Maintenance, Reliability and Condition Monitoring
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Six-DOF modular robotic arm bearing chatter suppression algorithm
Get PDFRobotic arms are frequently utilized in contemporary industrial production since they offer great qualities like high precision and low mass. How to minimize robotic arm tremors in order to maximize their control effect has emerged as one of the most critical issues to be resolved with the continued development of industrial intelligence. The study uses a combination of PID control and an artificial fish swarm technique to optimize the parameters and confirm the simulation control effect based on the kinematic analysis of a six-degree-of-freedom (Six-DOF) modular robotic arm. The findings demonstrated that the suggested fusion approach converges to zero in 80 iterations and has a recall of 0.893 and 0.785 at an accuracy of 0.8 and 0.9, respectively. The robotic arm control system’s average control effect is 42.96 %, which is a respectable control performance. In the second and third studies, the fusion approach stabilized actuator end tremor suppression after 0.01 s and 0.0001 s, respectively. It shows that the technique can effectively suppress robotic arm bearing tremor and has high flexibility for robotic arm tremor suppression, which offers trustworthy technological support for improving the motion control system of industrial robots
Automatic vibration control method for grasping end of flexible joint robot
Get PDFBecause flexible robots have flexible components such as reducers, there are problems of accuracy deviation and end vibration in the process of external interference and trajectory tracking. This leads to the proposal of a Sliding Mode Control Approach Based on RBF Neural Network (SMC-RBF) parameter optimization. This method is mainly applied to reduce the end vibration and running position error of flexible robot. Firstly, the Newton-Euler method is used to establish the dynamic model of robot considering joint flexibility. At the same time, the experiment optimizes the Sliding Mode Control (SMC) method through RBF neural network. The experiments verify the control methods of the two-joint flexible robot and the six-joint flexible robot respectively. In the control of two-joint robot, the maximum tracking curve error of SMC is only about 0.25 rad under the interference of pulse signal; And the recovery time is only about 1 s. In the control of 6-joint robot, the maximum error of RBF-sliding mode control method on XYZ axis is 0.7 mm, 0.25 mm and 1.25 mm respectively; The error on three axes is smaller than that of traditional PD control method. The results demonstrate that the tracking error of the improved mode control is small, the chattering phenomenon of the robot system is weakened as well
Exploring CO2 storage potential in Lithuanian deep saline aquifers using digital rock volumes: a machine learning guided approach
Get PDFThe increasing significance of carbon capture, utilization and storage (CCUS) as a climate mitigation strategy has underscored the importance of accurately evaluating subsurface reservoirs for CO2 sequestration [1]. In this context, digital rock volumes, obtained through advanced imaging techniques such as micro-Xray computed tomography (MXCT), offer intricate insights into the porous and permeable structures of geological formations [2]. This study presents a comprehensive methodology for assessing CO2 storage viability within Lithuanian deep saline aquifers, namely Syderiai and Vaskai, by utilizing petrophysical properties estimated from digital rock volumes [3, 4]. These petrophysical properties were derived from core samples collected from these formations. Utilizing machine learning algorithms, porosity was estimated while the Lattice Boltzmann method (LBM) was applied to determine permeability [5]. The methodology employed for estimating these petrophysical parameters was initially validated using samples from formations analogous to Lithuanian formations. Subsequently, it was applied to rock samples specifically obtained from Lithuanian formations. The estimated petrophysical properties were compared with peer-reviewed data from published literature. When fluids such as CO2 or H2 are injected into sub-surface reservoirs, they can alter pore and grain characteristics. Therefore, it is crucial to extract representative element volumes (REVs) from segmented volumes to study the impact of fluids on porosity and their distribution [6]. These mini models, representing small portions of the larger formation, assist in predicting fluid flow within the formation, which is vital for assessing the efficiency and safety of carbon capture and storage (CCS) operations. Subsequently, numerical modelling was conducted using the petrophysical parameters as inputs to assess the storage capacity of the Lithuanian formations using tNavigator software [7]. This research contributes to an enhanced understanding of pore space distribution and its role in various aspects of long-term CO2 storage. It also demonstrates the potential of integrating advanced imaging techniques, machine learning, and numerical modeling for accurate assessment and effective management of subsurface CO2 storage. This study shall aid in enhanced understanding of pore space distribution and their contribution towards various aspects of long-term storage. The results can be extended to study the geochemical reactions and geo-mechanical behaviour of the rocks. Such studies shall further facilitate identification of reservoir(s) wherein sequestration potential can be reliably explored
The effect of glass fiber on fresh properties of industrial based geopolymer concrete
Get PDFThis research study is primarily focused on evaluating the fresh properties of industrial-based 3D printable geopolymer concrete by adding glass wool strings and glass fibers activated by sodium silicate solution with a molar ratio of 2.4-2.6 (31 % SiO2 and 13 % Na2O). The glass wool strings, and recycled glass fiber are added to industrial-based geopolymer concrete at a dosage of 1 % to 5 % by volume of the concrete. The fresh concrete properties such as open time, setting time and shape stability of industrial-based geopolymer concrete (GPC) with glass wool and glass fibers were compared with those of industrial-based GPC without glass wool strings and glass fibers. The results show that the addition of glass wool increases the setting time of the concrete mix at room temperature. The deformation of the specimens at room temperature decreased by 39 %. The addition of glass fiber in geopolymers also increases the stiffness by 74 % compared to GPC without glass fiber
A review on path planning ai techniques for mobile robots
Get PDFAn Industrial Robot is used in industries for transporting, assembly, manufacturing and many more applications. Industrial robots include manufacturing robots, material handling robots, robotic arm and manipulator, mobile robots, assembly robots, etc. In this paper, Mobile Robots are further being discussed. One of the tools that a Mobile Robot uses to function is all with the help of Artificial Intelligence (AI) for performing several tasks autonomously. AI works as the intelligence of the human body for robots. AI is the technology that made it possible for robots to be capable of being totally autonomous. AI marks its presence in the Manufacturing Industry with the 4th Industrial Revolution. AI has several algorithms that help in collecting and analyzing data in order to help robots to function in specific ways. These techniques include Fuzzy Logic, Genetic Algorithm, Neural Network, etc. In this paper, the role of these algorithms in Mobile Robots is discussed. Based on the review of 74 papers and articles, it is observed that there are no review papers discussing the role of nature-based and conventional algorithms used for navigation in Mobile Robots. The use of different AI techniques for specific applications has been discussed in tabular form in this paper
An efficiency calculation model for ball screws by accounting for lead errors
Get PDFTransmission efficiency is a pivotal indicator, providing a comprehensive view of the overall performance of a ball screw. While extensive research has predominantly focused on computing transmission efficiency across various operating conditions, the factors influencing the variability have often been overlooked. This study introduces an innovative method for computing transmission efficiency, which considers lead error, drawing on deformation coordination theory and load distribution. Multiple ball screws of varying precision grades underwent rigorous testing to quantify lead errors. Subsequently, each screw was matched with an identical set of nuts to measure the respective transmission efficiencies. Experimental results reveal a linear correlation between lead error and transmission efficiency when both lead error and uneven ball load distribution in ball screws are considered. The relative error between the calculated transmission efficiency results and experimental values for ball screws of different precision grades falls within the range of 0 % to 7.42 %, confirming the validity of the proposed model in this paper
Application of optimized CNN algorithm in landslide boundary detection
Get PDFLandslide, as a natural geological phenomenon with great harm, seriously threatens human social activities and life safety. It has a variety of latent and immeasurable destructiveness, which has a significant impact on the economic losses in rural areas. Therefore, it is urgent to take measures to accurately identify landslides to reduce their negative impacts. However, traditional manual visual interpretation has been unable to meet the current needs for emergency rescue of landslides, so computer intelligent methods have been paid attention to. This study proposes a new recognition network to address the problem of low accuracy of intelligent landslide boundary recognition methods. Firstly, the experiment incorporated boundary structure information into the Full Convolutional Network (FCN) for optimization, and constructed an Improved Full Convolutional Network (IFCN) model to better achieve image reconstruction. After that, Attention Mechanism (AM) is further introduced to achieve accurate detection of landslide boundaries in images, namely the IFCN-AM model. The attention mechanism introduced include spatial attention mechanism and multi-channel attention mechanism. Both are responsible for enhancing the language representation ability of the model and aggregating the interrelated features between different channels. The experimental results show that IFCN-AM has a 3 % to 7 % improvement in accuracy, recall, F1 value, and MIoU value
Do chewing simulators influence the test results of dental materials? Systematic review
Get PDFInvestigate whether different results about the physical properties of the same biomaterial frequently found in the literature are due to chewing simulator deficiency. A literature review was performed by searching for data on indicators of test accuracy, reproducibility, maintenance of test parameters during all experiments, and standards in the articles or in the sites of manufacturers. The database searched was CAPES PORTAL, and the keywords used were “bite force” AND “simulator”, “chewing simulator” and “mastication simulator”. Including criteria for the papers are publication filter date of “January 1, 2016”, articles in English, Spanish and Portuguese language were accepted. The first 100 papers that seemed suitable when considering the title and abstract were recovered. Only one simulator used for food property studies had the parameters searched. In the customized simulators for biomaterial properties, only one showed standards, and 8 showed all other parameters searched. All manufactured simulators showed all parameters searched, and only two manufactures did not show standards. Based on the data obtained, the disparate results of experiments with dental materials appeared to be more related to the test conditions than to the testing machines. Knowledge Transfer Statement The findings of the current review suggest that the chewing simulators used in preclinical research are reliable, bringing safety to restorative processes regarding the material. Any difference in preclinical investigations about dental material physical properties is due to test conditions other than chewing simulators
Analysis of hydrocarbon solvents for the removal of various types of asphalt, resin and paraffin deposits
Get PDFIn this work the physical-chemical properties of asphaltene-resin-paraffin deposits are studied. Their component composition was determined. The results obtained are the basis for the selection of effective solvents and the choice of the method of removing deposits from oil reservoirs. Two hydrocarbon solvents with the brands “TSK А” and “TSK B” were tested. The solvent ability of solvents was tested
Analysis of methods for improving the efficiency of “Iceberg” gas air coolers
Get PDFRussia has the largest volume of natural gas reserves in the world. Recoverable natural gas reserves amount to about 67 trillion cubic meters, according to the Ministry of Natural Resources and Environment of the Russian Federation for 2023. In recent years, the development of the Unified Gas Supply System has been growing rapidly. Since 2021 the Government of the Russian Federation has been actively introducing draft laws and regulations related to the scaling of the country’s gasification. In June 2021 came out the Federal Law No. 184-FZ, which instructed the Government of the Russian Federation to adopt regulations aimed at implementation of provisions of free gasification of the country [1]. In September 2021 there was issued Decree No. 1547, [2] approving the new Rules for connecting gas-using equipment and capital construction facilities to gas distribution networks, which introduces the concept of pre-gasification. It is worth noting that new gas mains, compressor stations (CS) are put into operation, active reconstruction of the existing shops with exhausted gas compressor units (GCU) is carried out. One of the most urgent issues of the gas industry today is the efficient use of energy resources. Besides using the energy of flue gases from gas turbine drive of GPA, energy at gas throttling at gas distribution stations and other methods of energy saving, the significant role is played by the effective operation of air coolers of gas (ACG), the operation of which affects the reliable transportation of gas in the main gas pipeline (MG). The paper analyzes the methods of technical condition of gas air cooling devices of “Iceberg” type operated at the production site of the booster compressor station of “Gazprom Dobycha Nadym” LLC. The thermal efficiency of air coolers with all fans turned on and off was determined for the coldest and hottest months of the year. The electric energy savings of the frequency controlled drive (VFD) were calculated