Real-Time Intelligent Diagnosis of Co-frequency Vibration Faults in Rotating Machinery Based on Lightweight-Convolutional Neural Networks

The co-frequency vibration fault is one of the common faults in the operation of rotating equipment,and realizing the real-time diagnosis of the co-frequency vibration fault is of great significance for monitoring the health state and carrying out vibration suppression of the equipment.In engineering scenarios,co-frequency vibration faults are highlighted by rotational frequency and are difficult to identify,and existing intelligent methods require more hardware conditions and are exclusively time-consuming.Therefore,Lightweight-convolutional neural networks(LW-CNN)algorithm is proposed in this paper to achieve real-time fault diagnosis.The critical parameters are discussed and verified by simulated and experimental signals for the sliding window data augmentation method.Based on LW-CNN and data augmentation,the real-time intelligent diagnosis of co-frequency is realized.Moreover,a real-time detection method of fault diagnosis algorithm is proposed for data acquisition to fault diagnosis.It is verified by experiments that the LW-CNN and sliding window methods are used with high accuracy and real-time performance.

Molecular diagnosis and direct quantification of cereal cyst nematode(Heterodera filipjevi) from field soil using TaqMan real-time PCR

Heterodera filipjevi continues to be a major threat to wheat production worldwide.Rapid detection and quantification of cyst nematodes are essential for more effective control against this nematode disease.In the present study,a TaqManminor groove binder(TaqMan-MGB)probe-based fluorescence quantitative real-time PCR(qPCR)was successfully developed and used for quantifying H.filipjevi from DNA extracts of soil.The primers and probe designed from the obtained RAPD-SCAR marker fragments of H.filipjevi showed high specificity to H.filipjevi using DNA from isolatesconfirmed species of 23 Heterodera spp.,1 Globodera spp.and 3 Pratylenchus spp.The qPCR assay is highly sensitive and provides improved H.filipjevi detection sensitivity of as low as 4^(-3) single second-stage juvenile(J2)DNAs,10^(-3) female DNAs,and 0.01μgμL^(-1) genomic DNAs.A standard curve relating to the threshold cycle and log values of nematode numbers was generated and validated from artificially infested soils and was used to quantify H.filipjevi in naturally infested field soils.There was a high correlation between the H.filipjevi numbers estimated from 32 naturally infested field soils by both conventional methods and the numbers quantified using the qPCR assay.qPCR potentially provides a useful platform for the efficient detection and quantification of H.filipjevi directly from field soils and to quantify this species directly from DNA extracts of field soils.

Machine learning for parameters diagnosis of spark discharge by electro-acoustic signal

Discharge plasma parameter measurement is a key focus in low-temperature plasma research.Traditional diagnostics often require costly equipment,whereas electro-acoustic signals provide a rich,non-invasive,and less complex source of discharge information.This study harnesses machine learning to decode these signals.It establishes links between electro-acoustic signals and gas discharge parameters,such as power and distance,thus streamlining the prediction process.By building a spark discharge platform to collect electro-acoustic signals and implementing a series of acoustic signal processing techniques,the Mel-Frequency Cepstral Coefficients(MFCCs)of the acoustic signals are extracted to construct the predictors.Three machine learning models(Linear Regression,k-Nearest Neighbors,and Random Forest)are introduced and applied to the predictors to achieve real-time rapid diagnostic measurement of typical spark discharge power and discharge distance.All models display impressive performance in prediction precision and fitting abilities.Among them,the k-Nearest Neighbors model shows the best performance on discharge power prediction with the lowest mean square error(MSE=0.00571)and the highest R-squared value(R^(2)=0.93877).The experimental results show that the relationship between the electro-acoustic signal and the gas discharge power and distance can be effectively constructed based on the machine learning algorithm,which provides a new idea and basis for the online monitoring and real-time diagnosis of plasma parameters.

A Study on FMS's Real-time Fault Diagnosis Expert System

ＡＳｔｕｄｙｏｎＦＭＳ＇ｓＲｅａｌ－ｔｉｍｅＦａｕｌｔＤｉａｇｎｏｓｉｓＥｘｐｅｒｔＳｙｓｔｅｍＸＩＡＯＸｉａｎｇｓｈｅｎｇ；ＬＩＵＷｅｎｊｉａｎ；ＳＵＢａｏｈｕａ；ＭＡＹｕｌｉｎ（肖祥胜，刘文剑，苏宝华，马玉林）（ＦＭＳＲｅｓｅａｒｃｈＣｅｎｔｅｒ...

STUDY OF REAL-TIME EXPERT SYSTEM TOOL FOR INDUSTRIAL FAULT MONITORING AND DIAGNOSIS

From the requirements of industrial production,an integrated fault monitoring,diagnosis and repairing system is suggested in this paper. This new scheme of fault monitoring and diagnosis system is realized by a master-slave real-time expert system,and a real-time expert system tool for this system is also developed accordingly. As an example of application of this tool ,a realtime expert system for fault monitoring and diagnosis on DC mine hoist is developed. Experiments show that this tool possesses better supporting environment, strong knowledge acquisition ability, and convenience for use. The system developed by this tool not only meets the real-time requirement of DC hoist,but also can give correct diagnosis results.

Value of Real-Time Bedside Ultrasonography in the Etiologic Diagnosis of Acute Dyspnea

Objective: To explore the value of real-time bedside ultrasonography in the etiologic diagnosis of acute dyspnea. Methods: Sixty-two patients with acute dyspnea who were treated in our hospital from January 2016 to December 2020 were randomly selected and their clinical data were retrospectively analyzed. All patients were randomly divided into a control group for routine examinations (n = 31) and an observation group for real-time beside ultrasonography (n = 31). The costs of medical examinations, examination duration, and diagnostic results of severe pneumonia, acute cardiogenic pulmonary edema, pulmonary embolism, chronic obstructive pulmonary disease, and pneumothorax (including sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy) of the two groups of patients were compared and analyzed. Results: Compared with the control group, the observation group had significantly shorter examinations (P < 0.05). Although the cost of medical examinations of the observation group tended to be higher, the difference between groups was not significant (P > 0.05). Moreover, there were no significant differences in left ventricular ejection fraction, left ventricular end-diastolic diameter, or brain natriuretic peptide between the two groups (P > 0.05). Comparison of the etiologic diagnosis results between the two groups showed that the observation group had significantly higher diagnostic sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy for various causes compared with the control group (P < 0.05). Conclusion: Real-time bedside ultrasonography for the etiologic diagnosis of patients with acute dyspnea was quicker and had higher diagnostic accuracy;thus providing accurate guidance for the disease treatment, and having a higher promotional value in clinical practice compared with routine examinations.

Malfunction Diagnosis of the GTCC System under All Operating Conditions Based on Exergy Analysis

After long-term operation,the performance of components in the GTCC system deteriorates and requires timely maintenance.Due to the inability to directly measure the degree of component malfunction,it is necessary to use advanced exergy analysis diagnosis methods to characterize the components’health condition(degree of malfunction)through operation data of the GTCC system.The dissipative temperature is used to describe the degree of malfunction of different components in the GTCC system,and an advanced exergy analysis diagnostic method is used to establish a database of overall operating condition component malfunctions in theGTCC system.Ebsilon software is used to simulate the critical parameters of the malfunctions of the GTCC system components and to obtain the changes in the dissipative temperature of different components.Meanwhile,the fuel consumption and economic changes of the GTCC system on a characteristic power supply day under health and malfunction conditions are analyzed.Finally,the effects of maintenance costs,electricity,and gas prices on maintenance expenses and profits are analyzed.The results show that the GTCC system maintenance profit is 6.07$/MWh,while the GTCC system maintenance expense is 5.83$/MWh.Compared with the planned maintenancemode,the malfunction maintenance mode saves 0.24$/MWh.Simultaneously,the maintenance coefficient of GTCC should be adjusted under different malfunctions to obtain a more accurate maintenance period.

Tools for the diagnosis of hepatitis C virus infection and hepatic fibrosis staging

Hepatitis C virus(HCV)infection represents a major public health issue.Hepatitis C can be cured bytherapy,but many infected individuals are unaware of their status.Effective HCV screening,fast diagnosis and characterization,and hepatic fibrosis staging are highly relevant for controlling transmission,treating infected patients and,consequently,avoiding end-stage liver disease.Exposure to HCV can be determined with high sensitivity and specificity with currently available third generation serology assays.Additionally,the use of point-of-care tests can increase HCV screening opportunities.However,active HCV infection must be confirmed by direct diagnosis methods.Additionally,HCV genotyping is required prior to starting any treatment.Increasingly,high-volume clinical laboratories use different types of automated platforms,which have simplified sample processing,reduced hands-on-time,minimized contamination risks and human error and ensured full traceability of results.Significant advances have also been made in the field of fibrosis stage assessment with the development of non-invasive methods,such as imaging techniques and serum-based tests.However,no single test is currently available that is able to completely replace liver biopsy.This review focuses on approved commercial tools used to diagnose HCV infection and the recommended hepatic fibrosis staging tests.

Diagnosis of Mycobacterium tuberculosis using molecular biology technology

Objective:To present an integrated molecular biology dedicated system for tuberculosis diagnosis.Methods:One hundred and five sputum specimens from patients strongly suspected by clinical parameters of tuberculosis were studied by Ziehl-Neelsen staining,by cultivation on solid medium and by a balanced hemincsted fluorometric PCR system(Orange C3TB) that could preserve worker safety and produce a rather pure material free of potential inhibitors. DNA amplification was performed in a low cost tuberculosis termocycler-fluorotneter.Produced double stranded DNA was flurometrically detected.The whole reaction was conducted in one single tube which would not be opened after adding the processed sample in order to minimize the risk of cross contamination with amplicons.Results:The assay was able to delect 30 bacillus per sample mL with 99.8%interassay variation coefficient.PCR was positive in 23(21.9%) tested samples(21 of them were smear negative).In our study it showed a preliminary sensitivity of 94.5%for sputum and an overall specificity of 98.7%.Conclusions:Total run time of the test is 4 h with 2.5 real working time.All PCR positive samples are also positive by microbiological culture and clinical criteria.Results show that it could be a very useful tool to increase detection efficiency of tuberculosis disease in low bacilus load samples.Furthermore,its low cost and friendly using make it feasible to run in poor regions.

Diagnosis of cytomegalovirus encephalitis using metagenomic nextgeneration sequencing of blood and cerebrospinal fluid:A case report

BACKGROUND Cytomegalovirus(CMV)infections in the population are mostly subclinical,inapparent,or latent.However,it is rare in brain tissue.Most reported CMV encephalitis cases were patients with immunodeficiency.The diagnosis and detection rate of CMV encephalitis in patients with normal immune function needs to be further improved.CASE SUMMARY An 86-year-old male was admitted due to a sudden onset of unconsciousness for 3 h.The patient developed status epilepticus and was relieved after antiepileptic treatment.Encephalitis was considered due to the high signals of diffusionweighted imaging sequences in the right central region by magnetic resonance imaging.Metagenomic next-generation sequencing(mNGS)of blood and cerebrospinal fluid revealed CMV,with unique reads number being 614 and 1,respectively.Simultaneous quantitative PCR results showed CMV positive in blood samples and negative in cerebrospinal fluid samples.The patient was finally diagnosed as CMV encephalitis with status epilepticus.After the antiviral,hormonal,andγ-globulin pulse therapy,the patient’s condition improved,and he was finally discharged.CONCLUSION mNGS could be a reliable approach for the diagnosis of CMV encephalitis,with high efficiency,sensitivity,and specificity.

Design on Vibration Monitoring and Fault Diagnosis System of Large Water Pump Motor

Large water pump motor,whose operation decides the reliability of the whole production line,plays a very important role.Therefore,its online condition monitoring can help companies better know its operation,process fault analysis and protection.The essay mainly studies and designs large water pump motor′s real time vibration monitoring and fault diagnosis system.The essay completes the systems project design,the establishment of the system and performance test.Eddy-currentsensor,XM-120 vibration module,XM-320 axial translation module,XM-362 temperature module,XM-360 process amount module and XM-500 gateway module are used to measure the axial vibration and displacement of main motors.Laboratory tests prove that the system can meet the requirements of motor vibration monitoring.

A Novel Real-Time Fault Diagnostic System for Steam Turbine Generator Set by Using Strata Hierarchical Artificial Neural Network

The real-time fault diagnosis system is very great important for steam turbine generator set due to a serious fault results in a reduced amount of electricity supply in power plant. A novel real-time fault diagnosis system is proposed by using strata hierarchical fuzzy CMAC neural network. A framework of the fault diagnosis system is described. Hierarchical fault diagnostic structure is discussed in detail. The model of a novel fault diagnosis system by using fuzzy CMAC are built and analyzed. A case of the diagnosis is simulated. The results show that the real-time fault diagnostic system is of high accuracy, quick convergence, and high noise rejection. It is also found that this model is feasible in real-time fault diagnosis.

Established and Emerging Optical Technologies for the Real-Time Detection of Cervical Neoplasia: A Review

Cervical cancer remains a critically important problem for women, especially those women in the developing world where the case-fatality rate is high. There are an estimated 528,000 cases and 266,000 deaths worldwide. Established screening and detection programs in the developed world have lowered the mortality from 40/100,000 to 2/100,000 over the last 60 years. The standard of care has been and continues to be: a screening Papanicolaou smear with or without Human Papilloma Virus (HPV) testing;followed by colposcopy and biopsies and if the smear is abnormal;and followed by treatment if the biopsies show high grade disease (cervical intraepithelial neoplasia (CIN) grades 2 and 3 and Carcinoma-in-situ). Low grade lesions (Pap smears with Atypical Cells of Uncertain Significance (ASCUS), Low Grade Squamous Intraepithelial Lesions (LGSIL), biopsies showing HPV changes or showing CIN 1);are usually followed for two years and then treated if persistent. Treatment can be performed with loop excision, LASER, or cryotherapy. Loop excision yields a specimen which can be reviewed to establish the diagnosis more accurately. LASER vaporizes the lesion and cryotherapy leads to tissue destruction. Under long term study;loop excision, LASER, and cryotherapy have the same rate of cure. The standard of care is expensive and takes 6 - 12 weeks for the individual patient. During the last twenty years, new technologies that can view the cervix and even image the cervix with cellular resolution have been developed. These technologies could lead to a new paradigm in which diagnosis and treatment occurs at a single visit. These technologies include fluorescence and reflectance spectroscopy (probe or wide-field, whole cervix scanning approaches) and fluorescence confocal endomicroscopy or high resolution micro-endoscopy. Both technologies have received Federal Drug Administration (FDA) and have been commercialized. Research trials continue to show their remarkable performance. These technologies are reviewed and clinical trials are summarized. Emerging technologies are coming along that may compete with those already approved and include optical coherence tomography, optical coherence tomography with autofluorescence, diffuse optical microscopy, and dual mode micro-endoscopy. These technologies are also reviewed and where available, clinical data is reported. Optical technologies are ready to diffuse into clinical practice because they will save money and 3 or 4 visits in the developed world and offer the same standard of care to the developing world where more cervical cancer exists.

新能源汽车的故障及其维修技术研究

本文介绍了新能源汽车的背景和发展现状,分析新能源汽车可能出现的故障后,将其分为变速器故障、驱动电机故障以及空调系统故障等。在此基础之上,分析比较了新能源汽车的检修和维修技术,包括故障诊断技术、维修设备和工具、维修流程和服务能力等,以期为相关工作的开展提供参考。

秦EV轿车无钥匙启动失效故障诊断与排除

随着新能源汽车的渗透率不断升高,售后维修的压力随之增大。文章以比亚迪秦EV为例,阐述了无钥匙进入系统和无钥匙启动的工作原理,引入秦EV无钥匙启动系统组合故障案例,在诊断过程中,从故障现象、故障原因分析、维修资料查阅、诊断测试、故障机理五个方面详细的介绍了组合故障的排除过程。结果表明,该诊断思路能够快速排除故障,提高效率,可为职业院校师生和售后维修从业人员在维修教学过程提供借鉴意义。

美卓HP800圆锥破碎机常见故障及处理方法

针对美卓HP800圆锥破碎机常见故障进行了全面、深入的研究,包括机械、液压和电控系统的故障类型,并依据多学科理论如轴承学、流体力学和电子工程,结合实际操作经验,提出了一系列具有针对性和高实用性的解决方案。这些措施有效减少了设备的停机时间,显著提高了整体系统的可靠性和效率,为设备生产的稳定性提供了科学依据,有助于推动相关企业和技术人员在设备管理和维护方面达到更高的工作水平,对矿山设备管理和维护实践具有重要参考价值。

比亚迪秦EV高压上电逻辑及故障诊断思路

随着全球汽车产业的绿色转型,新能源汽车逐渐成为市场新宠,纯电动汽车的故障检修人员也成为汽车后市场的亟需人才,本文以比亚迪秦EV为例,旨在探讨高压上电逻辑、高压上电流程中的常见故障,以及高压不能上电的故障诊断思路。通过对高压上电逻辑的深入分析,了解影响高压上电的关键因素,并结合实际案例,提出有效的故障诊断方法和解决方案,为新能源汽车的故障检修提供了宝贵的经验和参考。

探析工业电机设备故障的诊断与检排技术

针对电机设备常见故障的诊断特点,介绍了电机设备常见故障的诊断方法,研究了电机设备常见故障的种类、原因分析及检排方法,提出了三相异步电动机故障分析及排除。

数控机床常见故障诊断与维护技术分析

数控机床作为现代制造业的重要装备,其故障诊断和维修技术的研究意义重大。对数控机床常见的故障类型进行了分析,包括电气故障、机械故障、软件故障等,对振动分析、热成像检测、系统自诊断技术等相应的故障诊断方法,结合实际案例进行了深入的探讨。在此基础上,提出了提高数控机床的运行可靠性,减少停机时间,降低维修费用的有效维修技术策略。

贝叶斯网络支持下的计算机硬件系统故障诊断分析

文章首先分析了硬件故障的特性,提出了将概率图模型作为解决方案的思路,接着详细介绍了如何构建反映系统拓扑和组件间依赖关系的贝叶斯网络模型,最终实施了包括数据采集、学习和预测在内的完整流程。服务器集群实际验证表明,该模型能够以高达89%的准确率进行故障诊断,且预测时间最多可提前1.5 h,显示出明显优于传统规则方法的智能化和动态化特点。