyzing the power spectrum and general dimension grom the fault sample,the relationship is achieved between sample status and the general simension from vibration signals of the equipment so as to provide reference to fault diagnosis.Furthermore,a correlation function of general dimension is proposed,and calculations are carried out for a monitor signal and samples signal.The diagnosis method based on fractal theory is effective through the concrete examples of the steam-electric generating set fault diagnosis,and the correlation coefficient of general dimension between a monitor signal and samples signal can improve the accuracy for fault diagnosis.     

基于推覆分析混凝土框架摇摆墙结构抗震性能研究

RC frame rocking wall structure is a new structure system, which combines RC frame with rocking wall. A 6-story RC frame following current design practice is taken as an example to study the seismic behavior of the new system. Elastic-plastic model is established, and pushover analysis is conducted by using a finite element program called Abaqus and a user subroutine library called PQFiber. The analysis results suggest that: (1) the rocking wall can significantly improve the strength and ductility of the entire structure. (2) Thanks to the rocking wall, the inter-story drift becomes more uniformly distributed and the story failure mechanism is prevented, although the rocking wall does not contribute much to avoid the ‘Strong beam weak column’ yielding mechanism. (3) The inner force distribution of the rocking wall is similar to a veridical placed simple supported beam.     

A new viewpoint and model of neural signal generation and transmission:Signal transmission on unmyelinated neurons

We establish a preliminary model of neural signal generation and transmission based on our previous research,and use this model to study signal transmission on unmyelinated nerves.In our model,the characteristics of neural signals are studied both on a long-time and a short time scale.On the long-time scale,the model is consistent with the circuit model.On the short time scale,the neural system exhibits a THz and infrared electromagnetic oscillation but the energy envelope curve of the rapidly oscillating signal varies slowly.In addition,the numerical method is used to solve the equations of neural signal generation and transmission,and the effects of the temperature on signal transmission are studied.It is found that overly high and overly low temperatures are not conducive to the transmission of neural signals.     

Ways of Increasing Synergy in Automated Factory Design and Commissioning Teamwork

The present paper is focused on the problems of reducing losses of resources at the start-up of new automated factories caused by human shortcomings in teamwork activities. The research is based on a unique database of empirical studies of human faults and mistakes at the design and commissioning of factory automation systems. This database covers over 25 automated factories on three continents, containing pulp and paper mills, chemical and petrochemical plants and power stations. It is shown that the most suitable tool for teamwork analysis is the design structure matrix （DSM）method, which allows visualisation of the full complexity of synergy relations between all team members on the basis of the frequency and amount of information interchange. The mathematical treatment of DSM matrixes enables us to form the most capable teams, to schedule and evaluate their activities. It is shown that as a result of logical analysis it is possible to create an optimal communication and cooperation system, where the competences and capabilities of the teams and their members can be more fully exploited.