Investigation of dynamics and power needs for container unloading from ship process

The operational problem of container unloading from the ship is analyzed in this paper. Dynamic “crane-cargo-ship” system was investigated, and a mathematical model was created. In the model, the gap between the container and the ship’s cargo hold, the mass of the cargo, the container’s center of the mass, and the frictional forces that may occur during lifting from the cargo hold were estimated. Numerical analysis of the system was performed. Results of numerical analysis were compared with experimental measurements of containers unloading process in port. Requirement of lifting power was modelled depending on mass of cargo. Additional power needs in case of contact forces between container and wall of the ship’s cargo hold were calculated. Rational lifting conditions could be deduced using a created mathematical model and the reliability of the container and cargo during lifting could be deduced.

A simulation strategy to determine the mechanical behaviour of cork-rubber composite pads for vibration isolation

The present work aimed to determine the performance of new cork-rubber composites, applying a modelling-based approach. The static and dynamic behaviour under compression of new composite isolation pads was determined using mathematical techniques. Linear regression was used to estimate apparent compression modulus and dynamic stiffness coefficient of compounds samples based on the effect of fillers, cork and other ingredients. Using the results obtained by regression models, finite element analysis (FEA) was applied to determine the behaviour of the same cork-rubber material but considering samples with different dimensions. The majority of the regression models presented R2 values above 90%. Also, a good agreement was found between the results obtained by the presented approach and previous experimental tests. Based on the developed methodology, the compression behaviour of new cork-rubber compounds can be accessed, improving product development stages.

Diagnostics of the drive shaft bearing based on vibrations in the high-frequency range as a part of the vehicle's self-diagnostic system

Currently, one of the trends in the automotive industry is to make vehicles as autonomous as possible. In particular, this concerns the implementation of complex and innovative selfdiagnostic systems for cars. This paper proposes a new diagnostic algorithm that evaluates the performance of the drive shaft bearings of a road vehicle during use. The diagnostic parameter was selected based on vibration measurements and machine learning analysis results. The analyses included the use of more than a dozen time domain features of vibration signal in different frequency ranges. Upper limit values and down limit values of the diagnostic parameter were determined, based on which the vehicle user will receive information about impending wear and total bearing damage. Additionally, statistical verification of the developed model and validation of the results were performed.

Remaining useful life prediction of cylinder liner based on nonlinear degradation model

In order to effectively monitor the wear and predict the life of cylinder liner, a nonlinear degradation model with multi-source uncertainty based on Wiener process is established to evaluate the remaining useful life (RUL) of cylinder liner wear. Due to complex service performance of cylinder liner, the uncertainty of operational environment and working conditions of cylinder liner wear are considered into the model by a random function. The probability density function (PDF) formula of RUL is derived, and the maximum likelihood estimation method is adopted to estimate the unknown parameters of PDF. Considering the evaluated parameters as the initial values, the model parameters are updated adaptively, and an adaptive PDF is obtained. Furthermore, the proposed model is compared with two classical degradation models. The results show that the proposed model has a good performance for predicting the life, and the error is within 5%. The method can provide a reference for condition monitoring of cylinder liner wear.

Short and long forecast to implement predictive maintenance in a pulp industry

Predictive maintenance is very important for effective prevention of failures in an industry. The present paper describes a case study where a wood chip pump system was analyzed, and a predictive model was proposed. An Ishikawa diagram and FMECA are used to identify possible causes for system failure. The Chip Wood has several sensors installed to monitor the working conditions and system state. The authors propose a variation of exponential smoothing technique for short time forecasting and an artificial neural network for long time forecasting. The algorithms were integrated into a dashboard for online condition monitoring, where the users are alerted when a variable is determined or predicted to get out of the expected range. Experimental results show prediction errors in general less than 10 %. The proposed technique may be of help in monitoring and maintenance of the asset, aiming at greater availability.

Hybrid methodology using balancing optimization and vibration analysis to suppress vibrations in a double crank-rocker engine

This study aims to present mathematical modelling to evaluate and analyze double crankrocker engine performance. The study suggests the use of two methods to reduce system vibration through balancing optimization and vibrational analysis. The combination of both methods acts as a verification method; besides it can be used as a tool for further system design enhancement and condition monitoring. The derived mathematical model is then used for balancing optimization to identify system shaking forces and moments, while variable speed is considered as an added parameter to evolve the optimization process. This factor shows better enhancement in reducing system shaking forces and moments compared to constant speed balancing method. Next, the system characteristics were concluded in terms of mode shapes and natural frequencies using modal and frequency response analysis, which give clear clue for secure system operational ground. Finally, the reduction in system vibrations was translated into engine’s centre of mass velocity, which evaluates balancing process effectiveness and indicate if further enhancement should be conducted.

Research on high-pressure hose with repairing fitting and influence on energy parameter of the hydraulic drive

Reliability and maintenance analysis of transport machines hydraulic drives, basically focused to power units: pumps, cylinders etc., without taking in to account junction elements. Therefore, this paper proposes a research analysis on high-pressure hoses and junctions during technical maintenance. Comparative analysis of fluid behavior and energy efficiency inside non-repaired and repaired high-pressure hoses is presented in this research. Theoretical and experimental research results for hydraulic processes inside high-pressure hose is based on the numerical simulations using Navier–Stokes equations and experimental measurement of fluid flow pressure inside high-pressure hoses. Research of fluid flow dynamics in the hydraulic system was made with main assumptions: system flow rate in the range from 5 to 100 l/min, diameter of the hoses and repairing fitting are 3/8". The pressure drops, power losses, flow coefficients at non-repaired and after maintenance hose was obtained as a result. Simulation results were verified by running physical experiments to measure the pressure losses.

Importance measure-based maintenance strategy considering maintenance costs

Maintenance is an important way to ensure the best performance of repairable systems. This paper considers how to reduce system maintenance cost while ensuring consistent system performance. Due to budget constraints, preventive maintenance (PM) can be done on only some of the system components. Also, different selections of components to be maintained can have markedly different effects on system performance. On the basis of the above issues, this paper proposes an importance-based maintenance priority (IBMP) model to guide the selection of PM components. Then the model is extended to find the degree of correlation between two components to be maintained and a joint importance-based maintenance priority (JIBMP) model to guide the selection of opportunistic maintenance (OM) components is proposed. Also, optimization strategies under various conditions are proposed. Finally, a case of 2H2E architecture is used to demonstrate the proposed method. The results show that generators in the 2E layout have the highest maintenance priority, which further explains the difference in the importance of each component in PM.

Lifetime performance evaluation model based on quick response thinking

In practice, lifetime performance index CL has been a method commonly applied to the evaluation of quality performance. L is the upper or lower limit of the specification. The product lifetime distribution is mostly abnormal distribution. This study explored that the lifetime of commodities comes from exponential distribution. Complete data collection is the primary goal of analysis. However, the censoring type is one of the most commonly used methods due to considerations of manpower and material cost or the timeliness of product launch. This study adopted Type-II right censoring to find out the uniformly minimum variance unbiased (UMVU) estimator of the lifetime performance index CL and its probability density function. Afterward this study obtained the 100×(1-α)% confidence interval of the lifetime performance index CL as well as created the uniformly most powerful (UMP) test and the power of the test for the product lifetime performance index. Last, this study came up with a numerical example to demonstrate the suggested method as well as the application of the model.