Frequency Of Defects Research Articles

Fault Characteristics Analysis of High-Speed Train Transmission Systems

The high-speed train speed has a higher requirement for stability and operating safety with its operating speed increasing. The main focus of this paper is on the fault characteristics analysis of a high-speed train transmission system. The governing equation and boundary conditions of the transmission system are derived using the finite element method, in which a Timoshenko beam element is introduced to represent the wheelset shaft, and a rigid mass element is utilized to represent the gears, bearings, and wheels. To investigate the vibration response mechanism of a high-speed train transmission system, the critical speed of the system and its modal response are given. According to the types of high-speed train component fault features, the local fault features of gear, bearing, and wheelset are given. Healthy and faulty systems with localized faults in gear, bearing, and wheelset are studied. The characteristics of amplitude and frequency are verified numerically and the transmission characteristics of signal and relation are explained when there is local fault defect in the system. The results show that under different fault types, the time domain response of the system has obvious periodic impulse response faults, and the fault frequency band characteristic distribution is different in the frequency domain response. The simulation results are consistent with the experimental results.

The fault frequency priors fusion deep learning framework with application to fault diagnosis of offshore wind turbines

In fault diagnosis, deep learning plays an important role, but still lacks good interpretability. To address this issue, we develop a novel fault frequency priors fusion deep learning (FFP-DL) framework by introducing fault frequency priors into deep learning. The FFP-DL framework contains two branches: fault frequency priors learning branch (FFPLB) and self-learning branch (SLB). We then propose a pre-training algorithm which can shorten the overall training time especially for training multiple models simultaneously. To illustrate its efficacy, we take convolutional neural network (CNN) as the specific deep learning model in the FFP-DL framework (FFP-CNN), and apply the FFP-CNN model to a private offshore wind turbines (OWTs) data. The experimental results show that the FFP fusion does help improve the performance of fault diagnosis in terms of accuracy and Marco-F1-score and provide good interpretability to the diagnosis results with the distinguished feature of predicted FFP. With the training data reduction, the performance of the FFP-CNN model does not deteriorate quickly, which implies that this framework is also suitable for less data. In addition, the result reveals the fact that the pre-training algorithm does reduce convergence epochs, which will help the FFP-CNN model train faster during the training process.

TMSST-CK fault feature extraction method for flexible thin-wall bearing based on the Gini index principle

A flexible thin-wall bearing (FTB) is forced to deform with the elastic deformation of the flexspline in motion, resulting in a completely different fault characteristic frequency (FCF) from ordinary rolling bearings. However, current extraction methods treat FTBs as ordinary ones and they are analyzed based on the spectrum, without considering the time-varying nature of the FCF in an FTB. In an effort to address this concern, this paper proposes a Gini index-based time-reassigned multisynchrosqueezing transform, where the window size is determined by the period impulses feature in the noise-removed signal. In addition, a frequency point selection method that contains fault characteristics of the FTB is proposed by calculating the maximum correlated kurtosis in the time–frequency (TF) plane. Furthermore, the instantaneous frequency is extracted by calculating the time interval between two consecutive impulses. The extracted fault frequency agrees well with the experimental result and outperforms other TF analysis techniques in demonstrating its time-varying nature.

Fault Types and Frequencies in Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: An Industry Survey

Predictive Maintenance 4.0 (PdM 4.0) showed a highly positive impact on chilled water system (CWS) maintenance. This research followed the recommendations of a systematic literature review (SLR), which was performed on PdM 4.0 applications for CWS at commercial buildings. Per the SLR, and to start making an excellent PdM 4.0 program, the faults and their frequencies must be identified. Therefore, this research constructed an industry survey, which went through a pilot study, and then shared it with 761 maintenance officers in different commercial buildings. The first goal of this survey is to verify the faults reported by SLR, explore more faults, and suggest a managerial solution for each fault. The second goal is to determine the minimum and maximum frequencies of faults occurrence, while the third goal is to verify selected operational parameters, in which their data can be used in smart buildings applications. A total of 304 responses are considered in this study, which identified additional faults and provided faults solutions for all CWS components. Based on the survey outcomes, justifiable frequencies are proposed, which can be used in creating the dataset of any machine learning model, and then to control the CWS performance.

Overcoming the Technical Challenges of Total Knee Arthroplasty in Patients Affected by Hereditary Multiple Exostoses: a Case Report and Literature Review

Hereditary multiple exostoses (HME), also known as familiar osteochondromatosis or diaphyseal aclasis, are an autosomal dominant inherited genetic pathology that is characterized by the presence of multiple benign osteochondromas. Knee deformity is common in patients with HME, with nearly a third of patients developing genu valgus. Total knee arthroplasty (TKA) has been used to correct valgus deformities with advanced knee osteoarthritis (OA). However, concomitant limb deformities and altered anatomy of the knee make this surgery particularly challenging. We present a case report and a mini-review of the literature on this topic. We present the case of a 50-year-old Caucasian woman, affected by hereditary multiple exostoses, who came to our attention for progressive pain in the right knee. Upon further examination, the knee had a prominent valgus alignment, concomitant valgus instability, and flexion contraction. The patient was treated with total knee arthroplasty using a semi-constrained design. The patient was re-evaluated at 24-month follow-up, and there were no signs of implant loosening, the knee function improved significantly, and the patient was very satisfied. Given the recurring technical difficulties of such procedure in these patients, we describe our experience as well as the need for preoperative planning, the use of appropriate constraint when required, the high frequency of ligament instability, bony defects, and patellar maltracking. TKA must be considered when necessary, in these patients, as good to excellent clinical results can be achieved and maintained, allowing for significant improvements in quality of life.Core Tips- TKA in HME-affected patients carries specific but manageable challenges.- Due to bone deformities and frequent severe valgus knee alignment, TKA should be considered even in younger patients.- Revision implants provide the flexibility and the necessary fixation, not always achievable with primary implants.- Bigger size components may be necessary in HME patients compared with patients of the same height.- Lateral ligament releases may often be necessary due to long-standing valgus deformity. If stability cannot be achieved, the use of a hinged implant should be considered.- Cementation of the metaphysis or the use of sleeves can provide additional rotational stability to the implant.

The effect of induction immunosuppression for kidney transplant on the latent HIV reservoir.

The HIV latent viral reservoir (LVR) remains a major challenge in the effort to find a cure for HIV. There is interest in lymphocyte-depleting agents, used in solid organ and bone marrow transplantation to reduce the LVR. This study evaluated the LVR and T cell receptor repertoire in HIV-infected kidney transplant recipients using intact proviral DNA assay and T cell receptor sequencing in patients receiving lymphocyte-depleting or lymphocyte-nondepleting immunosuppression induction therapy. CD4+ T cells and intact and defective provirus frequencies decreased following lymphocyte-depleting induction therapy but rebounded to near baseline levels within 1 year after induction. In contrast, these biomarkers were relatively stable over time in the lymphocyte-nondepleting group. The lymphocyte-depleting group had early TCRβ repertoire turnover and newly detected and expanded clones compared with the lymphocyte-nondepleting group. No differences were observed in TCRβ clonality and repertoire richness between groups. These findings suggest that, even with significant decreases in the overall size of the circulating LVR, the reservoir can be reconstituted in a relatively short period of time. These results, while from a relatively unique population, suggest that curative strategies aimed at depleting the HIV LVR will need to achieve specific and durable levels of HIV-infected T cell depletion.

Serious adverse reaction associated with the COVID-19 vaccines of BNT162b2, Ad26.COV2.S, and mRNA-1273: Gaining insight through the VAERS.

Background and purpose: Serious adverse events following immunization (AEFI) associated with the COVID-19 vaccines, including BNT162b2 (Pfizer-BioNTech), Ad26.COV2.S (Janssen), and mRNA-1273 (Moderna), have not yet been fully investigated. This study was designed to evaluate the serious AEFI associated with these three vaccines. Methods: A disproportionality study was performed to analyze data acquired from the Vaccine Adverse Event-Reporting System (VAERS) between 1 January 2010 and 30 April 2021. The reporting odds ratio (ROR) method was used to identify the association between the COVID-19 vaccines BNT162b2, Ad26.COV2.S, and mRNA-1273 and each adverse event reported. Moreover, the ratio of the ROR value to the 95% CI span was applied to improve the credibility of the ROR. The median values of time from vaccination to onset (TTO) for the three vaccines were analyzed. Results: Compared with BNT162b2 and mRNA-1273, Ad26.COV2.S vaccination was associated with a lower death frequency (p < 0.05). Ad26.COV2.S vaccination was associated with a lower birth defect and emergency room visit frequency than BNT162b2 (p < 0.05). There were 6,605, 830, and 2,292 vaccine recipients who suffered from COVID-19-related symptoms after vaccination with BNT162b2, Ad26.COV2.S, and mRNA-1273, respectively, including people who were infected by COVID-19, demonstrated a positive SARS-CoV-2 test, and were asymptomatic. Serious AEFI, including thromboembolism, hemorrhage, thrombocytopenia, cardiac arrhythmia, hypertension, and hepatotoxicity, were associated with all three vaccines. Cardiac failure and acute renal impairment events were associated with BNT162b2 and mRNA-1273, while seizure events were associated with BNT162b2 and Ad26.COV2.S. The median values of TTO associated with the three vaccinations were similar. Conclusion: These findings may be useful for health workers and the general public prior to inoculation, especially for patients with underlying diseases; however, the risk/benefit profile of these vaccines remains unchanged. The exact mechanism of SARS-CoV-2 vaccine-induced AEFI remains unknown, and further studies are required to explore these phenomena.

Frequency of morphological defects produced on the active surface of continuous and reciprocating rotation instruments after repeated use

Root canal preparation is essential for the adequate sanitization of dentinal tubule systems, allowing favorable conditions for sealing in the cervical-apical direction. Objective: To analyze the frequency of morphological defects produced in continuous and reciprocating rotation instruments after repeated uses by scanning electron microscopy (SEM). Material and methods: Forty-five replicates of prototyped lower molars were randomly assigned to three groups according to the system used: G1. Biorace®, G2. V-File®, or G3. Protaper Next®. After root canal preparation, all the instruments were washed in an ultrasonic vat and subsequently analyzed by SEM to visualize the morphological defects (dullness of the edges, grooves, microcavities, and cracks) in images obtained with a magnification of 50x to 1500x. To determine defects on each instrument’s surface, the active part was divided into 14 parts, with segments on the two sides from 1 to 7. The relationship between the number of defects observed in the different instruments was assessed using chi-square tests. Results: Defects were observed in all tested instruments, with statistically significant differences between the systems (P&lt;0.05). BioRace® system was associated with a significant higher number of defects, than V-File® (P&gt;&lt;0.05) but was not significantly different from ProTaper Next® (P&gt;0.05). No significant difference was observed between V-File® and ProTaper Next® groups (P&gt;0.05). Conclusion: All the analyzed instruments showed defects in the active surface after repeated use.

Enhancement and extraction of periodic transient based on hybrid intelligent fusion algorithm and its application in rolling bearing fault detection

Weak fault detection of rolling bearing presents difficult, because the periodic transient signature produced via localized incipient damage is easily submerged by various interference components and background noise. Hybrid intelligent fusion method is a breakthrough strategy for revealing feature frequency of rolling bearing fault by comprehensively using a variety of intelligent signal processing technologies, possessing the advantage of each technology. Considering the rolling bearing often construct a transmission device combination with gear and shaft, its vibration signal is often vulnerable to other multi-morphology components, such as harmonic modulation, noise. Thus, how to identify the fault frequency in repetitive transients is crucial to accurately identify rolling bearing fault detection. To address this issue, a novel hybrid intelligent method is proposed to effectively apply on periodic transients extraction, enhancement and rolling bearing fault diagnosis. The innovation of this method is to solve three problems, namely, the separation of multi-morphology components, noise reduction without periodic transients distortion, weak fault frequency enhancement. The proposed method is tested and validated on simulated signal, rolling bearing fault signal from accelerated rolling bearing degradation rig. In addition, comparisons with other classical rolling bearing fault detection methods have been conducted to highlight the superiority of the proposed methodology.

Bearing Fault Diagnosis usingEnhanced Envelope Analysis

Early fault detection and diagnosis of bearing is of paramount importance in wind turbines as it contributes to around 70% of gearbox and 21%-70% of generator failure. This paper presents an enhanced envelope analysis technique for bearing fault identification using vibration measurements. The raw vibration signal measured from the outer casing of the WT gearbox with faulty bearing has not only fault frequency component but also resonant frequency, discrete frequency (gear and shaft) and high frequency background noise. The present work diagnose bearing faults through a three-step process: i) using Auto- Regressive(AR) time series model to remove discrete frequency components of gear and shaft ii) fault-sensitive frequency and demodulation band selection using spectral kurtosis. The spectral kurtosis is expected to higher around the region of resonance frequencies when fault occurs otherwise the fault signal is modulated. iii) envelope analysis to obtain spectrum by Hilbert Transform (HT) and retrieval of fault information. The order of the AR model is chosen such that the residual signal exhibits maximum kurtosis and spectral kurtosis is computed through short time Fourier Transform (STFT). The enhanced envelope analysis technique for bearing fault diagnosis is verified and validated using numerical simulations and Korea Aerospace University bearing damage benchmark datasets.

Frequency Of Spinal Defects in Fetuses with Ventriculomegaly

Fetal ventriculomegaly (VM) is a dilation of the lateral ventricle. Different patients have different etiologies for fetal ventriculomegaly, which can be idiopathic, structural, or chromosomal. A measurement of 10–15 mm is commonly referred to as mild ventriculomegaly, while measurements of 15–20 and &gt;20 mm and above are defined as moderate and severe ventriculomegaly. Objective: To find the frequency of spinal defects (SD) in fetuses with ventriculomegaly (VM). Methods: It was a cross-sectional analytical study which included 103 pregnant ladies who had evidence of ventriculomegaly visited multiple centers during research period. Convenient sampling method was used. The presence of ventriculomegaly was confirmed using transabdominal probe with frequency 3-5 MHz. Frequency was calculated and crosstabs were made using SPSS version 21.0. Results: Among 103 pregnant patients, frequency of fetal spinal defects was 25.2%. Frequency of ventriculomegaly was as follow: mild ventriculomegaly 43.7%, moderate ventriculomegaly 31.2%, and severe ventriculomegaly 25.2%. Among 103 patients, 25.2% patients had AFI greater than 21. Frequency of mother's H/O any fetal spinal defects in their previous pregnancies was 15.5%. Conclusions: The study concluded that frequency of spinal defects in fetuses with ventriculomegaly was 25.2% and spinal defects occur in those patients who had severe ventriculomegaly (&gt;20mm) and had AFI greater than 25

Compound Fault Diagnosis of a Wind Turbine Gearbox Based on MOMEDA and Parallel Parameter Optimized Resonant Sparse Decomposition.

Wind turbines usually operate in harsh environments. The gearbox, the key component of the transmission chain in wind turbines, can easily be affected by multiple factors during the operation process and develop compound faults. Different types of faults can occur, coupled with each other and staggered interference. Thus, a challenge is to extract the fault characteristics from the composite fault signal to improve the reliability and the accuracy of compound fault diagnosis. To address the above problems, we propose a compound fault diagnosis method for wind turbine gearboxes based on multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) and parallel parameter optimized resonant sparse decomposition (RSSD). Firstly, the MOMEDA is applied to the preprocess, setting the deconvolution period with different fault frequency types to eliminate the interference of the transmission path and environmental noise, while decoupling and separating the different types of single faults. Then, the RSSD method with parallel parameter optimization is applied for decomposing the preprocessed signal to obtain the low resonance components, further suppressing the interference components and enhancing the periodic fault characteristics. Finally, envelope demodulation of the enhanced signal is applied to extract the fault features and identify the different fault types. The effectiveness of the proposed method was verified using the actual data from the wind turbine gearbox. In addition, a comparison with some existing methods demonstrates the superiority of this method for decoupling composite fault characteristics.

Delineating septo-optic dysplasia.

Septo-optic dysplasia (SOD), once a variable triad of septum pellucidum defects (SPDs), optic nerve hypoplasia (ONH), and hypopituitarism, has had multiple findings added, with uncertain causes, definitions, and limits. Literature review. SOD is a complex vascular sequence with confounders. Proximal anterior cerebral artery trunk disruptions cause overlapping primary effects, giving ONH alone most often, and isolated SPD less. ONH disruptions can spread to pituitary, SPD disruptions to the cerebral cortex, causing schizencephaly and related anomalies. Pituitary defects are rare without ONH, and cortical findings are rare without SPD. Extensions are unidirectional, so isolated pituitary or cortical defects are separate from SOD. Micro- an- ophthalmia, a suggested ONH variant, is not part of SOD. Disruption by-products can affect development, causing cognitive and endocrine issues, and structural anomalies such as corpus callosum thinning, ventriculomegaly, and hippocampal and olfactory findings. Limbic extensions may also contribute to the same structural defects as by-products. Midline CNS developmental anomalies can act as disruptive foci, most likely through vascular variants, but have separate pathogenesis. Relative frequencies of specific pituitary hormone defects change as SOD rates increase. Increasing relative rates of midline CNS developmental defects and cortical anomalies are consistent with rising levels of exogenous exposures sensitizing to midline predispositions.

The frequency of ulcerative-erosive defects and ulcerative bleeding of the gastroduodenal zone in patients with coronavirus infection COVID-19

Aim : to determine the frequency of erosive and ulcerative defects and ulcerative bleeding of the gastroduodenal zone in patients with COVID-19 infection. Materials and methods . Fibroesophagogastroduodenoscopy was performed in patients in the hospital for the COVID-19 infection treatment when they had heartburn, dyspepsia, or signs of gastrointestinal bleeding among patients. In total, endoscopy was performed in 387 patients (116 men and 271 women, mean age 65.4 years). Erosive esophagitis was assessed according to the Los Angeles classification (1994), candidiasis esophagitis according to the Kodsi classification (1976), esophageal varices according to K. J. Paquet (1983), classification of ulcerative bleeding according to J. A. Forrest (1974). Results . Erosions in the esophagus was found in 25.3% of the examined patients, gastric and duodenal erosions—in 44.4% of persons, gastric and duodenal ulcers — in 10.1% of patients. Gastroduodenal bleeding was determined in 5.7% of the examined patients and was associated with ulcerative defects in 81.8% of cases. Male gender was a strong risk factor for erosions, ulcers, and bleeding from the upper gastrointestinal tract. Conclusion . In patients with COVID-19, complications from the gastrointestinal tract, manifested by ulcerative defects and bleeding from the gastroduodenal zone, are a significant problem. It seems rational to propose to treat patients with COVID-19 infection receiving massive anti-inflammatory, anthrombocytic, anticoagulant therapy in the same way as is customary in the management of cardiological and rheumatological patients for the prevention of NSAID-gastropathy.

Three-dimensional computed tomography mapping and clinical predictive factors for morphologic characterization of displaced femoral neck fractures.

This study aimed to define the distribution and frequency of fracture lines and bone defects in displaced femoral neck fractures (DFNFs) using a three-dimensional (3D) mapping technique, and to investigate the factors associated with the area of bone defects in patients with DFNFs. The data of 256 adult patients with DFNFs were retrospectively reviewed. Multiplanar reconstructions of the DFNFs were made using computed tomography (CT) images, and the DFNF fragments were virtually reduced to match a 3D model of the femoral neck. Subsequently, 3D mapping was performed by graphically superimposing all of the fracture lines and bone defects onto a femoral neck template. The 3D mappings were independently examined by two orthopedic surgeons, and the interobserver agreement was analyzed. For intraobserver analysis, one of the surgeons measured the mappings twice more, and the intraclass correlation coefficients (ICCs) were calculated. A linear regression analysis was conducted to explore bone defect area-related factors. The cohort comprised 141 (55%) patients with left hip injuries and 115 (45%) patients with right hip injuries. On the 3D maps, the dense zones of the fracture lines were largely observed from the superior to the posterior part of the femoral neck, while the dense zone of the bone defect was primarily concentrated in the posterior part of the femoral neck. Only a few dense zones were located in the anterior and inferior parts of the femoral neck. An overlapping region between the fracture line and the bone defect was located in the 2.5th to 4.5th (5th) part of the 1/10 of the superior (posterior) femoral neck length. Both the fracture line and bone defect mapping techniques had good intra- and inter-observer reliability, with ICCs of 0.879 (0.977) and 0.780 (0.974), respectively. Garden type and age were positively correlated with bone defects, while simplified AO Foundation/Orthopaedic Trauma Association (AO/OTA) classification was negatively associated with bone defects. The fracture lines and bone defects of the DFNFs were mainly located in the superior and posterior parts of the femoral neck, while an overlapping region was observed in the subcapital area of the femoral neck. 3D mapping is a reliable method for searching for DFNF features, and separately studying fracture lines and bone defects can further elucidate the morphology of these fractures. Bone defects in patients with DFNFs were associated with Garden type, simplified AO/OTA classification, and age.

Does primary trauma lead to developmental defects in permanent teeth?

Introduction A systematic review of existing evidence to determine if trauma in the primary dentition causes alteration in the development of the underlying permanent dentition.Data sources Six electronic databases (PubMed, Medline, MEDES, Scopus, Lilacs and Embase) were used to search a range of dental terms relating to dental trauma to locate studies between 1972-2020.Study selection Study selection was carried out by two authors by reviewing title, abstract and then full articles. A third author was consulted if consensus for inclusion was needed. Eligibility criteria included all scientific articles concerning sequalae to the human permanent dentition following trauma to the primary dentition. Only English, German and Spanish languages were included. For evaluation, the studies must have satisfied the following: a) minimum sample of 50 children to be representative; b) radiographic examination; and c) appropriate follow-up period up to permanent successor eruption.From 537 studies, 18 studies were identified for consideration in the review, comprising of 13 cross-sectional studies, two cohort studies and three case control studies.Data extraction and synthesis The Newcastle-Ottawa Scale was used to extract data and determine study quality. Only studies determined as high quality were included in the review. Four cross-sectional studies and three case control studies, totalling seven studies, were used. Data from these high-quality studies was summarised into table format.Results Large variation in study sample size existed from 138-753 traumatised teeth and 78-879 children. Both sexes were included in all studies and the children were aged between 0-17 years.Some studies found there was no difference in rate of trauma between girls and boys, while others found there was a higher incidence of trauma in boys than girls. The most frequently traumatised teeth were the upper primary central incisors. Whilst most studies covered all types of primary trauma, two only studied intrusion and one specified the type of primary trauma as luxation or fracture injuries.Whilst some of the studies concluded a higher frequency of defects to permanent teeth following primary intrusion trauma aged four and under, others showed no significant differences between the age of intrusion and the effect to the successor incisor.Enamel defects of the permanent teeth were the most common sequalae with a wide prevalence reported between 4.5-68.8%. Enamel defects were classified as hypoplasia and hypocalcification. Ectopic or altered eruption, crown or root dilacerations and odontoma development were observed less often, with the latter very rarely.Conclusions Primary tooth intrusion trauma causes the highest proportion of sequalae presenting as enamel defects. Younger patients experiencing primary trauma are more likely to obtain damage to the succeeding dentition. The existing quality of evidence is limited due to the observational nature of the studies available.

Bearings Health Monitoring Based on Frequency-Domain Vibration Signals Analysis

Rotating machine health monitoring is critical for system safety, cost savings, and increased reliability. The need for a simple and accurate fault diagnosis method has led to the development of various monitoring techniques. They incorporate vibration, motor’s current signature, and acoustic emission signals analysis in condition monitoring. So, based on using vibration signal analysis, a test rig was built for bearing fault identification. The test rig replicates and investigates various bearing problems, such as those found in the inner and outer races. An accelerometer, type ADXL335, was interfaced to a data acquisition device (DAQ USB-6215) for collecting vibration signals under various operating circumstances. In addition, a load cell was embedded with the test rig, interfaced with a digital panel meter, and used for recording the applied load on the bearings. The time-domain signal analysis technique was used after acquiring vibration signals at various bearing health states. Then, the time-domain signal was converted to the frequency domain using the fast Fourier transform, and the result was analyzed to investigate the generated fault frequencies. Finally, the obtained frequencies were compared with the theoretical values extracted from the theoretical equations, and the method proved its effectiveness in detecting the fault generated.

A FCEEMD Energy Kurtosis Mean Filtering-Based Fault Feature Extraction Method

Aiming at the problem that fault feature extraction is susceptible to background noises and burrs, we proposed a new feature extraction method based on a new decomposition method and an effective intrinsic mode function (IMF) selection method. Firstly, pairs of white noises with opposite signs were introduced to neutralize the residual noises in ensemble empirical mode decomposition (EEMD) and suppress mode mixing. Both the reconstruction error (1.8445 × 10−17) and decomposition time (0.01 s) were greatly reduced through fast, complementary ensemble empirical mode decomposition (FCEEMD). Secondly, we integrated the energy and kurtosis of the IMF and proposed an effective IMF selection method based on energy kurtosis mean filtering, and the background noise of the signal was greatly suppressed. Finally, the periodic impacts were extracted from the IMF reconstruction signal by multipoint optimal minimum entropy deconvolution adjusted (MOMEDA). The fault frequencies were extracted from the periodic impacts through Hilbert demodulation, and the relative errors between the measured values and the theoretical values were all less than 0.05. The experimental results show that the proposed method can extract fault features more efficiently and provide a novel method for the fault diagnosis of rotating machinery.

High-speed train wheel set bearing fault diagnosis and prognostics: evaluation of signal processing methods under multi-source interference

Despite the numerous studies on bearing fault diagnosis based on frequency domain or time-frequency domain analyses, there is a lack of a fair assessment on which method or methods are practically effective in identifying the fault frequencies of damaged bearings in noisy environments. Most methods were developed based on experiments with simple lab test rigs equipped with bearings having manufactured artificial defects, and the signal-to-noise ratio under lab conditions is too ideal to be useful for verifying the effectiveness of a signal processing method. The purpose of this study is to evaluate the effectiveness of advanced signal processing methods applied in a high-speed train operating environment with multi-source interference. In this work, the most advanced signal processing methods (including spectral kurtosis, deconvolution, and mode decomposition) are studied, and the shortcomings of each method are analyzed. Based on the characteristics of high-speed train wheel set bearings (HSTWSBs), the concept of fault characteristic signal-to-noise ratio (FCSNR) is put forward to quantitatively evaluate the fault periodicity intensity, and corresponding improved methods are proposed by combining the FCSNR with existing signal processing methods; all these methods consider the periodic characteristics and impact characteristics of the bearing fault. The simulation signal and actual signals of HSTWSB with natural defects help verify the effectiveness of the proposed methods. Finally, the advantages and disadvantages of the different signal processing methods are objectively evaluated, and the application scope of each method is analyzed and prospected. This study provides a reference and new ideas for the fault diagnosis of HSTWSB and other industrial bearings.

Congenital malformations in the vertebral column: associations and possible embryologic origins.

Cases of associations between random spinal congenital defects have previously been reported, yet several questions remain unanswered. Firstly, why are associations between what seems to be random combinations of vertebral malformations observed? Secondly, is there a common event or pattern that connects the associated defects? Therefore, this study aimed to identify congenital defects in the vertebral column and also to determine whether any associations, if present, between vertebral malformations exist. This article consequently discusses the possible embryological disruptions that may lead to the formation of various defects in the vertebral column. A random skeletal sample (n=187) was selected from the Pretoria Bone Collection housed in the Department of Anatomy, University of Pretoria (Ethics 678/2018). The sample was evaluated to determine the frequencies of spinal congenital defects in each set of remains. Identifiable congenital malformations were observed in 48.1% (n=90/187) of the sample. The results demonstrated a high probability of association between the different defects observed in the vertebral column. Findings are of value as they provide a reasonable explanation to why seemingly random cases of associations have been reported by several authors. This study is clinically relevant as severe spinal defects have been shown to have high morbidity in patients and mortality in infants.