Reliability Of Mechanical Systems Research Articles

A Deep Learning-Based Remaining Useful Life Prediction Approach for Bearings

In industrial applications, nearly half the failures of motors are caused by the degradation of rolling element bearings (REBs). Therefore, accurately estimating the remaining useful life (RUL) for REBs are of crucial importance to ensure the reliability and safety of mechanical systems. To tackle this challenge, model-based approaches are often limited by the complexity of mathematical modeling. Conventional data-driven approaches, on the other hand, require massive efforts to extract the degradation features and construct health index. In this paper, a novel online data-driven framework is proposed to exploit the adoption of deep convolutional neural networks (CNN) in predicting the RUL of bearings. More concretely, the raw vibrations of training bearings are first processed using the Hilbert-Huang transform (HHT) and a novel nonlinear degradation indicator is constructed as the label for learning. The CNN is then employed to identify the hidden pattern between the extracted degradation indicator and the vibration of training bearings, which makes it possible to estimate the degradation of the test bearings automatically. Finally, testing bearings' RULs are predicted by using a $\epsilon$-support vector regression model. The superior performance of the proposed RUL estimation framework, compared with the state-of-the-art approaches, is demonstrated through the experimental results. The generality of the proposed CNN model is also validated by transferring to bearings undergoing different operating conditions.

Mechanical system reliability analysis using reliability matrix method

Mechanical systems, including building ones, consist of a huge number of elements. Thus, traditional methods of reliability block diagram and logical schemes, oriented to small-element systems, aren’t appropriate for reliability analysis. In this paper a fundamentally new method for reliability assessment of mechanical systems is considered. It’s based on the reliability matrix. The reliability matrix is the difference between the characteristic matrix and the connection matrix, which are formed from the structural scheme. Probability of failure or probability of success of the system is equal to determinant of the reliability matrix. The use of the matrix method proposed by the authors in conjunction with computer software has more perspective, it allows to work with complex mechanical systems, significantly reduces the time of analysis and decrease the risk of errors. This method of calculation is optimized for inclusion in Civil Engineering CAD software.

Superlubricity of 1,3-diketone based on autonomous viscosity control at various velocities

Abstract Superlubricity, especially achieved using oil-based materials, is of great significance for the reliability of mechanical systems. In this study, the superlubricity (μ ≈ 0.006) of steel surfaces using a synthetic 1,3-diketone lubricant EPBD-02/01 was investigated. The friction test shows that the superlubricity of EPBD-02/01 was induced by a tribochemical running-in process, through which the contact pressure was dramatically reduced. By comparing with a surface generated by the mechanical polishing, it was found that the surface-chemisorption of diketone plays an important role in the lubrication. Moreover, combining with the shear-thinning behavior of EPBD-02/01, it was supposed that the superlubricity of 1,3-diketone is based on autonomous viscosity control over a wide range of velocities in the thin film lubrication regime.

Measurement on critical shear stress of circular point contact utilizing Atomic Force Microscope

We propose Bowdon-Johnson-Kendall-Roberts model to measure the critical shear stress of circular point contact, and the critical shear stress map is constructed through the lateral force mode and force map mode of Atomic Force Microscope to research the interface property of nanomaterials. The mean critical shear stresses are measured as 0.24 MPa for monolayer MoS2 and 0.69 MPa for graphene. MoS2 nanosheet and graphene are of the lower critical shear stress and friction coefficient than those of the bulk materials, which are good agreement with the regularities in nanotribology. The critical shear stress can be used to not only quantitatively characterize the frictional properties, but also analyze the friction at different loading stages. The critical shear stress map would play an important role in sliding contact of nanomaterials for the drive part design and nanotribological reliability of nanoelectronic mechanical system.

Reliability Assessment of Safety Systems with Asymmetrical Redundancy Architecture

Application of an M-out-of-N redundancy architecture is a well-known measure for improving the reliability of safety systems. Most scientific papers addressing the reliability assessment of such systems consider a conventional homogeneous M-out-of-N redundancy architecture that is performed for identical channels. However, often in practice, an M-out-of-N redundancy architecture does not have identical channels. Reliability assessment of such heterogeneous systems (electrical/electronic and mechanical) with nonidentical channels and a combination of constant and nonconstant failure rates is considered in this paper. Such type of M-out-of-N redundancy architecture is introduced in this research as “asymmetrical redundancy”. It can be used for enhancing the reliability of old mechanical systems or for reducing mutual influence of channels and increase of diagnostic coverage. This paper also presents a new “window-based Markov method” for PFD[Formula: see text] (average probability of failure on demand) and PFH (average frequency of dangerous failures) calculation for systems with an asymmetrical redundancy architecture and compares the results with those obtained by using the steady-state semi-Markov method and Monte-Carlo simulation. The applicability of the developed method is demonstrated in a simple case study.

Evaluation of Wear on Macro-Surface Textures Generated by ns Fiber Laser

The demand for improved performance and long term reliability of mechanical systems dictate the use of advanced materials and surface engineering techniques. A small change in the surface topography can lead to substantial improvements in the tribological behaviour of the contact surfaces. One way of altering the surface topography is by surface texturing by introducing dimples or channels on the surfaces. Surface texturing is already a successful technique which finds a wide area of applications ranging from heavy industries to small scale devices. This paper reports the effect of macro texture shapes generated using a nanosecond fiber laser on wear of high carbon chromium steel used in large size bearings having rolling contacts. Circular and square shaped dimples were generated on the surface to assess the effect of sliding velocities on friction coefficient. Graphite was used as solid lubricant to minimise the effect of wear on textured surfaces. The laser parameters such as power, scan speed and passes were optimised to obtain macro circular and square dimples which was characterised using a laser confocal microscope. The friction coefficients of the circular and square dimples were observed to lie in the same range due to minimum wear on the surface. On the contrary, at medium and higher sliding velocities, square dimples exhibited lower friction coefficient values compared to circular dimples. The morphology of textured specimen was characterised using Scanning Electron Microscope.

Reliability Estimation of Aero-engine Based on Mixed Weibull Distribution Model

Aero-engine is a complex mechanical electronic system, based on analysis of reliability of mechanical electronic system, Weibull distribution model has an irreplaceable role. Till now, only two-parameter Weibull distribution model and three-parameter Weibull distribution are widely used. Due to diversity of engine failure modes, there is a big error with single Weibull distribution model. By contrast, a variety of engine failure modes can be taken into account with mixed Weibull distribution model, so it is a good statistical analysis model. Except the concept of dynamic weight coefficient, in order to make reliability estimation result more accurately, three-parameter correlation coefficient optimization method is applied to enhance Weibull distribution model, thus precision of mixed distribution reliability model is improved greatly. All of these are advantageous to popularize Weibull distribution model in engineering applications.

Gamma Degradation Process and Accelerated Model Combined Reliability Analysis Method for Rubber O-Rings

The sealing performance of rubber O-rings plays an irreplaceable role in ensuring the high reliability and safety of mechanical systems. However, traditional statistical analysis may not consider the aging process of rubber O-rings at different temperatures and the time-varying characteristics of rubber material parameters. In view of these problems, an improved reliability analysis method based on the accelerated aging test of rubber O-rings is proposed in this paper. This method is featured by a combination with the traditional accelerated model and the Gamma stochastic process. This paper first adopts the stationary Gamma process to describe the degradation of compression set which is the performance degradation indicator of rubber O-rings. Then, the reliability model is derived from the Gamma degradation model. Next, the Arrhenius model is used to represent the shape parameter of Gamma degradation model and the approach of maximum likelihood estimation is adopted to solve the parameters. Finally, the rubber O-rings of gas steering engine were selected and a series of accelerated aging tests were conducted to obtain the reliability and the storage lifetime of rubber O-rings at different temperature stresses through our improved method. Besides, the comparison with the traditional statistical method is also conducted to prove the advantage of this method.

A multiscale noise tuning stochastic resonance for fault diagnosis in rolling element bearings

Condition monitoring of rotating machinery is important to extend the mechanical system's reliability and operational life. However, in many cases, useful information is often overwhelmed by strong background noise and the defect frequency is difficult to be extracted. Stochastic resonance (SR) is used as a noise-assisted tool to amplify weak signals in nonlinear systems, which can detect weak signals of interest submerged in the noise. The multiscale noise tuning SR (MSTSR), which is originally based on discrete wavelet transform (DWT), has been applied to identify the fault characteristics and has also increased the signal-to-noise ratio (SNR) improvement of SR. Therefore, a novel tri-stable SR method with multiscale noise tuning (MST) is proposed to extract fault signatures for fault diagnosis of rotating machinery. The wavelet packets transform (WPT) based MST can obtain better denoising effect and higher SNR of resonance output compared with the traditional SR method. Thus the proposed method is well-suited for enhancement of rotating machine fault identification, whose effectiveness has been verified by means of practical vibration signals carrying fault information from bearings. Finally, it can be concluded that the proposed method has practical value in engineering.

Macroscopic Superlow Friction of Steel and Diamond-Like Carbon Lubricated with a Formanisotropic 1,3-Diketone.

Energy dissipation due to friction and wear is reducing the energy efficiency and reliability of mechanical systems. Thus, great efforts are being made to minimize friction for technical applications. In our present work, we investigate the tribological behavior of stainless steel 100Cr6 with a-C:H and a-C:H:Si coating lubricated with a surface-active formanisotropic 1,3-diketone. The results show that superlow friction can be achieved on the macroscale using a steel 100Cr6 self pairing (COF ∼ 0.005) and with 100Cr6 in combination with a-C:H coating (COF ∼ 0.008). Furthermore, the replacement of steel with a-C:H coating leads to a considerable decrease of wear. The reduced COF arises from the chemical interaction of the lubricant with the surface and nascent iron ions. It was found that interfacial parameters correlate with tribological results. In addition, the alignment of the formanisotropic molecules in the tribological contact at thin-film lubrication leads to an anisotropic viscosity with a minimum shear resistance in sliding direction. Atomistic simulation of tribochemical interactions was conducted to derive a friction model based on the thin-film lubrication theory. This investigation indicates the potential to substantially reduce friction and wear using this fluid in real technical applications.

On the use of temperature for online condition monitoring of geared systems – A review

Gear unit condition monitoring is a key factor for mechanical system reliability management. When they are subjected to failure, gears and bearings may generate excessive vibration, debris and heat. Vibratory, acoustic or debris analyses are proven approaches to perform condition monitoring. An alternative to those methods is to use temperature as a condition indicator to detect gearbox failure. The review focuses on condition monitoring studies which use this thermal approach. According to the failure type and the measurement method, it exists a distinction whether it is contact (e.g. thermocouple) or non-contact temperature sensor (e.g. thermography). Capabilities and limitations of this approach are discussed. It is shown that the use of temperature for condition monitoring has a clear potential as an alternative to vibratory or acoustic health monitoring.

Investigation on surface structuring generated by electrochemical micromachining

Surface geometrical features and their functionality depend on the manufacturing process which is employed for fabrication of surface structures. Maskless electrochemical micromachining (EMM) is used to generate various surface structures for diminishing and controlling friction and wear to increase the lifetime, reliability, and efficiency of mechanical systems. This paper presents a method for the generation of structured surfaces on stainless steel (SS-304) surfaces by using maskless EMM. The micropatterned tool is composed of 800 µm diameter circular holes in a 5 × 5 matrix form. The indigenously developed EMM set up consists of an EMM cell, electrical power supply system, and a controlled vertical cross-flow electrolyte circulation arrangement to control the influence of process parameters during the generation of the micro features of structured surfaces. The single structured cathode tool is used for the mass production of structured surfaces with a short fabrication time in the industrial context by avoiding the use of an individual masking process for each workpiece. The process has been characterized in terms of the effects of predominant process parameters such as machining voltage, electrolyte concentration, duty ratio, pulsed frequency, and machining time on the machined surface characteristics such as current efficiency, machining accuracy, and depth of the circular pattern on the stainless steel surfaces. A mathematical model is also developed to determine the theoretical depth of the dimple pattern and correlate the theoretical depths with actual depths as obtained by experimentation. Moreover, an effort has been made to study the structuring characteristics on the basis of micrographs obtained during the EMM.

A nonlinear contact pressure distribution model for wear calculation of planar revolute joint with clearance

As various errors result from manufacture and assembly processes or wear effect, clearance joint widely exists in mechanical system as a base component. The coupling analysis of tribology and dynamics of clearance joint is important to the reliability of mechanical system. A nonlinear contact pressure distribution mode (NLCP) is proposed to combine dynamics analysis with wear calculation together in this paper. The discrete thought of Winkler model is adopted to deal with contact problem with a high conformal rate. The contact relationship in a local microcontact area can be regarded as the contact between cylinder and plane. And the local contact pressure is acquired based on Hertz contact theory. The NLCP model has not only described the nonlinear relationship between contact pressure and penetration depth, but also avoided the complexity in contact pressure computation. The performance of NLCP model is demonstrated in comparison with asymmetric Winkler model, revealing that NLCP model has enhanced the calculation accuracy with a good efficiency. A comprehensive experimental study on the wear calculation of a slider–crank mechanism with clearance joint is presented and discussed to provide an experimental verification for NLCP model. The paper’s work has solved the contact problem with a high conformal rate and has described the nonlinear relationship between contact pressure and penetration depth. It has great value to the wear analysis of clearance joint.

Analysis and Application of Mechanical System Reliability Model Based on Copula Function

Abstract There is complicated correlations in mechanical system. By using the advantages of copula function to solve the related issues, this paper proposes the mechanical system reliability model based on copula function. And makes a detailed research for the serial and parallel mechanical system model and gets their reliability function respectively. Finally, the application research is carried out for serial mechanical system reliability model to prove its validity by example. Using Copula theory to make mechanical system reliability modeling and its expectation, studying the distribution of the random variables (marginal distribution) of the mechanical product’ life and associated structure of variables separately, can reduce the difficulty of multivariate probabilistic modeling and analysis to make the modeling and analysis process more clearly.

Bayesian kriging modeling for spatiotemporal prediction in squeeze casting

The deterioration of a shot sleeve in squeeze casting due to thermo-mechanical fatigue often results in lowering the reliability and availability of the squeeze casting machine, thus reducing its productivity, meanwhile increasing the life-cycle maintenance cost. This paper presents an efficient Bayesian kriging meta-modeling method for spatiotemporal prediction under data uncertainty and non-normality, with the target applications for controlling the deformation, optimizing machine design, and predicting component fatigue cracking thus improving the reliability and availability of mechanical system. Spatiotemporal kriging model is established to substitute the complicated computer model by using numerically simulated data. Bayesian probabilistic approach is then developed to quantitatively evaluate the validity and predictive capacity of kriging meta-model, considering data uncertainty. The Anderson-Darling goodness-of-fit test is employed to perform the normality hypothesis test of difference values of validation data. Box–Cox transformation method is utilized to convert the non-normality data with the purpose of facilitating the overall validation assessment of meta-models with higher accuracy. Bayesian confidence measure is presented to quantify the confidence on the predictive capacity of the kriging meta-models, given the transformed data. A procedure is proposed to implement the proposed probabilistic methodology for meta-modeling and model validation with non-normality response series. The impact of data normality assumption and decision threshold parameter in quantitative model assessment is also investigated by using Bayesian inference approach. The effectiveness of the proposed methodology and procedure is demonstrated with the spatiotemporal temperature prediction in squeeze casting.

Measurements of Flow Rate and Force Coefficients in a Short-Length Annular Seal Supplied with a Liquid/Gas Mixture (Stationary Journal)

ABSTRACTDeep sea compression systems must work under strenuous conditions with either gas in liquid or liquid in gas mixtures, mostly inhomogeneous. Off-design operation affects the mechanical system's overall efficiency and reliability, with penalties in leakage and rotordynamic performance of secondary flow components, namely, seals. This article introduces a test rig to characterize the leakage and dynamic force coefficients of a short-length annular seal (L/D = 0.36, clearance = 0.127 mm) operating under various flow regimes ranging from pure gas, to bubbly (liquid in gas), to foamy (gas in liquid), to pure liquid. The test rig includes of rotating journal and a softy supported cartridge that make a clearance annular seal that is supplied with a liquid/gas mixture. Flowmeters record the fluid's passage, and with manual control of the streams, the mixture has a known liquid (or gas) volume fraction at the seal inlet plane. Two orthogonally mounted electromagnetic shakers excite the cartridge with periodic (single-frequency) forces spanning a wide frequency range. Eddy current sensors and accelerometers record the seal cartridge motions and a frequency domain parameter identification method delivers the seal dynamic force coefficients.For tests with a pressure supply/pressure discharge ratio = 3.0 and 3.5 and a nonrotating journal, the article reports the flow rate for an ISO VG10 oil in air mixture with liquid volume fraction (LVF) at the inlet plane increasing from pure gas to pure liquid. Wet seal stiffness and mass and damping force coefficients follow for a seal operating with a pressure supply/pressure discharge ratio = 2.0 and operating with air (only) and also with an oil-in-air mixture with inlet LVF = 2% and 4%. The experimental results, the first reported, reveal that a small amount of liquid increases the damping coefficients of the wet seal 10-fold (or more). Predictions from a computational bulk flow model also demonstrate that the seal damping coefficient varies greatly with small contents of liquid in the oil/gas mixture, although agreement with the experimental force coefficients is not compelling due to the likely inhomogeneity of the mixture flowing though the seal.

An adaptive demodulation approach for bearing fault detection based on adaptive wavelet filtering and spectral subtraction

Fault diagnosis of rolling element bearings is important for improving mechanical system reliability and performance. Vibration signals contain a wealth of complex information useful for state monitoring and fault diagnosis. However, any fault-related impulses in the original signal are often severely tainted by various noises and the interfering vibrations caused by other machine elements.Narrow-band amplitude demodulation has been an effective technique to detect bearing faults by identifying bearing fault characteristic frequencies. To achieve this, the key step is to remove the corrupting noise and interference, and to enhance the weak signatures of the bearing fault. In this paper, a new method based on adaptive wavelet filtering and spectral subtraction is proposed for fault diagnosis in bearings. First, to eliminate the frequency associated with interfering vibrations, the vibration signal is bandpass filtered with a Morlet wavelet filter whose parameters (i.e. center frequency and bandwidth) are selected in separate steps. An alternative and efficient method of determining the center frequency is proposed that utilizes the statistical information contained in the production functions (PFs). The bandwidth parameter is optimized using a local ‘greedy’ scheme along with Shannon wavelet entropy criterion. Then, to further reduce the residual in-band noise in the filtered signal, a spectral subtraction procedure is elaborated after wavelet filtering. Instead of resorting to a reference signal as in the majority of papers in the literature, the new method estimates the power spectral density of the in-band noise from the associated PF. The effectiveness of the proposed method is validated using simulated data, test rig data, and vibration data recorded from the transmission system of a helicopter. The experimental results and comparisons with other methods indicate that the proposed method is an effective approach to detecting the fault-related impulses hidden in vibration signals and performs well for bearing fault diagnosis.

Improvement of dimensional uniformity on micro-dimple arrays generated by electrochemical micro-machining with an auxiliary electrode

Micro-dimples play an important role in improving the performance and reliability of mechanical systems. Through-mask electrochemical micro-machining (TMEMM) is a feasible alternative for generating micro-dimples. However, in TMEMM, the electrical field intensity at the edge is higher than that in other areas, which leads to poor dimensional uniformity of the micro-dimple arrays. In this paper, an auxiliary electrode with a positive potential was proposed to enhance the uniformity of distribution of the electrical field on the workpiece. Simulation results indicate that the auxiliary electrode with an appropriate potential is useful for improving the uniformity of the electrical field distribution. Experiments verify that with the potential of 10 V on the auxiliary electrode, the dimensional uniformity of the micro-dimple arrays was improved significantly, and the normalized dimensions of the arrays increased to 0.95. This approach is therefore effective in obtaining micro-dimple arrays with uniform dimensions.

Pulsed electrochemical micromachining for generating micro-dimple arrays on a cylindrical surface with a flexible mask

Abstract Micro-dimple arrays play an important role in improving the performance and reliability of mechanical systems, and micro-dimples on the surfaces of piston rings and sliding bearings may reduce friction. Although many methods can be employed to create micro-dimples on cylindrical surfaces, it is still a challenge to generate micro-dimple arrays on cylindrical surfaces with high efficiency and low cost. In this paper, a patterned polydimethylsiloxane (PDMS) mask with good flexibility is introduced as a mask in through-mask electrochemical micromachining (TMEMM) for generating micro-dimple arrays on a cylindrical surface, in which thousands of micro-dimples can be fabricated in tens of seconds. In addition, the reusability of the PDMS mask is experimentally verified. To enhance removal of the product, the use of a pulsed current is introduced into TMEMM of micro-dimples. The experimental results show that the pulse duty cycle plays a significant role in enhancing the removal of product and improving the uniformity of the micro-dimple arrays. And the effect was weakened with increasing pulse duty cycle. Compared with duty cycles of 40, 60, and 80%, the highest current efficiency with a duty cycle of 20% is obtained at a frequency of 10 kHz. Finally, micro-dimple arrays with a diameter of approximately 110.6 μm and a depth of 11 μm are successfully generated on the cylindrical surface.

Fuzzy Dynamic Reliability Models of Parallel Mechanical Systems Considering Strength Degradation Path Dependence and Failure Dependence

Fuzzy dynamic reliability models of mechanical parallel systems with respect to stress parameters and strength parameters are developed in this paper. Strength degradation path dependence (SDPD) and failure dependence of components in the system are two main problems to be addressed in developing fuzzy dynamic reliability of mechanical systems, which are taken into account in the proposed reliability models. In addition, the SDPD sensitivity function and the failure dependence sensitivity function are defined to analyze the influences of the fuzzy characteristics of stress on the effects of SDPD and failure dependence of mechanical components on dynamic reliability. The bolted joint systems for connection between launch vehicle and satellite are chosen as illustrative examples to demonstrate the proposed model. Moreover, Monte Carlo simulations are carried out to validate the effectiveness of the proposed models. The results show that SDPD and failure dependence of components have significant impacts on fuzzy dynamic reliability of mechanical systems. Besides, the influences of the fuzzy characteristics of stress on SDPD sensitivity and that on failure dependence sensitivity are different.