Key Engineering Materials Vol. 588

Abstract: This article presents a non-linear model of deep groove ball bearing and results of simulation. Vibrations of this bearing are studied for a wide range of clearance. An evolution from periodic to chaotic vibrations is visible due to increase of clearance. A number of phenomena associated with non-linear dynamics are observed, for instance: bistability, chaotic vibrations, windows of periodical vibrations, jump of amplitude, period-doubling cascade leading to chaos, bifurcation directly leading to chaos, and self-similarity of a Poincaré section. Moreover, amplitudes of vibrations are presented as functions of clearance. This provides an opportunity to select failure modes. Unfortunately, relations clearance amplitude and amplitude - clearance are ambiguous.

Abstract: The optimization of the construction of gears leading to the minimization of dynamic effects and to meet all basic criteria is in many cases only possible by applying numerical methods. The models allow determining the influence of a range of factors on the dynamic phenomena. Proper experimental tests are often not possible because the number of options of influencing factor sets is very large. Using simulation models allows limiting the volume of experimental studies to the necessary minimum, and hence is beneficial from the economic standpoint. The paper describes numerical and laboratory researches on the influence of selected construction, technological and operational factors on the dynamic effects and vibroactivity in gears. Numerical analyses were performed using a custom-developed dynamic model of a test stand with the gears operating in the circulating power system. The models details were presented at the International Congress on Technical Diagnostics in 2008. The idea behind this article is to present selected results of simulation calculations and laboratory tests to determine the possibility of minimizing the noise and vibration of gears. Selected results of the calculations were also compared with the results of laboratory tests to demonstrate the high compatibility of the two test methods.

Abstract: Condition monitoring of machines (systems) is the science and technology for the assessment of condition of running machine by means of observation of machine phenomenal field, where some symptom of condition can be captured and measured (see for example [Collacott 77]). This means that we are trying to determine the fault space of the machine, its dimensionality and fault advancement, by some observed symptoms of condition, creating in this way our observation space. The fault space of a system (machine) can be assumed by some prior knowledge taken from the experience with the other running machines, and the same concerns with symptom observation space with some redundancy.

Abstract: The modern commercial vehicle with a weight of more than 3,5 [Mg] is a complex design solution, which contains many of mechatronic systems. The standard equipment are the ability of the driver assistance systems such as ABS (Anti-Lock Braking System), ESP (Electronic Stability Program), ASR (Acceleration Slip Regulation). The technical condition of the modern car's suspension determines the value of the indicators of road safety. An essential element of the suspension system, whose function is to change the mechanical vibration energy into thermal energy, is the shock absorber. Incorrect functioning of shock absorbers affects the quality of the operation of these systems improve safety. In the case of gradually wears of shock absorber even an experienced driver is able to notice this phenomenon. For this reason it becomes necessary the need for regular technical condition monitoring of dampers. Diagnostic dampers on buses and trucks are limited to the organoleptic examination and propose based on intermediate symptoms such as accelerated tire wear. The paper describes the method for estimating the suspension damping characteristics of commercial vehicle in operating conditions.

Abstract: Aircraft and avionics, offshore, marine and other complex engineering systems often operate in harsh environmental and operational conditions and must meet stringent requirements of cost, reliability, safety and maintainability. To achieve these aims modern design management and a vast array of computer aided techniques are applied during the design and testing stages. Maintainability requirements, long ignored by designers and manufacturers, assumed great importance and forced rethinking of the way the design of new systems and their maintenance should be carried out. One of the technologies to deal with this problem is Condition Based Maintenance (CBM) which is used widely in various industries to reduce risk and improve system availability. CBM is based on detection and diagnosis of failures, assessing effects of such failures on life of the system health and prescribing maintenance actions to extend system life. However, the experience with CBM shows that high expectation of reduced costs, improve maintainability etc. are often not met, and the major reasons for it are problems with risk identification (what failures can be expected) and detection (what sensors to select). The paper reviews these problems and other barriers to effectiveness of CBM and presents model-based approach to risk identification which can lead to improved CBM.

Abstract: In order to reduce the risk of failures, the optimal design selection from the viewpoint of machine reliability must be conducted. Therefore, one should analyze thoroughly the dynamics of the rotor-bearing-casing system in the whole operating range of the machine. The rotating system presented in the paper is supported in non-conventional bearings. The actual study consists in the investigation of new coating materials in the bearing design and the improvement in rotating system dynamics to increase the total efficiency, maintain the cleanness of the working medium and ensure operation of bearings in wide temperature ranges. Despite many advantages, air-foil bearings meet problems of friction and wear in critical moments of their operation, furthermore their complete theoretical model is difficult to establish. Different modeling theories of such bearing dynamic characteristics are shortly described. The current tendency in numerical and experimental methods for diagnostics of rotor support systems of low power rotating machinery is outlined.

Abstract: Over the last few decades a number of different techniques have been developed for impact damage detection in composite structures. The most frequently used methods in Non-Destructive Testing (NDT) are: ultrasonic testing, acoustics emission, X-ray and visual inspection. These methods are quite effective but often require expensive equipment, a large number of transducers or highly qualified staff. Additionally, these techniques are used locally. Therefore monitoring of large structures in many cases is very difficult or even impossible. Recent years have seen many new developments mostly free from these limitations. This paper investigates the triple correlation technique for impact damage detection in composite structures. The method correlates fundamental and higher harmonics of signal vibration response

Abstract: This paper discusses the main issues of Uncertainty Analysis (UA) in general and also argues and illustrates its particular relevance to structural dynamics. Brief descriptions are given of the most prevalent of the many frameworks for uncertainty representation. The three main uncertainty-related problems of relevance to structural dynamics are then discussed, namely quantification, fusion and propagation. In order to illustrate the application of ideas of UA in a realistic scenario, there then follows a case study conducted on an aerospace structure, namely the wing of a Gnat trainer aircraft. The case study considers evidence-based classifiers as an alternative to probabilistic classifiers for the problem of damage location within the context of Structural Health Monitoring. Dempster-Shafer theory is employed to construct neural network classifiers with the potential to admit ignorance, rather than misclassify.

Abstract: Bearing defect is statistically the most frequent cause of an induction motor fault. The research described in the paper utilized the phenomenon of the current change in the induction motor with bearing defect. Methods based on the analysis of the supplying current are particularly useful when it is impossible to install diagnostic devices directly on the motor. The presented method of rolling-element bearing diagnostics used indirect transformation, namely Clark transformation. It determines the vector of the spatial stator current based on instantaneous current measurements of the induction motor supply phases current. The analysis of the processed measurement data used multilayered, one-directional neural networks, which are particularly attractive due to their nonlinear structure and ability to learn. During the research 40 bearings: undamaged, with damages of three types and various degrees of fault extent, were used. The conducted research proves the efficiency of neural networks for detection and recognition of faults in induction motor bearings. In case of tests of the unknown state bearings, an efficiency approach to failure detection equaled 77%.

Abstract: Gears faults are one of the most common issues in rotating machinery. If not detected on time, they may result in severe dysfunction of the kinematic chain or even in catastrophic breakdown of the whole mechanism. Vibration based methods dedicated to gears monitoring are widely studied and applied techniques, that in majority rely on comparison of some spectral features. In this paper, however, the method based on fractal theory and wavelet decomposition is studied for possible application to gears diagnostics. The discussed technique may serve as a tool for signal contraction and/or signals comparison according to frequency content. Presented results are based on experimental data recorded from gradually deteriorated gearbox and gear with mechanically introduced local fault.