標題: Titlebook: New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques; Advanced Machine Lea Guangrui Wen,Zihao Lei,Xin Huang B [打印本頁] 作者: 類屬 時間: 2025-3-21 19:08
書目名稱New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques影響因子(影響力)
書目名稱New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques影響因子(影響力)學(xué)科排名
書目名稱New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques網(wǎng)絡(luò)公開度
書目名稱New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques被引頻次
書目名稱New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques被引頻次學(xué)科排名
書目名稱New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques年度引用
書目名稱New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques年度引用學(xué)科排名
書目名稱New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques讀者反饋
書目名稱New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques讀者反饋學(xué)科排名
作者: 毀壞 時間: 2025-3-21 22:21
Sparse Model-Driven Deep Learning for Weak Fault Diagnosis of Rolling Bearingsoach to digging the fault features of vibration signals, but it is not liable to reliably extract the fault features while maintaining good generalization. Therefore, this chapter proposes a novel end-to-end Deep Network-based Sparse Denoising (DNSD) framework based on the model-data-collaborative l作者: 細微差別 時間: 2025-3-22 00:39
Memory Residual Regression Autoencoder for Bearing Fault Detectionen only by normal data has received increasing attention in recent years. In this chapter, an innovative deep learning-based model, namely, Memory Residual Regression Autoencoder (MRRAE) is developed to improve the accuracy of anomaly detection in bearing condition monitoring. The memory module and 作者: 營養(yǎng) 時間: 2025-3-22 04:48 作者: 大笑 時間: 2025-3-22 12:16
Performance Degradation Assessment Based on Transfer Learning for Bearinglenge of generalization for performance degradation assessment models. And it is costly and time-consuming to collect a large amount of labeled data for supervised diagnosis, especially when the task comes from a new operating condition. Thus in this chapter, a novel bearing degradation assessment m作者: 多節(jié) 時間: 2025-3-22 16:06
Remaining Useful Life Prediction on Transfer Learning for Bearingying operational conditions, conventional RUL prediction models trained on some run-to-failure (RTF) datasets are unlikely to be generalized to a new degraded process. To increase the generalizability, recent studies have focused on the development of the deep domain adaptation methods for RUL predi作者: 獸皮 時間: 2025-3-22 17:18
Deep Sequence Multi-distribution Adversarial Model for Abnormal Condition Detection in Industrysy in losing effective information due to manual features extracting. Deep learning-based methods can solve the problem effectively, but the detection accuracy is still not satisfactory. In addition, most of the methods cannot take the time-ordered specialty into account, which is significant for ti作者: 膽大 時間: 2025-3-22 23:56
Multi-scale Lightweight Fault Diagnosis Model Based on Adversarial Learningmples is limited in industrial practice, and these samples usually are contained with complex environmental noise. Therefore, it is necessary to develop a generalizable DL model with strong feature learning ability. To tackle the above challenges, this chapter proposes a multi-scale lightweight faul作者: 惡臭 時間: 2025-3-23 04:42
Performance Degradation Assessment Based on Adversarial Learning for Bearing crucial to monitor the health status of rolling bearings so as to ensure the safe and stable operation for mechanical equipment. After detecting and diagnosing faults, how to identify the extent of bearing failure and performance degradation becomes a key step in condition-based maintenance. Howeve作者: Astigmatism 時間: 2025-3-23 07:58 作者: 失敗主義者 時間: 2025-3-23 12:16
Community Clustering Algorithms and Its Application in Machine Fault Diagnosis methods and proves its effectiveness in mechanical fault diagnosis. Community clustering, as one of them, has made great progress in recent years. However, the existing community clustering algorithms have the disadvantages of lacking significant global extreme value and huge search space. Therefor作者: 我邪惡 時間: 2025-3-23 14:29 作者: 兩棲動物 時間: 2025-3-23 19:09 作者: nephritis 時間: 2025-3-24 01:33
Guangrui Wen,Zihao Lei,Xuefeng Chen,Xin Huangtswissenschaft – je unterschiedliche Begrifflichkeiten und Bedeutungen herausgebildet. Es handelt sich mithin um einen ?schillernden“ transdisziplin?ren Begriff, der im Kontext des vorliegenden Bandes, mit seinem Fokus auf der Interrelationalit?t von Genre und Medium, spezifisch medienwissenschaftli作者: myriad 時間: 2025-3-24 05:22
Guangrui Wen,Zihao Lei,Xuefeng Chen,Xin Huangthe presence of diverse extracellular stimuli to the cell interior. All known GPCRs share a common architecture of seven membrane-spanning helices connected by intra- and extracellular loops. Most GPCR-mediated cellular responses result from the receptor acting as a ligand-activated guanine nucleoti作者: Foolproof 時間: 2025-3-24 07:00 作者: 畏縮 時間: 2025-3-24 13:16 作者: BIDE 時間: 2025-3-24 17:55
Guangrui Wen,Zihao Lei,Xuefeng Chen,Xin Huange local concentrations of protein substrates. In many cases, the distribution of potential substrates is mfluenced by interactions with noncatalytic regions of the enzymes such as autophosphorylation sites, Src homology 2 (SH2) domains, and Src homology 3 (SH3) domains. These interactions may recrui作者: insert 時間: 2025-3-24 19:58 作者: 令人作嘔 時間: 2025-3-24 23:55
Guangrui Wen,Zihao Lei,Xuefeng Chen,Xin Huang few years a large body of evidence has been accumulated that suggests that Rho-like proteins play a critical role in the organization of the actin cytoskeleton and are tinpltcated in cell growth and transformation (.). Like other GTPases, Rho-family members cycle between the inactive guanosme drpho作者: 新字 時間: 2025-3-25 05:01
Guangrui Wen,Zihao Lei,Xuefeng Chen,Xin Huangen a CdiA protein on the surface of one cell and a β-barrel protein on the surface of a neighboring cell. This interaction triggers the transport of a protein toxin into the neighboring cell where it exerts its lethal activity. Several classes of CdiA proteins that bind to different β-barrel recepto作者: 不公開 時間: 2025-3-25 07:45 作者: 總 時間: 2025-3-25 15:18
Guangrui Wen,Zihao Lei,Xuefeng Chen,Xin Huangx parts of the world.) The cardinal’s garb, the memento mori, the trombone of God, and the lion (lower right) that we see in the image above (figure 1) have been employed in dozens, perhaps hundreds, of mimeses of this translator through the centuries, for example by Caravaggio, Lucas Cranach, Albre作者: confide 時間: 2025-3-25 18:37
Guangrui Wen,Zihao Lei,Xuefeng Chen,Xin Huanglanguages of the world—but especially to French, which would bring with it the anti-Catholicism of the French Revolution. One suspects that his hatred of translation may be a coded way of expressing hatred for the content of these translations, the discourse of the philosophes that had led France to作者: 排他 時間: 2025-3-25 21:07 作者: vertebrate 時間: 2025-3-26 02:08
New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques978-981-97-1176-5Series ISSN 2194-8402 Series E-ISSN 2194-8410 作者: 旅行路線 時間: 2025-3-26 04:52
Smart Sensors, Measurement and Instrumentationhttp://image.papertrans.cn/n/image/669661.jpg作者: 匍匐前進 時間: 2025-3-26 11:09 作者: euphoria 時間: 2025-3-26 15:47 作者: 不易燃 時間: 2025-3-26 20:05
Guangrui Wen,Zihao Lei,Xuefeng Chen,Xin Huangion of the protein by the catalytic domain of Src (.). Similarly, the SH2 domain of the Abl tyrosine kinase is required for hyperphosphorylation of rts substrate p130. (.). Substitutions of SH2 domains in nonreceptor tyrosme kinases with heterologous SH2 domains result in the phosphorylation of alternative substrates in vivo (.).作者: Mutter 時間: 2025-3-27 00:18 作者: CUB 時間: 2025-3-27 04:10 作者: 節(jié)省 時間: 2025-3-27 07:47 作者: Supplement 時間: 2025-3-27 10:58 作者: 即席演說 時間: 2025-3-27 16:08
Guangrui Wen,Zihao Lei,Xuefeng Chen,Xin Huangp- hensive detailed methods, studies in genetically tractable systems, fluorescence microscopy in live single cells, ex vivo analysis of primary cells fro978-1-61737-633-7978-1-59745-048-5Series ISSN 1064-3745 Series E-ISSN 1940-6029 作者: Agronomy 時間: 2025-3-27 21:23
Guangrui Wen,Zihao Lei,Xuefeng Chen,Xin Huangeins, and the binding of various scaffolding proteins to intracellular receptor domains. In some cases, these processes appear to generate signals in conjunction with, or even independent of, G protein activation.作者: NIB 時間: 2025-3-28 00:03
2194-8402 artificial intelligence techniques to monitor, diagnose, and perform predictive maintenance of critical structures and machines, such as aero-engine, gas turbines, wind turbines, and machine tools...The main ma978-981-97-1178-9978-981-97-1176-5Series ISSN 2194-8402 Series E-ISSN 2194-8410 作者: atopic-rhinitis 時間: 2025-3-28 05:28
Guangrui Wen,Zihao Lei,Xuefeng Chen,Xin Huangnd the p67-phox of nicotrnamide adenine dinueleotide phosphate (reduced form) (NADPH) oxrdase (.). CDC42Hs effecters include PAK kinases and the Wiskott Aldrich Syndrome Protein (WASP) (.,.). Rho was recently shown to interact with several protein kinases related to protein kinase N (.,.).作者: Vertical 時間: 2025-3-28 08:17
New Generation Artificial Intelligence-Driven Diagnosis and Maintenance TechniquesAdvanced Machine Lea作者: 確認 時間: 2025-3-28 14:10 作者: 否認 時間: 2025-3-28 16:34 作者: Ruptured-Disk 時間: 2025-3-28 18:51
Guangrui Wen,Zihao Lei,Xuefeng Chen,Xin Huanganstilian forged out of the endless translations of Gallic literature that were flooding the Spanish book market. Vargas Ponce estimated that in the last decades of the eighteenth century, one-third of everything published in Spain was a translation (García Garrosa 55).作者: 不容置疑 時間: 2025-3-29 02:13 作者: 閑逛 時間: 2025-3-29 04:38
Fault Diagnosis of Polytropic Conditions Based on Transfer Learningion (VMD) and mixed domain feature extraction to fully mine the state information and intrinsic attributes of the vibration signal. Secondly, the dimensionality reduction and optimization of features are achieved through extreme gradient promotion, and meaningful and sensitive features are selected 作者: 石墨 時間: 2025-3-29 07:29 作者: 北極熊 時間: 2025-3-29 13:31
Remaining Useful Life Prediction on Transfer Learning for Bearings were applied separately to reduce the distribution discrepancy of the temporal features. In this way, two novel domain adaption methods, i.e., OCA-LSTM-ABDA and OCA-LSTM-DBDA, were proposed for RUL prediction with time-varying operational conditions. Comprehensive experiments on aircraft turbofan 作者: 生存環(huán)境 時間: 2025-3-29 16:40 作者: 咒語 時間: 2025-3-29 22:47 作者: 萬靈丹 時間: 2025-3-30 00:16
Performance Degradation Assessment Based on Adversarial Learning for Bearingof the label sets in source domain and target domain is the same, that is, source domain and target domain have the same number of categories. This is different from real scenarios in industrial practice where the set of labels in the target domain is a subset of the source domain. In other words, t作者: 下垂 時間: 2025-3-30 07:09
Modelling and Feature Extraction Method Based on Complex Network and Its Application in Machine Faulring fault diagnosis and degradation state recognition. Analysis of the experimental data and bearing life cycle data shows that the method proposed in this chapter is effective and that the extracted features have effective separability and high accuracy in fault recognition and the degradation det作者: 發(fā)出眩目光芒 時間: 2025-3-30 10:38 作者: LATE 時間: 2025-3-30 16:18
Remaining Life Assessment of Rolling Bearing Based on Graph Neural Networkture extraction and deep learning to mine and characterize the structured information of the signals. (2) It is difficult for the existing deep learning methods to model data in non-Euclidean spaces. In order to solve the above problems, this chapter proposes a remaining useful life assessment metho作者: 油膏 時間: 2025-3-30 19:26
Intelligent Fault Diagnosis Method Based on Multi-source Data and Multi-feature Fusione convolution and fusion convolution blocks are used for deep feature extraction and fusion. Finally, a joint loss function is reconstructed under the framework of unsupervised learning, which considers the distribution differences of the features and the label information simultaneously. The experi
