Engineering Machinery Research Articles

Effect of cooling temperature on microstructure and mechanical properties of Ti microalloyed steel

Ti is a relatively inexpensive alloying element. Ti micro-alloying enables steel to have higher strength, which has already been applied to steel products in many domains, including engineering machinery. In this work, the effects of cooling temperature upon the mechanical properties and microstructure of Ti microalloyed steel were researched by OM, TEM, tensile and impact tests. The consequences show that as the final cooling temperature (FCT) decreased, the steel plate microstructure changed from PF + P + B (less) to GB + PF (less)+ P (less), and the grain size decreased obviously. As the temperature further decreased to 607°C, the intragranular dislocation tangles and subgrains increased significantly. The size and number of large TiC precipitates in the steel plate decreased with the decrease of the final cooling temperature. Additionally, the mean size of precipitates decreases gradually. As the FCT varied between 672°C and 645°C, the steel plate strength and low temperature toughness were significantly improved. As the temperature is further reduced to 607°C, the strength increase was reduced. Due to the improvement of grain uniformity, the low temperature toughness was further enhanced to 156 J.

An acoustic emission onset time determination method based on Transformer

Acoustic emission (AE) technology, as the main method of non-destructive testing technology, has been widely used in structural health monitoring (known as SHM) in the fields of machinery and civil engineering. Locating the failure source is an important application of SHM, and accurately identifying the moment when the AE signal first reaches the sensor (which is called onset time) is of vital importance. Deep learning model has been widely used in onset time determination of AE signals in recent years due to its powerful feature extraction ability. However, as one of the most popular models, Transformer has not been further studied in such field and its effectiveness remains to be proven. In this paper, a novel AE onset time determination method based on Transformer is proposed. Firstly, a preprocessing method based on segmentation-concatenation is applied to divide original data into several connected small segments, while the integrating labeling method is applied on small label segments. Secondly, the preprocessed data and labels are substituted into the Transformer model for training. Finally, for the sequence processed by the Transformer model, the first-time index that reaches the maximum value is obtained as the determination result. Based on the Hsu-Nielson source AE data, the feasibility and performance of this method are analyzed and compared with several commonly used methods: Akaike information criterion (AIC), short/long term average combined with AIC (STA/LTA-AIC), floating threshold (FT) and 1D-CNN-AIC method. The results show that the proposed method is significantly better than AIC, STA/LTA-AIC and FT. Moreover, the determination efficiency is greatly improved while the performance of the proposed method is close to that of 1D-CNN-AIC. Meanwhile, the method has robust performance especially in low signal-to-noise ratio scenario. In practical applications with small-scale data, the proposed method is of relatively high reference as well as application value.

A two‐stage solution method for the design problem of medium‐thick plates in steel plants

AbstractThe medium‐thick plate is an important type of steel product widely used in construction and engineering machinery. The orders are usually characterised by multiple specifications and small quantities. The plate design is an important part in the production process of medium‐thick plate, which includes the combination of sub‐plates and the size design of the motherboard. A multi‐objective model for medium‐thick plate design is proposed based on the 2D bin packing model, comprehensively considering spatial and size constraints of the plate production. A two‐stage genetic algorithm (TSGA) is developed to solve the proposed model. In the first stage, an improved GA is used to optimise the corresponding relationship between the sub‐plates and the slab, as well as the size of the motherboard. In the second stage, an exact algorithm based on the integer programming model is applied to calculate the order layout to minimise the surplus materials. To validate the proposed method, computational experiments are conducted based on actual production data from a steel plant. The experimental results show the effectiveness of the TSGA algorithm in solving the plate design problem.

Derivation of Solution Bundles in Hybrid Portfolios of Industrial Solution Providers in Machinery Engineering

Companies in the machinery engineering sector are identifying increased demand from their customers for integrated solutions that consist of product, service and software elements tailored to the customers’ specific needs. The companies must therefore transform themselves from classic product providers into industrial solution providers. In addition to the opportunity to differentiate themselves from other competitors, the transformation of the business model to the distribution of customer-specific value propositions provides new revenue opportunities. Progressive digitization and the increasing integration of service and software elements in the value chain are considered to be key enablers of the transformation into an industrial solution provider. In order to realize the transformation successfully, it is necessary to plan the portfolio holistically on the basis of systematized customer requirements and the existing elements in the portfolio. This paper therefore presents a methodology for deriving suitable solution bundles to realize the value propositions. For this purpose, an integrated architecture of the solutions is created, a comparison of the solution elements with the customer requirements is performed, and finally, a staggering of the solutions in the portfolio is conducted.

Preface

The International Conference on Energy and Power Engineering originates from 2022 and has attracted various promising researchers who are developing new directions in the field of energy and power engineering. The 2023 2nd International Conference on Energy and Power Engineering (EPE 2023), held via virtual form in Xi’an, China from October 13th to 15th, 2023, was meant to unite researchers, scientists, experts, and academic staff as well as a wide range of participants of professional community from China and other countries concerned.Energy is a powerful driving force for the development of human society. How to store, transform and use energy safely, cleanly and efficiently to realize sustainable human development has always been a topic of global discussion. Therefore, EPE 2023, with about 80 participants, was held to realize the sustainable sharing of research results, knowledge and ideas, thus contributing to the development of cutting-edge technology and academic prosperity.Highly eventful program of the Conference, the list of well-established organizations-participants and devoted engagement of many colleagues throughout all the stages of the Conference preparation instill confidence in practical importance of mutual initiative. The framework of the Conference comprised keynote speeches, oral presentations, poster presentations, and academic investigation, discussing significant problems facing energy and power engineering, proposing innovative ideas and approaches to solution of the problems, and considering new possibilities of application and development of cutting-edge energy and power technology.The Conference has become one of the venues for demonstrating scientific achievements of international class by leading scientists and young scholars and would facilitate the strengthening of academic cooperation, meanwhile the Conference proceedings would be expressed in the form of international scientific publishing. Various topics of the papers, gone through a vigorous peer review process, are covered in the proceedings, including: Energy Conversion and Application, Thermal Energy and Power, Power Machinery and Vehicle Engineering, Fluid Machinery and Automation, Power Plant Electrical Equipment, etc.On behalf of the Conference Organizing Committee, we would like to thank the reviewers for their efficient and thoughtful actions. Particularly, we acknowledge the publishing support from the members of Journal of Physics: Conference Series. We hope that the future conferences of EPE will be as successful and stimulating as indicated with the contributions presented in this volume.The Committee of EPE 2023List of Committee Member is available in this pdf.

Development of a methodology for the derivation of technical requirements for (cyber-) physical product-service systems in service-oriented business models

Digitalization and Industry 4.0 are catalysts for business model innovation, particularly in machinery and plant engineering. Service-oriented business models (Subscription, pay-per-use, …) have emerged as a promising avenue, fostering sustainable product-service systems (PSS) and nurturing enduring customer relationships. Unlike traditional transactional models, where customers make one-time purchases of products or services, subscription models involve regular payments for access to offerings over time or provide on-demand access to services or resources, often through cloud-based platforms. This offers significant advantages for vendors, allowing for predictable, recurring revenue streams and the ability to tailor offerings better, thus evolving customer needs. Simultaneously, customers benefit from increased flexibility, cost-effectiveness, and access to the latest solutions, creating a win-win scenario for both parties. The transition to "as-a-service" models significantly changes the prerequisites and requirements for the PSS and thus requires a comprehensive reassessment of its core requirements. While various approaches exist for designing PSS within the machine tool industry, none systematically delineates the specific design guidelines required to adapt effectively for service-oriented business models. This paper describes a methodology for the derivation of characteristics of service-oriented business models in the machine tool industry and their implications for the design of (cyber-) physical PSS.

Does Implementing Hybrid Carbon Asset Pledge Financing Benefit Production and Emission Reduction for Emission-Dependent Engineering Machinery Remanufacturing?

Does Implementing Hybrid Carbon Asset Pledge Financing Benefit Production and Emission Reduction for Emission-Dependent Engineering Machinery Remanufacturing?

Tungsten coating technologies for agricultural machinery engine parts

The article reviews the possibilities of using tungsten for engine parts of agricultural machinery and the transition to electric motors. The use of electric motors for agricultural machinery and experience in the production of electric tractors is described. A description of the manufacturers of electric tractors and their advantages is given. The materials of motor parts are described, including the use of tungsten. CVD coatings are selected and described as a technology for electric motor applications. The technology of obtaining tungsten coatings on the electrodes of the engine of agricultural machinery by the method of obtaining CVD coatings is proposed. In this article, the CVD coating mode is selected and the properties of the obtained coating according to the selected mode are analysed. The advantages of the coating are identified and the future development of the technology is described.

СПОСОБ ПЕРЕДАЧИ ДИАГНОСТИЧЕСКИХ ДАННЫХ О ТЕХНИЧЕСКОМ СОСТОЯНИИ ДВИГАТЕЛЕЙ СЕЛЬСКОХОЗЯЙСТВЕННОЙ ТЕХНИКИ

The article analyzes modern wireless data transmission technologies. Their advantages and disadvantages are revealed. A method for remote transmission of diagnostic data from agricultural machinery engines using Lora technology is proposed. A simplified diagram for transmitting diagnostic data is presented. Laboratory studies of the diagnostic method were performed.

Research on the application method of agricultural machinery engineering automation based on multimodal characteristics

Abstract Agricultural operators can predict the yield of wheat at different stages of growth, development, and harvesting and take different measures to realize precise management. The purpose of this paper is to apply agricultural mechanical engineering automation to wheat yield prediction, and a UAV multimodal data wheat yield prediction model is developed using the RMGF algorithm. Different data sources, such as vertical distribution of terrain and spatial variability, canopy height and wheat plant height, canopy temperature difference, vegetation spectral characteristics, and vegetation index, were extracted using an agricultural UAV. Then GF decomposition algorithm based on MSD decomposes the multimodal image into an approximate image and detail image, and after optimization of the fused weight map using RSA, the fused image is obtained by IMST according to the optimized weight map. The model was used to carry out regression analysis of yield prediction for three types of wheat, heat-tolerant, medium heat-tolerant, and high-temperature-sensitive, and finally predicted the wheat yield from 2015 to 2024 in a production area. It was found that the R² of the RMGF multimodal model in this paper predicted the three kinds of wheat yields as 0.7936, 0.8609, and 0.9262 with excellent accuracy results. The predicted yields were basically in line with the actual yields in the high-yield portion, with large prediction errors above 9000 kg/ha. The prediction error for wheat was within 0-2.26%, and the predicted yield in a main wheat production area was 7050 kg/ha in 2024. This study provides a feasible method for large-scale yield estimation in the main production area, which contributes to high-throughput plant phenotyping and agricultural precision reform.

Design and Development of Mini Tractor Operated Multipurpose Equipment for Groundnut Crop

A study was developed to design and fabricate a multipurpose equipment during the year of 2021 in the Departmental Workshop of Farm Machinery and Power Engineering and evaluated at field of Dr. NTR College of Agricultural Engineering, Bapatla, Andhra Pradesh, India. The proposed design of machine is economical to fabricate, and have greater design simplicity than its counterpart, with proper seed placement at desired depth, distance between rowsis adjusted because of tynes are fitted with the nut and bolts. Developed multipurpose equipment also done spraying and weeding attachment can be used simultaneously on single run in groundnut crop so that, the time and labour can be saved and it can be used for any narrow row crops for intercultural operations. The overall dimensions of developed multipurpose equipment are 1800×600×1550 mm and the weight of machine was 150 kg. The designed and develop machine was operated at various speeds i.e 1.8, 2.5 and 3.2 km h-1. The field efficiency while doing sowing, spraying and weeding of equipment varies from 78,83 and 78% at 1.8, 2.5 and 3.2 km h-1. The different operations were operated effectively at 2.5 km h-1. The use of multipurpose equipment helps to overcome the problems of drudgery, labour shortage timeless of operation and as a result, the farm power availability in farms can be increased. Hence, there is a need for a multipurpose implement for carrying different operations in groundnut crop.

Repurchase or pledge? Financing and production decisions of engineering machinery remanufacturing firms

Under carbon cap and trade policy, engineering machinery firms have engaged in remanufacturing and invested in carbon emission reduction technologies. However, they often struggle with a lack of funding, but carbon quota financing offers a solution. Taking a capital-constrained engineering machinery remanufacturer as the research object, this paper first formulates four decision models, i.e. (no capital constraints, no financing), (capital constraints, no financing), (capital constraints, carbon quota repurchase financing) and (capital constraints, carbon quota pledge financing), then the equilibrium results are compared. Finally, the numerical simulations are performed to study the impact of carbon emission reduction and quality uncertainty of recycled products. The results show that if remanufacturers possess adequate carbon quotas, carbon quota pledge financing can always improve profits effectively, otherwise, the effectiveness of financing strategies depends on the difference between extra profits and financing costs. Both financing strategies can increase the output of new products and reduce that of remanufactured products. Increasing the quality threshold of recycled products is beneficial for remanufacturing, environmental protection and profits. Investing in carbon emission reduction benefits remanufacturing and the environment, however, it reduces remanufacturers' profits in the short term.

Is carbon asset pledge financing contributing to the operation of emission-dependent engineering machinery remanufacturing with emission abatement?

As a new financing strategy in the carbon trade market, carbon asset pledge financing (CAPF) provides a new financing channel for capital-constraint firms. For the carbon emission-dependent engineering machinery remanufacturer, how to formulate an optimal production plan under CAPF is still an unsolved problem. In this study, we suppose the emission-dependent remanufacturer adopts the pure carbon asset pledge financing (PCAPF) to solve capital shortage problem, and then study the optimal production and carbon emission reduction (CER) decisions of remanufacturers under PCAPF. The results show that: i) Only when the remanufacturer's initial capital is below a certain threshold can it benefit from PCAPF, and the threshold is different under all remanufacturing strategies. ii) Compared with no CER, the yield of new products increases when CER is implemented. However, whether remanufactured products increase depends on different remanufacturing strategies. iii) Under PCAPF, a high carbon asset pledge rate is not conducive to the production and profit of remanufacturers regardless of CER, and the increase of carbon price fluctuation coefficient negatively affects the production and environment without CER. However, the correlation among them is related to the threshold of the CER rate. iv) With/without CER, the yield of new/remanufactured products, environmental impact, and profit decrease sequentially with the choice of complete remanufacturing, partial remanufacturing, and non-remanufacturing under PCAPF. Meanwhile, although the increase of the CER rate increases environmental impact, whether it can improve the profit of remanufacturers is related to the threshold of unit emission of remanufactured products. Thus, the remanufacturer should balance the trade-off when implementing CER.

Failure analysis of a loader hydraulic cylinder and its end cap structure improvement

With the rapid development in the manufacturing sector, lightweight manufacturing has become an inevitable trend. However, achieving lightweight engineering machinery requires the structural redesign of most internal components, including the hydraulic cylinders in hydraulic systems. When evaluating the lifespan of redesigned loader hydraulic cylinders using simulated pulse experiments, it was evident that the fillet weld between the connecting end cap and cylinder barrel failed and fractured before reaching its full lifespan. Consequently, in order to assess the failure conditions of the loader hydraulic cylinder, the generation and extension of the failure cracks were explored using methods such as macroscopic fracturing, hardness testing, metallographic analysis, inclusion component analysis, and finite element analysis. During this process, the end cap structure of hydraulic cylinder was improved using finite element analysis. The results showed that the presence of numerous coarse spherical carbides at the tip of the weld cracks and the formation of dislocation tangles around the carbides, resulting in high stress concentrations and accelerated fatigue crack propagation. Additionally, the specific welding-joint structure of the hydraulic cylinder, resulting in high stress concentrations and accelerated fatigue crack initiation at the weld. After improving the hydraulic-cylinder end cap structure using finite element analysis, the fatigue life of the hydraulic cylinder was improved. This work provides a theoretical basis for the design and manufacture of lightweight and high-life hydraulic cylinders.

Tuning transcription factor DegU for developing extracellular protease overproducer in Bacillus pumilus

BackgroundGlobal transcription machinery engineering (gTME) is an effective approach employed in strain engineering to rewire gene expression and reshape cellular metabolic fluxes at the transcriptional level.ResultsIn this study, we utilized gTME to engineer the positive transcription factor, DegU, in the regulation network of major alkaline protease, AprE, in Bacillus pumilus. To validate its functionality when incorporated into the chromosome, we performed several experiments. First, three negative transcription factors, SinR, Hpr, and AbrB, were deleted to promote AprE synthesis. Second, several hyper-active DegU mutants, designated as DegU(hy), were selected using the fluorescence colorimetric method with the host of the Bacillus subtilis ΔdegSU mutant. Third, we integrated a screened degU(L113F) sequence into the chromosome of the Δhpr mutant of B. pumilus SCU11 to replace the original degU gene using a CRISPR/Cas9 system. Finally, based on transcriptomic and molecular dynamic analysis, we interpreted the possible mechanism of high-yielding and found that the strain produced alkaline proteases 2.7 times higher than that of the control strain (B. pumilus SCU11) in LB medium.ConclusionOur findings serve as a proof-of-concept that tuning the global regulator is feasible and crucial for improving the production performance of B. pumilus. Additionally, our study established a paradigm for gene function research in strains that are difficult to handle.

Review of Lattice Boltzmann Method Applied to Computational Aeroacoustics

This paper presents the research studies carried out on the application of lattice Boltzmann method (LBM) to computational aeroacoustics (CAA). The Navier-Stokes equation-based solver faces the difficulty of computational efficiency when it has to satisfy the high-order of accuracy and spectral resolution. LBM shows its capabilities in direct and indirect noise computations with superior space-time resolution. The combination of LBM with turbulence models also work very well for practical engineering machinery noise. The hybrid LBM decouples the discretization of physical space from the discretization of moment space, resulting in flexible mesh and adjustable time-marching. Moreover, new solving strategies and acoustic models are developed to further promote the application of LBM to CAA.

МОНИТОРИНГ КАЧЕСТВА МОТОРНОГО МАСЛА ПО НАКОПЛЕНИЮ НЕРАСТВОРИМЫХ МЕХАНИЧЕСКИХ ПРИМЕСЕЙ

The quality of the oil deteriorates during the intensive operation of agricultural machinery engines in adverse conditions, which leads to wear of the rubbing surfaces of parts, disruption of the engine and an increase in the risk of an emergency operating or emergency situation. The causes of emergencies of engine components, as well as methods for their reduction through the use of an engine oil diagnostic system, are discussed in the article. The degree of contamination of engine oil with insoluble impurities is one of the diagnostic parameters by which the operability of the entire technical system is determined. Modern methods of analysis (laser diffraction, electron X-ray microscopy) have established the main characteristics of impurities in used engine oils and their relationship with the degree of wear of engine elements of agricultural machinery. The use of this type of diagnostics allows you to assess the condition of the most important systems of the car. The diagnosed signs can show the presence of technical problems of the fuel and air systems, the cylinder piston group of the engine, and violations in operation. It is proposed to use the elementary concentration of iron in the selected samples of engine oil as a diagnostic parameter of tribomonitoring, which is an indicator of the degree of wear of parts of the piston group of the engine of agricultural machinery. The dependence of the metal concentration (CFe) in engine oil on the silicon content (CSi) obtained from the results of X-ray spectral microweighting is approximated by an exponential dependence, which increases the accuracy of predicting the engine oil resource and the technical condition of the car. The use of these control methods makes it possible to unambiguously determine the nature of equipment operation and detect the occurrence of defects in a timely manner.

Multiple-signal defect identification of hydraulic pump using an adaptive normalized model and S transform

Axial piston pump plays a pivotal role in a hydraulic transmission system since it can supply the core power source. The complexity of structure and the invisibility of failure feature bring more difficulties and challenges to fault identification of an axial piston pump. It is of great meaning to exploit an effective and feasible fault identification method for the safe and stable system operation. An improved convolutional neural network (CNN) is constructed by mining and utilizing the interdisciplinary advantages of artificial intelligence and machinery engineering. First, the modeling takes the batch normalization strategy into account due to its capability of decreasing the data distribution differences. Second, Bayesian algorithm is used for intelligent tuning of hyperparameters. Third, the improved CNN is applied to fault identification based on the S transform of multiple source signals. The performance of the proposed method is demonstrated by the experiments on an axial piston pump. The identification accuracies based on three signals reach 88.17%, 95.94%, and 99.44%. Results show that it can automatically recognize typical faults of the axial piston pump, and present the superiority to common CNNs.

Development and Performance Evaluation of Maize Stalk Harvester

A power operated maize stalk harvester was designed and developed in the Dept. of Farm Machinery and Power Engineering, MPUAT, Udaipur, Rajasthan during 2018-19. The objective of this study is to optimize the operational parameters of the maize stalk harvesting by using the RSM techniques. The effects of independent parameters i.e., blade speed (2000, 4000 and 6000 rpm) and stalk moisture content (38, 42 and 46%) on cutting efficiency (%) and fuel consumption (l/h) were studied. To correlate the independent parameters with the dependent parameters, the central composite rotatable design (CCRD) method with a quadratic model was used. The findings indicated that the variations in blade speed and stalk moisture content affected the cutting efficiency (%) and fuel consumption (l/h). To assess the statistical significance of the model, an analysis of variance (ANOVA) was performed, which showed good agreement between the experimental data and data predicted by the model. The blade speed of 4000 rpm and stalk moisture content of 46.0% was found to be the optimum for power operated maize stalk harvester with the 96.52% cutting efficiency and 0.72 l/h fuel consumption.

Automation and Performance Evaluation of a Solar Tunnel Dryer Using Arduino UNO

The study on automation of an existing solar tunnel dryer was done using the Arduino UNO and DHT11 sensor during 2020–2021 at the Research Farm, Department of Farm Machinery and Power Engineering, Sam Higginbottom University of Agriculture, Science, and Technology, Allahabad, Uttar Pradesh, India. To ensure optimal drying conditions, the Arduino UNO was employed to regulate the operation of an exhaust fan. This control system was activated whenever the humidity level inside the dryer reached a specific threshold. The system was configured to operate at three different humidity levels- 35%, 30% and 25% for three weeks of five working days each. Potatoes weighing 5000 g were sliced and spread inside the dryer daily between 9:30 am to 5:30 pm, ensuring consistent and regular activity within the specified timeframe. It was found that the moisture removal rate and the successive drying time were fastest when the exhaust fan was operated to remove 25% humidity, followed by 30% and 35%. During the third week, the drying time was two hours less than the first week and one hour less than the second. These results demonstrate that removing humidity at lower levels significantly contributed to faster drying. Therefore, it can be inferred that automating the solar tunnel dryer and maintaining a lower humidity threshold can significantly enhance the efficiency of the drying process.