Search

Computer numerical control (CNC) machine tool is the foundation of the equipment manufacturing industry, and its technical level is an important indicator to measure the development level of a country’s equipment manufacturing industry. Tool wear during machining has a great impact on the important performance indicators of CNC machine tools, such as machining accuracy, machining efficiency and reliability. Tool wear monitoring is of great significance to improve the machining efficiency, machining accuracy and reliability of CNC machine tools. Multidomain features (time domain, frequency domain and time–frequency domain) can accurately characterise the degree of tool wear. However, manual feature fusion is time consuming and prevents the improvement of monitoring accuracy. A new tool wear prediction method based on multidomain feature fusion by attention-based depth-wise separable convolutional neural network is proposed to solve these problems. In this method, multidomain features of cutting force and vibration signals are extracted and recombined into feature tensors. The proposed hypercomplex position encoding and high-dimensional self-attention mechanism are used to calculate the new representation of input feature tensor, which emphasizes the tool wear sensitive information and suppresses large area background noise. The designed depth-wise separable convolutional neural network is used to adaptively extract high-level features that can characterise tool wear from the new representation, and the tool wear is predicted automatically. The proposed method is verified on three sets of tool run-to-failure data sets of three-flute ball nose cemented carbide tool in machining centre. Experimental results show that the prediction accuracy of the proposed method is remarkably higher than other state-of-art methods. Therefore, the proposed tool wear prediction method is beneficial to improve the prediction accuracy and provide effective guidance for decision making in processing.

In Takagi and Sugeno (T-S) fuzzy fault tree analysis (FFTA), the construction of T-S fuzzy gates relies too much on expert experience, which will result in inevitable subjective errors. In order to overcome this disadvantage, a new method was proposed in which the construction of T-S gates no longer relies solely on historical data and expert experience but is also determined by the importance of the basic events to the top event. In the proposed method, fault degrees were described as fuzzy numbers; fault probabilities were described as fuzzy possibilities. The importance index of basic events can be solved through the analysis of the fuzzy fault tree model by Monte Carlo (MC) simulation. The proposed method is suitable for systems where exact information on the fault probabilities of the components and the magnitude of failure and effect on the system are not available. The concept and calculation method of T-S probability importance was presented. Finally, the proposed method is applied to analyze the reliability of the NC turret seal subsystem, the accuracy of the method is verified by comparing with the methods based on traditional FFTA and T-S FFTA, and the weak points of the system are obtained by importance analysis, which will provide data for system fault diagnosis and preventive maintenance.

In view of the shortcomings of the lathe tool measuring instrument used in the present experimental teaching, a device for measuring the geometric angle of the lathe tool by using magnetic encoder is studied. The device combines the machine and electricity organically to realize the digital display of the measuring instrument. At the same time, in consideration of the geometric angle measurement of the lathe tool completed in the reference plane, we design the mechanical structure of the measuring instrument and the 3 ways of realizing measure slice, shaft shoulder and shaft end. The instrument is simple in structure and convenient in measurement. It can measure the geometric angle of the lathe tool and improve the measurement accuracy. It is applied to the experimental teaching of the undergraduate course and has achieved very good teaching effect.

Additional file 1.

With the wide application of distributed generators (DGs) and other distributed energy sources (DERs) being integrated to distribution systems, the DGs can be described as different load flow models. Traditional load flow calculation model might have difficulty in getting the load flow results fast and accurately. A novel model to solve the load flow problem is proposed in this paper, especially for distribution systems with DGs. Based on the analysis of DGs' characteristics, the buses are classified into 5 types: slack bus, PQ bus, interconnecting (IC) bus, PV bus and PI bus. Using the current injection equations written in rectangular coordinates, different variables (I, θ, V, α, I x , Q) are introduced into the proposed model for different bus types. The computational results validate the effectiveness and accuracy of the proposed method, when compared to the traditional load flow model in terms of power injections.

The load spectrum of the feed system for the numerical control (NC) machine tool is the objective basis of the reliability design and life prediction. So, a compilation method of load spectrum is proposed by using the mixture Weibull distribution (MWD). First, the load distribution in each feed direction is fitted by using the MWD. Among them, the Bayesian information criterion (BIC) determines the number of mixture components, the parameters of MWD are estimated by using the improved expectation maximization (IEM) algorithm, where the initial values of parameters are determined by the hidden Markov model (HMM). Second, the correlation between the loads in different feed directions is analyzed, and the joint distribution function (JDF) is established. Finally, the program loading spectrum is compiled by using the ratio coefficient. In this paper, the relative feed speed spectrum in the X-direction and Z-direction of NC lathes are established, case analysis results show that the relative feed speed distributions that use the proposed method have high fitting precision, and the load spectrum are compiled, which will be able to apply the reliability test, accelerated test and life prediction. Thus, the study of load spectrum has important theoretical significance and engineering application value.

Plenty of transmission substations in large scale power system are designed to deliver power to electricity users far away from power plants, and most of them can be seen as interconnecting (IC) nodes. Interconnecting node has the characteristic of zero power injection, thereafter causes zero current injection to the power system. A novel power flow calculation model is proposed, based on the elimination of IC node equations, to get more fast power flow calculation. The power network equations of IC nodes are eliminated so as to reduce the total dimension of the power flow model. Then, element-wise Jacobian matrix are deduced according to the reduced system power balance equations, in relationship to partial voltage vectors of non-interconnecting nodes. Tests on IEEE standard systems are then performed to validate the proposed method, and computation efficiency are compared with the traditional formulation of power flow model.

Electron-beam induced radiation damage can give rise to large structural collapse and deformation of low k and ultra low k IMD in semiconductor devices, posing great challenges for failure analysis by electron microscopes. Such radiation damage has been frequently observed during both sample preparation by dual-beam FIB and TEM imaging. To minimize radiation damage, in this work we performed systematic studies on every possible failure analysis step that could introduce radiation damage, i.e., pre-FIB sample preparation, FIB milling, and TEM imaging. Based on these studies, we utilized comprehensive technical solutions to radiation damage by each failure analysis step, i.e., low-dose/low-kV FIB and low-dose TEM techniques. We propose and utilize the low-dose TEM imaging techniques on conventional TEM tools without using low-dose imaging control interface/software. With these new methodologies or techniques, the electron-beam induced radiation damage to ultra low k IMD has been successfully minimized, and the combination of single-beam FIB milling and low-dose TEM imaging techniques can reduce structure collapse and shrinkage to almost zero.