Sample Entropy-Based Approach to Evaluate the Stability of Double-Wire Pulsed MIG Welding

Abstract

According to the sample entropy, this paper deals with a quantitative method to evaluate the current stability in double-wire pulsed MIG welding. Firstly, the sample entropy of current signals with different stability but the same parameters is calculated. The results show that the more stable the current, the smaller the value and the standard deviation of sample entropy. Secondly, four parameters, which are pulse width, peak current, base current, and frequency, are selected for four-level three-factor orthogonal experiment. The calculation and analysis of desired signals indicate that sample entropy values are affected by welding current parameters. Then, a quantitative method based on sample entropy is proposed. The experiment results show that the method can preferably quantify the welding current stability.

Quantitative evaluation method of arc sound spectrum based on sample entropy

“…(2), m, r are respectively the dimension of vector and threshold for calculating the sample entropy, SampEn(P,m,r,N) is a proposed function by ourselves used in Matlab, the detailed mathematical description was included in our previous works [34,35].…”

Research of a Multi-Frequency Waveform Control Method on Double-Wire MIG Arc Welding

“…Considering the different situations above and combining electromagnetic theories, relative experiments and corresponding analyses [19][20][21], a new multi-frequency double-wire waveform control method (Figure 3d) was proposed in this work. It can be seen from the figure that when the leading wire current switched from peak stage to base stage after one cycle, the central control system gave out a signal which made the trailing wire current turning from base stage to peak stage.…”

“…The experimental results were collected by our self-designed dynamic arc wavelet analyzer, and then the electrical signals were intuitively analyzed by means of transient current waveform, voltage-current probability density distribution, transient energy graph, and other relative tools. In addition, combining the phenomena observed during the welding process and quality obtained under different parameters combination, the welding quality can be quantitatively described by combining the entropy calculation of stability of electrical signals, probability density distribution evaluation and arc sound stability evaluation, then each quality score can use a mean value of three experiments, as detailed illustrated in the previous works [20,24]. Table 2 shows the experimental parameters and corresponding quality scores.…”

A Multistage Hybrid Model ICEEMDAN-SE-VMD-RDPG for a Multivariate Solar Irradiance Forecasting

“…Higher SE is exhibited by less foreseeable time series; whereas, the time series with regular patterns reveals a smaller SE value [50]. The SE process can be explained by the following steps [51]: (i) The time series with N points as the original data can be given as:…”