Diagnosis of Bearing Fault Using Morphological Features Extraction and Entropy Deconvolution Method

It is observed that the bearing failure of rotating machinery is a pulse in the vibration signal, but it is mostly immersed in noise. In order to effectively eliminate this noise and detect pulses, a novel an image fusion technology based on morphological operators inference is proposed. The correctness of morphological operators lies in the correct selection of structural elements (SE). This report presents an effective algorithm for SE selection based on kurtosis, which makes the analysis free empirical method. When analyzing three different groups of faults, the results show that this method effectively and robustly generates impulse. It enables the algorithm to detect early faults too. Recently, minimum entropy deconvolution (MED) was introduced to the machine in the field of condition monitoring, to enhance the detection of rolling bearing and gear failures. MED analysis helps to extract these pulses and diagnose their source, namely defects bearing components. In this research, MED will be reviewed and reintroduced, Application in fault detection and diagnosis of rolling bearings. MED parameters are selected and its combination with pre-whitening. Test cases are presented to illustrate benefits of MED technology. The simulation has been done on MATLAB and a graphical user interface has been created for analysis of bearing and detection of bearing faults using morphological features

Bearing prognostics using neural network under time varying conditions

Condition based maintenance (CBM) aims to schedule maintenance activities based on condition monitoring data in order to lower the overall maintenance costs and prevent unexpected failures. Effective CBM can lead to reduced downtime, less inventory, reduced maintenance costs, reliable operation and safety of entire system. The key challenge in achieving effective CBM is the accurate prediction of equipment future health condition and thus the remaining useful life. Existing prognostics methods mainly focus on constant loading conditions. However, in many applications, such as some wind turbine, transmission and engine applications, the load that the equipment is subject to changes over time. It is critical to incorporate the changing load in order to produce more accurate prognostics methods. This research is focused on the bearing prognostics, which are key mechanical components in rotary machines, supporting the entire load imposed on machines. Failure of these components can stop the operation due to machine down time, thus resulting in financial losses, which are much higher than the cost of bearing. In this thesis, an artificial neural network (ANN) based method is proposed for equipment health condition prediction under time varying conditions. The proposed method can be applied to bearing as well as other components under condition monitoring. In the proposed ANN model, in addition to using the age and condition monitoring measurement values as an inputs, a new input neuron is introduced to incorporate the varying loading condition. The output of the ANN model is accumulated life percentage, based on which the remaining useful life can be calculated once the ANN is trained. Two sets of simulated degradation data under time varying load are used to demonstrate the effectiveness of the proposed ANN method, and the results show that fairly accurate prediction can be achieved using the proposed method. The other key contribution of this thesis is the experiment validation of the proposed ANN prediction method. The Bearing Prognostics Simulator, after extensive adjustment and tuning, is used to perform bearing run-to-failure test under different loading conditions. Vibration signals are collected using the data acquisition system and the Labview software. The root mean square (RMS) measurement of the vibration signals is used as the condition monitoring input for the validation of the proposed ANN prediction method. Two bearing failure histories are used to train the ANN model and test its prediction performance. The results demonstrate the effectiveness of the proposed method in dealing with real-world condition monitoring data for health condition prediction. The proposed model can greatly benefit industry as well as academia in condition based maintenance of rotary machines

Devising Methods to Avoid Formation of Defects in a Ball Bearing through FFT Analyzer

Most of the essentials part is rolling element bearings in rotating machinery. Between the two parts of linear and relative motion are permitted for the function of bearings. During the operation, the bearings are often subjected to high speed and severe conditions. Under these severe operating conditions, defects are often developed in the bearing components. If no corrective measures are taken, the machine could halt or be seriously damaged. A different effect of bearing failure yields its own distinctive damage like primary damage and secondary damage are peeling and flaws. Excessive internal clearance, vibration, noise, are primary damage has been considered for the necessities. An unsuccessful bearing of times displays a mix of primary and secondary harm

Research requirements for development of advanced-technology helicopter transmissions

Helicopter drive-system technology which would result in the largest benefit in direct maintenance cost when applied to civil helicopters in the 1980 timeframe was developed. A prototype baseline drive system based on 1975 technology provided the basis for comparison against the proposed advanced technology in order to determine the potential for each area recommended for improvement. A specific design example of an advanced-technology main transmission is presented to define improvements for maintainability, weight, producibility, reliability, noise, vibration, and diagnostics. Projections of the technology achievable in the 1980 timeframe are presented. Based on this data, the technologies with the highest payoff (lowest direct maintenance cost) for civil-helicopter drive systems are identified

Prognostic-based Life Extension Methodology with Application to Power Generation Systems

Practicable life extension of engineering systems would be a remarkable application of prognostics. This research proposes a framework for prognostic-base life extension. This research investigates the use of prognostic data to mobilize the potential residual life. The obstacles in performing life extension include: lack of knowledge, lack of tools, lack of data, and lack of time. This research primarily considers using the acoustic emission (AE) technology for quick-response diagnostic. To be specific, an important feature of AE data was statistically modeled to provide quick, robust and intuitive diagnostic capability. The proposed model was successful to detect the out of control situation when the data of faulty bearing was applied. This research also highlights the importance of self-healing materials. One main component of the proposed life extension framework is the trend analysis module. This module analyzes the pattern of the time-ordered degradation measures. The trend analysis is helpful not only for early fault detection but also to track the improvement in the degradation rate. This research considered trend analysis methods for the prognostic parameters, degradation waveform and multivariate data. In this respect, graphical methods was found appropriate for trend detection of signal features. Hilbert Huang Transform was applied to analyze the trends in waveforms. For multivariate data, it was realized that PCA is able to indicate the trends in the data if accompanied by proper data processing. In addition, two algorithms are introduced to address non-monotonic trends. It seems, both algorithms have the potential to treat the non-monotonicity in degradation data. Although considerable research has been devoted to developing prognostics algorithms, rather less attention has been paid to post-prognostic issues such as maintenance decision making. A multi-objective optimization model is presented for a power generation unit. This model proves the ability of prognostic models to balance between power generation and life extension. In this research, the confronting objective functions were defined as maximizing profit and maximizing service life. The decision variables include the shaft speed and duration of maintenance actions. The results of the optimization models showed clearly that maximizing the service life requires lower shaft speed and longer maintenance time

Tribological investigation on the degradation process of contact fatigue in rolling bearings

Rolling contact fatigue in rolling element bearing (REB) is a common surface degradation and failure mechanism. Limited experimental studies were reported on fatigue degradation, in particular, in grease lubricated conditions. This project examines the evolution of the fatigue degradation process through collecting, imaging and characterisation of the damaged surface to further understand the tribological changes in the process. Ball bearings with a seeded, irregular-shaped dent on the outer race were tested in a grease lubricated condition and on a bearing test rig. Moulding technique was used to replicate the damaged surface during the fatigue test. Also, 4 different shapes of initial defects and round-shaped dents in 3 sizes were introduced onto the outer raceway of test bearings to study effects of the shapes and sizes of initial defects on the fatigue degradation process as they are considered significant factors in fatigue propagation. This study has confirmed that the fatigue damage propagated on both the trailing and leading edges of the initial defect. The quantitative analysis reported that the wear depth on the trailing edge was measured more than that on the leading edge by over 100 μm, indicating different stresses distribution on the two edges of the seeded defect. In addition, the leading-edge damage surface was observed ‘self-healing’ or smoothening phenomenon. The shape study suggested similarities with propagating behaviour among the tested shapes of the initial defects. The initial shapes of defects mainly affected the fatigue propagation at the early stage where the first spall was initiated and fatigue progression on the leading-edge side of damaged surface in terms of the length of defected surface and the features of the damaged surface. The size influence study demonstrated that increasing size of the defect enlarged the effect of impact by rolling elements, evidenced by generating rougher surface, and thus shortened fatigue life. The study provides insights in the fatigue process of rolling bearings through monitoring the evolution of the tribological features of the degraded surface. The obtained information can be useful in fatigue model validation and development of effective online techniques for monitoring and prediction of the fatigue progress of REBs

Dynamic Analysis, Identification and Control Studies of Aero-Engine Model Rotor-Bearing Systems

Aero-engines have high speed rotors carrying multi-stage turbine and compressor discs. Such systems need continuous monitoring during the operating regime. These rotors are mounted on ball bearings supported with squeeze film dampers and connected to stator casings. The motions of bearings and rotor are influenced by each other and therefore such a system requires structural dynamic studies. These rotors involve several nonlinear factors including contact forces, varying compliance vibration of ball bearing, nonlinear oil-film force of squeeze film damper etc Solving such nonlinear dynamic problems using the traditional transfer matrix method, modal synthesis approach, finite element method or impedance coupling technique is therefore a challenging task. Present work focuses on modelling of rotors using ball bearing nonlinearities along with nonlinear secondary transient excitations using finite element modelling. In order to validate the finite element model, preliminary dynamic analysis is carried out using linear spring-damper bearing elements. Results are illustrated both for LP rotor model and twin-spool rotor. Initially, the natural frequencies obtained from the computer program based on Timoshenko beam elements are validated with ANSYS results. Further, the results are also validated with those obtained from impact hammer tests on a scaled dual disk rotor-bearing system. To utilize this finite element model, the time and frequency-domain response studies are conducted with double-row ball bearing forces, rub-impact forces, Muszynska’s gas transients along with squeeze-film forces. In all the cases, differences from simple rotor supported by single-row ball bearings with only unbalance excitations have been reported. Using the fundamental frequency and its amplitude, an inverse modelling approach is applied to predict the parameters of rotor bearing system such as increased bearing clearance, changes in disc unbalances and the centralizing spring constants in squeeze-film damper. In this regard, a trained model of 3-layer perceptron neural network model is employed. In the second study, changes in dynamic response due to waviness and race-way defects in ball-bearings are first studied using modified contact force relations. Using this data, type of bearing fault is estimated from the statistical parameters of the time-domain signal by training an unsupervised Kohenen’s neural network model. Here, the simulated data is collected from the rotor over an operating speed range. In the third study, the additional stiffness of rotor due to rub-impact forces is identified from optimization modelling. Such identification of rotor stiffening effect using finite element modelling is a new concept. Two types of control studies are proposed to minimize the amplitudes of rotor during the critical operating conditions. Semi active electromagnetic damper design helps in reducing vibration amplitudes of the LP rotor over a frequency range of interest. Here, the damper comprises of an electro-magnet and a spring. The required current and spring stiffness are identified from the basic relations and the results of control are illustrated with a two-disc LP rotor model. In active controller design, an electromagnetic actuator model is employed. The nominal gap maintained between the rotor and actuator coils is used in computing the actuator force. A proportional derivative (PD) control strategy is used to estimate the required forces. A neural network based alternate control scheme also proposed to compute the required actuator forces. In overall, the work focussed on the dynamic analysis of dual disc rotor model subjected to parametric nonlinear bearing loads under the action of various external forces and some controller design aspects applicable to this rotor

Slip in radial cylindrical roller bearings and its influence on the formation of white etching cracks

Ungünstige Betriebsbedingungen und unzureichende Radialkräfte führen zu Schlupf in Radial-Zylinderrollenlagern. Das kann zu verschiedenen Ausfallmechanismen, wie Anschmierung, Fressschäden, Abplatzen und auch sogenannten White Etching Cracks (WEC) führen, die bereits nach einem Bruchteil der berechneten Lagerlebensdauer auftreten können. In dieser Arbeit wird durch systematische Tests der Einfluss der Lagerbetriebsbedingungen (Radialkraft, Drehzahl und Öldurchfluss), sowie der Ausführung des Lagers (Lager- und Käfigtyp, Material, Führung und Toleranzklassen) auf die Entstehung des Wälzkörper- und Satzschlupfs untersucht. Die Wälzkörper vollrolliger Lager in der lastfreien Zone werden verzögert und sind in der Beschleunigungsphase einem vollständigen Rollenschlupf ausgesetzt. Für mit Käfig ausgestattete Zylinderrollenlager übertrifft der einteilige den zweiteiligen Käfig durch eine geringere Schlupfneigung, besonders unter begrenztem Öldurchfluss. Rollengeführte Käfige zwingen die Rollen dazu mit dem rotierenden Innenring zu interagieren, wodurch weniger Schlupf verursacht wird. Polyamid als Käfigwerkstoff bietet Gewichteinsparungen, wird aber bei hohen Lagertoleranzen nicht empfohlen, da es deformiert und somit einen höheren Schlupf bewirkt. Bei moderaten Lagertoleranzen tragen mehr Rollen zur Belastungsübertragung bei. Das kann zu höherem Rollenschlupf als bei hohen Toleranzen führen, da verringerte Traktionskräfte auf die Rollen wirken. Wird ein Lager jedoch durch eine enge Toleranzklasse (TC) vorgespannt, kann der Schlupf unter jeglichen Betriebsbedingungen verhindert werden. Der Einfluss von Schlupf auf die Bildung von WEC am Innen- und Außenring eines Zylinderrollenlagers wurde in insgesamt vier Dauerlaufversuchen mit einem zweiphasigen Belastungsschema untersucht. Während der Niedriglastphase wird das Lager bei erhöhtem Schlupf betrieben und danach einer hohen Lastphase ausgesetzt, während der Ermüdungsrissfortschritt von WEC auftreten kann. Es wurde festgestellt, dass Betriebsbedingungen mit hohem Schlupf weniger kritisch für die WEC-Bildung (an beiden Lagerringen) sind. Die sehr geringe Radialkraft, die in der Niedriglastphase aufgebracht wird, um einen hohen Schlupf zu ermöglichen, führt zu einer geringen Flächenpressung, die nicht WEC-kritisch ist. Ein weiterer Grund ist die längere Regenerationszeit zwischen zwei Überrollungen, die bei einem hohen Sollschlupf auftreten. Kritischer sind die dynamischen Kraftverhältnisse für die stehenden Lagerringe. Sie würden den Rollenschlupf unter der wechselnden Lastzonenbreite akkumulieren, was WEC-kritischer ist. Obwohl die vollrolligen Lager einen hohen Satzschlupf und 100%igen Rollenschlupf in der Lastzone erleiden, zeigten sie auch nach mehr als 3400 Teststunden, unter den für Käfiglager sehr kritischen Prüfbedingungen, keine Anzeichen eines WEC-Ausfalls.Unfavorable operating conditions and inadequate radial force cause slip to occur in radial cylindrical roller bearings. This can also lead to several failure mechanisms such as smearing, scuffing, spalling, and White Etching cracks (WEC) that can occur at a small percentage of the calculated bearing life. In this work, through systematic testing, the influence of the bearing operating conditions (radial force, speed, and lubricant flow rate) as well as the bearing’s design (bearing type, cage type, material, guidance as well as the clearance class) on the development of the roller- and the rolling set slip was studied. The rollers of the full complement bearing stall in the load-free zone, and they suffer from a 100% roller slip at the acceleration zone. For caged bearings, a single-part cage outperforms the two-part cages by having lower slip tendency under restricted oil flow rates. Cages that are roller-guided force the rollers to interact more with the rotating inner ring and thus suffer from an overall lower slip. For the cage material, Polyamide cages offer weight savings. However they are not recommended under elaborated clearance as they would deform and cause high slip. Under moderate clearance, more rollers contribute to the load transfer. This leads to higher roller slip than under higher clearance level due to the decrease in traction forces acting on each roller. However, preloading a bearing by using the TC clearance class while using a tight fitting for both rings my lead to the elimination of the slip under any operating conditions. The influence of slip on the formation of WEC on the inner and outer rings of a cylindrical roller bearing was studied by conducting a total of four endurance tests using a two-phase loading scheme. In the low-load phase, a slip-rich environment is introduced to the bearing during which lubricant smearing can take place. After that, a high load phase is introduced to the bearing during which, fatigue crack propagation of WEC is enabled. It was found that high-slip operating conditions are less critical for the WEC formation on both bearing rings. The very low radial force that must be used in the low load phase to allow such a high slip to occur would result in a low contact pressure that is not WEC-critical. Another reason is the longer regeneration time between two overrollings occurring at a high set slip. Dynamic force conditions are more critical for the stationary bearing rings. They would accumulate the roller slip under the changing load zone width which is more WEC-critical. Although suffering from high set slip and 100% roller slip in the load zone, full complement bearings didn’t show any sign of WEC failure even after testing them for more than 3400 hours under very critical testing conditions for caged bearings

The Federal Conference on Intelligent Processing Equipment

Research and development projects involving intelligent processing equipment within the following U.S. agencies are addressed: Department of Agriculture, Department of Commerce, Department of Energy, Department of Defense, Environmental Protection Agency, Federal Emergency Management Agency, NASA, National Institutes of Health, and the National Science Foundation