Research on Rotating Machinery Fault Diagnosis Based on Improved Multi-target Domain Adversarial Network

Aiming at the problems of low efficiency,poor anti-noise and robustness of transfer learning model in intelligent fault diagnosis of rotating machinery,a new method of intelligent fault diagnosis of rotating machinery based on single source and multi-target domain adversarial network model(WDMACN)and Gram Angle Product field(GAPF)was proposed.Firstly,the original one-dimensional vibration signal is preprocessed using GAPF to generate the image data including all time series.Secondly,the residual network is used to extract data features,and the features of the target domain without labels are pseudo-labeled,and the transferable features among the feature extractors are shared through the depth parameter,and the feature extractors of the multi-target domain are updated anatomically to generate the features that the discriminator cannot distinguish.The modelt through adversarial domain adaptation,thus achieving fault classification.Finally,a large number of validations were carried out on the bearing data set of Case Western Reserve University(CWRU)and the gear data.The results show that the proposed method can greatly improve the diagnostic efficiency of the model,and has good noise resistance and generalization.

Shugan Jieyu capsule effects on peripheral blood micro-124, micro- 132, and brain-derived neurotrophic factor in patients with mild to moderate depression

BACKGROUND To assess the effectiveness of Shugan Jieyu capsules on peripheral blood miR-124,miR-132,and brain-derived neurotrophic factor(BDNF)levels in patients with mild to moderate depression following coronary artery intervention[percuta-neous coronary intervention(PCI)]for coronary heart disease.Patients with mild-to-moderate depression of the liver-qi stagnation type after PCI for coronary heart disease at the 305th Hospital of the People’s Liberation Army were enrolled from June 2022 to November 2023 and randomly assigned to two groups:Experimental(treated with Shugan Jieyu capsules)and control(tr-eated with escitalopram oxalate tablets).This study compared the antidepressant effects of these treatments using 17-item Hamilton Rating Scale for Depression(HAMD-17)scores,metabolic equivalents,low-density lipoprotein cholesterol,BDNF,high-sensitivity C-reactive protein levels,miR-124 and miR-132 levels,distribution of immune-related lymphocyte subsets,and traditional Chinese me-dicine syndrome scores before and after 6 weeks of treatment.RESULTS No significant difference was observed in any index between the two groups before treatment(P>0.05).After treatment,the total efficacy rates were 93.33%and 90.00%in the experimental and control groups,respectively.Experimental group had significantly lower scores for the main and secondary syndromes compared to the control group(P<0.05).No significant difference was observed in the metabolic equivalents between the two groups be-fore and after treatment(P>0.05).The levels of low-density lipoprotein cholesterol,high-sensitivity C-reactive pro-tein,and miR-132 were significantly lower,whereas those of miR-124,BDNF,CD3+T lymphocytes,CD3+CD4+T helper lymphocytes,and CD3+CD4+/CD3+CD8+cells were significantly higher in the experimental group com-pared to the control group(P<0.05).The incidence of adverse reactions during experimental group was signi-ficantly lower than that in control group(P<0.05).CONCLUSION Shugan Jieyu capsules have good efficacy in patients with mild-to-moderate depression after PCI,and its me-chanism may contribute to the regulation of miR-124,miR-132,BDNF levels,and lymphoid immune cells.

Weak Fault Feature Extraction of the Rotating Machinery Using Flexible Analytic Wavelet Transform and Nonlinear Quantum Permutation Entropy

Addressing the challenges posed by the nonlinear and non-stationary vibrations in rotating machinery,where weak fault characteristic signals hinder accurate fault state representation,we propose a novel feature extraction method that combines the Flexible Analytic Wavelet Transform(FAWT)with Nonlinear Quantum Permutation Entropy.FAWT,leveraging fractional orders and arbitrary scaling and translation factors,exhibits superior translational invariance and adjustable fundamental oscillatory characteristics.This flexibility enables FAWT to provide well-suited wavelet shapes,effectively matching subtle fault components and avoiding performance degradation associated with fixed frequency partitioning and low-oscillation bases in detecting weak faults.In our approach,gearbox vibration signals undergo FAWT to obtain sub-bands.Quantum theory is then introduced into permutation entropy to propose Nonlinear Quantum Permutation Entropy,a feature that more accurately characterizes the operational state of vibration simulation signals.The nonlinear quantum permutation entropy extracted from sub-bands is utilized to characterize the operating state of rotating machinery.A comprehensive analysis of vibration signals from rolling bearings and gearboxes validates the feasibility of the proposed method.Comparative assessments with parameters derived from traditional permutation entropy,sample entropy,wavelet transform(WT),and empirical mode decomposition(EMD)underscore the superior effectiveness of this approach in fault detection and classification for rotating machinery.

Exploration of Teaching Reform of Food Machinery and Equipment Course Based on New Engineering Concept

The new engineering concept aims to train high-quality engineering talents to meet the needs of future science and technology and industrial development through the reform of education and teaching.Under the background of"new engineering",by introducing cutting-edge knowledge of the industry and interdisciplinary integration,adopting innovative teaching methods such as project-driven teaching and flipped classroom,strengthening experimental teaching and school-enterprise cooperation,and establishing comprehensive evaluation and feedback mechanism,Food Machinery and Equipment course is reformed to improve the teaching quality and train high-quality engineering talents to meet the needs of modern food processing industry.

Impacts of Micro- and Nano-Plastics on Soil Properties and Plant Production in Agroecosystems: A Mini-Review

Micro- and nano-plastics (MNPs) are tiny plastic particles resulting from plastic product degradation. Soil MNPs have been identified as potential influential factors affecting various soil properties and crop biomass productivity. This mini-review provides a synthesis of recent findings concerning their effects on soil physicochemical properties, microorganisms, organic carbon content, soil nutrients, greenhouse gas emissions, soil fauna, and their impacts on plant ecophysiology, growth, and production. The results indicate that MNPs may markedly impede soil aggregation ability, increase porosity, decrease soil bulk density, enhance water retention capacity, influence soil pH and electrical conductivity, and escalate soil water evaporation. Exposure to MNPs may predominantly induce changes in soil microbial composition, reducing the diversity and complexity of microbial communities and microbial activity while enhancing soil organic carbon stability, influencing soil nutrient dynamics, and stimulating organic carbon decomposition and denitrification processes, leading to elevated soil respiration and methane emissions, and potentially decreasing soil nitrous oxide emission. Additionally, MNPs may adversely affect soil fauna, diminish seed germination rates, promote plant root growth, yet impair plant photosynthetic efficacy and biomass productivity. These findings contribute to a better understanding of the impacts and mechanistic foundations of MNPs. Future research avenues are suggested to further explore the impacts and economic implications.

Italian textile machinery orders remain stable in Q1 2024

For Italian textile machinery sector,2024 has begun without anything seemingly special.The first quarter has seen the orders index,as reported by the Economics Department of ACIMIT-the Association of Italian Textile Machinery Manufacturers-remain stationary compared to the same period the previous year.In absolute terms,the index came in at 61.2 points(basis:2021=100).

基于电子商务环境的农机管理系统设计

介绍了电子商务环境的背景和现状,详细描述了农机管理系统的实际需求和业务流程,并根据系统设计原则设计了系统总体架构,最后从人机管理、作业管理及综合信息等3个方面实现了农机管理系统。系统在测试过程中取得了较好的应用效果,是一种具有广泛应用前景的高效农机管理系统。

Summary and Improvement Measures for Soil Compaction Caused by Machinery

As agricultural mechanization is becoming more and more popular, soil compaction, on basis of agricultural machinery, has become a serious problem that can not be ignored. Soil compaction, which is caused by frequent til age and large load in the field, may have different effects on various properties of soil. Soil com-paction may result in different conditions, such as increased soil density and the mechanical resistance, and decreased soil ventilation and the capacity of water holding and storage, but uptaking capacity of chemical elements is restricted. There-fore, soil compaction has some negative impacts on soil properties, physical y, chemical y, or biological y, as wel as plant growth. This research analyzed the cause and the harm of soil compaction in recent years, and some effective mea-sures were proposed to improve soil compaction, in order to reduce the extent of soil compaction caused by agricultural machinery.

Technical Regulation of Foxtail Millet Production by Combining Machinery and Agronomy

In order to solve the problems of low production efficiency,great loss and low yield,Millet Research Institute of Hebei Academy of Agriculture and Forestry Sciences integrated the plastic film mulching technique and mechanized production technique,forming a foxtail millet production technique combining machinery and agronomy.The foxtail millet production technique combining machinery and agronomy regulates millet production from the links of soil preparation,fertilization,variety selection,seeding,intertillage and fertilization and harvest,so as to achieve the effects of promoting the matching between agro-machinery and agronomy,improving the level of millet production mechanization,realizing light simplified production and saving labor cost.This technical regulation has a broad application prospect.

水稻软盘毯状苗分离机设计与试验

目前,水稻种植环节中育秧环节与移栽环节之间的水稻苗盘分离环节的机械化程度相较于其他环节较为薄弱。为提高水稻全程机械化作业水平,降低生产成本,设计了一种适用于水稻毯状苗与塑料软盘分离的机械装置,主要由输送机构、分离机构、扶苗机构、集苗机构、动力系统和机架组成。对装置的结构及工作原理进行了描述,分析确定各个机构的结构参数。以分离率、茎叶损伤率、基质损伤率为试验指标进行苗盘分离试验,结果表明:水稻软盘毯状苗分离机作业效果较好,分离成功率在95%以上,能够降低生产成本,提高生产效率;茎叶损伤率及基质损伤率均在3%以下,保证后续水稻毯状苗移栽工作的顺利进行,较小的茎叶损伤与基质损伤也保证了后续水稻生长过程中不会受到较大的影响,满足水稻育秧农艺要求和水稻工厂化技术规范要求。

肉苁蓉种子离散元仿真参数标定

为寻求肉苁蓉种子离散元模型的物料特性参数,采用物理和仿真试验相结合的方法,以不同物性参数组合下肉苁蓉种子休止角为响应值,采用Plackett-Burman试验对参数进行筛选,获取显著性参数,即肉苁蓉种间静摩擦因数、肉苁蓉种间动摩擦因数、肉苁蓉种子-钢板静摩擦因数、肉苁蓉种子-钢板恢复系数。通过Box-Behnken试验建立休止角与显著性参数回归模型并优化,获取接触参数最优值,即肉苁蓉种间静摩擦因数为0.65、肉苁蓉种间动摩擦因数为0.07、肉苁蓉种子-钢板恢复因数为0.54、肉苁蓉种子-钢板静摩擦因数为0.43。通过仿真与物理试验对比验证,得到二者相对误差为2.05%,表明标定参数可为肉苁蓉种子播种机械仿真提供数据依据。

HIGHER ORDER SPECTRA AND ITS APPLICATION IN MACHINERY FAULT DIAGNOSIS

The application of higher order spectra to machinery faults diagnosis is studied in this paper.A brief review of bispectra is presented,and more emphasis is placed on the ability of higher order spectra to extract diagnostic information from fault signals.Furthermore,by use of the algorithm of higher order spectra,two kinds of typical mechanical faults are analyzed.Results show that the high order spectra analysis is a more efficient method in machinery diagnosis compared with the FFT based spectral analysis.

具有避障功能的农机自动作业全覆盖路径规划方法

针对不同尺寸和类型障碍物条件下的农机车辆自动作业全覆盖路径规划问题,提出了静态全覆盖路径规划方法和路径优化方案。根据矩形田块信息、障碍物信息、农机最小转弯半径和机具宽度,自动选定作业方向、作业行距、地头转弯区域和转弯模式等参数;根据障碍物形状、高覆盖率高作业路径比的需求,对算法进行优化调整,以达到更好的作业效果。软件仿真测试结果表明:对有小矩形障碍物的田块,改进后的算法覆盖率提升了0.11%,重复率降低了0.71%;对大矩形障碍物的田块,两种分区路径的覆盖率分别为89.24%和98.08%,重复率分别为3.53%和2.84%。研究结果表明:算法提高了田块的利用率,降低了作业成本,能够有效避开大小障碍物,同时满足高覆盖率和低重复率的田间作业要求。

云控制水肥药械智能监控平台的设计与实现

随着我国农业现代化水平的提高,以水肥药械为核心的现代农业服务体系成为未来行业发展的方向。为此,采用B/S结构模式,使用Django框架,选用MySQL数据库,设计并实现了一种云控制水肥药械智能监控平台。平台拥有完善的机构、数据交互、用户和权限等管理功能,可实现水肥药械的数字化管理;嵌入了基于Bi-LSTM与LightGBM融合的参考作物蒸散量预测方法,可实现对作物灌溉的实时预测;增加了作物施肥计算公式以及施肥用药数据库,可为用户对肥、药的施用提供科学的参考依据。实际运行及性能测试结果表明:平台的架构和模块设计合理,功能较全面和灵活,可有效满足设施园区对于水肥药械的管理需求,推动现代化农业发展。

MICRO-Ⅱ网络数据采集方案

从工厂底层自动化及信息集成技术角度 ,详细介绍了GD公司MICRO Ⅱ控制系统的特点及其网络结构 ,提出了实现MICRO Ⅱ系统网络数据采集的 2种解决方案的可行性。通过对MICRO Ⅱ数据采集的实现 ,完全可以改变GDX1/X2包装机组目前的“信息孤岛”状态。

Particle Swarm Optimization-Support Vector Machine Model for Machinery Fault Diagnoses in High-Voltage Circuit Breakers

According to statistic data,machinery faults contribute to largest proportion of High-voltage circuit breaker failures,and traditional maintenance methods exist some disadvantages for that issue.Therefore,based on the wavelet packet decomposition approach and support vector machines,a new diagnosis model is proposed for such fault diagnoses in this study.The vibration eigenvalue extraction is analyzed through wavelet packet decomposition,and a four-layer support vector machine is constituted as a fault classifier.The Gaussian radial basis function is employed as the kernel function for the classifier.The penalty parameter c and kernel parameterδof the support vector machine are vital for the diagnostic accuracy,and these parameters must be carefully predetermined.Thus,a particle swarm optimizationsupport vector machine model is developed in which the optimal parameters c andδfor the support vector machine in each layer are determined by the particle swarm algorithm.The validity of this fault diagnosis model is determined with a real dataset from the operation experiment.Moreover,comparative investigations of fault diagnosis experiments with a normal support vector machine and a particle swarm optimization back-propagation neural network are also implemented.The results indicate that the proposed fault diagnosis model yields better accuracy and e-ciency than these other models.

The application on order analysis for the rotating machinery with LabVIEW

Order analysis is regarded as one of the most significant method for monitoring and analyzing rotational machinery for the phenomenon of " frequency smear".However,the order analysis based on resampling is a signal processingwhich converts the constant time interval sampling into constant angle interval sampling,while with the variety of the rotational speed.The superiority of the order analysis is investigatedon implement of order analysis.Andthrough comparing the advantage and disadvantage between spectrum and order analysis,the paper will discuss the order analysis form a deep perspective.

Demodulation Based on Harmonic Wavelet and Its Application into Rotary Machinery Fault Diagnosis

The harmonic wavelet transform（HWT） and its fast realization based on fast Fourier transform（FFT） are introduced. Its ability to maintain the same amplitude-frequency feature is revealed. A new method to construct the time-frequency（TF） spectrum of HWT is proposed, which makes the HWT TF spectrum able to correctly reflect the time-frequency-amplitude distribution of the signal. A new way to calculate the HWT coefficients is proposed. By zero padding the data taken out, the non-decimated coefficients of HWT are obtained. Theoretical analysis shows that the modulus of the coefficients obtained by the new calculation way and living at a certain scale are the envelope of the component in the corresponding frequency band. By taking the cross section of the new TF spectrum, the demodulation for the component at a certain frequency band can be realized. A comparison with the Hilbert demodulation combined with band-pass filtering is done, which indicates for multi-components, the method proposed here is more suitable since it realizes ideal band-pass filtering and avoids pass band selecting. In the end, it is applied to bearing and gearbox fault diagnosis, and the results reflect that it can effectively extract the fault features in the signal.

DEVELOPMENT OF VIRTUAL INSTRUMENT IN CHARACTERISTIC ANALYSIS OF ROTATING MACHINERY BASED ON INSTANTANEOUS FREQUENCY ESTIMATION

Based on the recently quick-developing time-frequency analysis (TFA)technique and virtual instrument (VI) technique, a virtual instrument in characteristic analysis ofrotating machinery is researched and developed successfully. By utilizing instantaneous frequencyestimation (IFE) theoretics of TFA technique, and based on IFE of peak searching on thetime-frequency spectrum, order analysis (OA) functions is put forward and implemented, such as orderspectrum, order spectrum matrix, order tracking, order tracking filtering, and order componentextraction, etc. Unlike the home and abroad existing popular characteristic analyzers, which needkey phasing devices such as shaft encoder, phase-locked loop (PLL), phase-locked multiple frequency,tachometer, etc, to implement constant angle sampling directly or indirectly, whereas thisinstrument only uses the vibration signal of rotating machinery to carry out OA. This instrumentmakes up the shortage of these traditional instruments in analyzing the non-stationary signal ofrun-up and run-down process of rotating machinery. Therefore, it is a great breakthrough for theexisting order analyzers.

Osteoblast Behavior on Hierarchical Micro-/Nano-Structured Titanium Surface

In the present work, osteoblast behavior on a hierarchical micro-/nano-structured titanium surface was investigated. A hi- erarchical hybrid micro-/nano-structured titanium surface topography was produced via Electrolytic Etching （EE）. MG-63 cells were cultured on disks for 2 h to 7 days. The osteoblast response to the hierarchical hybrid micro-/nano-structured titanium surface was evaluated through the osteoblast cell morphology, attachment and proliferation. For comparison, MG-63 cells were also cultured on Sandblasted and Acid-etched （SEA） as well as Machined （M） surfaces respectively. The results show signifi- cant differences in the adhesion rates and proliferation levels of MG-63 cells on EE, SLA, and M surfaces. Both adhesion rate and proliferation level on EE surface are higher than those on SLA and M surfaces. Therefore, we may expect that, comparing with SLA and M surfaces, bone growth on EE surface could be accelerated and bone formation could be promoted at an early stage, which could be applied in the clinical practices for immediate and early-stage loadings.