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A New Human Action Recognition Method Based on Skeletons From Depth Sensors 基于深度传感器骨架的人体动作识别新方法
IF 4.3 2区 综合性期刊
IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582376
Chaoya Wang;Hua Han;Kaiyu Xu;Li Huang
{"title":"A New Human Action Recognition Method Based on Skeletons From Depth Sensors","authors":"Chaoya Wang;Hua Han;Kaiyu Xu;Li Huang","doi":"10.1109/JSEN.2025.3582376","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582376","url":null,"abstract":"Skeleton data from depth sensors, enriched with substantial information and compact in storage, provides a streamlined sequential representation. It is resilient to environmental variables such as background noise, attire, and illumination. Consequently, skeleton-based human action recognition emerges as an important topic in computer vision. Its key task is to extract distinctive features, specifically those critical for differentiating human actions. This work proposes an ambiguous-feature-refinement (AFR) and orthogonal-basis-coordinate-transformation-(OBT)-based residual graph convolution neural network (AOnet) model for skeleton-based human action recognition. First, multiple input branches (MIBs) are proposed and employed to enrich skeletal information features at the early data-input stage while maintaining a compact and effective representation of data. Second, since many actions exhibit highly similar joint features, an AFR model is introduced to further distinguish ambiguous features without considering external information interaction. This step benefits the extraction of distinctive spatial-temporal (ST) features, thereby improving the differentiation among action categories. Finally, an OBT method is proposed to convert refined nonlinear ST features into linear ones and augment the model’s ability to capture higher order dynamic information. The proposed method has been evaluated on two large-scale datasets. The experimental results confirm that AOnet demonstrates superior performance over the state of the art.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29161-29172"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Novel Acoustic Temperature Measurement Technology of Transformers Based on Ultrasonic Sensing 基于超声传感的变压器声温测量新技术
IF 4.3 2区 综合性期刊
IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582597
Dongxin He;Yunhao Li;Haoxin Guo;Jiefeng Liu;Xinhua Guo;Dewen Zhang;Dechao Yang;Qingquan Li
{"title":"A Novel Acoustic Temperature Measurement Technology of Transformers Based on Ultrasonic Sensing","authors":"Dongxin He;Yunhao Li;Haoxin Guo;Jiefeng Liu;Xinhua Guo;Dewen Zhang;Dechao Yang;Qingquan Li","doi":"10.1109/JSEN.2025.3582597","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582597","url":null,"abstract":"This article addresses the challenges of monitoring the internal temperature of oil-immersed power transformers, where the metal shell barrier limits the effectiveness of conventional temperature measurement methods, and existing detection techniques lack accuracy and practicality. To tackle these issues, an ultrasonic temperature measurement method is introduced in this article, combined with machine learning algorithms for enhanced temperature inversion and monitoring. First, an experimental platform is established to collect acoustic data at various temperatures, analyze interference noise from transformer core vibrations, and filter out magnetically induced noise. After that, the key time-domain features that reflect the change in dynamic waveform with temperature are extracted. Finally, the random forest (RF), k-nearest neighbor (KNN), and support vector machine (SVM) are used to build a transformer temperature identification model, and feature optimization is achieved with the help of two feature dimensionality reduction methods, RF, and correlation-based feature selection (CFS). Experimental results show that the RF, GS-KNN, and ZOA-SVM models achieve recognition accuracies of 88.57%, 94.29%, and 91.43%, respectively. These findings highlight the proposed method’s ability to accurately diagnose internal transformer temperatures, which is of some significance in engineering practice.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29890-29901"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Dual-IMU Positioning System Based on IHDE and Multiconstraint Framework 基于IHDE和多约束框架的双imu定位系统
IF 4.3 2区 综合性期刊
IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582279
Jiaxin Liu;Shiliang Wang;Feifan Lin;Yue Yu;Yu Liu;Jiangfeng Huang;Hui Peng;Liangying Wu
{"title":"A Dual-IMU Positioning System Based on IHDE and Multiconstraint Framework","authors":"Jiaxin Liu;Shiliang Wang;Feifan Lin;Yue Yu;Yu Liu;Jiangfeng Huang;Hui Peng;Liangying Wu","doi":"10.1109/JSEN.2025.3582279","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582279","url":null,"abstract":"Inertial navigation systems (INSs) provide continuous high-frequency positioning with inherent stability. The pedestrian positioning system based on INS is considered to be an important application of the Global Navigation Satellite System (GNSS)-degraded environments and open outdoor scenarios, including but not limited to emergency rescue, security patrol, soldier positioning, and many other fields. To improve the positioning accuracy of the pedestrian INS, a dual-IMU positioning correction algorithm is proposed. First, an improved heuristic drift elimination (IHDE) algorithm is proposed. The IHDE establishes a linear regression model for the INS positioning solution of a single inertial measurement unit (IMU), and the observation vector and observation matrix based on the type of pedestrian motion are constructed to reduce the INS error by combining the heading difference between the main heading and the calculated heading. Then, the pedestrian’s two-foot constraint relationship is used to establish a constraint model to mutually constrain the position information of the left and right foot to correct the positioning accuracy. Comprehensive experiments demonstrate that the proposed algorithm achieves that the solved trajectory is closer to the real trajectory, and the average closed-loop error is reduced from 2.6%D to 0.3%D compared with the traditional mechanical algorithm. In summary, the proposed algorithm effectively improves the INS positioning accuracy and has high value in engineering applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29565-29575"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Double-Sided Metamaterial-Inspired Microwave Sensor for Monitoring of Alkali–Silica Reaction (ASR) in Cement-Based Mortar Samples 用于监测水泥基砂浆样品中碱-硅反应(ASR)的双面超材料微波传感器
IF 4.3 2区 综合性期刊
IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582644
Ugur C. Hasar;Hamdullah Ozturk;Huseyin Korkmaz
{"title":"Double-Sided Metamaterial-Inspired Microwave Sensor for Monitoring of Alkali–Silica Reaction (ASR) in Cement-Based Mortar Samples","authors":"Ugur C. Hasar;Hamdullah Ozturk;Huseyin Korkmaz","doi":"10.1109/JSEN.2025.3582644","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582644","url":null,"abstract":"Ordinary Portland cement (OPC) structures are the simplest and oldest type of cement in use today. Their service lives, however, are largely limited by the alkali-silica reaction (ASR), which has the potential of producing microstructures throughout OPC structures. There is, therefore, a need for accurate detection of the ASR. In this study, we propose a double-sided metamaterial (MM)-inspired microwave sensor for the identification of the ASR occurring inside OPC mortar samples. Different from previous studies for ASR detection, our design heavily relies on a resonance phenomenon, resulting in a relatively highly accurate and sensitive detection. The resonator has designed cells operating over 2.6–3.95 GHz (S-band) in which microwave signals are very sensitive to water reactions, giving a high sensitivity for ASR detection. Simulations and experiments were performed for the S-band to validate our sensor. Expansion tests are conducted, and SEM micrographs are taken to support microwave measurements. Confidence interval (CI) analysis is conducted to assess the integrity of measurements.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28360-28367"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fault Diagnosis of Rolling Bearings by Integrating Laplace Wavelet Residual Network With Cauchy Kernel Maximum Mean Discrepancy Method 基于拉普拉斯小波残差网络与柯西核最大均值差法的滚动轴承故障诊断
IF 4.3 2区 综合性期刊
IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582423
Kaixin Wu;Zhanhua Wu;Yuyuan Wu;Yongjian Li;Qing Xiong
{"title":"Fault Diagnosis of Rolling Bearings by Integrating Laplace Wavelet Residual Network With Cauchy Kernel Maximum Mean Discrepancy Method","authors":"Kaixin Wu;Zhanhua Wu;Yuyuan Wu;Yongjian Li;Qing Xiong","doi":"10.1109/JSEN.2025.3582423","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582423","url":null,"abstract":"Rolling bearings are critical components extensively applied in modern industries and play a significant role in ensuring the safety of high-speed rotating machinery systems. Accurate fault recognition of rolling bearings is essential for ensuring the safety of mechanical systems. This study proposes a method for diagnosing rolling bearing faults, utilizing a Laplace wavelet residual network integrated with a spatial attention mechanism (SAM) model and the Cauchy kernel-induced maximum mean discrepancy (CK-MMD) method (LRSDAN) to address the problems of complex variations in operational environments, different defect types, and differences in the distribution of collected data in real-world environments. This method incorporates a wavelet convolutional layer to comprehensively extract the shock components associated with bearing faults, employs a residual network (ResNet) to increase the model depth, and utilizes a SAM to extract the key vibration information. Subsequently, CK-MMD was applied as a metric to reduce the interdomain distribution differences and domain shift phenomena by an unbiased estimation technique based on the MMD. The model was validated on the datasets characterized by time-varying speed and variable load conditions. The investigation outcomes corroborate the reliability and superiority of the LRSDAN model in fault diagnosis performance through two publicly available datasets.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29173-29188"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Human Tangential Activity Recognition Based on Swin Transformer and Supervised Contrastive Learning Using Interferometric Radar 基于Swin变压器和干涉雷达监督对比学习的人体切向活动识别
IF 4.3 2区 综合性期刊
IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582424
Lele Qu;Jiaqi Cong;Tianhong Yang;Lili Zhang
{"title":"Human Tangential Activity Recognition Based on Swin Transformer and Supervised Contrastive Learning Using Interferometric Radar","authors":"Lele Qu;Jiaqi Cong;Tianhong Yang;Lili Zhang","doi":"10.1109/JSEN.2025.3582424","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582424","url":null,"abstract":"Micro-Doppler (mD) signatures are widely used in the field of radar-based human activity recognition (HAR). However, these mD signatures tend to weaken significantly for human tangential activities, which increases the similarity between features of various activities and causes a notable decline in classification performance. To address this issue, this article proposes a human tangential activity recognition method based on a swin transformer (ST) and supervised contrastive learning (SCL) using interferometric radar. The proposed SCL-ST network integrates the feature fusion, ST encoder, and SCL framework. Specifically, a frequency-modulated continuous wave (FMCW) interferometric radar with one transmitter and two receivers is employed to capture echo data of human tangential activities. The echo data are preprocessed to generate single-channel mD spectrograms and dual-channel interferometric spectrograms. The training of the SCL-ST network is divided into two stages. Initially, the SCL-ST network is pretrained using the supervised contrastive loss. The generated mD and interferometric spectrograms are fed into the proposed SCL-ST network, which is equipped with the multilayer perceptron (MLP) projection head. The MLP projection head is capable of mapping feature vectors into a latent space, thereby enhancing the ability of the ST encoder to extract features related to diverse tangential activities. Subsequently, all parameters preceding the MLP projection head are frozen. The MLP classification head is employed to replace the projection head, and the network is then trained using cross-entropy loss to implement downstream classification tasks. Experimental results demonstrate that the proposed SCL-ST network can effectively classify different human tangential activities and achieve a recognition accuracy of 98.89%.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29189-29200"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Field Curvature Aberration Correction Using Cylindrically Curved CMOS Image Sensors 利用圆柱弯曲CMOS图像传感器校正场曲率像差
IF 4.3 2区 综合性期刊
IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582384
Shigeyuki Imura;Masahide Goto;Hiroto Sato
{"title":"Field Curvature Aberration Correction Using Cylindrically Curved CMOS Image Sensors","authors":"Shigeyuki Imura;Masahide Goto;Hiroto Sato","doi":"10.1109/JSEN.2025.3582384","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582384","url":null,"abstract":"We demonstrate the lateral field curvature aberration correction of a lens employing a cylindrically curved complementary metal-oxide–semiconductor (CMOS) image sensor without using multiple lenses. By employing a silicon-on-insulator (SOI) structure and applying etching using xenon fluoride (<inline-formula> <tex-math>${mathrm {XeF}}_{{2}})$ </tex-math></inline-formula>, we fabricated an extremely thin CMOS image sensor with an 11- <inline-formula> <tex-math>$mu $ </tex-math></inline-formula> m thickness without causing damage to the CMOS circuitry. Because of the structural characteristics of SOI, i.e., extremely small thickness and high SiO2 content, the fabricated CMOS image sensor is flexible and does not break easily even when curved. The device was curved on a concave surface, fixed to a cylindrical pedestal, and mounted on a package using wire bonding to implement a cylindrically curved CMOS image sensor with a curvature radius of 20 mm. Using the fabricated CMOS image sensor, we successfully captured video images (<inline-formula> <tex-math>$320times 240$ </tex-math></inline-formula> pixels). A comparison between these images and those obtained from a flat CMOS image sensor showed that blurring at the lateral periphery of the images can be reduced using a single lens by curving the CMOS image sensor.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"28308-28313"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
High-Dynamic Visual Systems Utilizing Mamba-Integrated Event-Based Solutions for Motion Deblurring 利用mamba集成的基于事件的运动去模糊解决方案的高动态视觉系统
IF 4.3 2区 综合性期刊
IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582694
Zhi-Xuan Zhang;Shanq-Jang Ruan
{"title":"High-Dynamic Visual Systems Utilizing Mamba-Integrated Event-Based Solutions for Motion Deblurring","authors":"Zhi-Xuan Zhang;Shanq-Jang Ruan","doi":"10.1109/JSEN.2025.3582694","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582694","url":null,"abstract":"Motion blur in dynamic scenes poses a significant challenge for computer vision applications. Traditional image sensors capture complete frames at fixed intervals, often failing to precisely record the positions of objects during rapid motion, resulting in blurred images. Event-based vision sensors (EVSs) offer a novel solution by asynchronously capturing pixel-level changes in luminosity, generating event data highly sensitive to temporal dynamics. This article presents an enhanced motion deblurring framework that integrates the Mamba module within the architecture. The proposed model leverages the high temporal resolution and asynchronous data acquisition capabilities of EVSs to combine event data with frame-based imagery, enriching motion representation and improving image clarity. Key components, such as the event-image fusion-Mamba module (EIFMB) and the event-guided masking module (EGMM), are introduced to adaptively integrate and process dynamic and static visual information. Experimental results on benchmark datasets demonstrate significant improvements in deblurring performance, with the model achieving a peak signal-to-noise ratio (PSNR) of 36.62 and a structural similarity index (SSIM) of 0.977, validating the effectiveness of this approach.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"30227-30237"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Hybrid Energy-Efficient Clustering With Reinforcement Learning for IoT-WSNs Using Knapsack and K -Means 基于背包和K均值的物联网wsns混合强化学习节能聚类
IF 4.3 2区 综合性期刊
IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582381
Abdul Aleem;Rajesh Thumma
{"title":"Hybrid Energy-Efficient Clustering With Reinforcement Learning for IoT-WSNs Using Knapsack and K -Means","authors":"Abdul Aleem;Rajesh Thumma","doi":"10.1109/JSEN.2025.3582381","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582381","url":null,"abstract":"Wireless sensor networks (WSNs) play a fundamental role in the Internet of Things (IoTs), with widespread applications in areas such as smart city infrastructure, industrial control systems, and environmental monitoring. Despite their broad utility, challenges related to energy efficiency and network longevity persist. To address these issues, this article introduces an integrated framework that leverages distributed energy-efficient clustering (DEEC), the energy-efficient Knapsack algorithm (EEKA), K-means clustering, and reinforcement learning (RL) to optimize energy usage and improve overall network performance. While cluster-heads (CHs) selection is conducted in a balanced manner by DEEC to prevent energy depletion, the selection of sensor node CHs also avoids exhausting sensor node energy. EEKA optimizes task allocation under energy constraints, allowing for efficient distribution of tasks based on available energy levels. This approach conserves more energy spent on data transmission compared to other techniques, as K-means clustering minimizes intracluster communication overhead. Moreover, during varying conditions such as cluster sizes or transmission power, parameters related to the network can be adaptively tuned in real-time by RL, enhancing stability and performance. Simulation results demonstrate a significant improvement in energy efficiency with this hybrid model compared to traditional approaches under similar conditions. Therefore, for sustainable energy management within IoT-enabled WSNs, the DEEC-EEKA–K-means-RL framework offers a robust adaptive method for efficient resource utilization across diverse operational contexts, rather than relying solely on robustness and resilience-based solutions.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"30047-30059"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fan Pressurization Method to Measure House Leakage Area Using Built-in Exhaust Fans and Window Openings as Reference Areas 以内置排风机和开窗作为参考面积测量房屋泄漏面积的风机加压法
IF 4.3 2区 综合性期刊
IEEE Sensors Journal Pub Date : 2025-06-30 DOI: 10.1109/JSEN.2025.3582369
Y. Kurihara;K. Kobayashi;K. Watanabe
{"title":"Fan Pressurization Method to Measure House Leakage Area Using Built-in Exhaust Fans and Window Openings as Reference Areas","authors":"Y. Kurihara;K. Kobayashi;K. Watanabe","doi":"10.1109/JSEN.2025.3582369","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3582369","url":null,"abstract":"The fan pressurization method described in ISO 9972:2015 evaluates the air permeability of houses by measuring the effective leakage area (ELA). This method uses a specialized blower equipped with a volumetric airflow meter and a differential pressure sensor. This study proposes an alternative that utilizes a differential pressure sensor along with household exhaust fans to depressurize a house. Additionally, the known area of an open house window is used to calibrate the ELA against the corresponding geometrical area. To validate this method, the relationship between the geometric leakage area and the ELA obtained through this approach, as well as comparisons with other methods, were examined via theoretical analysis and experiments in a small container space. In a single room in an actual building characterized by substantial leakage gaps, such as those around interior doors, the total leakage area measured with a gap meter was 311.5 cm2, and the proposed method yielded the same value, demonstrating excellent agreement between the two. The proposed method was tested in a 36-year-old American-style house with a total floor area of 226.59 m2 and resulted in an ELA of 672 cm2 and a C-value of 2.96 cm2/m2. The geometrically measurable leakage area and the area estimated using the proposed method showed good agreement, confirming the reliability of the approach. Furthermore, the C-value of 2.96 cm2/m2, derived from the ELA measured in an actual house experiment, falls within the typical range for residential buildings (110 cm2/m<inline-formula> <tex-math>${}^{{2}}text {)}$ </tex-math></inline-formula>.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 15","pages":"29880-29889"},"PeriodicalIF":4.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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