SolidWorks Enterprise PDM与IRIS体系的完美融合

本文以某铁路设备企业为背景,介绍了SolidWorks Enterprise PDM融合国际轨道交通工业标准在该企业的应用。     

光电稳定跟踪平台中微机电陀螺滤波方法研究

根据微机电陀螺的实测数据,分析了其噪声特性,建立了微机电陀螺零漂的AR模型.研究了基于Kalman滤波的陀螺去噪算法,给出了去噪结果,分析了Kalman滤波不能够在微机电陀螺信号去噪中获得较好效果的原因.在此基础上,将基于阈值决策的小波去噪方法应用于微机电陀螺的信号处理中,给出了滤波结果.实测结果表明由于后者不依赖于噪声的精确模型,根据噪声在不同频段的统计特性采用阈值决策滤波,具有更好的抑噪效果.最后给出了两种滤波算法的比较结果.     

摩擦对稳定跟踪平台低速性能影响的研究

以某型直升机驾驶员夜视系统稳定跟踪平台伺服系统设计为背景，针对系统中存在的非线性摩擦影响，着眼于摩擦模型、二质量伺服系统模型以及摩擦补偿问题，从理论上进行了探讨。     

Robust tracking control for micro machine tools with load uncertainties

The quality of the micro-mechanical machining outcome depends significantly on the tracking performance of the miniaturized linear motor drive precision stage. The tracking behavior of a direct drive design is prone to uncertainties such as model parameter variations and disturbances. Robust optimal tracking controller design for this kind of precision stages with mass and damping ratio uncertainties was researched. The mass and damping ratio uncertainties were modeled as the structured parametric uncertainty model. An identification method for obtaining the parametric uncertainties was developed by using unbiased least square technique. The instantaneous frequency bandwidth of the external disturbance signals was analyzed by using short time Fourier transform technique. A two loop tracking control strategy that combines the μ-synthesis and the disturbance observer (DOB) techniques was proposed. The μ-synthesis technique was used to design robust optimal controllers based on structured uncertainty models. By complementing the μ controller, the DOB was applied to further improving the disturbance rejection performance. To evaluate the positioning performance of the proposed control strategy, the comparative experiments were conducted on a prototype micro milling machine among four control schemes: the proposed two-loop tracking control, the single loop μ control, the PID control and the PID with DOB control. The disturbance rejection performances, the root mean square (RMS) tracking errors and the performance robustness of different control schemes were studied. The results reveal that the proposed control scheme has the best positioning performance. It reduces the maximal errors caused by disturbance forces such as friction force by 60% and the RMS errors by 63.4% compared with the PID control. Compared to PID with DOB control, it reduces the RMS errors by 29.6%.     

Parameter identification of inertially stabilized platforms using current command design

Accurate parameter identification is essential when designing controllers for inertially stabilized platforms (ISPs). But traditional identification methods suffer from observation measurement noise and operating restrictions of ISPs. To address this issue, a novel identification method based on current command design and multilevel coordinate search (MCS) algorithm without any higher order measurement differentiations was proposed. The designed current commands were adopted to obtain parameter decoupled models with the platform operating under allowable conditions. MCS algorithm was employed to estimate the parameters based on parameter decoupled models. A comparison experiment between the proposed method and non-linear least square method was carried out and most of the relative errors of identified parameters obtained by the proposed method were below 10%. Simulation and experiment based on identified parameters were conducted. A velocity control structure was also developed with disturbance observer (DOB) for application in disturbance compensation control system of an ISP. Experimental results show that the control scheme based on the identified parameters with DOB has the best disturbance rejection performance. It reduces the peak to peak value (PPV) of velocity error integral to 0.8 mrad which is much smaller than the value (10 mrad) obtained by the single velocity controller without DOB. Compared with the control scheme based on sweep model with DOB compensation, the proposed control scheme improves the PPV of velocity error integral by 1.625 times.     

光电稳定平台伺服系统动力学建模与参数辨识

针对光电稳定平台伺服系统模型参数辨识问题,提出了线性和非线性模型参数分离辨识方法。在线性模型参数辨识过程中,利用差动逆M序列信号作为输入,相应的响应信号作为输出,并应用最小二乘方法辨识线性离散模型参数,从而降低非线性因素的影响。在非线性模型参数辨识过程中,以LuGre摩擦模型为基础,针对摩擦和不平衡质量相互耦合的问题,提出了考虑不平衡质量的LuGre模型静态参数辨识方法;然后,利用电流信号作为摩擦力测量值,对LuGre模型动态参数进行辨识,得到包含不平衡质量和动态摩擦的系统非线性部分模型参数。构建了单轴光电稳定平台实验系统,利用本文提出的方法对实验系统动力学模型参数进行了辨识。结果表明:质量不平衡力矩的辨识值为0.183N·m,略高于理论值0.18N·m,满足辨识精度要求。实验证实提出的辨识方法可以实现对模型线性与非线性参数的有效辨识。     

基于EEMDFK和注意力CNN网络的刀具磨损状态识别

针对加工数据采集存在数据量大且干扰信号复杂,导致刀具磨损状态识别方式复杂、识别精度低等问题,提出一种基于快速谱峭度图的集合经验模态分量选取(EEMDFK)与注意力机制的卷积神经网络(ACNN)相结合的识别方法。针对集合经验模态存在选取模态分量困难的情况,引用快速谱峭度图选择策略选取最优分量。通过集合经验模式分解从所采集的不同状况下的刀具振动信号分解出故障信号特征;通过快速谱峭度图选择策略选取内在模函数并进行HHT时频分析,生成时频图;将时频图输入所设计的识别模型进行学习,通过注意力机制提高特征提取效率,并使保存的模型在测试集中对不同刀具磨损状态进行了识别。实验结果表明,该方法对刀具不同状态下的识别率可达99.7%,实现了不同磨损状态下刀具的智能识别,并具有较好的泛化能力和鲁棒性。     

工业铬系催化剂的乙烯聚合性能研究

在实验室小试气相聚合釜中对工业铬系催化剂进行了聚合评价研究。考察了不同聚合反应温度和反应压力下工业CAT-1催化剂、CAT-2催化剂的聚合行为,并对其产品进行了性能测试和分析。     

基于线性光耦HCNR200的DSP采集电路设计与实现

介绍了Agilent公司的高线性度模拟光耦HCNR200的基本结构及工作原理。利用该器件设计了一种模拟信号与DSP隔离与检测的硬件电路,较好地解决了将AGC信号采集到DSP过程中测量范围小、线性度低的问题。最后用最小二乘法对实验数据进行分析,结果表明该电路具有较高的电压检测精度和线性度,在高稳定性、高线性度的模拟信号隔离的场合具有广泛的应用前景。