Machine Construction Research Articles

OPTIMIZATION OF DYNAMIC MODES OF MOTION OF CONSTRUCTION MECH-ANISMS AND (CRAWLER) MACHINES TAKING INTO ACCOUNT LINEAR RE-SISTANCE PROPORTIONAL TO THE SPEED OF DISPLACEMENT

The paper substantiates the methodology of optimization of dynamic modes of motion of construction mech-anisms and tracked machines taking into account linear resistance proportional to the speed of movement of the object in the operating environment. To optimize the mode of motion, usually single criteria reflecting certain properties of construction mechanisms and crawler machines or complex criteria reflecting the com-plex of their properties are used. The optimal mode of motion, which leads to minimization of force loads in the drive mechanism, is determined on a physically justified basis. For this purpose, a generalized integral dynamic criterion for the motion coordinate is formulated in the form of the criterion action by Appel, in which the component of the resistance force proportional to the mechanism/machine speed is taken into ac-count. The use of methods of classical variational calculus allows us to establish the optimal values of the main dynamic characteristics of the movement of construction mechanisms and crawler machines, laws of such movements, at which minimize during the period of start-up (braking, reversing) the amount of load on the drive mechanism of the machine. The results obtained in the work can be further used to clarify and im-prove engineering methods of calculation of motion characteristics of construction machines (in particular, with crawler) and mechanisms both at the stages of their design/construction and in the modes of real opera-tion, in transient processes (start-up, braking, reversing, etc.) in order to create favorable (energy-saving and accident-free) conditions of their functioning.

The impact of industrial structure upgrading on regional coordination development in the digital era: evidence from China

This paper investigates how industrial structure upgrading influences regional coordination in the digital era, using data from 253 Chinese prefecture-level cities between 2011 and 2021. The research employs a double machine learning model and constructs a Gini coefficient to quantify intracity disparities. Findings indicate that industrial structure upgrading reduces regional disparities overall, with stronger effects during the rapid digital economy development phase. However, in the initial phase of digital infrastructure construction, upgrading intensified disparities due to uneven access to resources and technologies. The analysis also reveals heterogeneity: cities with advanced industrial structures benefit from enhanced coordination, while those with underdeveloped structures face widened disparities. Digitalization moderates these effects by fostering innovation diffusion and improving resource distribution. This paper offers insights into how digitalization and industrial upgrading interact to influence regional coordination, providing a basis for tailored policies to achieve balanced and sustainable urban development.

Study on Torsional Shear Deformation Characteristics of Segment Joints Under the Torque Induced by Tunnel Boring Machine Construction

Study on Torsional Shear Deformation Characteristics of Segment Joints Under the Torque Induced by Tunnel Boring Machine Construction

PENGARUH JENIS WELDING GROOVE TERHADAP KEKUATAN IMPACT PLAT BAJA ASTM A36 MENGGUNAKAN MESIN LAS SMAW

Currently, metal joining with welding process is increasingly used, both in building construction, piping, and machine construction. This is due to the many advantages obtained from joining by welding. The use of the right welding groove will also affect the welding results. The purpose of using welding groove is for the place to fill the welding material and can also strengthen the design of the metal joint. Welding groove plays an important role in improving the design and properties of the joint in the welding process. ASTM A36 welding using SMAW welding current 110 A is carried out with Groove variations, namely VGroove, Square Groove, and Bevel Groove and using E6013 electrodes with a diameter of 2.6 mm. The purpose of this study was to determine the strength of SMAW welding joints on ASTM A36 against the Charphy impact test. the required impact charphy effort results (W) are on V Groove of 73.519 J, Square Groove of 67.43 J, and Bevel Groove of 70.485 J. And produces an impact charphy value (K) on V Groove of 0.918 J / ????????2, on Square Groove of 0.842 J / ????????2 and on Bevel Groove of 0.881 J / ????????2. The impact charphy value on V Groove with SMAW welding current of 110 A on ASTM A36 carbon steel is the best with the required impact charphy results (W) namely on V Groove of 73.519 J and the impact charphy value (K) on V Groove of 0.918 J / ????????2

PENGARUH JENIS WELDING GROOVE TERHADAP KEKUATAN IMPACT PLAT BAJA ASTM A36 MENGGUNAKAN MESIN LAS SMAW

Currently, metal joining with welding process is increasingly used, both in building construction, piping, and machine construction. This is due to the many advantages obtained from joining by welding. The use of the right welding groove will also affect the welding results. The purpose of using welding groove is for the place to fill the welding material and can also strengthen the design of the metal joint. Welding groove plays an important role in improving the design and properties of the joint in the welding process. ASTM A36 welding using SMAW welding current 110 A is carried out with Groove variations, namely VGroove, Square Groove, and Bevel Groove and using E6013 electrodes with a diameter of 2.6 mm. The purpose of this study was to determine the strength of SMAW welding joints on ASTM A36 against the Charphy impact test. the required impact charphy effort results (W) are on V Groove of 73.519 J, Square Groove of 67.43 J, and Bevel Groove of 70.485 J. And produces an impact charphy value (K) on V Groove of 0.918 J / ????????2, on Square Groove of 0.842 J / ????????2 and on Bevel Groove of 0.881 J / ????????2. The impact charphy value on V Groove with SMAW welding current of 110 A on ASTM A36 carbon steel is the best with the required impact charphy results (W) namely on V Groove of 73.519 J and the impact charphy value (K) on V Groove of 0.918 J / ????????2.

From construction machines to remote construction robots: control, interfaces, and usability of the Cranebot.

Construction machines, for example cranes, excavators, or bulldozers, are widely diffused systems operating outdoors in harsh and dangerous environments, such as building sites, forests, and mines. Typically, construction machines require the on-site presence of highly skilled users to manage the complexity of their control and the high power of hydraulic actuation. Construction machines could benefit from recent developments of robot avatar technology that has demonstrated the viability of remotizing human physical activities, leveraging on intuitive interfaces and controls. Similar approaches could also improve the overall usability of construction machines, making them safer and accessible for untrained users. With this in mind, we developed a novel system for the remote control of cranes through intuitive and immersive interfaces. To validate the solution, we evaluated the experience of approximately 80 untrained users that remotely operated a crane during the 33rd Edition of Bauma, the world's leading fair for construction machines.

Optimization of Federated Learning Communication Costs through the Implementation of Cheetah Optimization Algorithm

Recently, Federated Learning (FL) has promptly gained aggregate interest owing to its emphasis on the data privacy of the user. As a privacy-preserving distributed learning algorithm, FL enables multiple parties to construct machine learning (ML) algorithms without exposing sensitive information. The distributed computation of FL may lead to drawn-out learning and constrained communication processes, which necessitate client-server communication cost optimization. The two hyperparameters that have a considerable effect on the FL performance are the number of local training passes and the ratio of chosen clients. Owing to training preference across different applications, it is challenging for the FL practitioner to manually choose these hyperparameters. Even though FL has resolved the problem of collaboration without compromising privacy, it has a transmission overhead because of repetitive model updating during training. Various researchers have introduced transmission-effective FL techniques for addressing these issues, but sufficient solutions are still lacking in cases where parties are in charge of data features. Therefore, this study develops an Optimization of Federated Learning Communication Costs through the Implementation of the Cheetah Optimization Algorithm (OFLCC-COA) technique. The OFLCC-COA technique is mainly applied for effectually optimizing the communication process in the FL to minimize the data transmission cost with the guarantee of enhanced model accuracy. The OFLCC-COA technique enhances the robust performance in unsteady network environment via the transmission of score values instead of large weights. Besides, the OFLCC-COA technique improves the communication efficiency of the network by transforming the form of data that clients send to servers. The performance analysis of the OFLCC-COA model occurs utilizing different performance measures. The simulation outcomes indicated that the OFLCC-COA model obtains superior performances over other methods in terms of distinct metrics

METHODS OF RESEARCHING HYDRODYNAMIC AND RELATED PROCESSES IN STRUCTURES (REVIEW ARTICLE)

The article contains an analysis of publications on research methods of hydrodynamic and related processes in structures. In particular, attention is paid to centrifugal pumps. The existing technical solutions of these pumps are highlighted, as well as the operation of planetary hydraulic motors, where wear of the working surfaces of the rotors occurs. The problem of ensuring the stability of the dynamic characteristics of the hydraulic drive during transient processes using passive pulsation dampers is analyzed. An analysis of research devoted to the use of energy-efficient hydraulic motors in running modules of mechatronic systems of construction, road, utility, agricultural, railway and other self-propelled machines was carried out. The method of smoothing the working surfaces of the stator and rotor using computer modeling to eliminate the influence of the rotor on the stator during their interaction is considered. An analysis of the calculation and design of the optimal radial gap of the piston pair in the axial-piston pump was carried out. The dynamic model of cylinder block leakage and the lubricating film based on the lubrication of a pair of spherical valve plates for axial-piston pumps are analyzed. An analysis of the dynamic response of a two-tandem axial-piston pump with two-circuit flow control under pressure obstruction conditions was carried out. The diagnostic scheme for detecting malfunctions of the hydraulic piston pump was analyzed. For such heavily loaded machines as military, such connected models and research methods are necessary, as recommendations based on more adequate models are more grounded and perfect.

Control of the size and distribution of residual macronapples by rolling rollers

Abstract. Microarc oxidation (MAO) is used to improve the wear and corrosion resistance of agricultural, road construction and mining machinery parts. Applying layers of aluminum to a steel product and then converting part of it into corundum ceramics will help to create maximum hardness, wear resistance and high adhesion strength. Problem. Abrasive and corrosion-abrasive wear causes the greatest damage to agricultural, road construction and mining machines. Natural abrasive, consisting mainly of SiO2 particles with a hardness of HV = 10 GPa, can only be protected by using materials with a hardness higher than the hardness of the abrasive. The solution to this problem is the application of wearresistant layers. Increasing wear resistance can be achieved by producing corundum ceramics by the micro-arc oxidation (MAO) method. Goal. The goal is to create wear-resistant corundum coatings on 40KhS steel by microarc oxidation with gas-plasma spraying of an aluminum layer. Methodology. The X-ray diffraction analysis of the coatings was performed in this work. The X-ray analysis was performed at room temperature using a DRON-4 diffractometer in monochromatic Kα-Cu radiation. When deciphering the obtained diffractograms, the ASTM. Originality. The study showed that it is possible to form a high-hardness (HV ≈ 17 GPa) oxide coating on an aluminum layer deposited by gas plasma spraying on 40KhS steel. Practical value. The resulting structure and high hardness of MАO coatings are a prerequisite for ensuring their high wear resistance to abrasive wear and corrosive environments experienced by parts of agricultural, earthmoving and road machines.

Application of machine learning methods for predicting esophageal variceal bleeding in patients with cirrhosis.

To develop and compare machine learning models based on CT morphology features, serum biomarkers, and basic physical conditions to predict esophageal variceal bleeding. Two hundred twenty-four cirrhotic patients with esophageal variceal bleeding and non-bleeding were included in the retrospective study. Clinical and serum biomarkers were used in our study. In addition, the open-access segmentation model was used to generate segmentation masks of the liver and spleen. Four machine learning models based on selected features are used for building prediction models, and the diagnostic performances of models were measured using the receiver operator characteristic analysis. Two hundred twenty-four cirrhosis patients with esophageal varices, including 112 patients with bleeding (mean age 52.8 ± 11.5 years, range 18-80 years) and 112 patients with non-bleeding (mean age 57.3 ± 10.5 years, range 34-85 years). The two groups showed significant differences in standardized spleen volume, fibrinogen, alanine aminotransferase, aspartate aminotransferase, D-dimer, platelet, and age. The ratio of the training set to the test set was 8:2in our research, and the 5-fold cross-validation was used in the research. The AUCs of linear regression, random forest, support vector machine, and adaptive boosting were, respectively, 0.742, 0.854, 0.719, and 0.821 in the training set. For the test set, the AUCs of models were, respectively, 0.763, 0.818, 0.648, and 0.804. Our study used CT morphological measurements, serum biomarkers, and age to build machine learning models, and the random forest and adaptive boosting had potential added value in predictive model construction. Question Esophageal variceal bleeding is an intractable complication of liver cirrhosis. Early prediction and prevention of esophageal variceal bleeding is important for patients with liver cirrhosis. Findings It was feasible and clinically meaningful to construct machine learning models based on CT morphology features, serum biomarkers, and physical conditions to predict variceal bleeding. Clinical relevance Our study may provide a promising tool with which clinicians can conduct therapeutic decisions on fewer invasive procedures for the prediction of esophageal variceal bleeding.

Multi-Step Prediction of TBM Tunneling Speed Based on Advanced Hybrid Model

The accurate prediction of tunneling speed in tunnel boring machine (TBM) construction is the basis for the timely adjustment of the operating parameters of TBM equipment to ensure safe and efficient tunneling. In this paper, a multi-step prediction model of TBM tunneling speed based on the EWT-ICEEMDAN-SSA-LSTM hybrid model is proposed. Firstly, four datasets were selected under different geological conditions, and the original data were preprocessed using the binary discriminant function and the 3σ principle; secondly, the preprocessed data were decomposed using the empirical wavelet variation (EWT) to obtain several subseries and residual series; then, Intrinsic Computing Expressive Empirical Mode Decomposition With Adaptive Noise (ICEEMDAN) was used to perform further decomposition on residual sequences. Finally, several subsequences were fed into a Long Short-Term Memory (LSTM) network optimized by the Sparrow Search Algorithm (SSA) for multi-step training and prediction, and the predicted results of each subsequence were added up to obtain the final result. A comparison with existing models showed that the performance of the prediction method proposed in this paper is superior to other models. Of the four datasets, the average accuracy from the first step prediction to the fifth step prediction reached 99.06%, 98.99%, 99.07%, and 99.03%, respectively, indicating that the proposed method has high multi-step prediction performance and generalization ability. In this sense, this paper provides a reference for other projects.

Determination of Battery Capacity and Type in Electric Wheel Loader Machines Considering Variable Operating Conditions

In recent years, the development and production of fully electric battery vehicles have become increasingly common in the construction equipment sector. Conventional construction machines with diesel internal combustion engines are losing popularity in city centers with high human density due to the harmful gases and high noise levels emitted into the environment. In some developed countries, the use of conventional machines has already been prohibited in some areas, and it is reflected in the media that other administrations have been concentrating on similar activities. In addition to easy access to charging stations in city centers, charging systems that can provide high power, especially in construction sites where machines operate, and charging the machines within a particular area makes charging more practical than passenger vehicles. The machines have multiple consumers, such as the powertrain and hydraulic systems, and have various operating conditions. Therefore, the power demand and energy consumption should be definite correctly. The requirement analysis for the battery package of the fully electric wheel loader has been made according to various operating scenarios, and the capacity of the battery package is investigated. Different battery types are compared, and their pros and cons are explained. Several field tests, measurements, and engineering calculations have provided data. The overall schematic plan of the fully electric machine has been created, and technical details have been explained.

Unconventional Structures of Asynchronous Motors with Two Stators and Single-Rotor Radial Air Gaps in the Context of Their Applicability Assessment

The fundamental idea underlying the research presented in this paper was the desire to use less magnetically charged areas of the general construction of induction machines by increasing the active working surface by interposing a new internal stator armature. This results in a new air gap and foreshadows the advantage of increasing the torques developed by the motor considered, compared to the equivalent standard motor, at the same volume of iron. The following research-validation methods were followed: theoretical studies (analytical simulation and FEM), an experimental model (prototype), and testing on the experimental platform. We recall obtaining solid conclusions on the technological construction, functional and energy characteristics, as well as superior performances of over 50% regarding electromagnetic torques compared to the equivalent classic version. The prototype of this type of machine was surprising due to the ease with which the rotor can be rotated, highlighting the reduced inertia. In conclusion, concerning the problem addressed and the objectives pursued, the research had, in essence, an applied and experimental nature. The recent development of permanent-magnet synchronous motor constructions has led to the concept of creating such motors in the constructive configuration specified in the paper (two stators and two radial air gaps).

I-WASP—Intelligent and Wireless Technologies for Automatically Generated Shift Protocols in Conventional Tunnelling

The research project i‑WASP, a collaboration of specialized German and Austrian companies and research institutions, looks at the question of how complex processes on a conventional tunneling construction site can be automatically recorded, analyzed, and classified through the development of innovative solutions for data acquisition, transmission, and processing. A trained artificial intelligence will be able to automatically produce accurate minute diagrams based on accelerometer and positional data gathered from the construction machines.

The diagnostic efficacy of seven autoantibodies in early detection of ground-glass nodular lung adenocarcinoma.

Persistent ground-glass nodules (GGNs) carry a potential risk of malignancy, however, early diagnosis remained challenging. This study aimed to investigate the cut-off values of seven autoantibodies in patients with ground-glass nodules smaller than 3cm, and to construct machine learning models to assess the diagnostic value of these autoantibodies. In this multi-center retrospective study, we collected peripheral blood specimens from a total of 698 patients. A total of 466 patients with ground-glass nodular lung adenocarcinoma no more than 3cm were identified as a case group based on pathological reports and imaging data, and control group (n=232) of patients consisted of 90 patients with benign nodules and 142 patients with health check-ups. Seven antibodies were quantified in the serum of all participants using enzyme-linked immunosorbent assay (ELISA), and the working characteristic curves of the subjects were plotted to determine the cut-off values of the seven autoantibodies related ground-glass nodular lung adenocarcinoma early. Subsequently, the patients were randomly divided into a training and test set at a 7:3 ratio. Eight machine-learning models were constructed to compare the diagnostic performances of multiple models. The model performances were evaluated using sensitivity, specificity, and the area under the curve (AUC). The serum levels of the seven autoantibodies in case group were significantly higher than those in the control group (P < 0.05). The combination of the seven autoantibodies demonstrated a significantly enhanced diagnostic efficacy in identifying ground-glass nodular lung adenocarcinoma early when compared to the diagnostic efficacy of the autoantibodies when used respectively. The combined diagnostic approach of the seven autoantibodies exhibited a sensitivity of 84.05%, specificity of 91.85%, and AUC of 0.8870, surpassing the performance of each autoantibody used individually. Furthermore, we determined that Sparrow Search Algorithm-XGBoost (SSA-XGBOOST) had the best diagnostic performance among the models (AUC=0.9265), with MAGEA1, P53, and PGP9.5 having significant feature weight proportions. Our research assessed the diagnostic performance of seven autoantibodies in patients with ground-glass nodules for benign-malignant distinction, and the nodules are all no more than 3cm especially. Our study set cut-off values for seven autoantibodies in identifying GGNs no more than 3cm and constructed a machine learning model for effective diagnosis. This provides a non-invasive and highly discriminative method for the evaluation of ground-glass nodules in high-risk patients.

Development and construction example of automatic operation system for ground improvement construction machine

Development and construction example of automatic operation system for ground improvement construction machine

Experimental study of aluminum alloys and their welded joints for compliance with roll-over protection structures requirements by GOST ISO 3471-2015

Background: Nowadays, tractor’s and construction machine’s cabins with integrated roll-over protecting structures are widely used. Using aluminum alloys for this load-bearing structures could tremendously reduce weight of the cabin, but usually it is not possible due to low mechanical properties of welded joint zone. Recently 3d-printing technologies of aluminum alloys appeared, that demonstrate high ductility and impact toughness. But their application in roll-over protecting structures requires additional research.Goal: research of stress-strain state of aluminum alloy specimens and their welded joint for compliance with roll-over protection systems of cabins requirements.Materials and methods: the experimental approach and simulations are used in this work. A universal tensile machine and impact testing machine are used in the experiment.Results: mechanical properties of samples made of 3d-printed aluminum alloys and their welded joints were obtained and their degree of compliance with passive safety requirements by GOST ISO 3471-2015 was established.Conclusions: 3d-printed aluminum alloys and their welded joints could be used in rollover protection structures of cabins in agricultural and construction machines.

Monitoring water quality parameters in urban rivers using multi-source data and machine learning approach

The systematic surveillance of nutrients and organic pollution in urban rivers is crucial for enhancing ecological integrity and promoting societal and economic sustainability. Currently, the primary methods of water quality monitoring involve on-site sampling and laboratory analysis, which are constrained by various factors such as terrain and climate. Remote sensing water quality monitoring, which enables large-scale, periodic, and comprehensive coverage, serves as an important supplement to these traditional methods. However, most current research on water quality monitoring predominantly relies on remote sensing technology, often overlooking the application of other multi-source data. In this study, we examined rivers in the Weihe River Basin by integrating field samples, Sentinel-2 multispectral imagery, meteorological elements, and land use types to construct machine learning (ML) models for predicting four water quality parameters (WQPs): ammonia nitrogen (NH3-N), total phosphorus (TP), chemical oxygen demand (COD), and dissolved oxygen (DO). The results showed that land use types significantly influenced the accuracy of predictions for NH3-N, TP, COD, and DO. Among the models evaluated, the Extra Tree Regression (ETR), eXtreme Gradient Boosting (XGBoost), and Gradient Boosting Regression (GBR) demonstrated the highest accuracy and transferability for monitoring WQPs in rivers. For instance, the models achieved the following coefficients of determination (R2) in 5-fold cross-validation: for NH3-N, R2 was 0.65 in both the testing and validation datasets; for TP, R2 was 0.71 and 0.68; for COD, R2 was 0.50 and 0.47; and for DO, R2 was 0.68 and 0.64, respectively. Therefore, our findings underscore the feasibility of using multi-source data and ML methods to quantify water pollutants in urban rivers, providing essential technical support for monitoring the spatiotemporal dynamics of river water quality across extensive geographical areas.

ERGONOMICS AS A FACTOR IN ENSURING SAFETY DURING THE OPERATION OF CONSTRUCTION MACHINES ON THE EXAMPLE OF EXCAVATORS

Problem statement. To improve the safe working conditions of excavator operators, it is important to effectively manage ergonomic quality indicators, increase the reliability of excavators, and improve the sanitary and hygienic conditions and comfort of operators. The set of ergonomic indicators of the operator–excavator system, including controllability, occupancy, serviceability, masterability and manufacturability, defines the concept of ergonomics (a criterion category of quality management that is also considered as an object of management). Changes in construction affect the efficiency of the operator-excavator system, taking into account specific production and technical, natural and climatic, and socio-economic conditions. The re-equipment of construction sites with new generation excavators equipped with modern control, computer information and diagnostic systems, hardware and software for data transmission, processing and analysis not only improves the efficiency of construction work but also changes the safe nature of human-machine interaction. The purpose of the article. Ensuring safety during the operation of construction machines (excavators), taking into account ergonomics criteria, which is an urgent scientific task, the solution of which will improve working conditions and increase the efficiency of excavators. Conclusion. The conducted research has shown that the ergonomic component “man – machine – environment” on the example of improving excavators allows to increase the safety of machines and improve the working conditions of construction machine operators. The use of the mathematical apparatus of fuzzy set theory to evaluate and manage the ergonomics of excavators is due to the nature and specificity of the functioning of the elements of the “operator–excavator” system. Information about the system elements can be represented by subjective opinions or judgements, inaccurate data or errors in measurements and parameter calculations. Therefore, it is necessary to use mathematical tools that take into account quantitative and qualitative information presented in linguistic form.

Research into Energy-Saving Control Strategies of a Bulldozer Driven by a Torque Converter Based on the Minimum Fuel Consumption Rate of the Whole Machine

In order to address the issue of poor fuel efficiency in hydraulic bulldozers during operation, this paper proposes a speed–load control strategy aimed at minimizing the overall fuel consumption rate of the machine. First, input–output models of the engine, hydraulic torque converter and the entire vehicle were established. Then, based on the bulldozer’s output power and fuel consumption rate, a performance metric for the overall fuel consumption rate was proposed to reflect the machine’s working efficiency. The characteristics of the overall fuel consumption rate were analyzed under different load, speed, and gear conditions. Next, a work point optimization control strategy was proposed for the whole machine energy-saving mode and constant power mode, aiming to minimize the overall fuel consumption rate while using the load, speed, and gear as control variables. To verify the feasibility of the work point optimization control strategy, simulations were conducted for both the energy-saving and constant power modes. The simulation results showed that in the whole machine energy-saving mode, this control strategy resulted in the lowest fuel consumption compared to constant speed control strategies at 1500, 1700, and 2000 rpm, with significant reductions in most cases. In the constant power mode, a comparison between four optimal operating points and the whole machine energy-saving mode revealed that while the former had slightly higher fuel consumption, it ensured a stable power output. Finally, experimental testing demonstrated that the proposed control strategy reduced the overall fuel consumption rate by 12.5% compared to the constant speed mode, verifying the effectiveness of the strategy. The study concludes that the energy-saving control strategy, through the coordinated switching between the two modes in complex operating conditions, not only ensures a stable power output for the bulldozer but also significantly improves fuel efficiency, providing an important reference for optimizing the efficiency of transmission systems in construction machines.