基于热膨胀的点焊实时控制系统的研制

提出了一种在恒流点焊控制器基础上加入电极热膨胀位移控制规则的方法。利用激光位移传感器及其外围电路，建立了热膨胀的微机点焊控制系统，并使用屏蔽电路实现恒流控制与热膨胀控制的相互切换。实验结果表明，该系统具有自适应特性，能够实时的实现点焊过程中的质量监控。     

基于电极位移的电阻点焊控制器研究

电阻点焊是车身装配最主要的手段，焊点质量好坏直接影响整车的性能。基于电极位移提出了一种电阻点焊实时闭环控制方法，利用高精度非接触式激光位移传感器及其相关控制电路，建立了热膨胀位移采集系统。基于最优电极位移曲线，采用PID控制算法，通过实时改变可控硅导通角来控制焊接控制器的各周波的焊接电流，控制焊点质量。针对双相高强钢DP600进行了试验，结果表明，该系统能够有效地控制焊接质量，保证了焊点的拉剪强度，并能有效抑制飞溅。     

电阻点焊过程多传感器实时监测

构建了基于RS-485分布式单片机同步数据采集系统,所设计的电阻点焊电流、电压、电极位移和电极压力传感器满足点焊过程质量实时监测要求.研究发现:利用电极位移的极差和电极压力的极差可以判断铝合金脉冲点焊焊点未熔合或未完全熔合缺陷.当焊点出现内喷溅时,电极位移出现向下尖脉冲信号,电压信号出现"下榻"现象,电极压力产生高频脉冲信号,该脉冲幅值和持续时间与内喷溅严重程度相对应.利用以上特征信息可以实时监测焊点质量.     

不锈钢多脉冲点焊过程热膨胀电极位移的变化规律

热膨胀电极位移是反映电阻点焊质量变化的重要指标,然而多脉冲焊接条件下热膨胀电极位移的动态变化与熔核生长的关系规律尚不清楚。基于商业有限元仿真软件ANSYS建立2D轴对称电-热-力耦合模型,对奥氏体不锈钢点焊过程中熔核生长、热膨胀电极位移变化以及各阶段电流对熔核形成的影响规律进行研究,并通过点焊实验对数值计算模型的有效性进行验证。研究结果表明:熔核首先在工件接触面处产生,然后沿径向与厚度方向生长,最终形成椭球状焊核;热膨胀电极位移与液态熔核尺寸具有相同的变化趋势,在焊接后期熔核进入平稳生长后,二者趋于线性相关。多脉冲焊接条件下焊接脉冲对熔核生长影响最大,预热脉冲和回火脉冲对其无明显影响。     

铝合金电阻点焊多信息融合与质量分类

采用分布式多传感器同步采集系统实现铝合金点焊质量实时监测,并利用LABVIEW图形化语言编制相关数据处理软件。研究发现：焊点内喷溅与点焊电压和电极位移信号波形“下榻”现象相关联;电极压力所产生的高频脉冲强度和持续时间与内喷溅强弱有关,三种特征信息根据内喷溅严重程度,同时发生或个别出现。所提取的9种特征信息能够反映点焊质量,信噪比高,可为实现铝合金点焊质量分类奠定基础。采用主成分分析可进一步实现信息融合和数据压缩,点焊质量判断准确率达98 %。     

电阻焊在线质量检测的软件实现

电阻焊质量在线评估的一种有效方法是对焊接过程中的重要物理量进行实时采集处理和显示。讨论了用VB6．0编程，实现工控计算机和80C196单片机之间的串行通信，以及动态曲线的生成和显示，从而对焊接电流和电极压力进行实时监测。联机试验所生成的波形图反映了三相次极整流点焊的动态焊接过程，可以作为判断焊接质量和焊机系统工作状况的重要依据，为点焊质量多参数联合监控奠定了基础。     

点焊电流有效值神经网络实时计算方法研究

通过理论分析,推导出交流电阻点焊电流有效值实时计算方程,建立了不同功率因数角的电流有效值系数K的神经网络计算模型,研究出电阻点焊电流有效值神经网络实时计算方法。在以DSP为核心的电阻点焊测控系统中实现了交流电阻点焊电流有效值实时计算。理论分析和实际检测表明,该方法的检测误差小于±0.9％,并且能够在二分之一周期内完成电阻点焊电流有效值的检测和计算。该方法的研究为电阻点焊质量的精确控制提供了可靠的保障。     

地下位移实时监测系统设计

介绍一个能实现地下位移远程实时监测的系统,并简要介绍了该系统的构成以及硬件和软件的设计.同时对该系统中采用的一种基于电磁感应互感原理的新型地下位移传感器进行了原理分析,并结合实验数据对传感器的参数选择进行了理论探讨.实验结果表明,该系统能较好的实现地下位移的远程实时监测.     

基于电极位移信号特征分析的电阻点焊质量监测

提出一种基于点焊过程信息采集和处理的焊点质量在线监测方法。通过对电极位移、动态电阻信号的实时采集和分析,利用电阻信号动态特征刻画熔核形成的不同阶段,从同步位移信号中提取12个与焊点质量相关的动态特征参量。通过对提取的特征参量与作为焊点质量评价指标的抗剪强度之间的相关性分析,选取相关性显著的特征参量作为输入和抗剪强度为输出,建立线性回归、非线性回归及径向基函数神经网络焊点质量监测模型。监测模型的有效性检验结果表明,建立的三种监测模型都可实现对焊点质量的在线监测。径向基函数神经网络模型的监测准确率高于其他两种模型,其平均验证误差为2.28%,最大验证误差低于10%。     

电阻点焊位移信号的混沌与分形特性试验

以混沌理论为基础对电阻点焊位移信号进行分析与研究,通过对7种不同工作状态下时间序列的最大Lyapunov指数计算,发现点焊位移信号的值均大于0,证明位移信号中存在混沌现象,应采用混沌的方法研究与分析点焊位移信号,该研究为点焊质量的判断和预测开辟有效的途径.由于用经典欧式几何方法描述位移信号误差较大,提出用分形维数作为特征值来量化具有混沌特性的点焊质量,点焊位移检测试验结果表明此方法能反映点焊质量微小变化,可提高质量检验的准确性.     

Quality control based on electrode displacement and force in resistance spot welding

The behaviors of electrode displacement and force during spot welding under various conditions, such as different weld currents, electrode forces, and welding times, were studied. Tests were conducted on a 170 kVA MFDC spot welder. Data were collected via a multichannel high-speed data acquisition system and were analyzed with MATLAB. Behaviors of 5182 aluminum and mild steel in spot welding were compared. Results show that nugget expansion rate does not reach zero for aluminium as it does for mild steel as nugget grew to a certain size. A linear relationship is found between the nugget size and maximum expansion that facilitates online weld quality evaluation. An electrode force peak is observed and believed relevant to the sufficient nugget size.     

材料属性温度相关热弹塑性接触问题研究

应用有限元方法建立了可考虑屈服应力温度相关效应的粗糙表面热弹塑性接触模型。研究了摩擦力和不同热输入情况下圆柱体与弹塑性平面的接触力学特性。求解了考虑屈服应力温度相关效应的粗糙表面热弹塑性接触问题,探讨了摩擦热效应对表面温升、接触压力、平均间隙及接触体应力分布的影响。提出了考虑热膨胀系数温度相关效应的热弹塑性接触模型。通过刚性圆柱体与半无限大平面的热弹塑性接触研究了热膨胀系数温度相关效应对接触体应力分布的影响。
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Modeling small-scale resistance spot welding machine dynamics for process control

Electrode displacement is generally regarded as a variable that can provide real-time information useful for monitoring and controlling resistance spot welding (RSW) process quality. However, in small-scale RSW production, it is difficult to measure the displacement because its magnitude is very small. By contrast, force signals are relatively large and thus are less susceptible to measurement noise. In this article, an empirical model is proposed to simulate the dynamics of an SSRSW head with the objective of calculating electrode displacement from the variation of electrode clamping force measured during welding. The parameters in the model were determined by fitting experimental force and displacement signals with polynomials and then performing an optimization search for parameters of first-order dynamic models. To verify the models’ accuracy, they were subsequently applied to simulate the electrode displacement curves of welds with expulsion and without expulsion. The calculated displacement curves agreed well with experimental measurements, and the occurrence of expulsion was clearly indicated by the model predictions. A more comprehensive model is under construction with an objective to eliminate displacement sensor in the monitoring and control of SSRSW process.     

Grey relational and neural network approach for multi-objective optimization in small scale resistance spot welding of titanium alloy

The prediction and optimization of weld quality characteristics in small scale resistance spot welding of TC2 titanium alloy were investigated. Grey relational analysis, neural network and genetic algorithm were applied separately. Quality characteristics were selected as nugget diameter, failure load, failure displacement and failure energy. Welding parameters to be optimized were set as electrode force, welding current and welding time. Grey relational analysis was conducted for a rough estimation of the optimum welding parameters. Results showed that welding current played a key role in weld quality improvement. Different back propagation neural network architectures were then arranged to predict multiple quality characteristics. Interaction effects of welding parameters were analyzed with the proposed neural network. Failure load was found more sensitive to the change of welding parameters than nugget diameter. Optimum welding parameters were determined by genetic algorithm. The predicted responses showed good agreement with confirmation experiments.

     

基于Volterra级数的转子故障诊断研究 

基于Volterra级数的转子故障诊断研究
唐浩;屈梁生;温广瑞
西安交通大学机械制造系统工程国家重点实验室,西安,710049
在简要介绍了Volterra级数基本理论的同时,应用遗传算法对Volterra级数的核进行了辨识,并取得了良好的辨识效果。与传统的基于信号处理的诊断方法不同,该方法将基于系统模型的Volterra级数非线性故障诊断方法应用于转子轴承系统的故障诊断,研究了转子在正常状态和碰摩状态下的起车过程中Volterra级数核的变化。实验结果验证了该方法的可行性与有效性。
This paper briefly introduced the basic theory of
Volterra series.Then,it identified the Volterra kernels by using genetic algorithm(GA) and achieved a satisfactory identification result.Being different from the traditional diagnosis schemes based on signal processing approach,the Volterra series method based on system modeling was employed in the area of fault diagnosis for rotor-bearing system.We
investigated the changes of Volterra kernels under normal state and rubbing state during run-up stages.Finally,experimental results certify its feasibility and effectiveness.
Volterra;nonlinear;genetic algorithm;fault diagnosis     

SPOT WELDING QUALITY FUZZY CONTROL SYSTEM BASED ON MULTISENSOR INFORMATION FUSION

The multisensor information fusion technology is adopted for real time measuring the four parameters which are connected closely with the weld nugget size(welding current,electrode displacement,dynamic resistance,welding time),thus much more original information is obtained.In this way,the difficulty caused by measuring indirectly weld nugget size can be decreased in spot welding quality control,and the stability of spot welding quality can be improved.According to this method,two-dimensional fuzzy controllers are designed with the information fusion result as input and the thyristor control signal as output.The spot welding experimental results indicate that the spot welding quality intelligent control method based on multisensor information fusion technology can compensate the influence caused by variable factors in welding process and ensure the stability of welding quality.