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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
Fault feature extraction method for rolling bearing based on MVMD and complex Fourier transform
Get PDFThe vibration signals caused by rolling bearing defects in different directions may be different, and the fault diagnosis based on single channel vibration signals may be made incorrectly, and the observation results may be understood wrong. To avoid it, a new rolling bearing fault feature extraction method based on multivariate variational mode decomposition (MVMD) and complex Fourier transform (CFT) were proposed. First, the orthogonally sampled vibration signals were combined into a multivariate signal, and the multivariate signal was decomposed into several intrinsic mode functions (IMFs) using the MVMD. As per this method, a unified mathematical model was used to model vibration signals in two directions, ensuring that fault features were decomposed to the same level. Finally, the CFT was applied to fuse the envelope signals in two directions in order to obtain a clearer and comprehensive amplitude-frequency feature. Simulation and test results verify the feasibility and superiority of the proposed method
Study on fluid-structure interaction vibration characteristics of absorber feed tank based on micro vibration monitoring
Get PDFAbsorber feed tank (AFT tower) is a kind of reinforced concrete structure supported steel tank. It is a composite structure used for desulfurization and cleaning in power industry. A large amount of slurry is sumped in the steel tank, and oxidation air is blown into the tank through a pipe to impact the slurry surface, then the agitator vibrates and disturbs the slurry in the tank. The structure has obvious vibration in daily operation, which is not conducive to the safety of the structure, but also brings greater psychological burden to the staff. Therefore, field monitoring and numerical simulation analysis are carried out for the AFT tower. The field investigation of AFT tower is also carried out. The video monitoring and local monitoring are used to monitor the AFT tower, and the corresponding laws of vibration are explored. A simplified simulation method for this kind of structure is proposed. The model is established with the aid of the fluid structure coupling function of ADINA finite element analysis software to study the vibration characteristics of AFT tower. The results show that the motion trajectory of AFT tower can be determined quickly by video monitoring. The local monitoring can demonstrate that the effect of mixer is the main factor of structural vibration, and the blowing in of oxidation wind intensifies the structural vibration response, resulting in different degrees of damage to the infilled wall between the columns of the structure. By comparing the numerical simulation results with the monitoring results, the reliability of the simplified model is verified, which provides a reference for analyzing the vibration response, damage mechanism and reinforcement design of this kind of structure
Study on ground vibration characteristics induced by liquid CO2 blasting technique in bench excavation
Get PDFThe liquid CO2 phase change fracturing technique has been widely applied in rock engineering for a long time. However, the ground vibration characteristics in bench excavation have not been well demonstrated. In this study, the particle velocities, main frequencies, and displacements of rock induced by liquid CO2 blasting are investigated based on field tests and numerical simulations. Firstly, three field tests of bench excavation using DM83-1.4 type liquid CO2 storage tube were implemented in a specific highway slope project, in which the TC-4850 N vibration monitors were installed at horizontal distances of 4.2 m, 10.6 m, 20.3 m and 32.2 m from the detonation source to detect the rock vibration velocity and frequency. Subsequently, by employing the dynamic finite element program LS-DYNA, a three-dimensional numerical model was established, and then the particle velocities and displacements were analyzed and discussed. The research results indicate that the peak particle velocity (PPV) decays with distance in an exponential pattern, that is, the PPV decays rapidly in the near zone of the blasting source, and it decays more slowly in the far zone. At the position of 20.3 m in the horizontal distance and 15.8 m in elevation, an elevation amplification effect appears with an amplification factor of 1.12. Moreover, the vibration frequency generated by the liquid CO2 phase change fracturing technique is in the range of 0-80 Hz, which is much smaller than that induced by explosive blasting. The main frequency in the near-field of the blasting source is dominated by the radial frequency (Fr), while the vertical frequency (Fv) is dominant in the far-field. The attenuation law of displacement is generally consistent with the vibration velocity, and the difference between radial and tangential displacement increases gradually with distance
Research on intelligent detection of pavement damage based on CNN
Get PDFIn order to timely detect road damage under complex constraints, the road damage mechanism was used to reclassify the types of road damage, the VGG-19 model was applied to identify and detect less road damage images intelligently through convolutional neural network and transfer learning and at the same time, the road damage situation was detected using the Softmax classifier and the feasibility and accuracy of the method were verified on the basis of the detection set. The results show that the detection and recognition accuracy of the model proposed in this paper reaches 86.2 %, an increase of 6.2-49.8 percentage points than the detection results of other convolutional neural network models. Therefore, it can be concluded that the transfer learning- and convolutional neural network-based road damage intelligent detection methods proposed in this paper are feasible, and this research is helpful to realize high-precision real-time intelligent detection of road damage
Determining the position of two cracks in a cantilever beam using artificial neural networks
Get PDFDuring functioning time, structures such as beams are subjected to a variety of loads caused by the working conditions and environment, which can lead to the development of cracks. The current research is concerned with detecting the presence and location of two transverse breathing cracks, in cantilever beams. Starting from the known fact that damages produce a stiffness degradation in structures altering their dynamic parameters, we performed modal simulations of damaged beams to determine their natural frequencies. By using the simulation data, we trained an artificial neural network (ANN), using the feedforward backpropagation algorithm, that is capable to detect the presence of the cracks, their position and for the case when the damages are in proximity, the model can determine if the cracks occur on the same face or opposite faces
Techno-economic modelling of the Baltic CCUS onshore scenario
Get PDFTechno-economic modelling of the Baltic onshore CO2 transport, storage, and utilization scenario included HeidelberCement-owned Kunda Nordic Cement (KNC) plant, the main Estonian cement producer, four Estonian and one Latvian power plant and CO2 mineral carbonation of the oil shale ash, as possible CO2 use option. In 2019 nearly 6.5 Mt of oil shale ash (OSA) was produced in Estonia from energy production. Estonian OSA could be used as an effective sorbent in the proposed CO2-mineralization process, using CO2 from flue gas and producing precipitated CaCO3 (PCC) of high quality. Mineral carbonation of 0.42 Mt CO2 using 3.8 Mt of fresh OSA and about 6.33 Mt CO2 produced annually by five Estonian and one Latvian plant transported by pipeline for storage into the North-Blidene structure in western Latvia are combined in the CCUS scenario. Cambrian Deimena Formation reservoir sandstone is located at the depth of 1035-1150 m in the selected saline aquifer. The average optimistic storage capacity of about 270 Mt allows planning CCUS project for 30 years. The share of the Estonian emissions avoided and stored in Latvia is 86.5 %, including 8.2 % by KNC, while Latvian stored emissions will compose 13.5 %. Annually 6.8 Mt CO2 could be captured, transported and injected, including 6 Mt CO2 avoided using transport and storage and 0.42 Mt CO2 avoided using MC of Estonian OSA. During 30 years nearly 204 Mt CO2 will be captured, used and stored, while 193 Mt CO2 could be avoided. The total average transport and storage (T&S) cost of the scenario is 18.4 €/t CO2 injected. This cost depends on the transport distance, according to the applied methodology, and it is the most expensive for the Eesti Energia PPs. The lowest T&S cost of 5.54 €/t CO2 injected will have Latvenergo TEC-2 PP located at a smaller distance from the storage site. At the price of EEAP (CO2 Emission Allowance Price in EU ETS) of 40 €/t CO2 and 50 €/t PCC, the CCUS scenario could be beneficial for three Eesti Energia and Latvenergo TEC-2 power plants. For the KNC and VKG Energia plants without CO2 use options, the higher EEAP of about 48-50 €/t CO2 is needed to cover all CCUS costs including capture, compression, transport, storage and monitoring. The transport and storage costs are distance-dependent, as pipelines are the most expensive part of the transport, storage and monitoring costs. At the present EEAP of about 90 €/t CO2, all the participating plants will get benefits from the proposed scenario. This study is supported by CLEANKER project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement n. 764816
Health diagnosis of marine engine room equipment based on BP and D-S evidence theory
Get PDFAiming at the problems of poor resolution and low precision in traditional health diagnosis of Marine engine room equipment, this paper proposes a health diagnosis method of intelligent Marine engine room equipment based on BP neural network and D-S evidence theory. Firstly, the time-domain parameters of the obtained acceleration signal are extracted and the energy in frequency domain after wavelet decomposition is calculated. Then the eigenvectors of time domain and wavelet packet energy were constructed respectively, and the normalized processing was input into two BP neural networks to obtain the classification results. Finally, the fault classification results in time domain and frequency domain are combined with the D-S evidence theory and output diagnosis. Through experimental analysis and verification of rolling bearing data from electrical Engineering Laboratory of Case Western Reserve University, the accuracy of the proposed method is better than that of time domain and frequency domain analysis alone, which improves the accuracy and reliability of fault classification
Treatment of vertical problems with jaw functional orthopedics based on scientific evidence. Part 2: deep bite
Get PDFThe vertical problems of the stomatognathic system that alter the overbite, either by increasing in the deep bite (DB) or decreasing in the anterior open bite (AOB), are among the great challenges of the dentofacial corrections in the treatment and the retention and stability protocols. In this paper the state of art of DB treatment with Jaw Functional Orthopedics (JFO) will be discussed. JFO has a unique diagnostic tool for changes in vertical growth of the face, the Articular Compass, developed by Simões. Individuals with hypodivergence and DB are, usually, difficult to treat and more difficult to stabilize the obtained results. Since 1950-decade Planas advocate that the Equiplan – a metal accessory used in functional orthopedic appliances (FOA) is efficient in deep bite treatment by levelling the occlusal plane. Promising results are found with a P = 0,00, but in aweak evidence study design based on the scientific evidence pyramid. Much of the discussion of incisor intrusion or molar extrusion to treat DB seems to be solved with the use of Equiplan, but it still has no scientific evidence, only clinical evidence. In conclusion Randomized Clinical Trials are needed to investigate the efficiency and Modus Operandi of JFO to treat DB