Overall Performance Evaluation of Tubular Scraper Conveyors Using a TOPSIS-Based Multiattribute Decision-Making Method

Properly evaluating the overall performance of tubular scraper conveyors (TSCs) can increase their overall efficiency and reduce economic investments, but such methods have rarely been studied. This study evaluated the overall performance of TSCs based on the technique for order of preference by similarity to ideal solution (TOPSIS). Three conveyors of the same type produced in the same factory were investigated. Their scraper space, material filling coefficient, and vibration coefficient of the traction components were evaluated. A mathematical model of the multiattribute decision matrix was constructed; a weighted judgment matrix was obtained using the DELPHI method. The linguistic positive-ideal solution (LPIS), the linguistic negative-ideal solution (LNIS), and the distance from each solution to the LPIS and the LNIS, that is, the approximation degrees, were calculated. The optimal solution was determined by ordering the approximation degrees for each solution. The TOPSIS-based results were compared with the measurement results provided by the manufacturer. The ordering result based on the three evaluated parameters was highly consistent with the result provided by the manufacturer. The TOPSIS-based method serves as a suitable evaluation tool for the overall performance of TSCs. It facilitates the optimal deployment of TSCs for industrial purposes

Multipoint Optimal Minimum Entropy Deconvolution Adjusted for Automatic Fault Diagnosis of Hoist Bearing

Multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) is a powerful method that can extract the periodic characteristics of signal effectively, but this method needs to evaluate the fault cycle a priori, and moreover, the results obtained in a complex environment are easily affected by noise. These drawbacks reduce the application of MOMEDA in engineering practice greatly. In order to avoid such problems, in this paper, we propose an adaptive fault diagnosis method composed of two parts: fault information integration and extracted feature evaluation. In the first part, a Teager energy spectrum amplitude factor (T-SAF) is proposed to select the intrinsic mode function (IMF) components decomposed by ensemble empirical mode decomposition (EEMD), and a combined mode function (CMF) is proposed to further reduce the mode mixing. In the second part, the particle swarm optimization (PSO) taking fractal dimension as the objective function is employed to choose the filter length of MOMEDA, and then the feature frequency is extracted by MOMEDA from the reconstructed signal. A cyclic recognition method is proposed to appraise the extracted feature frequency, and the evaluation system based on threshold and weight coefficient removes the wrong feature frequency. Finally, the feasibility of the method is verified by simulation data, experimental signals, and on-site signals. The results show that the proposed method can effectively identify the bearing state

Study Horizontal Screw Conveyors Efficiency Flat Bottomed Bins EDEM Simulation

It describes the development history flat bottom silo, characteristics and testing system, composition. For the poor current theory and computer simulation study on horizontal spiral conveyor in the system, Using Solidworks to establish a reasonable three-dimensional model of flat bottom silo Horizontal Screw Conveyors, to import the model into EDEM software, simulation. By setting parameters and the model material parameters, draw motion vectors of the material along the helical axis, horizontal screw conveyor average number of transported materials particles, The results with experimental results compared to abroad, Flat bottom silo systems used EDEM software for the efficiency study of horizontal screw conveyors is authenticity and reliability, at the same time, the simulation makes the screw conveyor filling rate to identify more specific , Save time on flat bottom bunker system design, shorten the development cycle

Digital twin rapid construction method of a mining hoisting system

The safe and reliable operation of the hoisting system is very important for the production of the whole mine. Therefore, it is necessary to realize the single-point global visualization and virtual remote cooperative linkage control of the mining hoisting system, so as to solve the problem that the traditional multi-point video surveillance can only cover some key components and obtain incomplete information. To solving the problem, the digital twin framework of a mining hoisting system that with the function of monitoring, control and servicing is constructed by industrial sensing, artificial intelligence, rapid modeling, cloud storage and other technologies. Based on the framework, a multi-dimensional and multi-scale digital twin rapid modeling method is proposed. Firstly, a large scale geometric model of the mining hoisting system is built by 3D laser scanning technology, filtering, Poisson 3D reconstruction and other point cloud processing algorithms. Secondly, using industrial sensor network, PLC data reading and conversion technology, the behavior model of mining hoisting system under massive data is established. Lastly the fault knowledge model of the mining hoisting system is constructed using the database technology, domain expert knowledge and cases. The multi-dimensional and multi-scale digital twin rapid modeling experiment is carried out in a mine, and the results are as follows. The efficiency of the geometric modeling method has improved 93% compared with the traditional CAD modeling method and the modeling result has great similar to the real mining hoisting system. The behavior modeling method realizes the mapping of real entity behavior without adding new sensors and without shutting down, saves a lot of cost and has strong real-time performance. The driving Scripts are written based on Unity3D software to deeply integrate behavioral model, knowledge model and geometric model. Synchronization and deduction of behavioral model are carried out based on the component level model with high fidelity of the geometric model and it can realize the non-delay cooperative linkage between virtual and real systems. Meanwhile, relevant professional knowledge in the field is triggered by real-time behavioral data to assist decision making. The establishment process of the whole digital twin model takes into account the cost and effect, which will greatly improve the operation security and intelligence degree of the mining hoisting system

Modeling and Simulation of a Novel Low-Speed High-Torque Permanent Magnet Synchronous Motor with Asymmetric Stator Slots

Focusing on the unstable electromagnetic performance of an air gap magnetic field caused by torque ripple and harmonic interference of a multi-slot and multi-pole low-speed high-torque permanent magnet synchronous motor (LHPMSM), an asymmetric stator slot is proposed to improve the comprehensive electromagnetic performance of the motor. Moreover, this paper develops an exact analytical model which predicts the magnetic field distribution based on Laplace’s and Poisson’s equations. The stator slot asymmetry is introduced into the model and solved by the method of separating variables. Taking a 40p168s LHPMSM as an example, numerical results of the no-load flux density field distributions are obtained by the finite element method (FEM) and employed to validate the analytical model. The influence of stator slot asymmetric structure on electromagnetic characteristics is subsequently analyzed. The results show that, compared with the semi-closed slot model, the asymmetric slot has better torque characteristics, and the electromagnetic characteristics of the motor can be significantly improved by optimizing the stator slot asymmetry. Finally, a prototype is manufactured and tested to validate the theoretical analysis

The Acoustical Behavior of Contra-Rotating Fan

The noise produced by a contra-rotating ventilator can cause injury to humans. Therefore, it is important to reduce noise caused by ventilators. In this study, the Ffowcs Williams and Hawkings (FW-H) model was used to simulate the acoustics of four different axial impeller spacing points based on the unsteady flow field through a FBD No. 8.0 contra-rotating ventilator. Experiments were conducted to verify the correctness of the numerical model. Meanwhile, the Variable Frequency Drive (VFD) drives the two motors of 55 kW to give the impellers different speeds to distinguish different conditions. The results showed that the main noise source of the ventilator was the two rotating impellers and the area between them. For the same axial space, the noise decreased with the increase of flow rate and then decreased. And the amplitude of the discrete pulse increased gradually. It can be concluded that the vortex acoustics decreased gradually with the increase of flow rate and the rotating acoustics were the major contributor. With the axial distance increasing, the noise caused by the two impellers was weak, and the frequencies of sound pressure level moved toward medium- and low-frequency bands gradually. The suitable axial space could reduce noise and improve the working environment

CO-Simulation Analysis of Hydraulic Steel-Belt Overwind Buffer Device

Abstract: In this study, we obtain overwind buffer distance by using the Lagrange equation to establish the twodegrees-of-freedom mathematical model with vertical shaft lifting system in rolling process. Design of a buffer device which is composed of a hydraulic energy absorption and strip plastic deformation energy absorbing and analyze its working principle with mechanical and hydraulic system. Analysis of the overwind buffer time and buffer distance with loaded full overwind and no-load speed by using ADAMS and AMESim to build mechanical hydraulic combined simulation model of hydraulic steel-belt overwind buffer device. The simulation results show that: buffer time is 0.67 sec and buffer distance is 0.38 m with loaded full overwind; buffer time is 0.523 sec and buffer distance is 0.05 m with no-load speed overwind. The design of Hydraulic steel-belt overwind buffer device conforms with the requirements of safety regulation in coal mine

Longitudinal Vibrations of the Viscoelastic Moving Belt

The longitudinal dynamic governing equation of the viscoelastic belt with one end subjected to concentrated mass was established based on the Kelvin-Voigt viscoelastic partial-differential constitutive law. The generalized coordinate method was adopted to solve dynamic displacement and dynamic tension. And then it was reduced to be a nonhomogeneous partial-differential equation where the analytical solutions with a constant acceleration were obtained. The effects of damping coefficient, the loading radio, and the constant acceleration of the belt on the dynamic response of the belt were investigated using the established dynamic model. The results show that the longitudinal vibration frequency of the viscoelastic moving belt increases with an increasing of the mass at the end. The increasing value of the loading radio, damping coefficient, and decreasing the acceleration will lead to a deceasing in dynamic tension. Moreover, the method of solution can be applied to axially moving viscoelastic materials with different boundary conditions

Application of Adaptive MOMEDA with Iterative Autocorrelation to Enhance Weak Features of Hoist Bearings

Low-speed hoist bearings are characterized by fault features that are weak and difficult to extract. Multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) is an effective method for extracting periodic pulses in a signal. However, the decomposition effect of MOMEDA largely depends on the selected pulse period and filter length. To address these drawbacks of MOMEDA and accurately extract features from the vibration signal of a hoist bearing, an adaptive feature extraction method is proposed based on iterative autocorrelation (IAC) and MOMEDA. To automatically identify the pulse period, a new evaluation index named autocorrelation kurtosis entropy (AKE) was constructed to select the optimal IAC. To eliminate the influence of the filter length on the decomposition effect, an iterative MOMEDA strategy was designed to gradually enhance signal impulse features. The Case Western Reserve University bearing dataset and bearing data from a self-made hoisting test setup were used to verify the effectiveness of IAC-MOMEDA in extracting weak features. Moreover, the capability of IAC-MOMEDA for features extraction of normal bearing vibration signal was further confirmed by field test data