Rolling Characteristics Research Articles

A comparison of tonnage-dependent shot blast and electro-discharge texturing methods

This study investigated the surface roughness characteristics of rolls textured using the Shot-Blast Texturing and Electro-Discharge Texturing methods. The rolling tests were carried out in an actual cold rolling mill tandem line, and the surface roughness transferred from the roughened rolls to the material with these two methods was examined. The study measured and compared the surface roughness of roughened rolls and the materials rolled by them. The study observed that the transfer ratio of electro-discharge texturing rolls was higher, but the transfer ratio of SBT rolls increased towards the end of the rolling campaign. The study also examined the extent to which the surface roughness of the rolls changed after rolling. Therefore, the level of reduction and how much was preserved were determined by comparing the surface roughness of the rolls before and after the rolling campaign. Shot-blast texturing rolls were found to have lost 53% of their roughness while electro-discharge texturing rolls lost only 33%.

Monitoring the Health Status of Rolling Bearings Based on Adaptive mean-shift

In order to monitor the structural health condition of rolling bearings in real time, an adaptive mean-shift algorithm was proposed to replace the fixed step size in the Mean Shift algorithm with adaptive variable step size. Wavelet packet energy entropy was used to extract the characteristics of rolling bearing vibration signals, and a series of centroids were clustered by adaptive mean-shift after dimensionality reduction. The centroid in normal state was used as the reference centroid to calculate the offsets of all centroids (including reference centroid) and reference centroid. Experiments show that the adaptive mean-shift algorithm converges quickly and has high accuracy. The centroid offset can be used to monitor the structural health effectively.

A novel underwater bipedal walking soft robot bio-inspired by the coconut octopus

In order to increase the compatibility between underwater robots and the underwater environment and inspired by the coconut octopus’s underwater bipedal walking, a method was proposed for bipedal walking for an underwater soft robot based on a spring-loaded inverted pendulum (SLIP) model. Using the characteristics of octopus tentacles rolling on the ground, a wrist arm was designed using the cable-driven method, and an underwater SLIP bipedal walking model was established, which makes an underwater soft robot more suitable for moving on uneven ground. An underwater bipedal walking soft robot based on coconut octopus was then designed, and a machine vision algorithm was used to extract the motion information for analysis. Experimental analysis shows that the underwater bipedal walking robot can achieve an average speed of 6.48 cm s−1, and the maximum instantaneous speed can reach 8.14 cm s−1.

Physicochemical and sensory characteristics of egg roll from composite flour (mocaf, breadfruit flour, orange sweet potato flour, breadfruit starch, and orange sweet potato starch)

The aim of this study was to determine the formulation of composite flour from mocaf, breadfruit flour, orange sweet potato flour, breadfruit flour and orange sweet potato flour in making good quality egg rolls. The analysis was carried out using a completely randomized design with a composite flour formulation consisting of 8 composite flour treatments and 1 control treatment. The analysed parameters were ash content, moisture content, fat content, fibre content, protein content, carbohydrate content and colour. The suitable egg roll formulation was evaluated based on de-garmo method amongst several parameters (moisture content, ash content, protein content, fat content, hedonic content dan colour value). It was concluded that, composite flour formulations of 40% mocaf, 20% breadfruit flour, 20% orange sweet potato flour, 10% breadfruit starch, and 10% orange sweet potato starch produced the best egg rolls. The finding research suggests that wheat flour can be replaced by other flours for egg roll making.

CFD prediction of full-scale ship parametric roll in head wave

With the advances in available brute-force computing power, parallel computations (overset grid technology and meta-modeling) will eventually open a path to the widespread application of full-scale computations. This study presents a computational fluid dynamics (CFD) prediction of a full-scale ship parametric roll in a regular head wave. An in-house unsteady Reynolds-averaged Navier–Stokes (URANS) CFD code was used for the simulations. The ONR Tumblehome surface combatant was selected as the research object, and the full-scale ship was studied under the same conditions as the model tests. Comparisons between the CFD results and model test results from the reference show good agreement and validate that the code could capture the details of parametric roll phenomenon in head waves. The full-scale predictions were compared with the model-scale results to assess the scale effect of the parametric roll. The induced force and moment acting on the hull under the parametric roll were analyzed. Simulations for ships with bilge keels were also performed at model- and full-scale to evaluate the effect of bilge keels. Numerical results demonstrate that the in-house URANS code could be used to predict the parametric roll characteristics for a full-scale ship at the design stage in the future.

Forecast of mechanical properties of metal products

Introduction. The mechanical properties of the metal depend primarily on their chemical composition and structure. The structure of metal materials is formed under the influence of different temperature modes of manufacture and cooling. Models for predicting the mechanical properties of steels and cast irons are based on the influence of chemical composition and structure. The paper considers an approach that allows to evaluate the mechanical properties of rolling (C) cast iron rolls with a pearlitic (P) matrix depending on the complex influence of the elements of their chemical composition. Materials and methods. The working area of СПХН roll cast iron samples from the surface up to 50 mm doped with chromium (X) and nickel (H) was investigated. The carbide content varied from 10 to 15 %; and lamellar graphite did not exceed 2 %. The results of the experiment. In the work for modeling the mechanical characteristics of cast iron rolls used the method of planning experiments. The choice of this technique is due to the multi-parameter technology of production of solid metal casting. The application of this technique allowed to obtain models for predicting the mechanical characteristics of roll cast iron SPHN depending on the influence of the elements of the chemical composition of the rolls (C, Si, Mn, P, S, Cr, Ni). The error in predicting the tensile strength sВ, bending strength sзгин bending and hardness according to the Shore HSD method did not exceed 5,89 %. When checking the models for convergence of results by Fisher's criterion at a critical value of Fcrit = 2,400 for sВ, this coefficient was 1,249; for sзгин fold was 1,289 and for HSD - 1,012. To analyze the effect of carbon on mechanical characteristics, two-dimensional dependence plots are constructed. Conclusions. Within the operating values of the parameters of the chemical composition of cast iron rolling mills СПХН-45 in accordance with existing regulations, a forecast of their mechanical characteristics within the allowable limits of error of experimental data. The results of the work allow to obtain mathematical models in the process of production of rolls of the СПХН brand to quickly establish their chemical composition within the standard technology in accordance with the customer's requirements for these mechanical characteristics. In addition, the obtained models can predict these characteristics of the manufactured rolls with minimal material and time costs.
 Keywords: rolling mills; elements of chemical composition; mechanical characteristics; multiparameter technology

Comparative Study on Rolling Characteristics of Hexagonal Bar with Special Alloy for Advancing Drawing System

Comparative Study on Rolling Characteristics of Hexagonal Bar with Special Alloy for Advancing Drawing System

Assessment of dough rheological characteristics and soft bread roll quality of wheat flour incorporated with seaweed powder

PurposeThis study aims to investigate the effects of incorporating seaweed composite flour on soft roll dough rheological characteristics and quality.Design/methodology/approachIn this study, wheat flour was substituted with seaweed powder obtained from red seaweed (Kappaphycus alvarezii) at varying proportions (100:0; 99:1; 98:2; 97:3; 96:4; 95:5, 94:6, 93:7 and 92:8) and applied in soft roll production. The effects of seaweed composite flour were evaluated in terms of rheological characteristics, proximate composition and physical properties. The sensory characteristics of the soft rolls was evaluated by 40 untrained panellists by using a hedonic scale.FindingsFarinograph analysis of the soft roll doughs showed that the incorporation of seaweed powder promoted an increase in water absorption, development time and mixing tolerance index, whereas it decreased stability time. Analysis of the proximate composition of the soft rolls showed that protein and carbohydrate contents decreased, but moisture, ash and crude fibre contents substantially increased. Dietary fibre increased with the increase in the proportion of seaweed powder added. The specific volume, bulk density and firmness of the soft rolls ranged from 3.01 to 5.48 cm3/g, 0.18 to 0.33 g/cm3 and 1.86 to 20.63 N, respectively. Sensory evaluation results showed that the mean score of sensory attributes decreased as the proportion of seaweed powder added was increased in the formulations. With regard to the overall acceptability, the panellists preferred the soft rolls with the least amount of seaweed powder added. The results of hedonic tests revealed that the panellists' acceptance decreased as higher amounts seaweed powder were added in the formulations.Originality/valueThis study showed that the seaweed powder of K. alvarezii can be utilised as an ingredient to improve the nutrient composition of baked products.

Numerical analysis of pitch and rolling motions of trimaran in oblique waves

The coupled motion of roll and pitch is noticeable when trimaran sails in oblique head waves, which will lead to negative influence on the safety and comfort of navigation. In this paper, the numerical simulation of the trimaran's motion in oblique waves was carried out by open source CFD tool OpenFOAM, and the computed motion response was analyzed to study the characteristics of the torsional rolling. The OpenFOAM-based hybrid method used in this paper was briefly introduced first, and the numerical method was validated and verified by both the grid convergence test and the comparison with experimental result. Both the amplitude and the time history of the computed motion are used for analysis, and the influence of wave steepness, wave heading and forward speed of trimaran on the characteristics of torsional rolling was investigated. The result shows that the large wave steepness and the low forward speed will lead to dangerous torsional rolling motion of trimaran in oblique waves, and the dangerous condition is mainly caused by nonlinear rolling motion; the motion state is more sensitive and changing obviously with other factors at large wave steepness wave conditions.

Process Design of Pilot Warm Rolling Mill for Difficult-to-deform Materials Research

Due to the increasing demands for warm rolling research of difficult-to-deform materials, the State Key Laboratory of Rolling and Automation of Northeastern University (NEU-RAL) developed a set of pilot warm rolling mill with its functions including: rolled piece heating online, rolls heating online, hydraulic screwdown, tension control and reversing rolling. The rolls heating uses induction heating mode and the rolled piece heating adopts direct resistance heating way. The warm rolling process is designed based on the characteristics of pilot warm rolling mill. The AZ31 magnesium alloy samples were rolled successfully and demonstrated that warm rolling is an effective method to process difficult-to-deform materials. The new pilot warm rolling mill has been successfully put into use in several research institutes of China, it will contribute further studying on warm rolling characteristics of difficult-to-deform materials.

Research on vibration characteristics of mill rolls based on nonlinear stiffness of the hydraulic cylinder

Considering the nonlinear stiffness constraint action from the hydraulic cylinder in the four-high rolling mill process, the vertical vibration dynamic model with two degrees of freedom is established. The nonlinear vertical vibration equation of roll system contained the nonlinear stiffness of the hydraulic cylinder is established on the basis of D'Alembert's principle, and the amplitude-frequency response of the vibration system is obtained by using average method. According to the actual parameters of rolling mill, the influence of the nonlinear stiffness of the hydraulic cylinder and external force on the amplitude-frequency response of the rolling mill is analyzed. Based on it, the behavior of mill vibration under the effect of different nonlinear stiffness is studies. The results show that the nonlinear stiffness of the hydraulic cylinder is larger and the rolling mill system is more unstable. The mill vibration behavior will gradually converge to stability when the nonlinear stiffness is weaker, and the mill vibration will be in a state of instability and divergent when the nonlinear stiffness is stronger. This conclusion provides a theoretical basis to suppress vibration of rolling mill.

Thermal insulation characteristics of roll forming alumina ball material

Rolling ceramic thermal insulation balls have advantages of low cost, large output and easy control of particle size, so it is likely to become the main raw material for 3D printing in the future, but there is little research on its thermal insulation. In this study, we used three kinds of rolling aluminum oxide balls as raw materials to obtain single-granularity-level and multi-granularity-level bulk materials. And the effects of temperature, particle size, and thermal fatigue times on the thermal conductivity of the samples were analyzed. Additionally, the experimental results were verified by FloEFD heat conduction simulation software using finite analysis method to analyze their heat conduction characteristics. With the increase of temperature from 400 °C to 1500 °C, the thermal conductivity of single-granularity-level and multi-granularity-level bulk materials increased linearly. The thermal conductivity of single-granularity-level bulk materials have no direct relationship with the particle size, and the thermal conductivity of multi-granularity-level materials with small particle size difference was a bit lower than that of materials with large particle size difference, and a bit higher than that of materials with single-granularity-level. The simulation results showed that the main reason for the above phenomenon was that the point contact between particles played a dominating role in the heat transfer process. When the contact area increased, the thermal conductivity increased obviously, and the thermal conductivity with the increasing of temperature decreased in a quadratic curve. The improved model considering the shrinkage could improve accuracy of simulation results. Heat flux at the surface contact area was 10.19 times higher than that of the point contact and 15.10 times higher than that of the solid-gas contact at 400 °C. Therefore, reducing the surface contact area and increasing the porosity could significantly reduce the thermal conductivity of the materials.

Fault Diagnosis of Rolling Bearings Based on an Improved Stack Autoencoder and Support Vector Machine

In recent years, autoencoder has been widely used for the fault diagnosis of mechanical equipment because of its excellent performance in feature extraction and dimension reduction; however, the original autoencoder only has limited feature extraction ability due to the lack of label information. To solve this issue, this study proposes a feature distance stack autoencoder (FD-SAE) for rolling bearing fault diagnosis. Compared with the existing methods, FD-SAE has stronger feature extraction ability and faster network convergence speed. By analyzing the characteristics of original rolling bearing data, it is found that there are evident differences between normal data and faulty data. Therefore, a simple linear support vector machine (SVM) is used to classify normal data and faulty data, and then the proposed FD-SAE is used for fault classification. The novel combination of SVM and FD-SAE has simple structure and little computational complexity. Finally, the proposed method is verified on the rolling bearing data set of Case Western Reserve University (CWRU).

Vertical–Horizontal Coupling Vibration of Hot Rolling Mill Rolls under Multi-Piecewise Nonlinear Constraints

This study establishes a vertical–horizontal coupling vibration model of hot rolling mill rolls under multi-piecewise nonlinear constraints considering the piecewise nonlinear spring force and piecewise nonlinear friction force constraints of the hydraulic cylinder in the vertical direction of the rolls, the piecewise stiffness constraints in the horizontal direction, and the influence of the nonlinear dynamic rolling force in the rolling process. Using the average method to solve the amplitude–frequency response equation of the coupled vibration system and taking the actual parameters of a 1780 mm hot rolling mill (Chengde Steel Co., Ltd., Chengde, China) as an example, we study the amplitude–frequency characteristics of the mill rolls under different parameter settings. The results show that the amplitude and resonance region can be reduced by appropriately reducing the external disturbance force and the nonlinear spring force of the hydraulic cylinder, appropriately increasing the nonlinear friction force, and eliminating the gap between the bearing seat and the mill housing, to avoid the amplitude jump phenomenon due to piecewise variation. Furthermore, using the singularity theory to study the static bifurcation characteristics of the coupled vibration system, we establish a relationship between the vibration parameters and the topological bifurcation solution of the coupled system. The transition sets and their corresponding bifurcation topological structure in three cases are given, and the steady and unsteady process parameter regions of the rolls are obtained. The dynamic behavior of the coupled vibration system can be controlled by varying the bifurcation parameter. This study provides a theoretical basis for restraining the vibration of hot rolling mill rolls and optimizing the process parameters.

Effects of heat treatment on a novel continuous casting direct rolling 6056 aluminum alloy: cold rolling characteristics and tensile fracture properties

In this study, 6056 aluminum alloy produced through continuous casting direct rolling (CCDR) was investigated. This alloy is used in the automotive industry because of its high corrosion resistance and strength. However, the material may become embrittled as a result of excessive deformation during cold forging. Therefore, preheat treatment was employed to improve the formability of 6056 aluminum alloy. Five different preheating conditions were considered in this study: annealing (O), solution treatment (W), aging for 2 h at 195 °C after solution treatment (SPA195), aging for 2 h at 230 °C after solution treatment (SOA230), and aging for 2 h at 250 °C after solution treatment (SOA250). The results show that the over-aged specimen SOA250 exhibited the best formability and could compress 85% of the original diameter after cold rolling. However, the ductility decreased considerably after cold rolling. To increase ductility and strength, a T6 treatment was applied after cold rolling. The ductility and strength of the specimen were increased significantly, similar to the manner in which the ductility and strength of a raw material that has undergone T6 heat treatment. The CCDR 6056 aluminum alloys subjected to solution treatment and over-aging treatment exhibited good cold rolling formability, and with the subsequent T6 heat treatment, the alloys exhibited high strength and ductility. The materials can thus be used for the manufacture of automotive fasteners.

Coupled Vibration Characteristics Analysis of Hot Rolling Mill with Structural Gap

It is important to study the vibration of rolling mills to improve the stability of rolling production. A dynamic rolling process model is established by considering the elastic recovery of the exit strip and the influence of multiroll equilibrium, and the accuracy of the model is verified by experimental data. On this basis, based on the distribution of friction force in the deformation zone, the rolling force and rolling torque are nonlinearized. In addition, a rolling mill structure model is established by considering the structure gap and a piecewise nonlinear horizontal‐vertical‐torsional vibration model of the rolling mill is established by combining the structure model and dynamic rolling process model. Finally, the amplitude‐frequency characteristics of the work roll under different external excitation amplitude and the dynamic bifurcation characteristics of the work roll under different gaps are analyzed. The study indicates that, by reducing excitation amplitude and structure gap, the system vibration can be reduced. The research results can provide a theoretical reference for further exploration of the coupling vibration of hot rolling mills.

Rolling Bearing Fault Diagnosis Based on CEEMDAN and Refined Composite Multiscale Fuzzy Entropy

Considering the nonlinear and nonstationary characteristics of rolling bearing vibration signals, we propose a rolling bearing fault diagnosis method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), refined composite multiscale fuzzy entropy (RCMFE), Laplace score (LS), and the particle swarm optimization-probabilistic neural network (PSO-PNN). First, the method employs CEEMDAN to decompose the vibration signal and select the intrinsic mode functions (IMFs) containing the primary fault information via the frequency-domain correlation coefficient method. Then, it uses RCMFE to extract the characteristic information from the selected IMF. In addition, it uses LS to select and construct low-dimensional sensitive feature vectors, which are incorporated into the PSO-PNN model for diagnostic analysis to realize the state recognition of rolling bearing. Finally, the effectiveness of the method is verified by the analysis of the experimental data.

Design and Analysis of the Crawling and Rolling Characteristics of the Crawling and Rolling Robot for the Lunar Extreme Terrain

Design and Analysis of the Crawling and Rolling Characteristics of the Crawling and Rolling Robot for the Lunar Extreme Terrain

A Fault Diagnosis Method of Rolling Bearing Integrated with Cooperative Energy Feature Extraction and Improved Least-Squares Support Vector Machine

To solve the problem that the bearing fault of variable working conditions is challenging to identify and classify in the industrial field, this paper proposes a new method based on optimization of multidimension fault energy characteristics and integrates with an improved least-squares support vector machine (LSSVM). First, because the traditional wavelet energy feature is difficult to effectively reflect the characteristics of rolling bearing under different working conditions, based on analyzing the wavelet energy feature extraction in detail, a collaborative method of multidimension fault energy feature extraction combined with the method of Transfer Component Analysis (TCA) is constructed, which improves the discrimination between the different features and the compactness between the same features of rolling bearing faults. Then, for solving the problem of the local optimal of particle swarm optimization (PSO) in fault diagnosis and recognition of rolling bearing, an improved LSSVM based on particle swarm optimization and wavelet mutation optimization is established to realize the collaborative optimization and adjustment of LSSVM dynamic parameters. Based on the improved LSSVM and optimization of multidimensional energy characteristics, a new method for fault diagnosis of rolling bearing is designed. Finally, the simulation and analysis of the proposed algorithm are verified by the experimental data of different working conditions. The experimental results show that this method can effectively extract the multidimensional fault characteristics under variable working conditions and has a high fault recognition rate.

Mesoscopic Simulation Method for Uniaxial Compression Test of RCC Dam Material Based on DEM

The roller compacted concrete (RCC) dam has become one of the most competitive dam types due to its fast construction speed, low cost, and strong adaptability. However, the macroscale compaction test can hardly reflect the mesoscopic structure on the RCC’s rolling characteristics. According to the characteristics of RCC dam materials, a numerical discrete element method (DEM) is proposed in this paper, which is used to simulate the irregular shape and proportion of RCC aggregates. Moreover, a mesoscopic parameter inversion method based on the adaptive differential evolution (ADE) algorithm is proposed to enhance the efficiency of model contact parameters determination and overcome the inconvenience and time-consumption of conventional methods. Compared with the physical test, the simulation compression curve has good consistency with the physical test curve, and the proposed method can adequately reflect the physical and mechanical properties of RCC dam materials, which provides a basis for the subsequent research on the properties of RCC dam materials under different filling times.