Fault Diagnosis of Reciprocating Compressors Valve Based on Cyclostationary Method

The relationship between second-order cyclostationary method and time-frequency distribution is studied, and cyclic autocorrelation（CA） function is indicated to be one sort of special time-frequency distribution method. Furthermore, a fault diagnosis method for reciprocating compressors based on empirical mode decomposition （EMD） and CA function is proposed, and then it is applied to the fault diagnosis of reciprocating compressor valve. Firstly, the vibration signal of reciprocating compressor valve is decomposed by using ENID method, and several intrinsic mode functions （IMFs） are obtained. Secondly, the IMFs are evaluated by some denoising criterions to remove the noise and interfering ones. Finally, the CA functions of the remained IMFs are calculated, which will be used to reconstruct the CA function of the original vibration signal. Engineering application indicates that this method can sufficiently inhibit the cross-interference items of CA function. Therefore, more explicit working conditions of reciprocating compressor components can be achieved.

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.

Reliability,Availability,Maintainability(RAM)study,on reciprocating compressors API 618

The Oil&Gas industry has continuously increased its requirements and together with the high complexity of technological systems and the higher competitiveness of markets,has compelled providers to implement adequate management strategies for these systems in order to improve their availability and productivity to meet those more demanding criteria.In this context,the complex of RAM factors constitute a strategic approach for integrating reliability,availability and maintainability,by using methods,tools and engineering techniques(Mean Time to Failure,Equipment down Time and System Availability values)to identify and quantify equipment and system failures that prevent the achievement of the productive objectives.The application of such methodologies requires a deep experience and know-how together with the possibility of acquiring and processing data in operating conditions.This paper presents the most relevant aspects and findings of a study conducted for assessing the operational performance of a reciprocating compressor system package installed and used in the oil and gas'industries.The study was based on the analysis of the behaviour of states defined for each individual parts and component of reciprocating compressor and also aimed to identify and evaluate the effects of RAMtype factors and was conducted in collaboration with a private company that,for privacy reasons,will be named RC company.The Methodologies procedures used in this descriptive study were the bibliographical research,documentary and content analysis of the main literature.Adopting the most suitable maintenance strategy is one of the main challenges that maintenance managers face.The main purpose of this work is to propose a new approach to evaluate maintenance strategies.In this study,three criteria called reliability,availability and maintainability(RAM)have been employed to compare to future maintenance strategies.

Valve Dynamic and Thermal Cycle Model in Stepless Capacity Regulation for Reciprocating Compressor

The existing researches of stepless capacity regulation system by depressing the suction valve for reciprocation compressor always adopt hypothesis that the compressor valves are open or close instantaneously, the valve dynamic has not been taken account into thermal cycle computation, the influence of capacity regulation system on suction valves dynamic performance and cylinder thermal cycle operation has not been considered. This paper focuses on theoretical and experimental analysis of the valve dynamic and thermal cycle for reciprocating compressor in the situation of stepless capacity regulation. The valve dynamics equation, gas forces for normal and back flow, and the cylinder pressure varying with suction valve unloader moment during compression thermal cycle are discussed. A new valve dynamic model based on L-K real gas state equation for reciprocating compressor is first deduced to reduce the calculation errors induced by the ideal gas state equation. The variations of valve dynamic and cylinder pressure during part of compression stroke are calculated numerically. The calculation results reveal the non-normal thermal cycle and operation condition of compressor in stepless capacity regulation situation. The numerical simulation results of the valve dynamic and thermal cycle parameters are also verified by the stepless capacity regulation experiments in the type of 3L-10/8 reciprocating compressor. The experimental results agree with the numerical simulation results, which show that the theoretical models proposed are effective and high-precision. The proposed theoretical models build the theoretical foundation to design the real stepless capacity regulation system.

Research on gas leakage through suction valves of reciprocating compressor under varying load conditions

A research concerning the coupling conditions of gas leakage through suction valves and capacity regulation is performed in an industrial reciprocating compressor.Both internal flow and thermodynamic characteristic are discussed in detail.The results show that the capacity of compressor can be regulated steplessly by controlling suction valve closure moment.And then the quantitative relationship between the capacity load and the closing angle of suction valve is revealed.The capacity load and valve leakage rate show obvious different features in P-V diagrams,which makes it easier to define appropriate features for detecting cracked or broken reciprocating compressor valves under varying load conditions.A set of curves of compression work and discharge gas mass are obtained and a method for rating thermal performance of a compressor is presented using these curves.

Fault diagnosis of reciprocating compressor cylinder based on EMD coherence method

Since there always exist interference components which caused by valve vibration,it is hard to directly use cylinder signal for fault diagnosis of reciprocating compressor. Based on Empirical Mode Decomposition (EMD) coherence,a new method for the fault diagnosis of reciprocating compressor cylinder is presented. Firstly,double channel signals of cylinder and valve are synchronously sampled. Secondly,cyclic cross-correlation function is used to eliminate the time delay between these signals. Finally,EMD coherence method is utilized to remove the interference components from cylinder signal. Thus,more concise and precise working condition information for cylinder and inner components can be obtained. So it is an effective method for fault diagnosis of reciprocating compressor cylinder.

A novel flow control scheme for reciprocating compressor based on adaptive predictive PID control

In the process of capacity regulation of reciprocating compressor, the frequent change of inlet temperature and pressure makes the control of exhaust flow unstable, resulting in the high pressure ratio of the intermediate stage. At last the compressor cannot operate safely. To solve the problem, a novel flow control scheme based on inlet temperature and pressure ratio is proposed. In this scheme, the intake model of the cylinder under the capacity regulation condition is established to calculate the load of the first cylinder. Then, the adaptive predictive PID(APPID) controller is designed to control the pressure ratio of other stages, and the grey prediction model is used to predict the pressure output to overcome the system delay. To solve the problem of control parameters tuning, an improved particle swarm optimization(PSO) algorithm is adopted to obtain the optimal control parameters.The effectiveness of the adaptive predictive PID control method is verified by a two-stage compressor model simulation.Finally, the flow control scheme is applied to the actual four-stage air reciprocating compressor flow control system. Although the temperature difference is greater than 15 ℃, the compressor exhaust flow is maintained at the set value and the pressure ratio is also maintained stable. At the same time, the compressor pressure ratio can be quickly adjusted without overshoot. The application result further verifies the feasibility and effectiveness of the scheme.

Flywheel and Induction Motor Sizing for Torque Fluctuation Optimization in Reciprocating Compressor

Reciprocating compressors are prone to high cyclic loads. The high required performance relies on a good design focusing a torque oscillation applied by the driver. In the first part of this job, dynamic model of reciprocating is presented. Newton-Euler method is used to get motion equations. In the second part, numerical results are presented. Simulations are used for calculating the driving moment as function of crankshaft motion. These results illustrate the effect of the flywheel and motor on its dynamics and are used for induction motor selection and flywheel sizing for optimizing crankshaft torque fluctuation and power consumption reduction.

Research on fault diagnosis method of piston rod based on harmonic wavelet and manifold learning

As the core part of reciprocating compressor,piston rod is easy to cause a serious accident when abrasion and breakage fault occur to it. Therefore,it is very important to monitor its running state. At present,a small number of reciprocating compressors have been installed on-line monitoring and diagnosis system,most of which can only monitor a single vertical subsidence of piston rod and it can't fully represent the running state of piston rod. Therefore,a method of monitoring the vertical and horizontal displacement of piston rod axis orbit is simultaneously used. In view of the characteristics that the piston rod axis orbit is disordered and difficult to extract features,purification of the axis orbit is carried out based on harmonic wavelet and then features are extracted such as vibration energy,natural frequency and the axis orbit envelope area. After that,a nonlinear local tangent space manifold learning algorithm is used to reduce the dimension of the features and obtain sensitive features. By analyzing the practical cases,the effectiveness of the method for fault monitoring and diagnosis of reciprocating compressor piston rod assembly has been verified. Finally,as BP neural network has the characteristics of solving complex nonlinear problems,the validity of the fault diagnosis method of reciprocating compressor piston rod based on harmonic wavelet and manifold learning is proved by actual case data analysis based on BP neural network.

Performance Evaluation on the In-Cylinder Heat Transfer of a Reciprocating Compressor using CO_(2) as a Working Fluid

The aim of this current work is to investigate the effects of operating parameters on heat transfer characteristics between gas and in-cylinder solid surfaces in a reciprocating compressor.A numerical model has been implemented in MATLAB based on mass balance,the first law of thermodynamics,and NIST REFPROP database for gas properties and thermodynamic relationships.The impacts of key parameters such as rotational speed,suction temperature,pressure ratio and suction pressure are particularly evaluated on heat transfer coefficient(HTC),heat flux(HF)and gas temperature.Results demonstrate that HTC increases markedly with the increase of rotational speed,pressure ratio and suction pressure,and decreases slightly with the increase of suction temperature;the instantaneous HF strengthens significantly with the increase of rotational speed,pressure ratio and suction pressure,whereas the mean HF magnitude transferred from gas to the wall decreases with the increase of rotational speed;the maximum gas temperature is more sensitive to suction temperature and pressure ratio.

Performance analysis and design of self-air-cooling reciprocating compressor’s cooling system

The cooling system,as an important part of high-pressure compressor,has always been a key technical bottleneck for its miniaturization. A new type self-air-cooling system is first proposed for the reciprocating compressor through ingenious structural design without any auxiliary equipment. The transient model of cooling system is established,which regards the cooling passage as a chamber with compressibility and heat exchange considering the linear and local flow resistance. The design principle is achieved by studying the working process and key parameters characteristics,which provides the theoretical foundation for the structural design. The experimental results show that the self-air-cooling system can quickly lower the temperature of the cylinder compared with natural cooling,which has considerable theoretical significance and practical value for the miniature high pressure compressor.

Effect of Fluid-Structure Interaction on Sealed Flow Field and Leakage Rate Based on Computational Fluid Dynamics

This paper addresses the issue of reciprocating compressors staggered labyrinth seal structure. The internal flow field of sealed structure, the displacement of cylinder and piston for different tooth profile angles are analyzed synchronously using FLUENT software, and the effects of fluid-structure interaction on the performance of the labyrinth seal are revealed. The results indicate that with the growth of tooth profile angle, the leakage rate of labyrinth seal tends to decrease first, and then increase. The results of fluid-structure interaction analysis are close to those of actual engineering. The effect of fluid-structure interaction makes tiny deformation in calculation mesh of piston and cylinder structure, and the coupling interaction affects the performance of the labyrinth seal.