Journal of Engineering and Thermal Sciences
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Clinical application of digitalization of occlusal contacts with dental scanner
Get PDFThis study aimed to evaluate the number, intensity and position of occlusal contact points in a case of mesiocclusion, hyperdivergence, with open bite. An occlusal record was taken from a patient with anterior and lateral open bite mesiocclusion, using the Planmeca Esmerald S intraoral scanner in maximum intercuspation. The intensity of the occlusal contact was analyzed with the software 3shape Ortho Analyzer Orthodontics, using the Occlusion Map module, through the 3D Color Map tool, with a 0.5 mm virtual articular paper. These results were compared to the occlusal support points defined by Planas [10]. The interpretation of the data obtained was made by assessing the interocclusal intensity of the contact points, number of contacts and position during three different moments (1S, 2S, 3S) in the record taking process. The chromatic scale of the Color Map is: red, orange, yellow, green and blue. To identify the occlusal contact points in digital, they are shown in red points when full contact occurs, while minimum contact is shown in blue. We evaluated the number of teeth with interocclusal contacts. It was determined that having the appropriate number of contacts does not imply that they are in the correct position. In addition, the method suggests reliability in the filing and record keeping of occlusal contacts. By identifying intensity, number and position of the occlusal support point we can objectively record interocclusal alterations
Corporeal-composition indicators, and physiological alterations in dental eruption
Get PDFWorldwide, obesity leads to major diseases in adults. Infants are affected as well, particularly because of growth and development issues. In this article we describe cases of early dental eruption in overweight and obese children, almost 1 year earlier than expected. The relations and mechanisms that cause these alterations remain to be determined
Recent advancements of signal processing and artificial intelligence in the fault detection of rolling element bearings: a review
Get PDFA rolling element bearing is a common component in household and industrial machines. Even a minor fault in this section has a negative impact on the machinery's overall operation. As a result, the industry suffers significant financial losses, and this damage can potentially result in catastrophic failures. Therefore, even a little fault in the rolling element bearings must be recognized and remedied as soon as possible. Many ways for detecting REB defects have been created in recent years, and new methods are being introduced on a daily basis. This article will provide a summary of such methods, with a focus on vibration analysis techniques. The newest advancements in this field will be recognizable to readers of this article. Anyone interested in defect diagnostics of rolling element bearings can utilize this material
Analysis of electromagnetic vibration and noise of permanent magnet synchronous motor based on field-circuit coupling
Get PDFIn order to study the influence of harmonics on the vibration and noise of permanent magnet synchronous motor, this paper introduces an analysis method based on field-circuit coupling, and establishes a complete analysis process from the control strategy to the vibration and noise response of the motor. Firstly, the coupling model including control strategy, main circuit model and electromagnetic field model is established. Secondly, the finite element model of the permanent magnet synchronous motor under the influence of coupling is established to analyze and compare the electromagnetic force wave characteristics of the coupling excitation and the sinusoidal excitation. Then, the coupled electromagnetic force is loaded into the structural field to simulate and calculate the vibration and noise. Finally, the effectiveness of the model is verified through experimental sound pressure level comparison under steady-state and speed-up conditions, and it provides a reference for vibration and noise prediction of the motor system
Research on online monitoring and early warning system of transmission line galloping based on multi-source data
Get PDFWhen the conductor is covered with ice on a non-circular section, and there is low-frequency, large-amplitude motion under wind excitation, it is usually called the transmission line galloping phenomenon. Due to the large amplitude, the galloping of the transmission line will lead to line fatigue, increase in tension, damage to hardware, or toppling of towers. In addition, it will also lead to flashover, tripping, and other transmission accidents caused by the short phase distance, which is not conducive to the safe operation of power grids. In order to improve the safety of power grid operation, this paper designed an online monitoring and early warning system for transmission line galloping on the basis of multi-source data and verified the system through implementation. It was found that the safety factor was 1.568, which determines its early warning level and affirms the feasibility of this study. This research has a positive role in improving the safe operation of the power grid
Bearing fault feature selection method based on dynamic time warped related searches
Get PDFTraditional feature selection algorithms rarely consider the dynamic misalignment between different time series, and have poor fault tolerance and robustness. In this paper, a fault feature selection method for rolling bearings based on Dynamic Time Warped Related Searches (DTWRS) is proposed. Firstly, the bearing fault feature set is constructed, and the dynamic time warping algorithm is used to calculate the shortest cumulative distance between feature of different faults, and this distance is used as the correlation evaluation standard. Then, two new search rules, dynamic time warping difference and dynamic time warping entropy, are proposed based on the minimum redundancy between bearing fault features and the maximum correlation between fault features and feature categories, use these two search rules to judge the ability of the feature to express the fault, define the quality of the fault feature and sort from good to bad according to the level of ability. Finally, in this order, the number of features is gradually increased and input to the fault classifier, and the sensitive fault feature set is obtained based on the principle of the highest recognition rate and the least number of features. The experimental results show that the fault feature selection method of rolling bearing based on DTWRS can increase the accuracy of fault diagnosis while minimizing the number of features, and improve the efficiency and effect of fault diagnosis
Dynamic response and contact characteristics of shaft-bearing-pedestal system with localized defect using 2-D explicit dynamics finite element model
Get PDFAs the core and precision component of a mechanical system, rolling element bearings would cause irreparable results once it breaks down. In order to study the dynamic response of bearing system caused by different localized defect sizes on outer raceway, a two-dimensional (2-D) explicit dynamics Finite Element Method (FEM) model of shaft-bearing-pedestal system with a localized defect is proposed. The model is verified by the experimental results. A new numerical method is used to investigate the influence of different defect sizes on the contact characteristics in this model. The indicator scfdefect-health is introduced to study the contact force with different defect sizes. The results show that the scfdefect-health increases with the increasing of defect depth and width, and the mathematic relationships are given for scfdefect-health. Therefore, the dynamic FEM model can be used to bearing fault diagnosis and defect prediction
Vehicle state and parameter estimation based on adaptive robust unscented particle filter
Get PDFIn order to solve the problem that the measured values of key state parameters such as the lateral velocity and yaw rate of the vehicle are easily interfered by random errors, a filter estimation method of vehicle state is proposed based on the principle of robust filtering and the unscented particle filter algorithm. Based on the establishment of a 3-DOF non-linear dynamic model and the Dugoff tire model of the vehicle, the adaptive robust unscented particle filter(ARUPF) is used to filter and estimate the parameters of the vehicle state, and to realize the longitudinal and lateral speed as well as the yaw rate of the vehicle during the driving process. The simulation and the real vehicle test results show that based on the adaptive robust unscented particle filter algorithm, the vehicle driving state estimation can be realized, the measurement parameters can be effectively filtered, and the estimation accuracy is high
Bio-CCS as a policy measure to achieve climate goals – the pioneering support scheme in Sweden
Get PDFBy 2045, Sweden is to have zero net emissions of greenhouse gases into the atmosphere. After 2045, Sweden should achieve negative emissions. To accomplish this, the use of bioenergy with carbon capture and storage (bio-CCS) will be important. Sweden should aim to capture and store two million tonnes of biogenic carbon dioxide per year by 2030. However, the feasible potential for bio-CCS in Sweden amounts to at least 10 million tonnes of biogenic carbon dioxide per year in a 2045 perspective. To support the development and deployment of CCS the Swedish energy Agency has been given two governmental assignments. 1. The first task/assignment, given in December 2020, was to establish a national centre for CCS. This task entails planning, coordination and promotion of CCS throughout the country. The Swedish Energy Agency will carry out its work in dialogue with both national and international stakeholders: industries, academia, governmental authorities and the Government Offices of Sweden. The present tasks for the centre are to implement a support system for bio-CCS and ensure that it is line with international conventions, such as the UN Convention on Biological Diversity and its moratorium on geo-engineering, and the London Convention and the London Protocol. The centre is also working with questions related to the accounting and reporting of negative carbon dioxide emissions in relation to national and international climate goals as well as following the emergence of a carbon market – voluntary and/or regulated – for negative emissions. 2. The second assignment was to roll-out the support system earlier proposed by the agency. The Swedish Energy Agency has concluded that a reverse action as the most cost-effective support system as well as to be compatible with EU state aid rules. The support system for bio-CCS has a budget framework of 3.6 billion €. A reverse auction means that, for example, a pulp and paper industry or a combined heat and power plant can submit a bid on how much carbon dioxide they can capture and store, and at what cost. The one who can deliver bio-CCS according to the stipulated requirements at the lowest cost, wins the auction. The Swedish Energy Agency hope to launch the first round of auction in 2023 and have the first storage of Swedish captured carbon dioxide taking place in 2026. Other countries can use Sweden’s knowledge and experiences when implementing bio-CCS. Exchanging knowledge, experiences and ideas with other countries are important to achieve large-scale deployment of bio-CCS in the Nordic-Baltic region and net-zero emissions in 2045
Research on IGOA-LSSVM based fault diagnosis of power transformers
Get PDFPower transformer is an important part of power equipment, and its functionality affects the proper operation of the whole power network. In order to diagnose power transformer faults effectively, the authors propose a fault diagnosis strategy based on an improved locust optimization algorithm for least squares vector machines (IGOA-LSSVM). Firstly, it was required to address the problem that the diagnostic prediction accuracy of the least squares vector machine is reduced due to its parameters. So this paper introduces the locust optimization algorithm with simple algorithm structure and good performance for optimizing the parameters. And at the same time, the authors generate an improved locust optimization algorithm with self-learning factors, proportional weight coefficients and Levy flight strategy. Secondly, the improved locust optimization algorithm is used for optimizing the least squares vector machine parameters. Finally, in the simulation experiments, the results of the benchmark test function illustrate that the IGOA algorithm has better performance, and the test results of a fault samples diagnosis of the power transformer equipment illustrate that the IGOA-LSSVM has good prediction effect and improves the fault identification accuracy compared with ACO-LSSVM and PSO-LSSVM in five types of fault diagnosis