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Injection Speed Optimization Based on Improved Generalized Predictive Control
Issue:
Volume 7, Issue 6, December 2022
Pages:
77-84
Received:
28 October 2022
Accepted:
14 November 2022
Published:
29 November 2022
DOI:
10.11648/j.eas.20220706.11
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Abstract: Injection molding is a typical nonlinear system, in which there is a need for high-precision control of injection velocity to produce sophisticated products. In view of the shortcomings in control precision of existing control systems, this paper proposes an improved generalized predictive control (GPC) model for high-precision injection velocity control. The velocity response curves are studied and corresponding control action coefficients under step disturbance with different velocity constants are determined based on the characteristics of curves. To overcome large overshoot and insufficient accuracy when controlling large delay processes, the softening factor is changed to a dynamic softening factor and the initial value of reference trajectory is determined with a new manner. To verify the performance of the propsed model, extensive simulation and experimental analysis are conducted considering parameters including horizon length, prediction horizon length, control horizon length, control weighting factor and softening coefficient. The resultsreveal that the improved GPC model achieves fairly high accuracy for the control of injection velocity, the errors is controlled within 0.05 cm/s, which can meet the injection precision requirement of actual injection molding machines. Moreover, the model can guarantee the starting and finishing ends of prediction horizon to overcome the over-regulation occurring in high precision control with other algorithms, meanwhile, the model also improves the control response velocity.
Abstract: Injection molding is a typical nonlinear system, in which there is a need for high-precision control of injection velocity to produce sophisticated products. In view of the shortcomings in control precision of existing control systems, this paper proposes an improved generalized predictive control (GPC) model for high-precision injection velocity c...
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Research on Efficient Development Technology of Chang7 Shale Reservoir of Ordos Basin
Dang Chenyue,
Zhang Yuliang,
Chai Xiaoyong,
Ding Zhenkun,
Dang Yongchao
Issue:
Volume 7, Issue 6, December 2022
Pages:
85-92
Received:
5 November 2022
Accepted:
28 November 2022
Published:
8 December 2022
DOI:
10.11648/j.eas.20220706.12
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Abstract: In view of the ordos basin Chang7 shale oil "pressure-stuffy-mining" shown in the process of "horizontal length is uneven, the drilling time after large volume fracturing, and drainage system strength is different", by the analysis of indoor experiments, numerical simulation and mine production data, comprehensive study regional geological characteristics and investment cost, optimize the length of the volume fracturing in ordos basin Chang7 shale oil reservoir efficient development technology policy. studies have shown: (1) Based on the relationship between geological characteristics of the study area and horizontal section length and production and single well investment, the reasonable horizontal section length in this area should be controlled at about 1500m; (2) The seepage process is mainly oil and water displacement in small pores for oil displacement, and the formation pressure time is 30-45 days; (3) Horizontal well return strength is large, and the oil time is relatively fast, but with the increase of the return strength, the horizontal well sand is serious, and the artificial crack diversion capacity is reduced; (4) Establishes the single well based reservoir classification structure of shale oil, based on the change characteristics of flow filling ratio in the return stage. The research results will effectively guide the development and production of shale oil reservoir in the combined area of Ordos Basin.
Abstract: In view of the ordos basin Chang7 shale oil "pressure-stuffy-mining" shown in the process of "horizontal length is uneven, the drilling time after large volume fracturing, and drainage system strength is different", by the analysis of indoor experiments, numerical simulation and mine production data, comprehensive study regional geological characte...
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Vision Code Execution Time Prediction Based on Multi-level and Multi-scale CNN
Issue:
Volume 7, Issue 6, December 2022
Pages:
93-99
Received:
24 November 2022
Accepted:
8 December 2022
Published:
15 December 2022
DOI:
10.11648/j.eas.20220706.13
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Abstract: Intelligent manufacturing relies heavily on industrial vision, and visual algorithms are rapidly being applied in the industry. However, industrial controllers are primarily used for logic control with deterministic execution cycles, and the uncertainty of vision code execution time strongly correlated with input affects their stability. To adjust the scanning cycle of the system in time to ensure system stability, an algorithm that can predict the time required for the vision code to process the target image is needed. In this paper, we analyze the weakness of traditional convolutional neural network models (CNN) and propose a multi-level and multi-scale CNN model (MLMS-CNN) for vision code execution time prediction. Instead of typical convolutional layers, we design an architecture to collect multi-scale features from the input feature maps. Moreover, a hierarchical structure is designed to reduce the loss of intermediate feature utilization by fusing features from different abstraction levels. We extract image features from images and runtime features from vision code blocks, then compare MLMS-CNN to six standard regression models, all of which are trained with the extracted features as input and the actual execution results of the visual code as output. The experimental results show that our model achieves better performance and stability.
Abstract: Intelligent manufacturing relies heavily on industrial vision, and visual algorithms are rapidly being applied in the industry. However, industrial controllers are primarily used for logic control with deterministic execution cycles, and the uncertainty of vision code execution time strongly correlated with input affects their stability. To adjust ...
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The Impact of Deterministic Relationships in Terms of Resilience and Security of the Housing Service Infrastructure
Issue:
Volume 7, Issue 6, December 2022
Pages:
100-114
Received:
11 November 2022
Accepted:
9 December 2022
Published:
23 December 2022
DOI:
10.11648/j.eas.20220706.14
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Abstract: The housing service sector is an important component of our society and an essential sector of the human that provides critical services. The housing service infrastructure and infrastructure serves as the cornerstone of societal systems, security, economic activity, individuals and households, local government management, and economic safety. The lack of capital investment or loss of the housing service infrastructures can cause billions of dollars of economic impacts across critical infrastructures. The economic perturbations in the housing service sector will lead to the inoperability of interrelated infrastructures and sectors. The main aim of this study is to define deterministic relationships between various infrastructures within an economic system to strengthen the security and resilience of the housing service infrastructure. This study conducts economic impact analysis which is the process of predicting the outcomes of a project using historical economic data. In the event of a loss of housing services infrastructure or housing-reliant sectors, identifying the critical infrastructure or economic sectors most affected will help minimize economic perturbations and related property damage. Moreover, the crisis management ability built into the housing service infrastructure will also help in a situation where the capital investment of the housing service infrastructure is lacking or lost.
Abstract: The housing service sector is an important component of our society and an essential sector of the human that provides critical services. The housing service infrastructure and infrastructure serves as the cornerstone of societal systems, security, economic activity, individuals and households, local government management, and economic safety. The ...
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Predicting the Acceptance of an Advisory Intelligent Speed Assistance System: A Case of Nigerian Drivers
Issue:
Volume 7, Issue 6, December 2022
Pages:
115-122
Received:
24 November 2022
Accepted:
14 December 2022
Published:
23 December 2022
DOI:
10.11648/j.eas.20220706.15
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Abstract: The use of advanced driver assistance systems (ADAS) to improve transport and road safety has been growing rapidly. For any significant reduction in crashes and fatalities, drivers must use these systems. Thus, the need to understand factors that will impact their adoption and acceptance. This study aims to test the efficacy of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in the investigation of acceptance of an advisory Intelligent Speed Assistance (ISA) by Nigerian drivers. This involves the examining of factors which might influence acceptance of an Advisory ISA system among a group of commercial Nigerian drivers. A test survey involving 20 participants was carried out before and after the use of a smart phone advisory speed limit system. The results indicate that the predictive power of the model was only significant after participants had used the system (Time 2), explaining 36% of the variance in Intention to use, with the construct of Performance Expectancy serving as the strongest predictor of intention. Overall, the findings suggest high acceptance levels from the drivers, as participants demonstrated strong beliefs and positive Intention to Use the system. The findings also show that participants’ acceptability levels reduced after using the ISA system. However, the results suggest that they could be other factors responsible for predicting intention to use the ISA system and thus should be further investigated. Based on these findings, the paper provides several implications for the implementation of ADAS and suggestions for future research.
Abstract: The use of advanced driver assistance systems (ADAS) to improve transport and road safety has been growing rapidly. For any significant reduction in crashes and fatalities, drivers must use these systems. Thus, the need to understand factors that will impact their adoption and acceptance. This study aims to test the efficacy of the Unified Theory o...
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