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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
Multi frequency weak signals detection based on under-sampling bistable stochastic resonance
Get PDFSignal detection has a wide range of practical applications. Compared with traditional weak signal detection, the nonlinear effect of noise in the bistable system is typical and easy to extend, so bistable stochastic resonance detection technique has a wider applicability. In this paper, the multi-frequency weak signals detection based on under-sampling bistable stochastic resonance is studied. Based on the theory of bistable stochastic resonance, a simulation model is established to simultaneously detect multiple low-frequency weak signals. The spectrum of input and output signals is obtained through numerical simulation calculation, and the system characteristics are analyzed. When the large parameter signal does not meet the adiabatic approximation theory, the appropriate sampling coefficient can be selected to directly under-sample the input signal to make it conform to the conditions, and then the scale inverse transformation can be carried out. Finally, combined with the simulation analysis, the correctness of the under-sampling bistable stochastic resonance system to detect the multi-frequency weak signals is verified, the sampling rate is reduced, and the complexity is effectively decreased
Precision local anomaly positioning technology for large complex electromechanical systems
Get PDFIn recent years, Prognostics Health Management (PHM) technology has become an important reference technology in fields such as avionics and electromechanical systems due to its ability to reduce costs and achieve state based maintenance and autonomous support. However, with the operation of large and complex electromechanical systems (ES), the data generated gradually ages the status of components, and traditional PHM technology is difficult to solve the problem of electromechanical system components becoming more complex. Based on this, this study takes the hydraulic actuator cylinder as an example to construct a local component fault detection model. Firstly, fault data features are extracted using wavelet packet energy spectrum, and then a fault detection model is constructed based on support vector machine (SVM). In response to the shortcomings of SVM, a smooth support vector machine (SSVM) is proposed to replace SVM, and an improved crow search algorithm (ICSA) is used to improve SVM. Finally, an intelligent detection model for hydraulic actuator cylinder faults based on ICSA-SSVM was constructed based on the above algorithms. The experimental results show that the ICSA-SSVM model has the fastest Rate of convergence, among which, the positioning accuracy is 0.96, the fitting degree is 0.984, the fault detection accuracy is 99.16 %, the recall value is 94.52 %, and the AUC value is 0.986, all of which are better than the existing fault detection models. From this, it can be seen that the precise local anomaly localization technology for large-scale complex electromechanical systems based on the ICSA-SSVM algorithm proposed in this study can improve the efficiency and accuracy of fault detection, achieve accurate and intelligent detection of ES local anomalies, and have certain positive significance for the development of China’s industry
The AI vantage: an exposition of global dynamics
Get PDFOver the past few years, there has been a growing interest in this field of Artificial Intelligence (AI). This review paper aims to examine the extent to which AI has been adopted across various domains in different regions of the world. Specifically, this study seeks to explore the effectiveness of AI in areas such as banking, governance, judiciary, and agriculture. While AI’s impact on these areas has been studied before, this research focuses on aspects that have not been given much needed attention so far. The study will begin by offering an overview of AI’s development from a regional perspective, analyzing 63 articles from leading journals and institutions to identify the most commonly used terminologies, theories, and technologies. The increasing computational power has played a crucial role in the advancement of AI. However, the role of AI in governance, judiciary, and legislature system has not been explored in depth in previous research. Furthermore, most studies tend to focus on single domain, whereas this paper aims to examine several domains and their relationship to AI. The study presents several AI-driven techniques, including Deep Neural Net (DNN), Artificial Neural Net (ANN), Candlestick Plots, Natural Language Processing (NLP), Explainable Deep Neural Net (xDNN), Attentional Maps, Digital Inventory, Deep Learning among others, that can be applied to enhance society’s performance in different domains. The research also delves deeper into the judiciary domain, proposing specific AI techniques that could be useful in this field. Additionally, tables summarizing different AI tactics relevant to each domain are presented
Challenges and opportunities for enhanced patient care with mobile robots in healthcare
Get PDFMobile robots are being used more frequently in healthcare environments to tackle a variety of issues, such as patient monitoring, drug administration, and support for healthcare professionals. However, considering how nascent the topic of deploying mobile robots in healthcare is, there hasn’t been much investigation into the potential benefits and drawbacks of doing so. The goal of this research study is to examine the current state of mobile robots in healthcare, the opportunities they present for enhancing patient care, and the difficulties that must be solved to take advantage of these advantages, including safety concerns, dependability and accuracy issues, and cost effectiveness issues. We identify critical elements that support the successful integration of mobile robots into healthcare environments, as well as potential drawbacks and ethical concerns such as patient privacy, informed consent, autonomy, and accountability related to their use, through a systematic review of the literature of mobile robot implementations in healthcare. Our results show the potential of mobile robots to enhance patient care by delivering more effective and efficient healthcare services, but they also emphasize the need for additional research and development to overcome the difficulties in integrating these robots into healthcare workflows. In the end, this research intends to provide a basis for future research and development in this fascinating and quickly developing sector, as well as to contribute to a better understanding of the opportunities and constraints connected with the use of mobile robots in healthcare
Thermal performance investigation of porous fins with convection and radiation under the influence of magnetic field using optimal homotopy asymptotic method
Get PDFA study on enhancement of heat transfer in thermal systems by convective-radiative porous fin with temperature-invariant thermal conductivity is presented in this paper using optimal homotopy asymptotic method. The efficacy of the method is displayed through the verification of the results with the previous studies. Also, significance of various parameters of the nonlinear model on the heat transfer enhancement of thermal systems using the solutions presented by the method are discussed. The graphical representation of the thermal behaviour of the extended surfaces is presented for pictorial discussion. The results illustrate that the augmentations of the conductive-radiative, conductive-convective, porosity and magnetic field cause the extended surface temperature to reduce as a result of increased rate of heat flow via the passive device. The graphical illustrations show that the efficiency and effectiveness of the fin is high at low values of the radiative-conductive, convective-conductive, porosity and magnetic field parameters. This study will assist in proper thermal analysis of fins for effective thermal managements of engineering systems
Overview of the prospects for the introduction of ultrasonic oil treatment in the main pipeline transport
Get PDFThis paper considers the most common methods of pipeline transport of high solidified oil existing at the moment. The effects of treating oil with magnetic and electric fields are given. The positive and negative effects of ultrasonic treatment in oil transport processes are considered. The totality and quality of the facts requires much more in-depth analysis on a number of issues in this area because with a lot of positive effects are present and negative, which do not allow to implement
Determination of reasonable parameters for skew bridge under different skew angles
Get PDFA finite element model is created using OpenSees software to perform a time history analysis in order to analyze the seismic response law of a skew bridge and the damage volume of its key components, using a typical 3×20 m skew continuous girder bridge as an example. The seismic response of the skew continuous girder bridge under various factors such as the size of the abutment expansion joint, shear key gap, and shear key strength is studied then the damage rate is assessed for the bearing, shear key, and pier. The research results show that under the action of earthquake ground motion with 0.3 g PGA, the seismic force transmitted to the pier is small, and the pier is elastic owing to the sliding of the bearing, but the damage degree of the shear key is larger than that of the bearing and pier. The impact increases the rotation effect of the main beam in the direction of off acute angle, resulting in a greater damage to the shear key at the acute angle than that at the obtuse angle. The damage of bearing and shear key increases and then decreases with the increasing of expansion joint, and the larger the skew angle is, the smaller the expansion joint will be corresponding to the maximum displacement of bearing and shear key. With the increase of the shear key gap, the deformation limitation effect of the shear key on the main beam decreases significantly, resulting in a linear increase in the bearing slip, which increases the risk of the main beam subsidence. With the increase of the shear key strength, the bearing and shear key damage decreases greatly at first, and then increases slightly. However, the pier damage increases obviously. In an area with a high risk of earthquake, it is recommended that the shear key can be a “fuse element”. For any oblique angle, the shear key gap can be reduced to 2 cm, and the shear key strength can be increased to 125 % or 150 %. When the skew angle is between 30 and 60, the expansion joint size can be increased to 12 cm or 16 cm
Extraction and recognition of music melody features using a deep neural network
Get PDFThe music melody can be used to distinguish the genre style of music and can also be used for retrieving music works. This paper used a deep learning algorithm, the convolutional neural network (CNN), to extract the features of musical melodies and recognize genres. Three-tuple samples were used as training samples in the training process. Orthogonal experiments were conducted on the number of music segments and the type of activation function in the algorithm in the simulation experiments. The CNN algorithm was compared with support vector machine (SVM) and traditional CNN algorithms. The results showed that there were obvious differences in the pitch and melody curves of different genres of music; the recognition performance was best when the number of music segments was six and the activation function was relu; the CNN algorithm trained by three-tuple samples had better recognition accuracy and spent less recognition time
Non-contact type dynamic responses test of wind turbines
Get PDFThe performance analysis of wind turbine systems should be considered when calculating the wind speed relative to the wind turbine structure, and is essential for wind turbine design. Since the conditions are precarious in transient state and the operating environments are challenging, the wind turbine is a complex, multivariate, nonlinear system. This paper presents a novel dynamic response test method for wind turbines based on three-dimensional digital speckle measurement. This method use a real-time speckle image collection of objects in various stages using binocular stereo vision to perform stereo matching of deformation points on object surface. A digital image correlation algorithm is used to rebuild three-dimensional space coordinates of matching points so as to achieve wind turbine dynamic response. A laboratory-scale experimental platform is constructed to test the dynamic response of the wind turbine system. In order to verify the accuracy of the proposed method, a three-dimensional model of a wind turbine is built. With dynamic structure response process adopted to carry out dynamic analysis and compare theoretical results with test results, the results vary by less than 10 %, indicating that the test method presented in the paper is feasible and effective