液压挖掘机振动掘削机理及其过程优化建模与智能控制策略研究
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摘要
至今为止,广泛应用的液压挖掘机由于掘削方式所限,仍然存在着能量利用率较低以及作业能力相对不足等严重问题,如何对工程机械中的能耗大户——液压挖掘机实施节能减排和智能控制,已成为工程技术研究的焦点之一。为了直接减小液压挖掘机掘削阻力,使在掘削作业过程中达到低能耗、高效率,并具有一定的自适应能力,本文以国家863课题[2003AA430200]“挖掘机的机电一体化及制造信息化”为依托,结合教育部“新世纪优秀人才支持计划”[NCET-05-0697],将振动理论应用于液压挖掘机掘削过程,采用理论分析与实验研究相结合的方法,以期探索一种合理有效的新型液压挖掘机土壤掘削方法,并对其掘削过程进行优化建模与智能控制策略研究,论文的主要工作如下:
(1)研究了土壤静强度特性、动强度特性,探讨了土壤掘削原理及失效机理,进行了岩土破碎过程静态加载和动态载荷作用下的仿真实验研究,得到了动态载荷振动冲击作用不但可以大幅降低掘削阻力,也可以改善刀具的受力方式,从而使得岩体在低于破坏强度时就产生破坏的结论。
(2)针对液压挖掘机振动掘削过程铲斗激振力检测信号不可避免地受到噪声干扰的实际情况以及该检测信号含噪声特征,应用软门限方法对以宽带随机噪声为背景的信号IMF分量作门限处理,提出了一种基于EMD的含噪信号噪声处理的算法,并进行了仿真应用研究,所获得的去噪处理算法为分析提取铲斗激振力信号的特征线谱提供了有力的工具。
(3)建立了基于LS-SVM的液压挖掘机振动掘削过程土壤参数在线辨识算法,并在此基础上进行了土壤固有频率等参数的在线辨识仿真研究,在线辨识仿真及共振柱实验法实验结果表明,该土壤参数在线辨识算法具有更小的误差、更好的辨识能力和较高的辨识精度,更能适合于动态系统的辨识。
(4)分析了激振频率、振幅和插入速度等对振动掘削阻力的影响,并对其进行了参数优选匹配,基于振动参数的优选匹配试验的极差分析结果,利用正交扩展型函数链神经网络建立了土壤振动掘削阻力软测量模型,并采用函数链神经网络进行了相应的在线自校正。通过与实测值对比验证了该软测量模型的建模精度和泛化能力。
(5)建立了静态掘削、正弦波激振掘削、三角波激振掘削三种掘削方式的液压挖掘机掘削功率消耗模型,并进行了实验研究,找到了一种节能效果较好的振动掘削方式。
(6)开发了一种将专家控制、非线性PI控制器以及单神经元相结合,采用自适应粒子群优化方法对其参数进行最优整定的液压挖掘机振动掘削智能控制系统,提出了基于Ultronics双阀芯结构控制阀的振动掘削执行机构的控制策略,并对其数据通讯和控制模式实现进行了研究。
(7)搭建了SWE85型液压挖掘机振动掘削实验平台,并对振动掘削控制系统的平稳性、高频响应特性、控制策略的适用性以及振动掘削阻力和功率消耗情况进行了实验研究。实验研究验证了所开发的液压挖掘机振动掘削控制系统具有较好稳定性、快速性等性能,符合振动掘削的功能要求。采用正弦波振动掘削可使掘削阻力降低到70%左右,功率消耗降低到80%左右。
总之,论文对液压挖掘机振动掘削新方法进行了系统的研究,取得了较高应用价值的研究成果,为其实用化研究打下了较为扎实的理论基础。
Nowadays it is known that there are some difficulties, such as lower energy rate and inadequate work capacity in the excavating process for hydraulic excavator because of conventional excavating pattern and it is very important for hydraulic excavator with high energy consuming from engineering machines how to realize optimum and intelligent control in excavating process. In order to minish directly excavating resistance and energy consuming of hydraulic excavator and enhance work efficiency and self-adaptive capacity, some main research task in this paper such as seeking after a reasonable and effective excavating method for soil and process optimization modeling and intelligent control strategy of hydraulic excavator are completed based on applying vibratory theory to soil excavating process for hydraulic excavator and using theory analysis and experiment research combinatively, and the research fund is obtained from "863 Research Fund[2003AA430200]"(namely mechanics-electronics and manufacture informatization of hydraulic excavator) and "Program for New Century Excellent Talents in University"[NCET-05-0697]. The main works of the paper are expressed as:
(1) The characteristic of static intensity and dynamic intensity were studied and excavating principle and invalidation mechanism to soil were discussed. The simulation experiment results about crashing rock and soil process based on dynamic load receal that vibratory impact function dynamic load can improve force method of shovel blade and minish excavating resistance in a big way, therefore, rock and soil can be destroyed even if its stress lower than its destructive intensity.
(2) In allusion to fact circs of noise jamming of exciting force signal from the buchet inevitably and the characteristic of noise from exciting force signal in the vibratory excavating process for hydraulic excavator, IMF weight of signal based on the wideband random noisy background is processed using soft threshold method and a signal denoising algorithm for noisy signal is given based on EMD method. The simulation results reveal that the signal denoising algorithm can enhance decomposing veracity of exciting force signal from the buchet, time effect property of extracting instantaneous parameters and can remove availably noise jamming of exciting force signal from the buchet.
(3) A online identification algorithm about rock and soil parameters in the vibratory excavating process for hydraulic excavator is given based on LS-SVM. And then online identification about some parameters of soil such as natural frequency was simulated. The results of its simulation and resonant column experiment reveal that the online identification algorithm is of smaller error, better identification capacity and higher identification precision and it is much fit for dynamic systems identification.
(4)The impacts on vibratory excavating resistance from the parameters such as exciting frequency, amplitude and inserting velocity were analyzed and the parameters were preferentially matched. Based on matched results, a soft sensing model of vibratory excavating resistance form rock and soil is established by using of orthogonal and extensible function chain neural network and its online self-correction was done accordingly by using of function chain neural network. The application results reveal that soft sensing model is of much high modeling precision and generalization capability.
(5) The excavating power consuming models due to different excavating methods such as static excavating, sine wave excavating and triangle wave excavating in the hydraulic excavator is established and corresponding experiments were done. A kind of excavating method with better effect in saving energy aspect than other excavating methods was gotten.
(6)An intelligent control system for vibratory excavating in the hydraulic excavator was designed by using of combinative expert control, non-linear PI controller and single neuron and its parameter can be tuned based on self-adaptive particle swarm optimization algorithms. The control tactic of executive machine for vibratory excavating was submitted based on Ultronics control valve with double cores and its data communication and control model application were studied.
(7)An experiment platform for vibratory excavating rock and soil in SWE85 hydraulic excavator is set up and the stability of control system for vibratory excavating, the respond characteristic of high frequency, the applicability of control strategy, excavating resistence and power consuming were studied by using of the experiments. The experiments results reveal that the vibratory excavating control system in hydraulic excavator is of better stability and rapid capability and can ensure that excavating resistence depress to 70% and power consuming depress to 80% when exerting sine wave vibratory methods.
In a word, a new vibratory excavating method for the hydraulic excavator was studied by the numbers in the paper and some research achievements with higher applied price were gotten, which can offer steadier theory basis for practicability.
(1)研究了土壤静强度特性、动强度特性,探讨了土壤掘削原理及失效机理,进行了岩土破碎过程静态加载和动态载荷作用下的仿真实验研究,得到了动态载荷振动冲击作用不但可以大幅降低掘削阻力,也可以改善刀具的受力方式,从而使得岩体在低于破坏强度时就产生破坏的结论。
(2)针对液压挖掘机振动掘削过程铲斗激振力检测信号不可避免地受到噪声干扰的实际情况以及该检测信号含噪声特征,应用软门限方法对以宽带随机噪声为背景的信号IMF分量作门限处理,提出了一种基于EMD的含噪信号噪声处理的算法,并进行了仿真应用研究,所获得的去噪处理算法为分析提取铲斗激振力信号的特征线谱提供了有力的工具。
(3)建立了基于LS-SVM的液压挖掘机振动掘削过程土壤参数在线辨识算法,并在此基础上进行了土壤固有频率等参数的在线辨识仿真研究,在线辨识仿真及共振柱实验法实验结果表明,该土壤参数在线辨识算法具有更小的误差、更好的辨识能力和较高的辨识精度,更能适合于动态系统的辨识。
(4)分析了激振频率、振幅和插入速度等对振动掘削阻力的影响,并对其进行了参数优选匹配,基于振动参数的优选匹配试验的极差分析结果,利用正交扩展型函数链神经网络建立了土壤振动掘削阻力软测量模型,并采用函数链神经网络进行了相应的在线自校正。通过与实测值对比验证了该软测量模型的建模精度和泛化能力。
(5)建立了静态掘削、正弦波激振掘削、三角波激振掘削三种掘削方式的液压挖掘机掘削功率消耗模型,并进行了实验研究,找到了一种节能效果较好的振动掘削方式。
(6)开发了一种将专家控制、非线性PI控制器以及单神经元相结合,采用自适应粒子群优化方法对其参数进行最优整定的液压挖掘机振动掘削智能控制系统,提出了基于Ultronics双阀芯结构控制阀的振动掘削执行机构的控制策略,并对其数据通讯和控制模式实现进行了研究。
(7)搭建了SWE85型液压挖掘机振动掘削实验平台,并对振动掘削控制系统的平稳性、高频响应特性、控制策略的适用性以及振动掘削阻力和功率消耗情况进行了实验研究。实验研究验证了所开发的液压挖掘机振动掘削控制系统具有较好稳定性、快速性等性能,符合振动掘削的功能要求。采用正弦波振动掘削可使掘削阻力降低到70%左右,功率消耗降低到80%左右。
总之,论文对液压挖掘机振动掘削新方法进行了系统的研究,取得了较高应用价值的研究成果,为其实用化研究打下了较为扎实的理论基础。
Nowadays it is known that there are some difficulties, such as lower energy rate and inadequate work capacity in the excavating process for hydraulic excavator because of conventional excavating pattern and it is very important for hydraulic excavator with high energy consuming from engineering machines how to realize optimum and intelligent control in excavating process. In order to minish directly excavating resistance and energy consuming of hydraulic excavator and enhance work efficiency and self-adaptive capacity, some main research task in this paper such as seeking after a reasonable and effective excavating method for soil and process optimization modeling and intelligent control strategy of hydraulic excavator are completed based on applying vibratory theory to soil excavating process for hydraulic excavator and using theory analysis and experiment research combinatively, and the research fund is obtained from "863 Research Fund[2003AA430200]"(namely mechanics-electronics and manufacture informatization of hydraulic excavator) and "Program for New Century Excellent Talents in University"[NCET-05-0697]. The main works of the paper are expressed as:
(1) The characteristic of static intensity and dynamic intensity were studied and excavating principle and invalidation mechanism to soil were discussed. The simulation experiment results about crashing rock and soil process based on dynamic load receal that vibratory impact function dynamic load can improve force method of shovel blade and minish excavating resistance in a big way, therefore, rock and soil can be destroyed even if its stress lower than its destructive intensity.
(2) In allusion to fact circs of noise jamming of exciting force signal from the buchet inevitably and the characteristic of noise from exciting force signal in the vibratory excavating process for hydraulic excavator, IMF weight of signal based on the wideband random noisy background is processed using soft threshold method and a signal denoising algorithm for noisy signal is given based on EMD method. The simulation results reveal that the signal denoising algorithm can enhance decomposing veracity of exciting force signal from the buchet, time effect property of extracting instantaneous parameters and can remove availably noise jamming of exciting force signal from the buchet.
(3) A online identification algorithm about rock and soil parameters in the vibratory excavating process for hydraulic excavator is given based on LS-SVM. And then online identification about some parameters of soil such as natural frequency was simulated. The results of its simulation and resonant column experiment reveal that the online identification algorithm is of smaller error, better identification capacity and higher identification precision and it is much fit for dynamic systems identification.
(4)The impacts on vibratory excavating resistance from the parameters such as exciting frequency, amplitude and inserting velocity were analyzed and the parameters were preferentially matched. Based on matched results, a soft sensing model of vibratory excavating resistance form rock and soil is established by using of orthogonal and extensible function chain neural network and its online self-correction was done accordingly by using of function chain neural network. The application results reveal that soft sensing model is of much high modeling precision and generalization capability.
(5) The excavating power consuming models due to different excavating methods such as static excavating, sine wave excavating and triangle wave excavating in the hydraulic excavator is established and corresponding experiments were done. A kind of excavating method with better effect in saving energy aspect than other excavating methods was gotten.
(6)An intelligent control system for vibratory excavating in the hydraulic excavator was designed by using of combinative expert control, non-linear PI controller and single neuron and its parameter can be tuned based on self-adaptive particle swarm optimization algorithms. The control tactic of executive machine for vibratory excavating was submitted based on Ultronics control valve with double cores and its data communication and control model application were studied.
(7)An experiment platform for vibratory excavating rock and soil in SWE85 hydraulic excavator is set up and the stability of control system for vibratory excavating, the respond characteristic of high frequency, the applicability of control strategy, excavating resistence and power consuming were studied by using of the experiments. The experiments results reveal that the vibratory excavating control system in hydraulic excavator is of better stability and rapid capability and can ensure that excavating resistence depress to 70% and power consuming depress to 80% when exerting sine wave vibratory methods.
In a word, a new vibratory excavating method for the hydraulic excavator was studied by the numbers in the paper and some research achievements with higher applied price were gotten, which can offer steadier theory basis for practicability.
引文
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