 |
 |
 |
| 24小時(shí)熱門(mén)版塊排行榜 |
- >論壇更新日志 (3187)
- >考研 (580)
- >導(dǎo)師招生 (466)
- >蟲(chóng)友互識(shí) (125)
- >文獻(xiàn)求助 (83)
- >碩博家園 (51)
- >考博 (45)
- >論文投稿 (40)
- >博后之家 (39)
- >招聘信息布告欄 (29)
- >休閑灌水 (28)
- >基金申請(qǐng) (22)
- >找工作 (17)
- >教師之家 (15)
- >文獻(xiàn)求助完結(jié)子版 (14)
- >論文道賀祈福 (13)
 |
 |
 |
||
 |
 |
 |
 |
 |
| 7 | 1/1 | 返回列表 |
| 查看: 850 | 回復(fù): 6 | |||
dwkwakaka新蟲(chóng) (初入文壇)
|
[交流]
基于可解釋性AI的工業(yè)系統(tǒng)故障診斷與健康管理技術(shù)研究
|
|
法國(guó)圖盧茲綜合理工大學(xué)，塔布國(guó)家工程師學(xué)院，工業(yè)生產(chǎn)過(guò)程實(shí)驗(yàn)室誠(chéng)招全獎(jiǎng)博士。 1.導(dǎo)師kamal medjaher: phm方向谷歌高被引學(xué)者，fmesto研究所資深研究院，lgp實(shí)驗(yàn)室主任，和善可親，帥氣可愛(ài)。 2.導(dǎo)師khanh nguyen: 全法優(yōu)秀研究員，基于深度學(xué)習(xí)的phm技術(shù)研究及xai方向的杰出青年教師，宛如耐心溫婉的師姐，溫柔細(xì)致。 3.項(xiàng)目由anr jcjc資助，英文交流，可來(lái)法后選擇性接受法語(yǔ)培訓(xùn)。 4.工作地點(diǎn)主要位于法國(guó)塔布，生活成本極低，工資喜人，辦公條件優(yōu)渥，與會(huì)法語(yǔ)或多國(guó)語(yǔ)言的同學(xué)雙人混搭，雙人辦公室辦公，不push，工業(yè)及學(xué)術(shù)會(huì)議頻繁，學(xué)生個(gè)人學(xué)術(shù)或工業(yè)發(fā)展助益明確。 5.硬性條件，參見(jiàn)附件圖片，主要需要在項(xiàng)目截止日期前取得碩士學(xué)位。 6. 有意者盡快聯(lián)系: 微信:dwkkakaka， 郵箱:kamal.medjaher@enit.fr, thi-phuong-khanh.nguyen@enit.fr 發(fā)自小木蟲(chóng)Android客戶端 |
回復(fù)此樓» 猜你喜歡
291求調(diào)劑
已經(jīng)有15人回復(fù)
-
材料學(xué)碩333求調(diào)劑
已經(jīng)有17人回復(fù)
-
070300化學(xué)求調(diào)劑
已經(jīng)有5人回復(fù)
-
070300一志愿211，312分求調(diào)劑院校
已經(jīng)有6人回復(fù)
-
物理學(xué)調(diào)劑
已經(jīng)有3人回復(fù)
-
08工科，295，接受跨專業(yè)調(diào)劑
已經(jīng)有5人回復(fù)
-
材料科學(xué)與工程調(diào)劑
已經(jīng)有12人回復(fù)
-
本2一志愿C9-333分，材料科學(xué)與工程，求調(diào)劑
已經(jīng)有5人回復(fù)
-
一志愿西交288化工專碩求調(diào)劑
已經(jīng)有4人回復(fù)
-
308求調(diào)劑
已經(jīng)有8人回復(fù)
dwkwakaka
新蟲(chóng) (初入文壇)
- 應(yīng)助: 0 (幼兒園)
- 金幣: 56.7
- 散金: 88
- 帖子: 31
- 在線: 17.2小時(shí)
- 蟲(chóng)號(hào): 7033191
- 注冊(cè): 2017-08-06
- 專業(yè): 機(jī)械動(dòng)力學(xué)
|
Laboratory: Production Engineering Laboratory (https://www.lgp.enit.fr/fr/index.html) Establishment: The National School of Engineering in Tarbes, INP Toulouse. Application: Send by email your CV including publication list (if any) and foreign language certificates (if any). Expected starting date of the thesis: 01/10/2022 Keywords: Monitoring, Data Processing and Analysis, Signal Processing, Diagnostics, Prognostics, Machine Learning, Deep Learning, Explainable AI, Edge Computing Unit. Candidate profile: ? Graduation: Master 2 Research or Engineer's degree with research experience ? Discipline: Engineering sciences or Computer sciences or Electrical /Electronics ? Knowledge/Skills: data processing and analysis, signal processing, programming on raspberry pi, diagnostics, fault prognostics, machine learning, deep learning ? Programming: Python and/or MATLAB ? Others: Analytical mind, strong writing skill, advanced English level, good team-working skills. I. Thesis objectives This thesis, a part of the project X-IMS (Explainable intelligent maintenance system), aims to develop a complete framework of self-monitoring, diagnostics, and prognostics functionalities for connected manufacturing systems. Such work has not yet been conducted and requires a combination of recent advances in multiple domains: Prognostics and Health Management (PHM), reliability, operation research and computer science. Going beyond the development of efficient AI-based PHM algorithms for a single system/component, we will investigate on the methodologies able to yield the structural/operational dependence of the system’s components. The fundamental key idea to achieve this target consists in 1) developing efficient algorithms for management and fusion of multiple input channels, e.g., historical failure database, asset configurations, operational context, manufacturing data, and 2) exploiting new advances on modelling multi-dependent component systems to derive an appropriate framework that allows presenting component interactio 發(fā)自小木蟲(chóng)Android客戶端 |
2樓2022-07-09 01:24:28
dwkwakaka
新蟲(chóng) (初入文壇)
- 應(yīng)助: 0 (幼兒園)
- 金幣: 56.7
- 散金: 88
- 帖子: 31
- 在線: 17.2小時(shí)
- 蟲(chóng)號(hào): 7033191
- 注冊(cè): 2017-08-06
- 專業(yè): 機(jī)械動(dòng)力學(xué)
|
interactions and facilitating the integration of component’s health information into an overall system health assessment and prediction. Furthermore, the developed model will also contribute to overcome the shortcomings of data-driven maintenance decision-making studies that usually ignore the interaction between components and their imperfect maintenance impacts on the overall system health state. Besides the scientific novelties mentioned above, this project also addresses a critical technical issue concerning the deployment of the developed algorithms on ECU to facilitate real-time fault detection, diagnostics and prognostics. The proposed X-IMS solutions could be tailored to the design properties and also to the computational limits of ECU. II. Previous works and expected scientific developments The development of a complete X-IMS framework, as discussed above, needs to address numerous scientific and technical challenges in different complementary fields. To achieve this ambitious goal, the results of our previous projects could be used, inherited and extended. One of the preliminary results facilitating the self-monitoring ability of X-IMS have been presented in [1]: a complete automated process from the extraction of low-level features to the construction of useful health indicator (HI). Nevertheless, this contribution does not address the issue of heterogenous data sources and requires further studies for the interpretation of the created HIs. After HI construction, the effectiveness of using a pertinent HI for fault detection and diagnostics of different systems in the smart manufacturing field was thoroughly investigated under various operating conditions with different sensor measurements in [2], [3]. For improving prognostic results, we developed an efficient hybrid approach based on the fusion of long- and short- term predictors to capture the degradation trend as well as the instantaneous changes of system health conditions [4]. However, the developed diagnostic and prognostics models are consid 發(fā)自小木蟲(chóng)Android客戶端 |
3樓2022-07-09 01:26:33
dwkwakaka
新蟲(chóng) (初入文壇)
- 應(yīng)助: 0 (幼兒園)
- 金幣: 56.7
- 散金: 88
- 帖子: 31
- 在線: 17.2小時(shí)
- 蟲(chóng)號(hào): 7033191
- 注冊(cè): 2017-08-06
- 專業(yè): 機(jī)械動(dòng)力學(xué)
|
However, the developed diagnostic and prognostics models are considered as black-boxes and do not take into account the interaction between system components. To scale up from component to system-level prognostics, in [5] we proposed a modeling approach that takes into account the component interactions and the mission profile effects on the prediction of system remaining useful life time. However, it is only the preliminary result of a fundamental research that needs more studies to be applicable in practice. Finally, a preliminary result in the area of data-driven maintenance decision-making was presented in [6]. As mentioned above, this study needs to be explored more deeply to integrate the interaction between components and the imperfect maintenance impacts on decision-making. Then, the decision optimization model should be investigated to explain the reason behind its outputs. In summary, for the X-IMS project the previous researches will be exploited to address the four following scientific challenges: ? Data fusion of heterogenous sources for HIs construction; ? Integration of component dependencies in AI-assisted diagnostic and prognostic models; ? Explainability of the created HIs and developed models. The PhD student will then work on the following tasks: ? Processing of data collected from different sources; ? Construction of effective and interpretable HIs; ? Development of Explainable Artificial Intelligence (XAI) models for fault detection & diagnostics at system level; ? Development of XAI-assisted prognostics for multi-dependent-component systems; ? Deployment of the developed functionalities (fault detection, diagnostic and prognostics) on an Edge Computing Unit. 發(fā)自小木蟲(chóng)Android客戶端 |
4樓2022-07-09 01:27:43
新垣結(jié)衣黑
新蟲(chóng) (初入文壇)
- 應(yīng)助: 0 (幼兒園)
- 金幣: 23
- 帖子: 6
- 在線: 13.4小時(shí)
- 蟲(chóng)號(hào): 4804709
- 注冊(cè): 2016-06-29
- 性別: GG
5樓2022-07-09 05:54:48
dwkwakaka
新蟲(chóng) (初入文壇)
- 應(yīng)助: 0 (幼兒園)
- 金幣: 56.7
- 散金: 88
- 帖子: 31
- 在線: 17.2小時(shí)
- 蟲(chóng)號(hào): 7033191
- 注冊(cè): 2017-08-06
- 專業(yè): 機(jī)械動(dòng)力學(xué)
6樓2022-07-11 17:07:23
dwkwakaka
新蟲(chóng) (初入文壇)
- 應(yīng)助: 0 (幼兒園)
- 金幣: 56.7
- 散金: 88
- 帖子: 31
- 在線: 17.2小時(shí)
- 蟲(chóng)號(hào): 7033191
- 注冊(cè): 2017-08-06
- 專業(yè): 機(jī)械動(dòng)力學(xué)
|
無(wú)任何語(yǔ)言，年齡，專業(yè)要求。但需要和老師能用英語(yǔ)交流，會(huì)機(jī)器學(xué)習(xí)者最好 發(fā)自小木蟲(chóng)Android客戶端 |
7樓2022-07-11 17:08:58
相關(guān)版塊跳轉(zhuǎn)
我要訂閱樓主 dwkwakaka 的主題更新
| 7 | 1/1 | 返回列表 |
| 最具人氣熱帖推薦 [查看全部] | 作者 | 回/看 | 最后發(fā)表 | |
|---|---|---|---|---|
|
[考研] 085404 22408 315分 +3 | zhuangyan123 2026-03-31 | 3/150 |
|
|---|---|---|---|---|
|
|
[考研] 085601一志愿中山大學(xué)深圳材料工程330求調(diào)劑 +5 | pipiver 2026-03-30 | 5/250 |
|
|
|
[考博] 材料專業(yè)申博 +4 | 杜雨婷dyt 2026-03-29 | 4/200 |
|
|
[考研] 求收留 +6 | 1943443204 2026-03-28 | 6/300 |
|
|
|
[考研] 一志愿鄭州大學(xué)，080500學(xué)碩，總分317分求調(diào)劑 +10 | 舉個(gè)栗子oi 2026-03-24 | 11/550 |
|
|
|
[考研] 一志愿廈門(mén)大學(xué)材料工程專碩354找調(diào)劑�。。� +5 | 貝唄鋇鋇 2026-03-30 | 5/250 |
|
|
|
[考研] 求調(diào)劑 +7 | 青春裁為三截 2026-03-29 | 7/350 |
|
|
|
[考研] 材料與化工304求B區(qū)調(diào)劑 +4 | 邱gl 2026-03-26 | 7/350 |
|
|
|
[考研] 一志愿北京工業(yè)大學(xué)，324分求調(diào)劑 +6 | 零八# 2026-03-28 | 6/300 |
|
|
|
[考研] 070305高分子化學(xué)與物理 304分求調(diào)劑 +12 | c297914 2026-03-28 | 12/600 |
|
|
|
[考研] 081200-11408-276學(xué)碩求調(diào)劑 +6 | 崔wj 2026-03-26 | 6/300 |
|
|
|
[考研] 0703化學(xué)調(diào)劑，求導(dǎo)師收 +9 | 天天好運(yùn)來(lái)上岸?/a> 2026-03-24 | 10/500 |
|
|
|
[考研] 材料求調(diào)劑一志愿哈工大324 +7 | 閆旭東 2026-03-28 | 9/450 |
|
|
|
[考研] 086000調(diào)劑 +3 | 7901117076 2026-03-26 | 3/150 |
|
|
|
[有機(jī)交流]
高溫高壓反應(yīng)求助
 10+4
|
chibby 2026-03-25 | 4/200 |
|
|
|
[考研] 求調(diào)劑 +4 | 零八# 2026-03-27 | 4/200 |
|
|
|
[考研]
材料調(diào)劑
5+4
|
想要一壺桃花水 2026-03-25 | 10/500 |
|
|
|
[考研] 303求調(diào)劑 +6 | 藍(lán)山月 2026-03-25 | 6/300 |
|
|
|
[考研] 290分調(diào)劑求助 +3 | 吉祥止止陳 2026-03-25 | 3/150 |
|
|
|
[考研] 0854人工智能方向招收調(diào)劑 +4 | 章小魚(yú)567 2026-03-24 | 4/200 |
|