一体化双丝弧焊电源智能控制策略与工艺性能评定方法
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摘要
目前双丝电源存在体积大、协同控制复杂、智能化程度较低的问题，而工艺性能难以定量评定的现状又进一步制约了智能化控制和智能优化技术在双丝电源中的实现。针对上述问题，提出一种能有效解决协同控制问题的一体化设计思想，并就双丝弧焊电源智能控制策略和工艺性能定量评定中的关键和难点问题进行了深入系统的研究。
提出了基于DSP的一体化双丝弧焊电源的设计方案，通过一个控制系统直接给定两路电流控制信号，同时控制两个有限双极性软开关主回路，解决了协同通信问题。为了指导元器件选择，避免设计的盲目性，进行了建模仿真研究，建立了基于元器件的主电路模型和基于信号流的控制系统模型，实现了两者的联接调试，利用整体仿真模型预测了双丝焊电源的工作过程。
出于信号降噪的目的，进行了数字滤波算法研究。研究了时滞滤波改进算法、自适应梯度格型改进算法。仿真试验表明时滞滤波改进算法滤波效果好，运行速度快，但算法受电流参数影响较大；自适应梯度格型改进算法在滤波效果、运行时间和光滑度上都有较好的表现。
研究发现双丝弧焊电源每路送丝速度不仅由自身的电流大小决定，还受到另一路电流大小等多种因素的影响。通过相关分析筛选了4个送丝速度主要影响因素，建立了支持向量机送丝速度预测控制模型。为了获得较好的模型精度，利用网格算法具体研究了参数对模型学习精度和泛化能力的影响。最后利用粒子群智能优化算法对支持向量机模型参数进行了选择。焊接试验结果表明，优化后的模型能取得较好的预测控制效果。
根据一体化设计思路，进行了控制系统软硬件设计。研究了电流不同脉冲阶段的信号特征，设计了自适应模糊PID控制器，实现PID参数的在线整定。试验表明模糊PID控制器动静特性更为优良。
从电信号的角度进行了工艺性能定量评定研究。利用样本熵算法分析了电流稳定性，并具体研究了电信号参数对样本熵的影响，设计了双丝定量评定指标。设计了电信号的统计学稳定性评价指标，利用交叉验证思想，对照样本熵指标进行了验证。
从电弧声入手，分析焊接过程的稳定性和飞溅情况。根据飞溅产生时电弧声能量增大的原理，利用短时能量的累计分布函数和概率分布图设计了统计学量化指标。进一步，利用声谱图研究电弧声的能量变化规律性，寻找时频面上峰值能量曲线，通过样本熵计算峰值能量的稳定度，设计了对应的指标进行定量评定。
为了避免焊缝质量评定的主观随意性，结合焊缝缺陷分级的国家标准，提出了一种模糊评价的方法。设计实现了级联式焊缝模糊评价模型，从缺陷程度上对焊缝进行了定量评定。
提出多信息融合的定量评定思想，利用支持向量机对电信号、电弧声、焊缝质量的量化结果建立回归模型，最终实现双丝焊接工艺性能的定量评定。
在自行搭建的焊接试验平台上对自主开发的一体化双丝弧焊电源进行了性能测试和双丝电流相位关系焊接试验，并对工艺性能进行了定量评定。结果表明，电源性能良好，评定结果可信。在此基础上，设计了一种双丝焊新型互补对称过渡脉冲电流控制方法，并利用正交试验法进行了研究和分析。试验显示，新工艺在稳定性和焊缝成型上具有一定优势。
综上，一体化双丝机设计思想的提出，解决了双丝焊机协同控制复杂的问题。双丝电源的输入信号数字滤波、送丝速度支持向量机预测、模糊PID控制等智能优化控制策略的研究，为智能化双丝焊电源的进一步开发奠定了基础。电信号、电弧声、焊缝质量定量评定指标和支持向量机多信息融合方法，为焊接工艺性能定量评定寻找了新途径。
At present, double wire welding power source has many shortcomings, such as large size,complex collaborative control and low intelligence. And the performance is difficult toquantitatively assess, which restricts the realization of intelligent control and intelligentoptimization in double wire power. In response to these issues, the integrated design ideas areproposed to solve collaborative control problems. Further, key and difficult problems inintelligent control strategies of double wire arc welding power source and quantitativeassessment of process performance are in depth research.
The design of integrated double wire arc welding power source based on DSP isproposed. The two current control signals are directly given by single control system thatcontrols two limited bipolar soft switching main circuits simultaneously, which solve thecollaborative communication problems. In order to guide component selection and avoiddesign blindness, modeling and simulation is done. Control system model based on signalflow and main circuit model based on components are established. And the connection anddebug between above two models is realized. The overall simulation model is used to predictthe working process of the double wire welding power.
For the purpose of the signal noise reduction, digital filtering algorithms, includingdelay filter improved algorithm and adaptive gradient lattice improved algorithm, are studied.The simulation results show that delay filter improved algorithm has good filtering effects andhigh running speed, but it is influenced easily by current parameters. While adaptive gradientlattice improved algorithm has better performance in terms of filtering effect, the running timeand smooth surface.
The study found that each wire feed speed of double wire arc welding power source isdetermined not only by their current size, but also by the other current size and a variety offactors. Through correlation analysis, four main influencing factors of wire feed speed arescreened out, and support vector machine predictive control model of the wire feed speed isestablished. In order to obtain better accuracy of the model, the impact of parameters on model learning precision and generalization ability is studied by grid algorithm. Finally, themodel parameters of support vector machines are chosen by particle swarm intelligenceoptimization algorithm. Welding test results show that the optimized model can obtain betterpredictive control.
According to integrated design ideas, the hardware and software of the control system isdesigned. Then the signal characteristics of different current pulse are studied, and adaptivefuzzy PID controller is designed. Finally, online tuning of PID parameters is realized.The experiments show that the static and dynamic characteristics of fuzzy PIDcontroller are superior.
Process performance is quantitatively assessed from the point of view of electrical signal.The current stability is analyzed by sample entropy algorithm, and the influence of signalparameters on the sample entropy is studied. Double wire quantitative assessment indicatorsand statistical stability evaluation indicators of the electrical signal are designed. Then theindicators are verified in the contrast to sample entropy indicators by the use of crossvalidation ideas.
Starting from the arc sound, the stability and splash of the welding process is analyzed.According to the principle that the arc sound energy increases when splash occurs, statisticalquantitative indicators are designed by the use of the cumulative distribution function of theshort term energy and probability distribution. Further, by the spectrogram, arc sound energyvariation is studied, and peak energy curve of time frequency surface is searched. The stability of the peak energy is calculated by sample entropy, and the corresponding index isdesigned for quantitative assessment
In order to avoid the subjective assessment of weld quality, combined with national standards for weld defect classification, a fuzzy evaluation method is proposed. The cascade weldfuzzy evaluation model is designed and implemented for quantitative assessmentof the weld defect.
The multi information fusion thought for quantitative assessment is presented.Regression model for electrical signal, the arc sound and quantitative results of weld quality isestablished by support vector machine. So the quantitative assessment of double wire weldingperformance is achieved.
On the self development welding test platform, the performance of self developedintegrated double wire arc welding power source is tested, and the double wire current phaserelationship welding experiment is done. The process performance is assessed quantitatively,too. The results show that the power performance is good, and the assessment results arereliable. On this basis, a new complementary symmetry transition pulse current controlmethod for double wire welding is designed. And the method is analyzed by orthogonal test.Trials have shown that new technology has certain advantages in stability and weld molding.
In summary, the integrated double wire welding power source solves the problem ofcomplex collaborative control. The intelligent optimization control strategies, such as digitalfiltering of double wire power input signal, support vector machines prediction of the wirefeed speed and fuzzy PID control, lay the foundation for the further development of the intelligent double wire welding power. The method of multi information fused with Electricalsignals, arc sound, quantitative assessment indicators of weld quality and support vectormachine find a new way for quantitative assessment of the welding performance.
提出了基于DSP的一体化双丝弧焊电源的设计方案，通过一个控制系统直接给定两路电流控制信号，同时控制两个有限双极性软开关主回路，解决了协同通信问题。为了指导元器件选择，避免设计的盲目性，进行了建模仿真研究，建立了基于元器件的主电路模型和基于信号流的控制系统模型，实现了两者的联接调试，利用整体仿真模型预测了双丝焊电源的工作过程。
出于信号降噪的目的，进行了数字滤波算法研究。研究了时滞滤波改进算法、自适应梯度格型改进算法。仿真试验表明时滞滤波改进算法滤波效果好，运行速度快，但算法受电流参数影响较大；自适应梯度格型改进算法在滤波效果、运行时间和光滑度上都有较好的表现。
研究发现双丝弧焊电源每路送丝速度不仅由自身的电流大小决定，还受到另一路电流大小等多种因素的影响。通过相关分析筛选了4个送丝速度主要影响因素，建立了支持向量机送丝速度预测控制模型。为了获得较好的模型精度，利用网格算法具体研究了参数对模型学习精度和泛化能力的影响。最后利用粒子群智能优化算法对支持向量机模型参数进行了选择。焊接试验结果表明，优化后的模型能取得较好的预测控制效果。
根据一体化设计思路，进行了控制系统软硬件设计。研究了电流不同脉冲阶段的信号特征，设计了自适应模糊PID控制器，实现PID参数的在线整定。试验表明模糊PID控制器动静特性更为优良。
从电信号的角度进行了工艺性能定量评定研究。利用样本熵算法分析了电流稳定性，并具体研究了电信号参数对样本熵的影响，设计了双丝定量评定指标。设计了电信号的统计学稳定性评价指标，利用交叉验证思想，对照样本熵指标进行了验证。
从电弧声入手，分析焊接过程的稳定性和飞溅情况。根据飞溅产生时电弧声能量增大的原理，利用短时能量的累计分布函数和概率分布图设计了统计学量化指标。进一步，利用声谱图研究电弧声的能量变化规律性，寻找时频面上峰值能量曲线，通过样本熵计算峰值能量的稳定度，设计了对应的指标进行定量评定。
为了避免焊缝质量评定的主观随意性，结合焊缝缺陷分级的国家标准，提出了一种模糊评价的方法。设计实现了级联式焊缝模糊评价模型，从缺陷程度上对焊缝进行了定量评定。
提出多信息融合的定量评定思想，利用支持向量机对电信号、电弧声、焊缝质量的量化结果建立回归模型，最终实现双丝焊接工艺性能的定量评定。
在自行搭建的焊接试验平台上对自主开发的一体化双丝弧焊电源进行了性能测试和双丝电流相位关系焊接试验，并对工艺性能进行了定量评定。结果表明，电源性能良好，评定结果可信。在此基础上，设计了一种双丝焊新型互补对称过渡脉冲电流控制方法，并利用正交试验法进行了研究和分析。试验显示，新工艺在稳定性和焊缝成型上具有一定优势。
综上，一体化双丝机设计思想的提出，解决了双丝焊机协同控制复杂的问题。双丝电源的输入信号数字滤波、送丝速度支持向量机预测、模糊PID控制等智能优化控制策略的研究，为智能化双丝焊电源的进一步开发奠定了基础。电信号、电弧声、焊缝质量定量评定指标和支持向量机多信息融合方法，为焊接工艺性能定量评定寻找了新途径。
At present, double wire welding power source has many shortcomings, such as large size,complex collaborative control and low intelligence. And the performance is difficult toquantitatively assess, which restricts the realization of intelligent control and intelligentoptimization in double wire power. In response to these issues, the integrated design ideas areproposed to solve collaborative control problems. Further, key and difficult problems inintelligent control strategies of double wire arc welding power source and quantitativeassessment of process performance are in depth research.
The design of integrated double wire arc welding power source based on DSP isproposed. The two current control signals are directly given by single control system thatcontrols two limited bipolar soft switching main circuits simultaneously, which solve thecollaborative communication problems. In order to guide component selection and avoiddesign blindness, modeling and simulation is done. Control system model based on signalflow and main circuit model based on components are established. And the connection anddebug between above two models is realized. The overall simulation model is used to predictthe working process of the double wire welding power.
For the purpose of the signal noise reduction, digital filtering algorithms, includingdelay filter improved algorithm and adaptive gradient lattice improved algorithm, are studied.The simulation results show that delay filter improved algorithm has good filtering effects andhigh running speed, but it is influenced easily by current parameters. While adaptive gradientlattice improved algorithm has better performance in terms of filtering effect, the running timeand smooth surface.
The study found that each wire feed speed of double wire arc welding power source isdetermined not only by their current size, but also by the other current size and a variety offactors. Through correlation analysis, four main influencing factors of wire feed speed arescreened out, and support vector machine predictive control model of the wire feed speed isestablished. In order to obtain better accuracy of the model, the impact of parameters on model learning precision and generalization ability is studied by grid algorithm. Finally, themodel parameters of support vector machines are chosen by particle swarm intelligenceoptimization algorithm. Welding test results show that the optimized model can obtain betterpredictive control.
According to integrated design ideas, the hardware and software of the control system isdesigned. Then the signal characteristics of different current pulse are studied, and adaptivefuzzy PID controller is designed. Finally, online tuning of PID parameters is realized.The experiments show that the static and dynamic characteristics of fuzzy PIDcontroller are superior.
Process performance is quantitatively assessed from the point of view of electrical signal.The current stability is analyzed by sample entropy algorithm, and the influence of signalparameters on the sample entropy is studied. Double wire quantitative assessment indicatorsand statistical stability evaluation indicators of the electrical signal are designed. Then theindicators are verified in the contrast to sample entropy indicators by the use of crossvalidation ideas.
Starting from the arc sound, the stability and splash of the welding process is analyzed.According to the principle that the arc sound energy increases when splash occurs, statisticalquantitative indicators are designed by the use of the cumulative distribution function of theshort term energy and probability distribution. Further, by the spectrogram, arc sound energyvariation is studied, and peak energy curve of time frequency surface is searched. The stability of the peak energy is calculated by sample entropy, and the corresponding index isdesigned for quantitative assessment
In order to avoid the subjective assessment of weld quality, combined with national standards for weld defect classification, a fuzzy evaluation method is proposed. The cascade weldfuzzy evaluation model is designed and implemented for quantitative assessmentof the weld defect.
The multi information fusion thought for quantitative assessment is presented.Regression model for electrical signal, the arc sound and quantitative results of weld quality isestablished by support vector machine. So the quantitative assessment of double wire weldingperformance is achieved.
On the self development welding test platform, the performance of self developedintegrated double wire arc welding power source is tested, and the double wire current phaserelationship welding experiment is done. The process performance is assessed quantitatively,too. The results show that the power performance is good, and the assessment results arereliable. On this basis, a new complementary symmetry transition pulse current controlmethod for double wire welding is designed. And the method is analyzed by orthogonal test.Trials have shown that new technology has certain advantages in stability and weld molding.
In summary, the integrated double wire welding power source solves the problem ofcomplex collaborative control. The intelligent optimization control strategies, such as digitalfiltering of double wire power input signal, support vector machines prediction of the wirefeed speed and fuzzy PID control, lay the foundation for the further development of the intelligent double wire welding power. The method of multi information fused with Electricalsignals, arc sound, quantitative assessment indicators of weld quality and support vectormachine find a new way for quantitative assessment of the welding performance.
引文
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