基于小波有限元和遗传优化算法的转轴裂纹诊断

构造Rayleigh-Euler和Rayleigh-Timoshenko区间B样条小波梁单元,分别离散柔性转轴和刚性转盘,建立转子系统有限元模型.求解裂纹转子前三阶固有频率,并将其拟合成裂纹相对位置和相对深度的函数.将裂纹识别中的匹配追踪问题转化为多维优化问题,以实测固有频率作为输入,利用遗传算法寻优求解出与输入值相差最小的样本点,进而测出裂纹的相对位置和深度.试验研究表明,所提出的裂纹诊断方法具有较好的精度和鲁俸性,且易于在工程实践中进行裂纹转子定量诊断.     

基于遗传算法的平板裂纹识别

裂纹的识别是故障诊断领域研究的一个热点问题.基于构件的固有频率变化,从反问题的角度出发,把裂纹的识别问题转化为一个优化问题,将裂纹的相对位置及深度参数转化为二进制编码,提出基于遗传算法的平板构件裂纹的识别方法.为了减少遗传算法的计算量,对遗传算法作了一定的改进.计算结果表明算法计算精度高,计算量小,可广泛的应用于拉深件裂纹识别及结构损伤检测等场合.     

基于区间B样条小波有限元的转子裂纹定量识别

研究一种基于区间B样条小波有限元的转子横向裂纹定量识别方法.构造包含转动惯量影响的区间B样条小波Rayleigh梁单元,高精度求解裂纹转子前三阶固有频率,获得裂纹相对位置和相对深度作为变量的固有频率解曲面.然后将实测的裂纹转子前三阶固有频率作为裂纹识别问题的输入,利用三条等高线的交点定量识别出裂纹存在的相对位置和相对深度.数值仿真和试验研究结果表明,该方法鲁棒性强,单元数量少,辨识精度和效率高,为转子系统裂纹定量识别提供了新方法.     

基于代理模型的螺旋输送器特征值反求

螺旋输送器的动态特性设计可归结于特征值反问题的求解.针对结构参数到结构响应之间的非线性映射关系,通过一种基于神经网络代理模型的优化策略,采用正交试验设计在设计空间中选择初始样本点,构造神经网络代理模型,神经网络结合遗传算法求解,利用神经网络的非线性拟合能力和遗传算法的非线性寻优能力,引入训练后的BP神经网络预测结果作为个体适应度值,获得全局最优值及对应输入值.解决了遗传算法能获全局最优解与有限元大量结构重分析之间的矛盾,是结构反问题的一种有效求解策略.     

工字截面梁轨结构裂纹损伤的小波有限元定量诊断

研究工字截面梁轨结构裂纹定量识别中的正反问题,即通过裂纹位置和深度求解结构的固有频率以及利用结构的固有频率,识别裂纹位置和深度.裂纹被看作为一扭转线弹簧,利用工字梁裂纹应力强度因子推导出线弹簧刚度,构造出结构的小波有限元刚度矩阵和质量矩阵,从而获得裂纹结构的前3阶固有频率.通过行列式变换,将反问题求解简化为只含线弹簧刚度一个未知数的一元二次方程求根问题,分别做出以不同固有频率作为输入值时裂纹位置与裂纹深度之间的解曲线,曲线交点预测出裂纹的位置与深度,试验结果验证算法的有效性.     

转子系统支承松动故障非线性参数识别

针对一端支承松动的转子-滚动轴承系统,利用遗传算法对松动端的故障非线性参数进行识别。针对传统遗传算法的早熟收敛问题,提出了一种改进的遗传算法。通过适应度函数的构建,将参数识别问题转化为参数优化问题,改进了遗传算法中新一代种群的生成机制。父代种群进行交叉与变异操作后,并不直接产生新一代种群,而是取父代种群与生成的种群中适应度排序靠前的个体组成新一代种群。改进的遗传算法能以较大的变异率进行遗传进化,克制了遗传算法的早熟收敛问题,加快进化速度。用改进遗传算法识别了转子支承松动参数,并研究了变异率和噪声对识别结果的影响。研究表明,改进的方法能有效提高松动参数的识别效率,变异率最高可达0.3,噪声不超过10%时能具有理想的识别精度。基于支承松动转子实验台的实测信号,利用改进遗传算法进行了参数识别,验证了改进算法的有效性。     

结构区间参数反求的DIRECT算法

提出一种基于DIRECT算法的结构区间参数反求方法。对于结构不确定性参数反求问题,一般转化为不确定性传播和模型参数优化的双层求解问题。首先,区间模型用来描述响应和待识别结构参数的不确定性,并建立了相应区间参数反求模型。其次,在迭代反求过程中自适应更新径向基函数用来近似原系统模型,并利用DIRECT算法来求解内层不确定性传播问题。最后,通过遗传算法来求解外层的优化模型,从而识别结构不确定性参数的区间。数值算例用来验证了该方法的正确性和有效性,并将该方法应用来反求车辆乘员约束系统中的不确定性参数。     

基于参数反求的齿轮裂纹时变啮合刚度计算方法

基于齿根应变测试技术和优化理论提出了齿轮时变啮合刚度反求计算方法,并将其应用于齿轮故障机理研究。构建了齿根动态应力与时变啮合刚度反问题模型,并搭建齿轮裂纹故障应变测试实验台来采集齿根应变;建立了相对应的有限元模型并将计算应变与测量应变代入反问题模型,从而实现齿轮啮合刚度的反向求解。计算结果表明,相比解析法和有限元法,所提方法显著提高了求解精度并且具备更高的可靠性。建立了齿根裂纹故障的齿轮系统动力学模型,通过对动力学响应进行时域及频域分析来揭示齿轮裂纹故障机理。     

基于混合神经遗传算法的梁式结构损伤识别研究

由于裂纹对结构动态行为具有重要影响,为识别结构裂纹的位置和深度,引入混合神经遗传算法。该方法将遗传算法(GA)与神经网络相结合,利用遗传算法全局寻优的特点对BP网络进行优化。通过有限元分析得到裂纹梁的固有频率,并将其作为神经网络的输入,裂纹的位置和深度作为网络的输出。首先,利用遗传算法(GA)优化网络的权重和阈值;然后将优化结果作为三层BP神经网络的初始值,经过样本数据的训练得到合适的网络;最后以裂纹梁固有频率作为测试值,得到裂纹参数的预测结果,通过理论值与预测值的比较,结果证明了该算法能够对结构损伤进行准确的识别。     

基于区间B样条小波有限元的裂纹故障定量诊断

研究基于模型的结构裂纹故障诊断中的正反问题，即求解含裂纹参数结构的固有频率以及利用实测固有频率，定量识别裂纹参数。构造用于求解正问题的一维区间B样条小波裂纹单元，通过求解裂纹结构有限元模型，绘制以裂纹等效刚度与裂纹位置为变量的三阶频响函数解曲线，将实际测出的系统前三阶固有频率作为输入，根据曲线的交点定量预示出裂纹的位置和深度。实验研究表明，文中构造的区间B样条小波裂纹单元有效克服了传统有限元分析在求解裂纹奇异性问题时存在的效率低、精度差甚至难以收敛到正确解的缺陷，同时具有足够的辨识精度，为早期裂纹故障定量诊断提供新方法。     

Model-based identification of two cracks in a rotor system

The dynamics and diagnostics of cracked rotor have been gaining importance in recent years. Relatively few authors have addressed the problem of multi crack assessment for rotors. In the present study a model-based method is proposed for the on-line identification of two cracks in a rotor. The fault-induced change of the rotor system is taken into account by equivalent loads in the mathematical model. The equivalent loads are virtual forces and moments acting on the linear undamaged system to generate a dynamic behaviour identical to the measured one of the damaged system. The rotor has been modelled using finite element method, while the cracks are considered through local flexibility changes. The cracks have been identified for their depths and locations on the shaft. The nature and symptoms of the fault, that is crack, are ascertained using the FFT.     

基于轴心轨迹形态的转子裂纹故障分析与诊断

基于转子系统轴心轨迹的形态分析,提出一种对多故障中的裂纹故障进行初步诊断的简便方法。通过对转子系统1/2临界转速附近的轴心轨迹形态分析,表明在1/2临界转速附近,裂纹-碰摩双故障转子系统轴心轨迹的内环形状随着转速的变化而改变,内环的偏置方向也随转速旋转一定角度。在碰摩转子系统中,其1/2临界转速附近的轴心轨迹形态与裂纹-碰摩双故障转子有明显区别。多故障系统轴心轨迹的形态分析为对其中的裂纹故障进行初步诊断提供了新方法,使转子故障诊断效率得到提高。同时结合分岔图及频谱图对不同转子系统的动力学响应进行了分析,利用Bently转子实验台对裂纹转子系统的轴心轨迹进行了实验验证。     

A novel method for real time gear fault detection based on pulse shape analysis

Early identification of faults in gearboxes is a challenging task, especially when the time is a critical factor. In this paper, a novel method for real time fault detection in gearboxes is proposed using adaptive features extraction algorithm to deal with non-stationary faulty signals. Moreover, integration of different techniques is presented in order to detect faults in a real time environment. Evolutionary algorithms are commonly used in different applications and have strong ability for optimization. However, they are inherently slow and not suitable for real time applications. The proposed method is based on a combination of conventional one-dimensional and multi-dimensional search methods, which showed high performance and accurate fault detection results compared with evolutionary algorithms. The effectiveness, feasibility and robustness of the proposed method have been demonstrated on experimental data. An average speed up factor of 87% has been successfully achieved with approximately 5% quality degradation in the results as compared with evolutionary algorithms like genetic algorithms.     

Damage identification in vibrating rotor-shaft systems by efficient sampling approach

In the paper a stochastic method for fault detection and identification in the shafts of rotating machines is proposed. This approach is based on the Monte Carlo simulations of rotor-shaft lateral–torsional–longitudinal vibrations mutually coupled by transverse cracks of various possible and randomly selected depths and locations on the shaft. For this purpose the structural hybrid model of a real faulty object is applied. This model is characterized by a high practical reliability and great computational efficiency, so important for many hundred thousand single numerical simulations necessary for a creation of the databases applied for inverse problem solution finally leading to crack identification. These databases are created with an arbitrary assumed probability densities of crack parameters which ensures appropriate spread of the dynamic responses of the considered faulty mechanical system. A sufficiently large database determined for the investigated object enable us to estimate almost immediately, i.e. within less than 1 s, the crack depth and axial position with identification errors not exceeding 9% and 5%, respectively. Thus, the proposed method seems to be a very convenient diagnostic tool for engineering applications in the industry.     

永磁同步电机转子位置复合检测及起动运行策略

电梯用永磁曳引机的驱动控制需要实时获取转子的机械角度,如何在曳引机起动及运行阶段准确地检测转子位置是需要解决的关键问题。基于正余弦型复合编码器,提出一种绝对式与增量式相结合的转子位置复合检测方案。首先在分析绝对式和增量式转子位置检测原理的基础上,对两种转子位置检测算法进行优化,提高转子位置检测精度;然后结合转矩最大矢量控制策略,提出在转子位置复合检测方案下的电机起动运行方案;最后,仿真与实验结果表明所提出的转子位置复合检测方案可以保证电机的正常稳定运行。     

Shape identification problems on detecting of defects in a solid body using inverse heat conduction approach

In this paper, a new shape identification method in the inverse heat conduction problem (IHCP) is applied to detect the location and size of defects in a solid body. Different defects are modeled in a solid body as an elliptical geometry whose parameters are estimated with a proposed inverse algorithm. The inverse algorithm consists of direct, inverse analysis, and gradient-based optimization method. The direct analysis is used a finite-element method in an unstructured grid system to solve the direct heat conduction problem. The inverse analysis is based on recording temperatures data on surface of solid body that calculates the objective function. The employed gradient-based optimization method is constructed using the adjoint, sensitivity, and conjugate gradient method (Powell-Beal’s version) that are used to calculate the gradient of objective function, step size, and minimizing the objective function, respectively. The effects of different noisy temperature data, different cavities on some domains, and different type of defects such as poor cure, porosity, and crack are investigated in this work. The results show that this proposed inverse algorithm is more efficient in detection of defects.     

Detection of rubbing location in rotor system by super-harmonic responses

A detection strategy for the rubbing locations in a rotor system based on the super-harmonic responses is developed. Firstly, the dynamics of the rotor system with rubbing fault is investigated based on the theory of nonlinear output frequency response function. Then, the relationship between the super-harmonic components of the vibrations of fault rotor system and the receptance matrix of the fault-free rotor system is established. The detection method is then set up for rubbing location along the rotor. With this approach, the rubbing location can be determined by using super-harmonic responses measured at only two nodes under one case of operating speed. Finally, numerical simulations and experimental observations are carried out to verify the efficiency of the proposed detection method for rubbing location in a rotor system.     

A two-stage method to identify structural damage sites and extents by using evidence theory and micro-search genetic algorithm

A two-stage method of determining the location and extent of multiple structural damages by using information fusion technique and genetic algorithm is presented in this paper. First the damage detection strategy is to localize the damage sites by using an evidence theory, which can perfectly integrate the damage identification information coming from both natural frequencies and mode shapes. Then, a micro-search genetic algorithm (MSGA) is proposed to determine the damage extent. A cantilever beam is analyzed as a numerical example to compare the performance of the proposed method with the multiple damage location assurance criterions (MDLAC) and the simple genetic algorithms. Simulation results show that identification results of the evidence theory are better than those both of the frequency MDLAC method and the mode shape MDLAC method, and the MSGA is also more accurate and effective than the simple genetic algorithms. Therefore, the two-stage method is very effective for the identification of multiple structural damages.