Production and Characterization of Cellulose Nanofiber Slurries and Sheets for Biomedical Applications

Cellulose nanomaterials are produced employing a multitude of methodologies including electrospinning, bacterial generation, acid digestion, and a variety of mechanical defibrillation techniques; the morphology of the nanomaterial produced is specific to the production process. Feedstocks range from various forms of woody biomass, to fungi, and have a great impact on the resulting product. The mechanical defibrillation technique, such as that employed in the present work, continuously breaks down cellulose fibers suspended in water via segmentation and defibrillation through grinding and refining. The process is typically operated until a desired level of fines is achieved in the resultant slurry of cellulose nanofiber (CNF), alternatively known as cellulose nanofibril. Mechanical defibrillation processes can be built to produce several liters in a small batch system or up to tons per day in a continuous pilot scale refiner system. In the present work a continuous system was developed with the capacity to produce 14 L of cellulose nanofiber slurry with consistent specifications and in a manner compliant with GMP/GLP protocols in order to be amenable to biomedical applications. The system was constructed within an ISO class 7 cleanroom and refining was performed on bleached softwood pulp suspension in purified water. This manuscript details the continuous grinding system, the processes employed to produce cellulose nanofiber, and characterizes the resultant cellulose nanofiber slurry and sheets formed from the slurry.

Research On Roundness Error Consistency Model For Crank Journal Cylindrical grinding

Cylindrical grinding is an important way to form the external shape error of the crank journal, and the accuracy consistency directly affects the interchangeability of products. To study the accuracy consistency of crank journal，a dynamic model of the grinding wheel-crankshaft grinding system based on Timoshenko beam is established, and the grinding transition process simulation algorithm with iterative convergence of grinding force-transient grinding amount cycle adapted to the model is proposed, which realizes the simulation of the roundness of the crank journal coupled with the process parameters of the grinding system. Aiming at the grinding position of each crank journal, the grinding roundness of five crank journals is simulated respectively. On this basis, the crank journal roundness consistency prediction model is established, and the effectiveness of the prediction model is verified by field experiments. Finally, the influence of grinding parameters on the consistency of the roundness of crank journal is studied. The research conclusion can provide a reference for the grinding accuracy consistency design of this type of crank journal.

A Efficient System based on Model Segmentation for Weld Seam Grinding Robot

Uneven surface quality often occurs when butt welds are manually grinding, so robotic weld grinding automation has become a fast-developing trend. Weld seam extraction and trajectory planning are important for automatic control of grinding process. However, most of the research on weld extraction is focused on before welding. Due to the irregular shape of the weld after welding, and too little work has been devoted to the weld identification after welding. Consequently, in this paper, a novel simple and efficient weld extraction algorithm is proposed, and the robot grinding path is planned. Firstly, a new flexible bracket structure for welding seam extraction is designed. Secondly, the weld seam section profile model is established, and the processing of spatial point cloud problem is transformed into the processing of two-dimensional point cloud problem. The least square method (LSM) based on threshold comparison is used to segment the weld seam, which greatly improved the processing speed and accuracy. Then the grinding path and pose are obtained according to the extracted weld space structure. Finally, a robotic welding seam automatic grinding system is built. Experiments show that the proposed method could well extract the irregular weld contour after welding and the grinding system built is reliable, which greatly improves the grinding efficiency.

THE EFFECT OF THE WEAR DEGREE OF WORKING ELEMENTS IN A JAW CRUSHER ON THE OPERATING EFFECTIVENESS OF A TWO-STAGE GRANITE GRINDING SYSTEM

The article presents an analysis of the influence of the wear degree of working elements in a jaw crusher on the crushing process and on the quality of the crushed material. The evaluation of the operating effectiveness of a technological system comprising two crushers was based on the quality indicator of the crushed product, i.e. on the share of irregular grains for a fraction with a mean grain size of 31.5/63 mm at each of the two stages of crushing. The wear degree was monitored by performing microscopic observations of the plates in the fixed jaw and by measuring the critical geometric characteristics of the crusher, e.g., tooth height, jaw size, and discharge opening size, during the entire service life of the crusher.

Active Compliant PID Learning Control for Grinding Robots

This article proposes a Proportional, Integral, and Derivative (PID) learning controller for rigid robotic disk grinding mechanism. It has been observed that the stiffness of the robotic arm for a grinder has a direct correlation with the sensitivity of the grinding forces. It is also drastically influenced by the end-effector path tracking error resulting in limited accuracy of the robot. The error in robot’s accuracy is also increased by external interferences, such as surface imperfections and voids in the subject material. These errors can be mitigated via efficient feedback. In the proposed methodology, the controller gain is tuned by implementing a learning-based methodology to PID controllers. The learning control for the robotic grinding system helps by progressively decreasing error between the actual grinded paths and required trace. Experimental results demonstrate that as the grinder machines the required path iteratively, its grinding accuracy improves due to the learning algorithm.

Prediction of Surface Roughness of Abrasive Belt Grinding of Superalloy Material Based on RLSOM-RBF

It is difficult to accurately predict the surface roughness of belt grinding with superalloy materials due to the uneven material distribution and complex material processing. In this paper, a radial basis neural network is proposed to predict surface roughness. Firstly, the grinding system of the superalloy belt is introduced. The effects of the material removal process and grinding parameters on the surface roughness in belt grinding were analyzed. Secondly, an RBF neural network is trained by reinforcement learning of a self-organizing mapping method. Finally, the prediction accuracy and simulation results of the proposed method and the traditional prediction method are analyzed using the ten-fold cross method. The results show that the relative error of the improved RLSOM-RBF neural network prediction model is 1.72%, and the R-value of the RLSOM-RBF fitting result is 0.996.

Designed a Passive Grinding Test Machine to Simulate Passive Grinding Process

Passive grinding is a high-speed rail grinding maintenance strategy, which is completely different from the conventional rail active grinding system. In contrast to active grinding, there is no power to drive the grinding wheel to rotate actively in passive grinding. The passive grinding process is realized only by the cooperation of grinding pressure, relative motion, and deflection angle. Grinding tests for passive grinding can help to improve the passive grinding process specifications and be used for the development of passive grinding wheels. However, most of the known grinding methods are active grinding, while the passive grinding machines and processes are rarely studied. Therefore, a passive grinding test machine was designed to simulate passive grinding in this study. This paper gives a detailed description and explanation of the structure and function of the passive grinding tester. Moreover, the characteristics of the grinding process and parameter settings of the testing machine were discussed based on the passive grinding principle. The design of a passive grinding test machine provides experimental equipment support for investigating passive grinding behavior and grinding process.