Because an electromagnet has a complex structure and manufacturing process, it is difficult to analyze the overall failure of the electromagnet. In order to solve this problem, a fault intelligent analysis and diagnosis system based on fuzzy fault tree and evidence theory is proposed in this paper. First, the failure structure and fuzzy fault tree are generated according to the experience. Second, the probability of failure caused by basic events is obtained based on the data statistics of the insufficient holding force of the electromagnet in the past. Then, the probability of the basic events is given by using the synthesis rules of evidence theory. Next, the belief interval of the basic event is set as the fuzzy number, and the intelligent analysis is completed by using the calculated fuzzy importance. Finally, the validity and feasibility of the proposed method is proved by using the failure of insufficient retention force in the electromagnet manufacturing process as an example.
In order to solve the problems of excessive elastic deformation and excessive inertia force existed in the drive mechanism of traditional die-cutting machine, a lightweight drive rod with full symmetrical structure is proposed as the main force bearing component of the drive mechanism based on the kinematics analysis. The elastic deformation and inertia force of the lightweight drive rod are verified by static simulation analysis, and show that the weight of the drive rod is significantly reduced under the same deformation conditions, the traditional one. Further compared with, taking the minimum elastic deformation and lightweight as the optimization objectives, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is used to optimize the structural parameters of the drive rod. The results show that under the working conditions of 350 T die-cutting force and 125 r/min rotating speed, the elastic deformation of lightweight drive rod after structural optimization is smaller (the maximum deformation is 0.00988 mm) and the weight is lighter (27% less). The research data presented in this paper can be used as the theoretical basis for future research on die-cutting mechanism. The lightweight drive rod proposed in this study can be used in die-cutting devices with high die-cutting speed and high die-cutting accuracy.
Product fault diagnosis has always been the focus of quality and reliability research. However, a failure–rate curve of some products is a symmetrical function, the fault analysis result is not true because the failure period of the products cannot be judged accurately. In order to solve the problem of fault diagnosis, this paper proposes a new Takagi-Sugeno (T-S) dynamic fault tree analysis method based on a Bayesian network accompanying the Wiener process. Firstly, the top event, middle event, and bottom event of the product failure mode are determined, and the T-S dynamic fault tree is constructed. Secondly, in order to form the Bayesian network diagram of the T-S dynamic fault tree, the events in the fault tree are transformed into nodes, and the T-S dynamic gate is also transformed into directed edges. Then, the Wiener process is used to model the performance degradation process of the stationary independent increment of the symmetric function distribution, and the maximum likelihood estimation method is applied to estimate the unknown parameters of the degradation model. Next, the product residual life prediction model is established based on the concept of first arrival time, and a symmetric function of failure–rate curve is obtained by using the product failure probability density function. According to the fault density function derived from the Wiener process, the reverse reasoning algorithm of the Bayesian network is established. Combined with the prior probability of the bottom event, the posterior probability of the root node is calculated and sorted as well. Finally, taking the insufficient braking force of electromagnetic brakes as an example, the practicability and objectivity of the new method are proved.
As the key component of a servo motor, the torque and temperature rise of the brake at the operating temperature affect the production quality of injection molding machines and other equipment. To achieve application of the brake and evaluate its performance at a high operating temperature, a high-torque permanent magnet brake with an axial disc structure is proposed. The permanent magnet consists of six small magnets instead of the traditional monolithic ring magnet. The key parameters of the coil are designed, and the magneto-thermal coupling method is established. The magneto-thermal coupling method considers the effect of temperature on material properties and feeds the temperature back to the electromagnetic field to correct the resistance, permeability, remanence and other coefficients. It then updates the heat source of the temperature field. The temperature rise is calculated iteratively between the electromagnetic field and the temperature field. The simulation results of the one-way method and the magneto-thermal coupling method are obtained and compared with the experimental results. The evaluation errors of the magneto-thermal coupling method for temperature and braking torque are 1.9% and 4.7% respectively, which are lower than the errors of the one-way method.
Product fault diagnosis has been a focus of research in the field of quality control. Many studies have been made to ensure the accuracy of fault diagnosis in electromagnet quality control direction. However, in the pursuit of perfect identification method, the fault diagnosis process is extremely complex in quality control management. A new fault diagnosis method for quality control of electromagnet machining processes based on [Formula: see text]–[Formula: see text] fault tree and grey relation degree analysis is proposed in this paper. First, [Formula: see text]–[Formula: see text] fault tree is used to analyze and describe the dynamic fault relationship of the electromagnet machining processes. In order to make the fault mode more intuitive and specific, [Formula: see text]–[Formula: see text] fault tree logic diagram is used to describe the actual fault form of machining processes. Second, according to the fault output algorithm of [Formula: see text]–[Formula: see text] fault tree, the fault rate of basic event in each cycle is calculated and the fault rate of intermediate event and top event in each cycle is obtained. Then, the grey relation method is applied to calculate the relation between the basic event and the trend of top event failure rates in electromagnet machining processes. Based on the obtained relation degree, the faulty system of electromagnet machining processes can be repaired pertinently and achieve the purpose of quality control. Finally, an example of electromagnet quality control’s fault diagnosis is used to verify the objectivity and simplicity of the new method.
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