Intelligent monitoring of the condition of hydrocarbon pipeline transport  facilities using neural network technologies

Земенкова, М. Ю.; Chizhevskaya, E. L.; Zemenkov, Yu D

doi:10.31897/pmi.2022.105

Cited by 29 publications

(18 citation statements)

References 20 publications

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“…The performance of a machine learning model is significantly affected by the neural network training process, wherein training with enough data and using the right methods will produce unsurpassed results [25][26][27]. The model is trained primarily with gradient descent, and the weights are updated based on the difference between the actual value and the value predicted by the neural network.…”

Section: Teaching Methodsmentioning

confidence: 99%

Incremental Machine Learning for Soft Pneumatic Actuators with Symmetrical Chambers

Kozhubaev,

Ovchinnikova,

Viacheslav

et al. 2023

Symmetry

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Soft robotics is a specialized field of robotics that focuses on the design, manufacture, and control of robots made of soft materials, as opposed to those made of rigid links. One of the primary challenges for the future use of continuous or hyper-redundant robotics systems in industrial and medical technology is the development of suitable modeling and control approaches. Due to the complex non-linear behavior of soft materials and the unpredictable motion of actuators, the task of modeling complex soft actuators is very time-consuming. As a result, earlier studies have undertaken research into model-free methods for controlling soft actuators. In recent years, machine learning (ML) methods have become widely popular in research. The adaptability of an ML model to a non-linear soft drive system alongside the varying actuation behavior of soft drives over time as a result of material characteristics and performance requirements is the key rationale for including an ML model. The system requires the online updating of the ML model in order to work with the non-linear system. Sequential data collected from the test bench and converted into a hypothesis are used to perform incremental learning. These methods are called lifelong learning and progressive learning. Real-time data flow training is combined with incremental learning (IL), and a neural network model is tuned sequentially for each data input. In this article, a method for the intelligent control of soft pneumatic actuators based on an incremental learning algorithm is proposed. A soft pneumatic actuator was subjected to three distinct test conditions in a controlled test environment for a specified duration of data gathering. Additionally, data were collected through finite element method simulations. The collected data were used to incrementally train a neural network, and the resulting model was analyzed for errors with both training and test data. The training and testing errors were compared for different incremental learning (IL) algorithms, including K-nearest neighbors, a decision tree, linear regression, and a neural network. The feasibility of the modulo-free intelligent control of soft pneumatic actuators based on an incremental learning algorithm was verified, solving the problem of the control of software actuators.

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Section: Teaching Methodsmentioning

confidence: 99%

Incremental Machine Learning for Soft Pneumatic Actuators with Symmetrical Chambers

Kozhubaev,

Ovchinnikova,

Viacheslav

et al. 2023

Symmetry

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“…Since 1993, there have been a number of micro-hole (5 to 50 µm diameter) incidents on gas distribution pipelines in the United States [13]. Most of these have been identified during accident investigations, while other cases have been accidental.…”

Section: Theoretical Investigationmentioning

confidence: 99%

Study of static charge accumulation in HDPE gas pipelines

Pshenin

Menshikov²,

Komarovskiy³

2023

E3S Web Conf.

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The accumulation of static charge in polyethylene pipes of gas network systems is a familiar process, which is paid attention to mainly to prevent accidents on pipelines. incidents related to static electricity can occur both during assembly works (coil tapping) and during the operation of gas pipelines (gas venting, etc.). Despite the fact that repeated attempts to study this process have been made by major operating organizations, today we can state that these regularities have not been studied in full. In this work we have made an attempt to describe theoretically the process of static charge accumulation on a pipe body, as well as to evaluate experimentally the adequacy of the proposed models.

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“…The second is that the normal sleep of the slave device ensures the low power consumption of the entire design system, highlighting the design advantages and prominent features of this system for wearable devices. While ensuring the normal operation of the above two functions, the relevant performance of the system is tested [24][25][26][27].…”

Section: Software Designmentioning

confidence: 99%

Energy efficient indoor wireless communication techniques based on BLE technology

Kozhubaev,

Ovchinnikova,

Krotova

et al. 2023

E3S Web of Conf.

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The paper presents the design of a wireless communication system for short-range, high-speed, and multi-node information acquisition based on BLE5.0 technology, targeting indoor wearable applications. The system employs the Nordic nRF52832 microcontroller, which integrates BLE5.0 transceivers, as the core, and includes designs for master-slave node communication, data acquisition, hardware circuitry, embedded and upper computer programs. The system is validated through upper computer software for device networking, multi-node data acquisition, and communication speed. The power consumption and communication distance of the devices are tested using a measurement device. The designed multi-node BLE5.0 communication system in this paper provides a technical foundation for the design of relevant short-range IoT applications and has broad application prospects.

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Intelligent monitoring of the condition of hydrocarbon pipeline transport facilities using neural network technologies

Cited by 29 publications

References 20 publications

Incremental Machine Learning for Soft Pneumatic Actuators with Symmetrical Chambers

Incremental Machine Learning for Soft Pneumatic Actuators with Symmetrical Chambers

Study of static charge accumulation in HDPE gas pipelines

Energy efficient indoor wireless communication techniques based on BLE technology

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