Dynamic analysis of three-dimensional helical geared rotor system with geometric eccentricity

Yimin Zhang,Qibin Wang,Hui Ma,Jing Huang,Chunyu Zhao 대한기계학회 2013 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.27 No.11

A dynamic model of a multi-shaft helical geared rotor system is presented. Rotating shafts of the system are modeled as Timoshenko beams. A general three-dimensional dynamic model of helical gear pairs with geometric eccentricity is developed for the gear mesh and bearing flexibility is included in the model as well. The transmission error and gear geometric eccentricity are simulated as excitations. Eigenvalue solution and the modal summation technique are used to predict the natural frequencies and forced responses of the system. Then two geared rotor system models are presented for validation of the gear dynamic model. It is demonstrated that the gear mesh model is effective for general geared rotor systems, spur and helical gears, one-stage and multi-stage systems. Finally, forced responses of an example system are analyzed to demonstrate the influences of the helical gear geometric eccentricity and the coupling between gear geometric eccentricity and rotor mass unbalance.

Bio-protective potential of lactic acid bacteria: Effect of Lactobacillus sakei and Lactobacillus curvatus on changes of the microbial community in vacuum-packaged chilled beef

Zhang, Yimin,Zhu, Lixian,Dong, Pengcheng,Liang, Rongrong,Mao, Yanwei,Qiu, Shubing,Luo, Xin Asian Australasian Association of Animal Productio 2018 Animal Bioscience Vol.31 No.4

Objective: This study was to determine the bacterial diversity and monitor the community dynamic changes during storage of vacuum-packaged sliced raw beef as affected by Lactobacillus sakei and Lactobacillus curvatus. Methods: L. sakei and L. curvatus were separately incubated in vacuumed-packaged raw beef as bio-protective cultures to inhibit the naturally contaminating microbial load. Dynamic changes of the microbial diversity of inoculated or non-inoculated (control) samples were monitored at $4^{\circ}C$ for 0 to 38 days, using polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE). Results: The DGGE profiles of DNA directly extracted from non-inoculated control samples highlighted the order of appearance of spoilage bacteria during storage, showing that Enterbacteriaceae and Pseudomonas fragi emerged early, then Brochothrix thermosphacta shared the dominant position, and finally, Pseudomonas putida showed up became predominant. Compared with control, the inoculation of either L. sakei or L. curvatus significantly lowered the complexity of microbial diversity and inhibited the growth of spoilage bacteria (p<0.05). Interestingly, we also found that the dominant position of L. curvatus was replaced by indigenous L. sakei after 13 d for L. curvatus-inoculated samples. Plate counts on selective agars further showed that inoculation with L. sakei or L. curvatus obviously reduced the viable counts of Enterbacteraceae, Pseudomonas spp. and B. thermosphacta during later storage (p<0.05), with L. sakei exerting greater inhibitory effect. Inoculation with both bio-protective cultures also significantly decreased the total volatile basic nitrogen values of stored samples (p<0.05). Conclusion: Taken together, the results proved the benefits of inoculation with lactic acid bacteria especially L. sakei as a potential way to inhibit growth of spoilage-related bacteria and improve the shelf life of vacuum-packaged raw beef.

Reliability-based sensitivity of mechanical components with arbitrary distribution parameters

Yimin Zhang,Xiangdong He,Zhou Yang,Qiaoling Liu,Bangchun Wen 대한기계학회 2010 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.24 No.6

This paper presents a reliability-based sensitivity method for mechanical components with arbitrary distribution parameters. Techniques from the perturbation method, the Edgeworth series, the reliability-based design theory, and the sensitivity analysis approach were employed directly to calculate the reliability-based sensitivity of mechanical components on the condition that the first four moments of the original random variables are known. The reliability-based sensitivity information of the mechanical components can be accurately and quickly obtained using a practical computer program. The effects of the design parameters on the reliability of mechanical components were studied. The method presented in this paper provides the theoretic basis for the reliability-based design of mechanical components.

Models of Pseudomonas Growth Kinetics and Shelf Life in Chilled Longissimus dorsi Muscles of Beef

Zhang, Yimin,Mao, Yanwei,Li, Ke,Dong, Pengcheng,Liang, Rongrong,Luo, Xin Asian Australasian Association of Animal Productio 2011 Animal Bioscience Vol.24 No.5

The aim of this study was to confirm Pseudomonas spp. as the specific spoilage organism (SSO) of chilled beef during aerobic storage and to establish a model to predict the shelf life of beef. Naturally contaminated beef was stored at $4^{\circ}C$, and the spoilage limit of Pseudomonas organisms was determined by measuring several quality indicators during storage, including the number of Pseudomonas organisms, total number of bacteria, total volatile basic nitrogen (TVBN) values, L value color scale scores and sensory evaluation scores. The beef was then stored at 0, 4, 7, 10, 15 or $20^{\circ}C$ for varying amounts of time, and the number of Pseudomonas organisms were counted, allowing a corresponding growth model to be established. The results showed that the presence of Pseudomonas spp. was significantly correlated to each quality characteristic (p<0.01), demonstrating that Pseudomonas spp. are the SSO of chilled beef and that the spoilage limit was $10^{8.20}$ cfu/g. The Baranyi and Roberts equation can predict the growth of Pseudomonas spp. in beef, and the $R^2$ value of each model was greater than 0.95. The square root model was used as follows, and the absolute values of the residuals were less than ${0.05:\;{\mu_{max}}^{1/2}$ = 0.15604 [T+(-0.08472)] (p<0.01), $R^2$ = 0.98, $\lambda^{-1/2}$ = 0.0649+0.0242T (p<0.01, $R^2$ = 0.94). The model presented here describes the impact of different temperatures on the growth of Pseudomonas spp., thereby establishing a model for the prediction of the shelf life of beef stored between 0 to $20^{\circ}C$.

Kinetic studies of hemicellulose hydrolysis of corn stover at atmospheric pressure

Yimin Zhang,Xuebin Lu,Ying Liang,Jing Yang,Shuting Zhang,Eiji Suzuki 한국화학공학회 2008 Korean Journal of Chemical Engineering Vol.25 No.2

The object of this work was to study the xylose production by hydrolysis of corn stover with diluted sulfuric acid at 100 oC. Several concentrations of H2SO4 (2%, 4% and 6% w/w) and reaction time (0-300 min) were evaluated. Kinetic parameters of mathematical models for predicting the concentrations of xylose, glucose and furfural in the hydrolysates were found. Optimal conditions for hydrolysis were 5.5% H2SO4 at 100 oC for 60 min; under these conditions, 86.7% of xylose yield and 2.82 g/g selectivity were attained, leading to liquors containing up to 18.73 g/l xylose, 6.64 g/l glucose and 0.63 g/l furfural. The models could be successfully used to predict the concentrations of xylose, glucose and furfural within 0-300 min under experimental acid concentrations. Furthermore, the hydrolysis process of corn stover using dilute acid could be conceived as the first stage of an integrated strategy for corn stover utilization.

Effect of different short-term high ambient temperature on chicken meat quality and ultra–structure

Minghao Zhang,Lixian Zhu,Yimin Zhang,Yanwei Mao,Mingyue Zhang,Pengcheng Dong,Lebao Niu,Xin Luo,Rongrong Liang 아세아·태평양축산학회 2019 Animal Bioscience Vol.32 No.5

Objective: This study investigated the effect of different acute heat stress (HS) levels on chicken meat quality and ultra-structure. Methods: Chickens were randomly divided into 7 groups to receive different HS treatments: i) 36°C for 1 h, ii) 36°C for 2 h, iii) 38°C for 1 h, iv) 38°C for 2 h, v) 40°C for 1 h, vi) 40°C for 2 h, and vii) un-stressed control group (25°C). Blood cortisol level, breasts initial temperature, color, pH, water holding capacity (WHC), protein solubility and ultra-structure were analyzed. Results: HS temperatures had significant effects on breast meat temperature, lightness (L*), redness (a*), cooking loss and protein solubility (p<0.05). The HS at 36°C increased L*24 h value (p<0.01) and increased the cooking loss (p<0.05), but decreased a*24 h value (p<0.05). However, as the temperature increased to 38°C and 40°C, all the values of L*24 h, cooking loss and protein denaturation level decreased, and the differences disappeared compared to control group (p> 0.05). Only the ultimate pH24 h at 40°C decreased compared to the control group (p<0.01). The pH in 36°C group declined greater than other heat-stressed group in the first hour postmortem, which contributed breast muscle protein degeneration combining with high body temperature, and these variations reflected on poor meat quality parameters. The muscle fiber integrity level in group 40°C was much better than those in 36°C with the denatured position mainly focused on the interval of muscle fibers which probably contributes WHC and light reflection. Conclusion: HS at higher temperature (above 38°C) before slaughter did not always lead to more pale and lower WHC breast meat. Breast meat quality parameters had a regression trend as HS temperature raised from 36°C. The interval of muscle fibers at 24 h postmortem and greater pH decline rate with high body temperature in early postmortem period could be a reasonable explanation for the variation of meat quality parameters.

Heterogeneous Large-Scale Data Fusion Mechanism of Energy Storage Power Station Based on Neural Network

Yimin Deng,Zhoubo Weng,Tianlong Zhang 한국멀티미디어학회 2023 The journal of multimedia information system Vol.10 No.2

To solve the problems of many automation systems, diverse data standards, and duplication of information content in the current energy storage power station system, and to further improve the freshness, current situation and accuracy of the energy storage power station big data, the heterogeneous large energy storage power station. The fusion of large-scale data has become a general trend. The usual data fusion algorithm is to fuse the features of sensor data in different spaces at the same time. Among them, the deep convolutional neural network (DCNN) has outstanding fusion performance, and realizes the integration of feature extraction, information association, and decision-making judgment by utilizing multiple convolutional layers, pooling layers, and fully connected layers. This paper proposes a data fusion algorithm based on convolutional neural network (AbDCNN-DAE). The algorithm introduces a denoising autoencoder and an attention mechanism, which can fuse data from various aspects to realize the arrangement of disorganized power grid data. The experimental results compared with other methods show that the algorithm proposed in this paper has better performance.

An active learning hybrid reliability method for positioning accuracy of industrial robots

Dequan Zhang,Song Liu,Jinhui Wu,Yimin Wu,Jie Liu 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.8

Popsitioning accuracy is an important index for evaluating the capacity of industrial robots. As a mechanism with multi-degree of freedom, the uncertainties of industrial robots are diverse and analyzing the positioning accuracy reliability is time consuming. To improve computation efficiency, a new active learning method based on Kriging model is proposed for hybrid reliability analysis of positioning accuracy with random and interval variables. In this study, the updated samples were selected through U learning function in the vicinity of limit-state function. A new stopping criterion based on expected risk function was exploited to judge whether the accuracy of Kriging model is enough. Two numerical examples and one engineering example were provided to verify the efficiency and accuracy of the proposed method. The results indicate that the proposed method is accurate and efficient.

Elastic buckling performance of FG porous plates embedded between CNTRC piezoelectric patches based on a novel quasi 3D-HSDT in hygrothermal environment

Yujie Zhang,Zhihang Guo,Yimin Gong,Jianzhong Shi,Mohamed Hechmi El Ouni,Farhan Alhosny Techno-Press 2023 Advances in nano research Vol.15 No.2

The under-evaluation structure includes a functionally graded porous (FGP) core which is confined by two piezoelectric carbon nanotubes reinforced composite (CNTRC) layers. The whole structure rests on the Pasternak foundation. Using quasi-3D hyperbolic shear deformation theory, governing equations of a sandwich plate are driven. Moreover, face sheets are subjected to the electric field and the whole model is under thermal loading. The properties of all layers alter continuously along with thickness direction due to the CNTs and pores distributions. By conducting the current study, the results emerged in detail to assess the effects of different parameters on buckling of structure. As instance, it is revealed that highest and lowest critical buckling load and consequently stiffness, is due to the V-A and A-V CNTs dispersion type, respectively. Furthermore, it is revealed that by porosity coefficient enhancement, critical buckling load and consequently, stiffness reduces dramatically. Current paper results can be used in various high-tech industries as aerospace factories.

Improved exact confidence intervals for a proportion using ranked-set sampling

Jesse Frey,Yimin Zhang 한국통계학회 2019 Journal of the Korean Statistical Society Vol.48 No.3

We develop new exact confidence intervals for a proportion using ranked-set sampling (RSS). The existing intervals arise from applying the method of Clopper and Pearson (1934) to the total number of successes. We improve on the existing intervals by using the method of Blaker (2000) and by replacing the total number of successes with the maximum likelihood estimator of the proportion. The new intervals outperform the existing intervals in terms of average expected length, and they are also good in an absolute sense, as they come within a few percentage points of a new theoretical bound on the average expected length. Like the existing intervals, the new intervals use a perfect rankings assumption. They are no longer exact under imperfect rankings, but provide coverage close to nominal for mild departures from perfect rankings.