Suppress vibration on robotic polishing with impedance matching

Installing force-controlled end-effectors on the end of industrial robots has become the mainstream method for robot force control. Additionally, during the polishing process, contact force stability has an important impact on polishing quality. However, due to the difference between the robot structure and the force-controlled end-effector, in the polishing operation, direct force control will have impact during the transition from noncontact to contact between the tool and the workpiece. Although impedance control can solve this problem, industrial robots still produce vibrations with high inertia and low stiffness. Therefore, this research proposes an impedance matching control strategy based on traditional direct force control and impedance control methods to improve this problem. This method's primary purpose is to avoid force vibration in the contact phase and maintain force-tracking performance during the dynamic tracking phase. Simulation and experimental results show that this method can smoothly track the contact force and reduce vibration compared with traditional force control and impedance control

5-hydroxymethylcytosine is dynamically regulated during forebrain organoid development and aberrantly altered in Alzheimer’s disease

5-hydroxymethylcytosine (5hmC) undergoes dynamic changes during mammalian brain development, and its dysregulation is associated with Alzheimer's disease (AD). The dynamics of 5hmC during early human brain development and how they contribute to AD pathologies remain largely unexplored. We generate 5hmC and transcriptome profiles encompassing several developmental time points of healthy forebrain organoids and organoids derived from several familial AD patients. Stage-specific differentially hydroxymethylated regions demonstrate an acquisition or depletion of 5hmC modifications across developmental stages. Additionally, genes concomitantly increasing or decreasing in 5hmC and gene expression are enriched in neurobiological or early developmental processes, respectively. Importantly, our AD organoids corroborate cellular and molecular phenotypes previously observed in human AD brains. 5hmC is significantly altered in developmentally programmed 5hmC intragenic regions in defined fetal histone marks and enhancers in AD organoids. These data suggest a highly coordinated molecular system that may be dysregulated in these early developing AD organoids

Formation and stability of lithium protective layer for corrosion protection of AA2024-T3 and AA2198-T8 aluminium alloys

As a possible replacement for chromate-based coatings in the aerospace industry, lithium leaching coatings have been widely studied in recent years. The formation mechanism of protective layer on AA2024-T3 aluminum alloys has been investigated intensively. In order to explore more possibilities for its application in aerospace industry, AA2198-T8 aluminum alloys is also be considered in research for its unique chemical composition which contains lithium. In this thesis, three kinds of different polymer coatings which are non-inhibiting coating, coating containing Li2CO3 and proprietary industrial Li2CO3-loaded coating XP420 are used. These three polymer coatings were applied on the AA2024-T3 and AA2198-T8 aluminum alloys samples. A defect was artificially made on the these samples. Then the samples were divided into two groups, one group is used directly for the experiment to investigate the formation of protective layer, one week neutral salt spray test were applied to another group in order to form the protective layer in advance and later used for the experiment. The second group is mainly focus on investigating the stability of protective layer. What is more, low volume of electrolyte was used during experiment considering the real environment of coating’s application. The research results showed that: (1) Under low volume electrolyte of 5ml aqueous 0.1M NaCl solution, the protective layer is successfully formed; (2) Li2CO3-loaded coating shows better corrosion inhibition performance compared to the non-inhibiting coating; (3) AA2198-T8 aluminum alloy containing lithium in its element composition further contributes to the formation of protective layer; (4) In general, proprietary industrial Li2CO3-loaded coating XP420 are more stable when exposed to the corrosion condition

Role of Mg Impurity in the Water Adsorption over Low-Index Surfaces of Calcium Silicates: A DFT-D Study

Calcium silicates are the most predominant phases in ordinary Portland cement, inside which magnesium is one of the momentous impurities. In this work, using the first-principles density functional theory (DFT), the impurity formation energy (Efor) of Mg substituting Ca was calculated. The adsorption energy (Ead) and configuration of the single water molecule over Mg-doped β-dicalcium silicate (β-C2S) and M3-tricalcium silicate (M3-C3S) surfaces were investigated. The obtained Mg-doped results were compared with the pristine results to reveal the impact of Mg doping. The results show that the Efor was positive for all but one of the calcium silicates surfaces (ranged from −0.02 eV to 1.58 eV), indicating the Mg substituting for Ca was not energetically favorable. The Ead of a water molecule on Mg-doped β-C2S surfaces ranged from –0.598 eV to −1.249 eV with the molecular adsorption being the energetically favorable form. In contrast, the Ead on M3-C3S surfaces ranged from −0.699 eV to −4.008 eV and the more energetically favorable adsorption on M3-C3S surfaces was dissociative adsorption. The influence of Mg doping was important since it affected the reactivity of surface Ca/Mg sites, the Ead of the single water adsorption, as well as the adsorption configuration compared with the water adsorption on pristine surfaces

Research of control strategies of MMC based on full bridge sub-modules

Although full bridge sub-module topologies require more power devices than half bridge topology, it can offer flexible control of positive, negative, and zero voltage output characteristics. Here, full-bridge MMC with three kinds of operating modes as positive, negative voltage output with low voltage operation, and DC-link fault current suppression with zero voltage output are studied. To deal with the problem of insulation reduction when long-distance overhead line is applied and reduced DC voltage operation is required when LCC is connected with MMC, the effect of constant power and reduced power transmission on the storage capacitor voltage balance are studied. What is more, the zero voltage output characteristic is also studied not only to avoid the problem that the sub-module capacitor voltage may diverge due to long time blocking converter during DC line fault but also to supply reactive power for AC grid. Control strategies are designed under different operating modes to achieve full bridge MMC flexible operation. Finally, a simulation model is built in PSCAD/EMTDC to simulate the output characteristics of full-bridge MMC in different operation modes

A Graph Aggregation Convolution and Attention Mechanism Based Semantic Segmentation Method for Sparse Lidar Point Cloud Data

In recent years, following the development of sensor and computer techniques, it is favored by many fields, i.e. automatic drive, intelligent home, etc., which the deep learning based semantic segmentation method for point cloud data collected by LiDAR. This type method can automatic extract features of point cloud, helping label semantic categories. However, compared to 2D images, 3D point cloud data is more expensive to acquire. Hence, to save research and production costs, the low-thread LiDAR is a good choice. For one observation scenario, following the decrease of the line, the point cloud becomes sparse, which may cause the information loss. To balance the cost and the segmentation effect, we provide a point cloud completion auxiliary semantic segmentation method. Here, the baseline of the proposed method is Bilateral Augmentation and Adaptive Fusion (BAAF) model. It is the main contribution that a completion module introduction in feature extraction part of BAAF. Under the premise of using low-thread LiDAR sensor to collect data, the semantic segmentation effect of 3D field point cloud is improved as much as possible. It provides theoretical basis for cost saving in practical industrial application. The feature extraction of completion module consists of Graph Aggregation Convolution (GAC) and attention mechanism. Then, we use shuffle transform to upsampling data. In addition, to analyze the effectiveness of the proposed method, we make a new dataset with sparse point cloud data, i.e. Sparse-SemanticKITTI dataset, based on public SemanticKITTI dataset. Furthermore, in experiment part, we prove the research significance. Moreover, we compare the segmentation results between classical methods to the proposed one based on point cloud data in SemanticKITTI, Sparse-SemanticKITTI and Semantic3D dataset, respectively. The effectiveness of the proposed one is obvious. Finally, the model complexity is analyzed. In sum, we provide a sparse point cloud semantic segmentation method to balance the cost and the effect

Robust Vibration Control Based on Rigid-Body State Observer for Modular Joints

The vibration caused by resonance modes frequently occurs during acceleration and deceleration of the modular joint integrated with flexible harmonic drive. The conventional equivalent rigid-body velocity method with observer can suppress the residual vibration induced by resonant frequency but has poor robustness to model uncertainties and external disturbances. Moreover, it cannot eliminate the torque ripple caused by the harmonic drive during low-speed uniform motion, reducing the velocity tracking accuracy. Hence, a velocity controller with a rigid-body state observer and an adjustable damper is designed to improve the robust performance and velocity tracking accuracy. The designed rigid-body state observer allows a higher gain so that the bandwidth of the observer can increase, and the equivalent rigid-body velocity can be acquired more accurately. Notably, the high gain observer reduces the sensitivity to model uncertainties and exotic disturbances, especially near the resonant frequency. In addition, the observer combined with an adjustable damper can suppress the residual vibration and torque ripple simultaneously. The proposed method is compared experimentally with a PI method and two other rigid-body velocity methods, such as the conventional equivalent rigid-body observer method and the self-resonance cancellation method, to verify its advantages

Comparison and Determination of Optimal Machine Learning Model for Predicting Generation of Coal Fly Ash

The rapid development of industry keeps increasing the demand for energy. Coal, as the main energy source, has a huge level of consumption, resulting in the continuous generation of its combustion byproduct coal fly ash (CFA). The accumulated CFA will occupy a large amount of land, but also cause serious environmental pollution and personal injury, which makes the resource utilization of CFA gradually to be attached importance. However, given the variability of the amount of CFA generation, predicting it in advance is the basis to ensure effective disposal and rational utilization. In this study, CFA generation was taken as the target variable, three machine learning (ML) algorithms were used to construct the model, and four evaluation indices were used to evaluate its performance. The results showed that the DNN model with the R = 0.89, R2 = 0.77 on the testing set performed better than the traditional multiple linear regression equation and other ML algorithms, and the feasibility of DNN as the optimal model framework was demonstrated. Applying this model framework to the engineering field enables managers to identify the next step of the disposal method in advance, so as to rationally allocate ways of recycling and utilization to maximize the use and sales benefits of CFA while minimizing its disposal costs. In addition, sensitivity analysis further explains ML’s internal decisions and verifies that coal consumption is more important than installed capacity, which provides a certain reference for ensuring the rational utilization of CFA