A fault diagnosis method of reciprocating compressor based on sensitive feature evaluation and artificial neural network

A method combining information entropy and radial basis function network is proposed for fault automatic diagnosis of reciprocating compressors.Aiming at the current situation that the accuracy rate of reciprocating compressor fault diagnosis which depends on manual work in engineering is very low,we apply information entropy evaluation to select the sensitive features and make clear the corresponding relationship of characteristic parameters and failures.This method could reduce the feature dimension.Then,a complete fault diagnosis architecture has been built combining with radial basis function network which has the fast and efficient characteristics.According to the test results using experimental and engineering data,it is observed that the proposed fault diagnosis method improves the accuracy of fault automatic diagnosis effectively and it could improve the practicability of the monitoring system.

Multi-body dynamic simulation research on the influence of piston engine crankshaft thrust bearings abrasion

Fault diagnosis studying on piston engine,crankshaft and gearbox is focused in this paper. The thrust bearing abrasion caused by axial movement of the crankshaft will affect the force of timing gears and oil pump gears,which will result in the fracture of gears,abnormal ignition,connecting rod cracking and collision of cylinder. Simulation based on CREO software is done to build three-dimensional models of crankshaft and gears of a WP10 diesel engine. The models are imported into ADAMS to complete multi-body dynamics simulations. The force analysis of gears in different kinds of axial movements is finished and variations rules of gear dynamic load is obtained. The presented results show that the crankshaft axial movement can cause overload and vibration on gears. Combined with the realistic case data,the fault feature through simulation research is validated and early warming parameters of gear fault are proposed.

Experimental Investigation on Vibration Control of Rotor-bearing System with Active Magnetic Exciter

Vibration control is an efficient way to minimize a rotating machine's vibration level so that its vibration fault-free can be realized.While,several factors,such as unbalance,misalignment and instability,contribute to the serious vibration of rotating machines.It is necessary that one apparatus can depress vibration caused by two or more reasons.The fault self-recovery(FSR) mechanism is introduced and investigated.Strategies of vibration control are investigated theoretically using numerical method firstly.Active magneticelectric exciter(AME) are selected as the actuator of a FSR device because it can provide suitable force by varying the control current in the exciters depending upon a proportional and derivative control law.By numerical study,it is indicate that only a small control force is needed to improve stability margins of the compressor and prevent subsynchronous vibration fault efficiently.About synchronous vibration,three control strategies,searching in whole circle,fast optimizing control(FOC),and none mistaking control,are investigated to show which of the control strategy can realize the fault self-recovery in the shortest time.Experimental study is conducted on a test rig with variable rotating speed.Results of the test indicate that the non-mistake control strategy can minimize synchronous vibration in less than three seconds.The proposed research can provide a new insight for subsynchronous and synchronous vibration restraining about centrifugal compressor.

Weighted Multi-sensor Data Level Fusion Method of Vibration Signal Based on Correlation Function

As the differences of sensor's precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn't require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor's own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.

Flow Field Characteristics of the Rotor Cage in Turbo Air Classifiers

The turbo air classifier is widely used powder classification equipment in a variety of fields. The flow field characteristics of the turbo air classifier are important basis for the improvement of the turbo air classifier's structural design. The flow field characteristics of the rotor cage in turbo air classifiers were investigated under different operating conditions by laser Doppler velocimeter(LDV), and a measure diminishing the axial velocity is proposed. The investigation results show that the tangential velocity of the air flow inside the rotor cage is different from the rotary speed of the rotor cage on the same measurement point due to the influences of both the negative pressure at the exit and the rotation of the rotor cage. The tangential velocity of the air flow likewise decreases as the radius decreases in the case of the rotor cage's low rotary speed. In contrast, the tangential velocity of the air flow increases as the radius decreases in the case of the rotor cage's high rotary speed. Meanwhile, the vortex inside the rotor cage is found to occur near the pressure side of the blade when the rotor cage's rotary speed is less than the tangential velocity of air flow. On the contrary, the vortex is found to occur near the blade suction side once the rotor cage's rotary speed is higher than the tangential velocity of air flow. Inside the rotor cage, the axial velocity could not be disregarded and is largely determined by the distances between the measurement point and the exit.

A Study on PC/104 Embedded Automatic Balancing Control System

In this paper,an embedded real-time control system for automatic rotor balancing was studied.Benefiting from the modular design,this system can be easily re-constituted or expanded under different working conditions.The special designed hardware resists harsh environment.As an embedded application,it was very important to save system consumptions on both hardware and software,so the algorithms for unbalance vibration identification and attenuation were deduced,meantime a unified fast algorithm structure was achieved through the geometric analysis.Based on this structure,the signal processing algorithm was tested by an open data source,while the control algorithm was simulated using a basic rotor model,and then connected to a hyper gravity machine running online auto-balancing.The result confirms that the unbalancing vibration is effectively restrained.

Method to deploy wireless relays in industrial wireless monitoring

In light of demands for wireless monitoring and the characteristics of wireless channel,a complete deployment method containing channel survey,path loss estimation,and gradient grade of wireless relay nodes is proposed.It can be proved by experiments that under the premise of meeting the requirements of real-time and redundant-topology,the total number of relay nodes could be minimized by using the proposed method.

A method to compress vibration signals using wavelet packet transformation combined with sub-band vector quantization

A novel compression method for mechanical vibrating signals,binding with sub-band vector quantization(SVQ) by wavelet packet transformation(WPT) and discrete cosine transformation(DCT) is proposed.Firstly,the vibrating signal is decomposed into sub-bands by WPT.Then DCT and adaptive bit allocation are done per sub-band and SVQ is performed in each sub-band.It is noted that,after DCT,we only need to code the first components whose numbers are determined by the bits allocated to that sub-band.Through an actual signal,our algorithm is proven to improve the signal-to-noise ratio(SNR) of the reconstructed signal effectively,especially in the situation of lowrate transmission.

A Simulation Study of Higee Rotor Auto-balancing Based on Iterative Learning Control

Hypergravity technology has a wide application prospect on many industry areas for its powerful ability on multiphase flow transport and reaction.In its long-term operation,vibration control of higee rotor is an important guarantee for high-quality continuous outputs.Offline approach has great influence on continuity of the whole production line.In order to study online auto-balancing control strategy,a mathematical model of higee rotor was established.Then basic Iterative Learning Control(ILC)algorithm and its improved structure based on vector analysis were introduced.Pure injection balancer and electromagnetic balancer were separately used as the actuator.Three different control algorithms(P control using Cohen-Coon parameter tuning law,basic ILC,and improved ILC based on vector analysis)were compared under single eccentric mass disturbance and continuous ones.Simulation results manifested the effects of ILC in rotor auto-balancing control,especially on the "over-control" issue during the balancing process.