Search results

The purpose of this paper is to study the fault diagnosis of internal combustion (IC) engine gearbox using vibration signals with signal processing and machine learning (ML) techniques.

Vibration signals from the gearbox are acquired for healthy and induced faulty conditions of the gear. In this study, 50% tooth fault and 100% tooth fault are chosen as gear faults in the driver gear. The acquired signals are processed and analyzed using signal processing and ML techniques.

The obtained results show that variation in the amplitude of the crankshaft rotational frequency (CRF) and gear mesh frequency (GMF) for different conditions of the gearbox with various load conditions. ML techniques were also employed in developing the fault diagnosis system using statistical features. J48 decision tree provides better classification accuracy about 85.1852% in identifying gearbox conditions.

The proposed approach can be used effectively for fault diagnosis of IC engine gearbox. Spectrum and continuous wavelet transform (CWT) provide better information about gear fault conditions using time–frequency characteristics.

In this paper, experiments are conducted on real-time running condition of IC engine gearbox while considering combustion. Eddy current dynamometer is attached to output shaft of the engine for applying load. Spectrum, cepstrum, short-time Fourier transform (STFT) and wavelet analysis are performed. Spectrum, cepstrum and CWT provide better information about gear fault conditions using time–frequency characteristics. ML techniques were used in analyzing classification accuracy of the experimental data to detect the gearbox conditions using various classifiers. Hence, these techniques can be used for detection of faults in the IC engine gearbox and other reciprocating/rotating machineries.

The purpose of this paper is to report a study in which the feasibility of conducting probabilistic finite element analysis (FEA) for crane hook design has been explored.

This paper presents the results of probabilistic analysis, where in the input random variables are varied and corresponding variations in the output parameters were observed. In this study, material properties and load have been considered as random input variables and the maximum stress, maximum deflection variations were considered as output random variables.

The probability of occurrence of output variation and the sensitivity of output variables on the input variables are the important results generated from this analysis. By performing this probabilistic analysis, the random selection of factor of safety could be avoided.

The implementation study has been carried out for a single product.

The usage of the approach will indicate the importance of probabilistic analysis in product design and development process. This process will enable the organization to compete in the global market.

A case study has been reported to indicate the feasibility of performing probabilistic FEA for crane hook design. Hence, the contributions are original.

The purpose of this paper is to investigate the void coalescence and corrosion behaviour of titanium Grade 4 sheets during single point incremental forming (SPIF) process with various spindle rotational speeds. The development of corrosion pits in 3.5 (%) NaCl solution has also been studied during SPIF process.

In this current research work, the void coalescence analysis and corrosion behaviour of titanium Grade 4 specimens were studied. A potentio-dynamic polarization (PDP) study was conducted to investigate the corrosion behaviour of titanium Grade 4 processed samples with various spindle speeds in 3.5 (%) NaCl solution. The scanning electron microscope and transmission electron microscope analysis was carried out to study the fracture behaviour and corrosion morphology of processed samples.

The titanium Grade 4 sheets obtained better formability and corrosion resistance by increasing the CNC spindle rotational speeds. In fact that, the significant plastic deformation affects the corrosion rate with various spindle speeds were recorded.

The spindle rotational speeds and vertical step depths increases then the titanium Grade 4 sheets showed better formability, void coalescence and corrosion behaviour as the same is evidenced in forming limit diagram and PDP curves.

The purpose of this paper is to investigate the strain distribution, stress-based fracture limit and corrosion behaviour of titanium Grade 2 sheets during single point incremental forming (SPIF) process, with various computerized numerical control (CNC) spindle rotational speeds and step depths. The development of corrosion pits in 3.5 (%) NaCl solution has also been studied during the SPIF process.

A potentiodynamic polarization (PDP) study was performed to investigate the corrosion behaviour of titanium Grade 2 deformed samples, with various spindle rotational speeds in 3.5 (%) NaCl solution. The scanning electron microscope (SEM) and transmission electron microscope (TEM) analysis was carried out to study the fracture behaviour, dislocation densities and corrosion morphology of deformed samples.

The titanium Grade 2 sheets exhibited better strain distribution, fracture limit and corrosion resistance by increasing the CNC spindle rotational speeds, tool diameters and vertical step depths (VSD). It was recorded that varying the spindle speed affected plastic deformation which in turn affected corrosion rate.

In this study, poor corrosion rate was observed for the as-received condition, and better corrosion rate was achieved at maximum speed of 600 rpm and 0.6 mm of VSD in the deformed sheet. This indicates that corrosion rate improved with increase in the plastic deformation. The EDS analysis report of corroded surface revealed the composition to be mainly of titanium and oxides.

This study discusses the strain distribution, stress-based fracture limit and corrosion behaviour by using titanium Grade 2 sheets during SPIF process.

This study is useful in the field of automobile and industrial applications.

With an increase in the spindle rotational speeds and VSD, the titanium Grade 2 sheets showed better strain distribution, fracture limit and corrosion behaviour; the same is evidenced in fracture limit curve and PDP curves.

The research investigates the impact of concrete design methods on performance, emphasizing environmental sustainability. The study compares the modified Bolomey method and Abrams’ law in designing concretes. Significant differences in cement consumption and subsequent CO2 emissions are revealed. The research advocates for a comprehensive life cycle assessment, considering factors like compressive strength, carbonation resistance, CO2 emissions, and cost. The analysis underscores the importance of evaluating concrete not solely based on strength but also environmental impact. The study concludes that a multicriteria approach, considering the entire life cycle, is essential for sustainable concrete design, addressing durability, environmental concerns, and economic factors.

The study employed a comprehensive design and methodology approach, involving the formulation and testing of 20 mixed concretes with strengths ranging from 25 MPa to 45 MPa. Two distinct design methods, the modified Bolomey method (three equations method) and Abrams’ law, were utilized to calculate concrete compositions. Laboratory experiments were conducted to validate the computational models, and subsequent analyses focused on assessing differences in cement consumption, compressive strength, CO2 emissions, and concrete resistance to carbonation. The research adopted a multidisciplinary perspective, integrating theoretical analysis, laboratory testing, and life cycle assessment to evaluate concrete performance and sustainability.

Conclusion from the study includes substantial variations (56%–112%) in cement content, depending on the calculation method. Abrams' law proves optimal for compressive strength (30 MPa–45 MPa), while the three equations method yields higher actual strength (30%–51%). Abrams' law demonstrates optimal cement use, but concrete designed with the three equations method exhibits superior resistance to aggressive environments. Cement content exceeding 450 kg/m³ is undesirable. Concrete designed with Abrams' law is economically favorable (12%–30% lower costs). The three equations method results in higher CO2 emissions (38–83%), emphasizing the need for life cycle assessment.

This study’s originality lies in its holistic evaluation of concrete design methods, considering environmental impact, compressive strength, and cost across a comprehensive life cycle. The comparison of the traditional Abrams' law and the three equations method, along with detailed laboratory tests, contributes novel insights into optimal cement use and concrete performance. The findings underscore the importance of a multicriteria approach, emphasizing sustainability and economic viability. The research provides valuable guidance for engineers and policymakers seeking environmentally conscious and economically efficient concrete design strategies, addressing a critical gap in the field of construction materials and contributing to sustainable infrastructure development.

The purpose of this paper is to recognize and label the faults in wind turbines with a new density-based clustering algorithm, named contour density scanning clustering (CDSC) algorithm.

The algorithm includes four components: (1) computation of neighborhood density, (2) selection of core and noise data, (3) scanning core data and (4) updating clusters. The proposed algorithm considers the relationship between neighborhood data points according to a contour density scanning strategy.

The first experiment is conducted with artificial data to validate that the proposed CDSC algorithm is suitable for handling data points with arbitrary shapes. The second experiment with industrial gearbox vibration data is carried out to demonstrate that the time complexity and accuracy of the proposed CDSC algorithm in comparison with other conventional clustering algorithms, including k-means, density-based spatial clustering of applications with noise, density peaking clustering, neighborhood grid clustering, support vector clustering, random forest, core fusion-based density peak clustering, AdaBoost and extreme gradient boosting. The third experiment is conducted with an industrial bearing vibration data set to highlight that the CDSC algorithm can automatically track the emerging fault patterns of bearing in wind turbines over time.

Data points with different densities are clustered using three strategies: direct density reachability, density reachability and density connectivity. A contours density scanning strategy is proposed to determine whether the data points with the same density belong to one cluster. The proposed CDSC algorithm achieves automatically clustering, which means that the trends of the fault pattern could be tracked.

The development of a new class of engineering materials is the current demand for aircraft and automobile companies. In this context metal, composite materials have a widespread application in different areas of manufacturing sectors.

In this paper, an attempt is made to develop the aluminium-based nano metal matrix composite reinforced with graphene nanoparticles (GNP) by using the stir casting method. Different weight percentage (0.4%, 0.8% and 1.2% by weight) of GNPs are used to fabricate metal matrix composites (MMCs). The developed nanocomposites were further validated by density calculation and optical microstructures to discuss the distribution of GNPs. The tensile test was conducted to determine the strength of the developed MMCs and also supported by fractographic analysis. In addition to it, the Rockwell hardness test and impact test (toughness) with fracture analysis were also conducted to strengthen the present work.

The results reveal the uniform distribution of GNPs into the matrix material. The yield strength and ultimate tensile strength obtained a maximum value of 155.67 MPa and 170.28 MPa, respectively. The hardness value (HRB) is significantly increased and 84 HRB was obtained for the sample with AA1100/0.4% GNP, while maximum hardness value (94 HRB) was obtained for the sample AA1100/1.2% GNP. The maximum value of toughness 14.3 Jules/cm² is recorded for base alloy AA1100 while increasing the reinforcement percentage, it decreases up to 9.7 Jules/cm² for AA1100/1.2% GNP.

Graphene nanoparticles are used to develop nanocomposites, which is one of the suitable alternatives for heavy engineering materials such as steels and cast irons. It has improved microstructural and mechanical properties which makes it preferable for many engineering and structural applications.

The purpose of this paper is to study formability, tensile properties, dislocation density and surface roughness of incrementally deformed Ti–6Al–4V alloy sheets during single-point incremental forming (SPIF) and multi-point incremental forming (MPIF) process. The development of corrosion pits in 3.5% NaCl solution has also been studied during SPIF and MPIF processes.

In this study, the formability, tensile properties, dislocation density, surface roughness and corrosion behaviour of deformed Ti–6Al–4V alloy sheets were studied. A potentio-dynamic polarization (PDP) study was conducted to study the corrosion behaviour of Ti–6Al–4V alloy samples during SPIF and MPIF processes and the results were also compared with base material (BM) in 3.5% NaCl solution. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) analyses were carried out to study the corrosion morphology and dislocation densities of deformed samples.

The deformed Ti–6Al–4V alloy sheets obtained higher plastic deformation, high tensile strength, good surface roughness and good corrosion resistance during MPIF process when compared with SPIF process.

It has been concluded that the maximum strain and good corrosion resistance have been achieved with MPIF process, which in turn increases the plastic deformation as compared with BM.

This study discussed the formability, tensile properties, surface roughness and corrosion behaviour of deformed Ti–6Al –4V alloy sheets during incremental sheet forming (ISF) process.

This study is useful in the field of medical, industrial and automobile applications.

The Ti–6Al–4V alloy is deformed using MPIF process, achieving better formability, tensile strength, good surface roughness and corrosion rate, and the same is evidenced in forming limit diagrams (FLDs) and PDP curves.

The purpose of this study is to experimentally investigate the large deformation compression characteristics of fused deposition modelling (FDM)-printed poly lactic acid (PLA), considering the combined effect of infill density and strain rate, and to develop a constitutive viscoplastic model that can incorporate the infill density to predict the experimental result.

The experimental approach focuses on strain rate-dependent (2.1 × 10⁻⁴, 2.1 × 10⁻³, and 2.1 × 10⁻² s⁻¹) compression testing for varied infill densities. Scanning electron microscopy (SEM) imaging of compressed materials is used to investigate deformation processes. A hyperelastic-viscoplastic constitutive model is constructed that can predict mechanical deformations at different strain rates and infill densities.

The yield stress of PLA increased with increase in strain rate and infill density. However, higher degree of strain-softening response was witnessed for the strain rate corresponding to 2.1 × 10⁻² s⁻¹. While filament splitting and twisting were identified as the damage mechanisms at higher strain rates, matrix crazing was observed as the primary deformation mechanism for higher infill density (95%). The developed constitutive model captured yield stress and post-yield softening behaviour of FDM build PLA samples with a high R² value of 0.99.

This paper addresses the need to analyse and predict the mechanical response of FDM print polymers (PLA) undergoing extensive strain-compressive loading through a hyperelastic-viscoplastic constitutive model. This study links combined effects of the printing parameter (infill density) with the experimental parameter (strain rate).

In this study, waste iron scale, which occurs in high amounts during steel production and contains high amounts of iron element, was used as a reinforcing material in the polypropylene (PP) matrix.

In the PP matrix, 33 micron-sized iron scale was added at 5%, 10%, 15% and 20% ratios. The composites were subjected to mechanical and dry sliding wear tests. The wear mechanisms occurring on the wear surfaces were determined by SEM supported by EDS. Tensile testing was performed using a tensile tester. Hardness tests were performed using a Shore-D hardness tester with ASTM-D-22 standards.

Composite reinforced with 5% iron scale showed the highest tensile strength. The addition of higher amounts of iron scale particles reduced the tensile strength of the composites compared to PP. Hardness increased from 58 to 64 Shore-D with the increase in scale content. The reinforcement of PP with iron scale increased the dry sliding wear resistance.

According to the authors’ knowledge, in the literature review, there was no study found on the effect of iron scale reinforcement on PP.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2020-0316/