Reasoning method and fault diagnosis method and system implementing the same

• 1. 基于工业以太网故障诊断方法中决策树的推理方法 [P] . 中国专利： CN104486096A . 2015-04-01
• 2. 空调故障诊断方法及装置、工程故障诊断方法及系统、空调 [P] . 中国专利： CN113294888A . 2021-08-24
• 3. FAULT DIAGNOSIS DEVICE, FAULT DIAGNOSIS SYSTEM, FAULT DIAGNOSIS METHOD, AND FAULT DIAGNOSIS PROGRAM [P] . WO2021111726A1 . 2021-06-10

  机译： 故障诊断装置，故障诊断系统，故障诊断方法和故障诊断计划

• 4. FAULT SYMPTOM DIAGNOSIS DEVICE, FAULT SYMPTOM DIAGNOSIS SYSTEM, FAULT SYMPTOM DIAGNOSIS PROGRAM, AND FAULT SYMPTOM DIAGNOSIS METHOD [P] . 日本专利： JP2015036961A . 2015-02-23

  机译： 故障症状诊断装置，故障症状诊断系统，故障症状诊断程序和故障症状诊断方法

• 5. Vehicle remote fault diagnosis for the server, remote fault diagnosis method for a vehicle, remote fault diagnosis for the program, and, automotive remote fault diagnosis system of [P] . 日本专利： JP4816992B2 . 2011-11-16

  机译： 用于服务器的车辆远程故障诊断，用于车辆的远程故障诊断方法，用于程序的远程故障诊断，以及车辆的远程故障诊断系统

• 1. Fault Diagnosis Method Based on Fractal Theory and Its Application in Wind Power Systems [J] . 赵玲, 黄大荣, 宋军 兵工学报（英文版） . 2012,第003期
• 2. Novel robust fault diagnosis method for flight control systems [J] . Guo Yuying, Jiang Bin, Zhang Youmin, 系统工程与电子技术（英文版） . 2008,第005期
• 3. Case Based Reasoning (CBR) Methodology for Car Fault Diagnosis System (CFDS) Using Decision Tree and Jaccard Similarity Method [C] . Sumana De, Baisakhi Chakraborty International Conference for Convergence in Technology . 2018
• 4. Robust fault diagnosis in linear and nonlinear systems based on unknown input, and sliding mode functional observer methodologies. [D] . Xiong, Yi. 2001
• 5. Intelligent Computer Systems for Multiple Sclerosis Diagnosis: a Systematic Review of Reasoning Techniques and Methods [O] . Leila Akramian Arani, Azamossadat Hosseini, Farkhondeh Asadi, 2018
• 6. ABSTRACT Various body parts or organs can be analysed to identify the different diseases in the human body. Fingernail analysis is one of the ways to identify disease in the human body. Nails are the body part which are farthest from the heart and therefore receive oxygen at last. As a result the nails are the first who show the symptoms of a disease in the human body. Fingernails can be easily captured for diagnosis and there are no heavy equipment or no specific conditions required to use nail image for disease diagnosis, like in other tests and scanning processes. Human nails deliver beneficial information about complaints or any nutritive imbalances in the human body depending upon their shape, texture and colour. In human beings, numerous systemic and skin diseases can be easily analyzed through careful examination of nails of both the limbs. A lot of nail illnesses have been found to be primary signs of numerous underlying systemic illnesses. The colour, texture or shape changes in nails are signs of many diseases mainly affecting nails. Considering all these properties of nails a system is proposed that uses digital image processing (DIP) methods for identifying such changes in the human nail to get more precise results and predict numerous diseases effortlessly. With the emerging Internet of Things (IOT) concept the generated report is made available remotely, this will help users to reduce transportation efforts. As the system has to deal with large and private data, the security of data must be ensured. To keep the data confidential, the Blockchain concept which is one of the most emerging concepts in the field of data management is used. The paper contains the implementation of the digital image processing for feature extraction of nail images, usage of IOT (ThingSpeak cloud) for data storage and implementation of Blockchain to keep the system secured and theft free. KEY WORDS: Int ernet of thin gs (IOT), Image proc essin g, Thin gSpeak, RG B vavalues, Mean pi xel vavalues, Bloc kchain , Hash key. Disease Diagnostic System: Abnormalities in Human Nail [O] . Pranav S. Wazarkar 2020
• 7. Method for Diagnosing Time Dependent Faults Using Model-Based Reasoning Systems [R] . Goodrich, C. H. 1995

• 1. Fault Diagnosis Method Based on System-phenomenon-fault Tree [J] . CHEN Guorong ,YAN Ping ,YI Runzhong . 中国机械工程学报 . 2011,第003期
• 2. Fault Diagnosis Method Based on System-phenomenon-fault Tree [J] . CHEN Guorong ,YAN Ping ,YI Runzhong . 中国机械工程学报 . 2011,第003期
• 3. An Aircraft Navigation System Fault Diagnosis Method Based on Optimized Neural Network Algorithm [J] . Jean-dedieu Weyepe . 中国科技纵横 . 2014,第015期
• 4. 基于故障树的航电系统故障诊断方法设计与实现 [C] . 郭鹏 ,李清 ,张涛 . 2010中国制导、导航与控制学术会议 . 2010
• 5. 飞控系统故障诊断方法研究与实现 [A] . 曾聪 . 2019