The complex and variable operating conditions of sucker-rod pumping wells pose a significant challenge for the timely and accurate identification of oil well operating conditions. Effective deep learning based on measured multi-source data obtained f...
Air-conditioning system operation pattern recognition plays an important role in the fault diagnosis and energy saving of the building. Most machine learning methods need labeled data to train the model. However, the difficulty of obtaining labeled d...
For a diesel engine, operating conditions have extreme importance in fault detection and diagnosis. Limited to various special circumstances, the multi-factor operating conditions of a diesel engine are difficult to measure, and the demand of automat...
To reduce hydrogen consumption by hydrogen fuel cell vehicles (HFCVs), an adaptive power-following control strategy based on gated recurrent unit (GRU) neural network operating condition recognition was proposed. The future vehicle speed was predicte...
Aging, degradation, or damage to internal insulation materials often contribute to transformer failures. Furthermore, combustible gases can be produced when these insulation materials experience thermal or electrical stresses. This paper presents an...
In this paper, the concept of symmetry is utilized to inform the structural design of our multi-sensor fusion framework—that is, the hierarchical feature extraction and spatial–temporal correlation modeling exhibit symmetrical properties...
General synthetic aperture radar (SAR) image automatic target recognition (ATR) methods perform well under standard operation conditions (SOCs). However, they are not effective in extended operation conditions (EOCs). To improve the robustness of the...
The safe and stable operation of hydropower units, as core equipment in clean energy systems, is crucial for power system security. However, anomaly detection under complex operating conditions remains a technical challenge in this field. This paper...
To address the need for intelligent scheduling and model integration under spatiotemporal variability and uncertainty in water systems, this study proposes a hybrid correction method for pump characteristic curves that integrates data-driven techniqu...
This paper presents an innovative method for estimating vehicle sideslip angle by integrating a dynamic–kinematic coupled Unscented Kalman Filter (UKF) with an adaptive strategy that ensures accuracy across various surface conditions and operat...
Integrating hydrogen fuel cell systems (FCS) remains challenging in the expanding electric vehicle market. One of the levers to meet this challenge is the relevance of energy supervisors. This paper proposes an innovative energy management strategy (...
Recent advances in artificial intelligence (AI) technologies such as deep learning open up new opportunities for various industries, such as cement manufacturing, to transition from traditional human-aided manually controlled production processes to...
We study a conditional finite-dimensional operator construction based on two imported Recognition-Science inputs: a continuous comparison cost satisfying a multiplicative coherence axiom and equilibrium calibration, and a three-coordinate, eight-tick...
In nuclear power systems, centrifugal pumps often need to operate under extreme conditions. However, accurately determining the cavitation status of centrifugal pumps under such extreme conditions is challenging. To improve the recognition accuracy o...
Due to the confined geometry of buildings, restricted smoke extraction leads to rapid accumulation and a sharp decline in visibility, severely impeding evacuation and rescue operations. Evacuation signage can help people quickly find the evacuation r...
With the advancement of intelligent human–computer interaction (IHCI) technology, the accurate recognition of an operator’s intent has become essential for improving the collaborative efficiency in complex tasks. To address the challenges...
This article advances a philosophical interpretation of contemporary cyberspace through the categories of recognition, negativity and invidious distinction. Existing accounts attribute digital self-exploitation to surveillance, economic coercion or b...
In an orchard automation process, a current challenge is to recognize natural landmarks and tree trunks to localize intelligent robots. To overcome low-light conditions and global navigation satellite system (GNSS) signal interruptions under a dense...
Energy conservation and emission reduction is a common concern in various industries. The construction process of electric wheel loaders has the advantages of being zero-emission and having a high energy efficiency, and has been widely recognized by...
Synthetic aperture radar (SAR) operating mode recognition plays a crucial role in SAR countermeasures and serves as the foundation for effective SAR interference. To address the limitations of current SAR operating mode recognition algorithms, such a...
Aiming at the problem of the difficulty of high-resolution synthetic aperture radar (SAR) image acquisition and poor feature characterization ability of low-resolution SAR image, this paper proposes a method of an automatic target recognition method...
Tractor condition recognition has important research value in helping to understand the operating status of tractors and the trend of tillage depth changes in the field. Therefore, this article presents a method for recognizing tractor conditions, pr...
Efficient flotation beneficiation heavily relies on accurate flotation condition recognition based on monitored froth video. However, the recognition accuracy is hindered by limitations of extracting temporal features from froth videos and establishi...
Maritime transport plays a pivotal role in global trade, where efficiency and accuracy in port operations are crucial. Among the various tasks carried out in ports, container code recognition is essential for tracking and handling cargo. Manual inspe...
This paper evaluates a data-driven classification approach of operational wind turbine blades based on consecutive tower-radar measurements that are each compressed in a two-dimensional slow-time to range representation (radargram). Like many real-wo...
In recent decades, technological advancements have transformed the industry, highlighting the efficiency of automation and safety. The integration of augmented reality (AR) and gesture recognition has emerged as an innovative approach to create inter...
To improve the automation level of highway maintenance operations, the lightweight YOLOv5-Lite-s neural network was deployed in embedded devices to assist an automatic traffic cone retractor in completing recognition and positioning operations. The s...
Asymmetric cove-edged graphene nano-ribbons were employed as metallic electrodes in a hybrid gap device structure with zig-zag graphene nano-ribbons terminations for amino acid recognition and peptide sequencing. On a theoretical basis, amino acid re...
The prevailing method for handling municipal solid waste (MSW) is incineration, a critical process that demands safe, stable, and eco-conscious operation. While grate-typed furnaces offer operational flexibility, they often generate pollution during...
Accurate speech recognition can provide a natural interface for human–computer interaction. Recognition rates of the modern speech recognition systems are highly dependent on background noise levels and a choice of acoustic feature extraction m...
Reliable fire detection is essential for ensuring the safe operation of power distribution substations. This study proposes a fire recognition framework for substation surveillance environments. First, an illumination adaptation module is introduced...
In ultra-deep drilling environments, downhole measurement tools often fail or cannot be deployed due to extreme high-temperature and high-pressure (HPHT) conditions. Consequently, mud-logging data become one of the few reliable real-time information...
Human–computer interaction (HCI) with screens through gestures is a pivotal method amidst the digitalization trend. In this work, a gesture recognition method is proposed that combines multi-band spectral features with spatial characteristics o...
Traffic sign recognition plays an important role in intelligent transportation systems. Motivated by the recent success of deep learning in the application of traffic sign recognition, we present a shallow network architecture based on convolutional...
Efficient monitoring and recognition of excavator operational activities are critical for improving productivity, safety, and intelligent construction management. Traditional vision-based activity recognition systems remain sensitive to challenging c...
Accurate diagnosis of aero-engine faults and precise signal characterization are crucial to ensuring operational reliability and service life prediction. The structural complexity of engines and the variability of operating conditions pose significan...
A target recognition method of synthetic aperture radar (SAR) images is proposed via matching attributed scattering centers (ASCs) to binary target regions. The ASCs extracted from the test image are predicted as binary regions. In detail, each ASC i...
Achieving situation recognition in ubiquitous sensor networks (USNs) is an important issue that has been poorly addressed by both the research and practitioner communities. This paper describes some steps taken to address this issue by effecting USN...
This paper proposes a synthetic aperture radar (SAR) automatic target recognition (ATR) method by target reconstruction based on attributed scattering centers (ASCs). The extracted ASCs can effectively describe the electromagnetic scattering characte...
Accurate identification of partial discharge (PD) and its types is essential for assessing the operating conditions of electrical equipment. To enhance PD pattern recognition under imbalanced and limited sample conditions, a method based on a Deep Au...
Achieving fast and accurate recognition of garlic clove bud orientation is necessary for high-speed garlic seed righting operation and precision sowing. However, disturbances from actual field sowing conditions, such as garlic skin, vibration, and ra...
Background: Automated identification of logistics units is a critical requirement in high-volume warehouse operations, particularly in retails that handle millions of cartons annually. Although barcode-based systems are widely used, they generate rec...
Fruit recognition based on depth information has been a hot topic due to its advantages. However, the present equipment and methods cannot meet the requirements of rapid and reliable recognition and location of fruits in close shot for robot harvesti...
Semi-automated urban rail transit systems still rely on human intervention during safety-critical events, yet emergency takeover performance has received far less attention than in SAE Level-3 road automation. This study focuses on the reaction phase...
Offshore photovoltaic coupled electrolysis hydrogen production systems operate in complex marine environments, which puts high requirements on safety for operation and maintenance. To reduce manual intervention and support remote operation and mainte...
With the increasing complexity of the electromagnetic environment and continuous development of radar technology we can expect a large number of modern radars using agile waveforms to appear on the battlefield in the near future. Effectively identify...
To investigate the impact of “bright to dark” uneven lighting conditions on driver recognition of retroreflective guide signs in the diverging zones of underwater ramp interchanges, this study adjusts the luminance contrast between adjace...
This paper proposes a synthetic aperture radar (SAR) automatic target recognition (ATR) method via hierarchical fusion of two classification schemes, i.e., convolutional neural networks (CNN) and attributed scattering center (ASC) matching. CNN can w...
Accurate recognition of both cold wave occurrence and wind power during cold wave events is critically significant to ensure the stable operation of the power system under extreme meteorological conditions. In view of the above problems, this paper p...
Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of conv...
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