[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$apiParty6fBuHLCPZ1LTYs42XHdVbjpSDOYYPYzyxeAGwSN5Tp8":3,"$apiPartyq-vUddZrsBLMfT8G_UxpFtws3fx2-sN5ONeicjBuP3Y":563,"$apiPartyq-vUddZrsBLMfT8G_UxpFtws3fx2-sN5ONeicjBuP3Y$H93EERW16b":563},{"product_data":4,"scene_data":21,"task_data":407,"modality_data":441,"domain_data":478},[5,9,12,15,18],{"name":6,"value":7,"add_value":8,"describe":8},"Rivo","1","",{"name":10,"value":11,"add_value":8,"describe":8},"Cubo","2",{"name":13,"value":14,"add_value":8,"describe":8},"Moye","3",{"name":16,"value":17,"add_value":8,"describe":8},"Juro","4",{"name":19,"value":20,"add_value":8,"describe":8},"Ordo","5",[22,73,135,197,232,267,302,337,372],{"name":23,"value":7,"add_value":24,"describe":25,"children":26},"Home & Indoor","sofa","AI enhances everyday home life. Our datasets cover real indoor scenes to support smart devices, robotics, and home intelligence.",[27,29,31,33,35,37,40,43,46,49,52,55,58,61,64,67,70],{"name":28,"value":7},"Living Room",{"name":30,"value":11},"Bedroom",{"name":32,"value":14},"Kitchen",{"name":34,"value":17},"Dining Area",{"name":36,"value":20},"Bathroom",{"name":38,"value":39},"Entrance \u002F Foyer","6",{"name":41,"value":42},"Corridor \u002F Hallway","7",{"name":44,"value":45},"Staircase","8",{"name":47,"value":48},"Home Office","9",{"name":50,"value":51},"Hobby \u002F Game Room","10",{"name":53,"value":54},"Worship Space","11",{"name":56,"value":57},"Garage","12",{"name":59,"value":60},"Utility \u002F Laundry Room","13",{"name":62,"value":63},"Pantry","14",{"name":65,"value":66},"Basement","15",{"name":68,"value":69},"Garden","16",{"name":71,"value":72},"Balcony","17",{"name":74,"value":11,"add_value":75,"describe":76,"children":77},"Office & Educational","workshop","AI is reshaping work and learning. Our datasets capture offices and classrooms to power automation and next-generation productivity tools.",[78,81,84,87,90,93,96,99,102,105,108,111,114,117,120,123,126,129,132],{"name":79,"value":80},"Open Office","18",{"name":82,"value":83},"Private Office","19",{"name":85,"value":86},"Co-working Space","20",{"name":88,"value":89},"Reception \u002F Lobby","21",{"name":91,"value":92},"Conference Room","22",{"name":94,"value":95},"Huddle Room \u002F Booth","23",{"name":97,"value":98},"Lecture Hall \u002F Auditorium","24",{"name":100,"value":101},"Classroom","25",{"name":103,"value":104},"Science Laboratory","26",{"name":106,"value":107},"Library","27",{"name":109,"value":110},"Design Studio","28",{"name":112,"value":113},"Pantry \u002F Breakroom","29",{"name":115,"value":116},"Cafeteria \u002F Canteen","30",{"name":118,"value":119},"Restroom (Commercial)","31",{"name":121,"value":122},"Gymnasium \u002F Sports Hall","32",{"name":124,"value":125},"Server Room","33",{"name":127,"value":128},"Mailroom \u002F Logistics","34",{"name":130,"value":131},"Janitorial Closet","35",{"name":133,"value":134},"Corridor \u002F Elevators","36",{"name":136,"value":14,"add_value":137,"describe":138,"children":139},"Healthcare & Medical","love-and-help","AI is advancing modern healthcare. Our datasets include clinics and hospitals to enable clinical insights and medical automation.",[140,143,146,149,152,155,158,161,164,167,170,173,176,179,182,185,188,191,194],{"name":141,"value":142},"Operating Theatre \u002F OR","37",{"name":144,"value":145},"Consultation Room","38",{"name":147,"value":148},"Treatment Room","39",{"name":150,"value":151},"Dental Clinic","40",{"name":153,"value":154},"Inpatient Ward","41",{"name":156,"value":157},"Nurse Station","42",{"name":159,"value":160},"ICU","43",{"name":162,"value":163},"NICU (Neonatal ICU)","44",{"name":165,"value":166},"Emergency Room (ER)","45",{"name":168,"value":169},"Hospital Corridor","46",{"name":171,"value":172},"Waiting Area","47",{"name":174,"value":175},"CT\u002FMRI","48",{"name":177,"value":178},"Medical Laboratory","49",{"name":180,"value":181},"Phlebotomy Room","50",{"name":183,"value":184},"Rehabilitation Gym","51",{"name":186,"value":187},"Assisted Living Room","52",{"name":189,"value":190},"Pharmacy","53",{"name":192,"value":193},"Sterile Processing Dept","54",{"name":195,"value":196},"Medical Storage","55",{"name":198,"value":17,"add_value":199,"describe":200,"children":201},"Business & Public Service","business","AI is elevating commercial and public services. Our datasets span retail, dining, and service centers to improve intelligent operations.",[202,205,208,211,214,217,220,223,226,229],{"name":203,"value":204},"Shopping Mall Atrium","86",{"name":206,"value":207},"Supermarket Shelf","87",{"name":209,"value":210},"Self-Checkout Counter","88",{"name":212,"value":213},"Restaurant Dining Hall","89",{"name":215,"value":216},"Commercial Kitchen","90",{"name":218,"value":219},"Hotel Lobby","91",{"name":221,"value":222},"Subway Platform","92",{"name":224,"value":225},"Security Checkpoint","93",{"name":227,"value":228},"Underground Parking","94",{"name":230,"value":231},"Bank Teller Zone","95",{"name":233,"value":20,"add_value":234,"describe":235,"children":236},"Industrial & Manufacturing","robot-arm","AI is modernizing industry. Our datasets capture factories and logistics spaces to support robotics and intelligent manufacturing.",[237,240,243,246,249,252,255,258,261,264],{"name":238,"value":239},"Final Assembly Line","96",{"name":241,"value":242},"Quality Control Station","97",{"name":244,"value":245},"Robotic Welding Cell","98",{"name":247,"value":248},"CNC Machining Center","99",{"name":250,"value":251},"Cleanroom","100",{"name":253,"value":254},"Automated Warehouse","101",{"name":256,"value":257},"Loading Dock","102",{"name":259,"value":260},"Sorting Center","103",{"name":262,"value":263},"Chemical Plant","104",{"name":265,"value":266},"Power Substation","105",{"name":268,"value":39,"add_value":269,"describe":270,"children":271},"Transportation & Driving","car","AI is revolutionizing mobility. Our datasets capture road networks, vehicle dynamics and traffic scenarios to support autonomous driving and intelligent transportation systems.",[272,275,278,281,284,287,290,293,296,299],{"name":273,"value":274},"Urban Intersection","56",{"name":276,"value":277},"Highway \u002F Expressway","57",{"name":279,"value":280},"Tunnel","58",{"name":282,"value":283},"Roundabout","59",{"name":285,"value":286},"School \u002F Hospital Zone","60",{"name":288,"value":289},"Toll Station","61",{"name":291,"value":292},"Construction Zone","62",{"name":294,"value":295},"Parking Garage","63",{"name":297,"value":298},"Driver Cabin","64",{"name":300,"value":301},"Adverse Weather","65",{"name":303,"value":42,"add_value":304,"describe":305,"children":306},"Outdoor & Construction","tent-tree","AI is optimizing outdoor operations. Our datasets capture construction sites, open-air work zones and outdoor infrastructure to support smart construction and autonomous outdoor machinery.",[307,310,313,316,319,322,325,328,331,334],{"name":308,"value":309},"Excavation Site","66",{"name":311,"value":312},"Scaffolding Area","67",{"name":314,"value":315},"Material Storage Yard","68",{"name":317,"value":318},"Site Entrance","69",{"name":320,"value":321},"Roadwork Zone","70",{"name":323,"value":324},"Bridge Infrastructure","71",{"name":326,"value":327},"Transmission Line","72",{"name":329,"value":330},"Open-pit Mine","73",{"name":332,"value":333},"Tunneling Site","74",{"name":335,"value":336},"Post-Disaster Rubble","75",{"name":338,"value":45,"add_value":339,"describe":340,"children":341},"Nature, Aerial & Aquatic","global-loop","AI is exploring the natural world. Our datasets capture terrestrial landscapes, aerial vistas and aquatic ecosystems to support environmental monitoring and autonomous exploration systems.",[342,345,348,351,354,357,360,363,366,369],{"name":343,"value":344},"Deep Forest","76",{"name":346,"value":347},"Farmland \u002F Crops","77",{"name":349,"value":350},"River \u002F Lake","78",{"name":352,"value":353},"Open Ocean","79",{"name":355,"value":356},"Underwater Coral Reef","80",{"name":358,"value":359},"Fish Farm","81",{"name":361,"value":362},"Mountain Terrain","82",{"name":364,"value":365},"Urban Low Altitude","83",{"name":367,"value":368},"Fire Scene","84",{"name":370,"value":371},"Desert \u002F Gobi","85",{"name":373,"value":48,"add_value":374,"describe":375,"children":376},"Virtul & Digital","siri","AI is reshaping the virtual realm. Our datasets capture digital twins, virtual environments and simulated spaces to support metaverse development and intelligent digital interaction.",[377,380,383,386,389,392,395,398,401,404],{"name":378,"value":379},"VR Social Space","106",{"name":381,"value":382},"Synthetic Driving Sim","107",{"name":384,"value":385},"Digital Twin City","108",{"name":387,"value":388},"FPS \u002F MOBA Game","109",{"name":390,"value":391},"Robotics Gym","110",{"name":393,"value":394},"AR Navigation","111",{"name":396,"value":397},"Virtual Showroom","112",{"name":399,"value":400},"Code \u002F IDE Interface","113",{"name":402,"value":403},"App GUI Screen","114",{"name":405,"value":406},"Synthetic 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座舱，通过语音、手势、面部识别等实现人机交互，如语音控制导航、音乐播放。\n驾驶员状态监测：识别疲劳、分心、抽烟、打电话等行为，通过大模型判断危险等级，触发相应提醒或干预机制。\n智能驾驶：AI 用于环境感知、路径规划与决策控制，使车辆能识别道路、行人、障碍物等，实现自适应巡航、自动泊车、车道保持等功能，提升驾驶安全性与便利性。",{"id":492,"value":492,"name":136,"intro":493,"add_value":137,"describe":493},4,"医学影像诊断：分析 CT、MRI 等影像，辅助医生检测疾病、识别病灶，如 AI 系统可快速发现肺部结节。\n医患对话助手：通过自然语言处理理解患者问题，提供初步健康建议或就诊指导，缓解医生接诊压力。\n智能健康管理：根据用户健康数据，提供个性化健康建议、疾病预警，如智能手环结合 AI 分析用户运动、睡眠、心率等数据。",{"id":495,"value":495,"name":496,"intro":497,"add_value":498,"describe":497},6,"Smart Devices","多模态交互：支持语音、手势、眼神等多种交互方式，如 AI 眼镜可通过语音指令实现翻译、搜索功能。\n智能感知与处理：使设备能感知环境、理解用户需求，如智能音箱根据环境噪音自动调节音量。\n个性化服务：根据用户使用习惯和偏好，提供个性化功能与服务，如智能手表为用户定制运动健身计划。","microscope",{"id":500,"value":500,"name":501,"intro":502,"add_value":503,"describe":502},8,"Law & Government","智能法律问答：面向公众或企业用户，提供合规、劳动法、婚姻继承、知识产权等常见法律问题的智能解答。\n合同审查与风险识别：利用大模型分析合同内容，识别潜在风险条款、漏洞或不合理约定，提升合同审核质量。\n法律知识图谱构建：自动梳理法规、案例、条文之间的引用关系，构建语义化知识图谱，支持智能分析和推理。","hammer",{"id":505,"value":505,"name":506,"intro":507,"add_value":508,"describe":507},7,"Education & Training","个性化学习：根据学生学习进度、能力和知识掌握情况，推送个性化学习内容与练习，如智能辅导系统为学生制定专属学习计划。\n智能教学辅助：AI 助教协助教师进行作业批改、答疑解惑，还可分析教学数据，为教师提供教学反馈，优化教学方法。\n虚拟学习环境：利用 AI 创建虚拟实验、历史场景等，让学生沉浸式学习，如在虚拟化学实验室中进行实验操作。","degree-hat",{"id":510,"value":510,"name":511,"intro":512,"add_value":513,"describe":512},5,"Agriculture & Food","作物病虫害识别与防治：通过图像识别分析农作物叶片、果实等症状，识别病虫害类型，给出防治建议，减少产量损失。\n农产品质量检测：利用图像和传感器数据，识别果蔬等农产品的成熟度、外观缺陷，进行自动分级，提高市场竞争力。\n农情监测与预测：利用卫星遥感、气象和传感器数据，结合大模型预测作物长势、干旱、洪涝等农情变化。","ph-farm",{"id":515,"value":515,"name":516,"intro":517,"add_value":518,"describe":517},9,"Retail & E-commerce","智能客服：通过自然语言对话理解用户需求，提供产品推荐、订单查询、退换货支持等服务，提升客户满意度。\n个性化营销推荐：基于用户浏览、购买、偏好等行为数据，生成个性化推荐内容与优惠策略，提高转化率和客单价。\n商品内容生成：自动撰写商品标题、卖点描述、使用说明等内容，适用于海量SKU的内容生产与多语言发布。","buy",{"id":520,"value":520,"name":521,"intro":522,"add_value":523,"describe":8},10,"Security & Protection",null,"safe-shield-line",{"id":525,"value":525,"name":526,"intro":522,"add_value":527,"describe":8},11,"Environment & Climate","weather",{"id":529,"value":529,"name":530,"intro":522,"add_value":531,"describe":8},12,"Energy & Resource","energy-leaf",{"id":533,"value":533,"name":534,"intro":522,"add_value":535,"describe":8},13,"Express & Logistics","speed-outline",{"id":537,"value":537,"name":538,"intro":522,"add_value":539,"describe":8},15,"Sports","baseball-outline",{"id":541,"value":541,"name":542,"intro":522,"add_value":543,"describe":8},16,"General Data","daily-booth",{"id":545,"value":545,"name":546,"intro":522,"add_value":547,"describe":8},17,"Content & Media","media",{"id":549,"value":549,"name":550,"intro":522,"add_value":551,"describe":8},18,"Construction","construction",{"id":553,"value":553,"name":554,"intro":522,"add_value":555,"describe":8},19,"IT & Telecom","tech",{"id":557,"value":557,"name":558,"intro":522,"add_value":498,"describe":8},20,"Science & Research",{"id":560,"value":560,"name":561,"intro":522,"add_value":562,"describe":8},21,"Language & Culture","lang",{"id":564,"unique_code":565,"title":566,"icon":8,"intro":567,"cate":483,"detail":568,"create_time":569,"update_time":570,"price":571,"view_count":572,"download_count":573,"unit":573,"amount":574,"is_create_order":573,"enterprise_id":488,"seo_keywords":575,"seo_description":576,"data_format":577,"file_size":578,"apply_scene":579,"training_task":580,"version":581,"dataset_type_id":492,"dataset_scene_id":553,"sample_file":522,"banner":8,"unit_name":8,"cate_name":449,"icon_url":8,"banner_url":8,"sample_file_url":8,"data_dict":582,"qa_list":623,"sample_metadatas":640,"text_sample_content":676,"enterprise_name":677,"enterprise_logo":678,"data_distribution":679},1075,"c441f5f081ac9299f748a4be4708dbda","XGS-PON Alarm Correlation and Root-Cause Inference Q&A Dataset","Train models to connect chronological OLT, PON port, and ONU alarms and infer likely causes of XGS-PON faults.","\u003Cp>This question-and-answer dataset covers alarms and status changes across OLTs, PON ports, and ONUs in XGS-PON access networks, with events presented in chronological order. Its examples trace alarm relationships, identify a likely initiating fault and downstream effects, and distinguish root causes from accompanying symptoms. It is designed for reasoning SFT, fault-causality analysis, and XGS-PON operations workflows.\u003C\u002Fp>","2026-10-09 18:54:03","2026-10-19 17:19:10","0.00",31,0,5000,"XGS-PON alarm dataset, alarm correlation, root cause inference, PON fault diagnosis, OLT alarms, ONU status analysis, reasoning SFT data, network operations","XGS-PON alarm correlation and root-cause inference Q&A covering OLT, PON port, and ONU status changes for reasoning SFT and fault analysis.","JSON","0.4GB","optical network fault diagnosis, telecom alarm correlation, network maintenance","alarm correlation, root cause analysis, fault diagnosis","V1.0",[583,588,593,598,603,608,613,618],{"id":573,"name":584,"field":585,"intro":586,"type":587},"File Name","file_name","File name","string",{"id":589,"name":590,"field":591,"intro":592,"type":587},7824,"Case Input","case_input","Chronological account of alarms and status changes across the OLT, PON port, and ONU, together with the question to be answered.",{"id":594,"name":595,"field":596,"intro":597,"type":587},7825,"Likely Initiating Fault","root_cause","Identifies the most likely initiating fault and explains the assessment using the event sequence and device states in the case.",{"id":599,"name":600,"field":601,"intro":602,"type":587},7826,"Final Answer","final_answer","Complete user-facing conclusion combining the alarm relationships, likely root cause, downstream effects, and distinction between cause and symptoms.",{"id":604,"name":605,"field":606,"intro":607,"type":587},7827,"Downstream Effects","downstream_effects","Describes subsequent alarms and status changes that may result from the initiating fault, including effects on ports or ONUs.",{"id":609,"name":610,"field":611,"intro":612,"type":587},7828,"Reasoning Rationale","reasoning_rationale","Summarizes the key event sequence, status changes, and evidence used to correlate alarms, infer a root cause, and rule out alternative explanations.",{"id":614,"name":615,"field":616,"intro":617,"type":587},7829,"Related Alarm Chain","related_alarm_chain","Chronological account of related alarms and status changes, including their causal or correlational relationships.",{"id":619,"name":620,"field":621,"intro":622,"type":587},7830,"Root Cause and Symptom Distinction","symptom_classification","Distinguishes the most likely root cause from resulting or concurrent symptoms and explains the basis for the distinction.",[624,628,632,636],{"id":625,"question":626,"answer":627},5747,"What does the dataset contain?","Each case describes OLT, PON port, and ONU alarms and status changes in chronological order. The Q&A covers alarm relationships, likely initiating faults, downstream effects, and the distinction between root causes and accompanying symptoms.",{"id":629,"question":630,"answer":631},5748,"How is the data structured, and what tasks does it support?","The data is provided as question-and-answer text with fields for the case input, related alarm chain, likely initiating fault, downstream effects, reasoning rationale, and final answer. It supports reasoning SFT, alarm-chain analysis, fault diagnosis, and model reasoning evaluation.",{"id":633,"question":634,"answer":635},5749,"How can I access and use the dataset?","Check the current dataset listing or platform for available access methods, sample details, file specifications, and delivery options. You can parse the cases and inference outputs by field, then adapt them to your target model's training format.",{"id":637,"question":638,"answer":639},5750,"What are the licensing and usage terms?","The dataset listing and platform agreement define the applicable license, commercial-use permissions, and redistribution restrictions. Review those terms before using the data for training, evaluation, or internal operations analysis.",[641,654,665],{"id":642,"relate_table":643,"relate_id":644,"file_size":573,"file_name":8,"path":8,"duration":573,"cate":483,"file_format":8,"audio_rate":8,"audio_channel":522,"audio_bit_depth":522,"quality":8,"annotation":645,"cate_name":646,"case_input":647,"root_cause":648,"final_answer":649,"downstream_effects":650,"reasoning_rationale":651,"related_alarm_chain":652,"symptom_classification":653},14627,"union_cubo",152951171,"{\"case_input\": \"At 11:06:18, ONU 12 on OLT-3 PON 4\u002F2 sends a dying-gasp alarm. At 11:06:20, the OLT marks ONU 12 offline after it stops responding. The PON port has no LOS alarm, and the other 31 ONUs remain online. The last recorded optical levels for ONU 12, at 11:05:50, were within their previously stable range. What is the most likely initiating event, how are the later state changes related, and what can and cannot be concluded from this timeline?\", \"root_cause\": \"The most likely initiating event is a local power interruption or loss affecting ONU 12. Its dying-gasp alarm precedes the offline state, while the PON port and other ONUs remain operational. The timeline does not establish whether the cause is the ONU's power supply, its power feed, or another local condition.\", \"final_answer\": \"The most likely sequence is a local power-related interruption at ONU 12, signaled by its dying-gasp alarm, followed by loss of communication and the OLT marking it offline. The offline state is a consequence, not the initiating fault. The healthy PON port and other 31 online ONUs argue against a port-wide outage. The timeline supports a local power-related cause but does not reveal whether the ONU, its power supply, or its power feed is responsible.\", \"downstream_effects\": \"After the dying-gasp alarm, ONU 12 stops responding and is marked offline, interrupting service to that ONU. No port-wide LOS or outage affecting the other 31 ONUs is reported.\", \"reasoning_rationale\": \"The dying-gasp alarm is the first event in the sequence and is followed two seconds later by the OLT's offline state. The event is confined to one ONU, the port remains free of LOS, and the last recorded optical levels were stable. These facts favor a local power-related interruption, but they do not identify its exact physical cause.\", \"related_alarm_chain\": \"11:06:18: ONU 12 sends a dying-gasp alarm. 11:06:20: The OLT marks ONU 12 offline after it stops responding. The PON port has no LOS alarm, and the other 31 ONUs remain online. The dying-gasp event precedes the loss of communication and is limited to ONU 12.\", \"symptom_classification\": \"The likely initiating fault is the local power-related event indicated by ONU 12's dying-gasp alarm. The subsequent loss of communication and offline state are consequences. The absence of a port LOS and the continued operation of the other ONUs make a shared optical-path outage less consistent with the observed sequence.\"}","文本","At 11:06:18, ONU 12 on OLT-3 PON 4\u002F2 sends a dying-gasp alarm. At 11:06:20, the OLT marks ONU 12 offline after it stops responding. The PON port has no LOS alarm, and the other 31 ONUs remain online. The last recorded optical levels for ONU 12, at 11:05:50, were within their previously stable range. What is the most likely initiating event, how are the later state changes related, and what can and cannot be concluded from this timeline?","The most likely initiating event is a local power interruption or loss affecting ONU 12. Its dying-gasp alarm precedes the offline state, while the PON port and other ONUs remain operational. The timeline does not establish whether the cause is the ONU's power supply, its power feed, or another local condition.","The most likely sequence is a local power-related interruption at ONU 12, signaled by its dying-gasp alarm, followed by loss of communication and the OLT marking it offline. The offline state is a consequence, not the initiating fault. The healthy PON port and other 31 online ONUs argue against a port-wide outage. The timeline supports a local power-related cause but does not reveal whether the ONU, its power supply, or its power feed is responsible.","After the dying-gasp alarm, ONU 12 stops responding and is marked offline, interrupting service to that ONU. No port-wide LOS or outage affecting the other 31 ONUs is reported.","The dying-gasp alarm is the first event in the sequence and is followed two seconds later by the OLT's offline state. The event is confined to one ONU, the port remains free of LOS, and the last recorded optical levels were stable. These facts favor a local power-related interruption, but they do not identify its exact physical cause.","11:06:18: ONU 12 sends a dying-gasp alarm. 11:06:20: The OLT marks ONU 12 offline after it stops responding. The PON port has no LOS alarm, and the other 31 ONUs remain online. The dying-gasp event precedes the loss of communication and is limited to ONU 12.","The likely initiating fault is the local power-related event indicated by ONU 12's dying-gasp alarm. The subsequent loss of communication and offline state are consequences. The absence of a port LOS and the continued operation of the other ONUs make a shared optical-path outage less consistent with the observed sequence.",{"id":655,"relate_table":643,"relate_id":656,"file_size":573,"file_name":8,"path":8,"duration":573,"cate":483,"file_format":8,"audio_rate":8,"audio_channel":522,"audio_bit_depth":522,"quality":8,"annotation":657,"cate_name":646,"case_input":658,"root_cause":659,"final_answer":660,"downstream_effects":661,"reasoning_rationale":662,"related_alarm_chain":663,"symptom_classification":664},14626,674197054,"{\"case_input\": \"From 16:42 to 16:51, ONU 7 on OLT-2 PON 2\u002F1 shows a gradual decline in its upstream receive level at the OLT, followed by intermittent ranging failures and repeated ONU LOS indications. At 16:52, ONU 7 goes offline. The PON port has no LOS alarm, and the other 23 ONUs on the port remain online with stable reported receive levels. No dying-gasp event is recorded. What is the likely alarm chain and initiating fault, and how should the root cause be distinguished from the symptoms?\", \"root_cause\": \"The most likely initiating fault is an optical impairment on the branch serving ONU 7, such as a degraded drop path or connection. The evidence supports a fault localized to this ONU's branch, but does not establish the exact component or physical cause.\", \"final_answer\": \"The likely chain is a gradual decline in ONU 7's upstream receive level, followed by intermittent ranging failures and LOS indications, and finally the ONU going offline. The most likely initiating fault is an optical impairment on ONU 7's branch; the exact component cannot be determined from these events. The ranging failures, LOS indications, and offline state are symptoms. Because the PON port and the other 23 ONUs remain stable, the evidence points to an ONU-specific issue rather than a port-wide outage.\", \"downstream_effects\": \"The declining upstream receive level is followed by intermittent ranging failures and LOS indications, then ONU 7 goes offline. Service to that ONU is interrupted. The other ONUs on PON 2\u002F1 remain online, and no port-wide outage is indicated.\", \"reasoning_rationale\": \"The level decline precedes the ranging failures and offline transition, and all reported instability is confined to ONU 7. The port and other ONUs remain stable, making a shared PON failure less consistent with the timeline. No dying-gasp event is recorded, and the evidence does not identify a particular connector, cable, or ONU component.\", \"related_alarm_chain\": \"16:42–16:51: The OLT reports a gradual decline in the upstream receive level for ONU 7. During the same interval, ONU 7 has intermittent ranging failures and repeated LOS indications. 16:52: ONU 7 goes offline. The PON port remains free of LOS, and the other ONUs remain online. The declining level is the earliest reported change and is associated with the later instability of this single ONU.\", \"symptom_classification\": \"The likely root cause is the ONU-specific optical-path impairment suggested by the declining receive level. The ranging failures, repeated LOS indications, and eventual offline state are symptoms of the resulting unstable link. The absence of a port LOS and the continued operation of the other ONUs argue against a PON-wide failure.\"}","From 16:42 to 16:51, ONU 7 on OLT-2 PON 2\u002F1 shows a gradual decline in its upstream receive level at the OLT, followed by intermittent ranging failures and repeated ONU LOS indications. At 16:52, ONU 7 goes offline. The PON port has no LOS alarm, and the other 23 ONUs on the port remain online with stable reported receive levels. No dying-gasp event is recorded. What is the likely alarm chain and initiating fault, and how should the root cause be distinguished from the symptoms?","The most likely initiating fault is an optical impairment on the branch serving ONU 7, such as a degraded drop path or connection. The evidence supports a fault localized to this ONU's branch, but does not establish the exact component or physical cause.","The likely chain is a gradual decline in ONU 7's upstream receive level, followed by intermittent ranging failures and LOS indications, and finally the ONU going offline. The most likely initiating fault is an optical impairment on ONU 7's branch; the exact component cannot be determined from these events. The ranging failures, LOS indications, and offline state are symptoms. Because the PON port and the other 23 ONUs remain stable, the evidence points to an ONU-specific issue rather than a port-wide outage.","The declining upstream receive level is followed by intermittent ranging failures and LOS indications, then ONU 7 goes offline. Service to that ONU is interrupted. The other ONUs on PON 2\u002F1 remain online, and no port-wide outage is indicated.","The level decline precedes the ranging failures and offline transition, and all reported instability is confined to ONU 7. The port and other ONUs remain stable, making a shared PON failure less consistent with the timeline. No dying-gasp event is recorded, and the evidence does not identify a particular connector, cable, or ONU component.","16:42–16:51: The OLT reports a gradual decline in the upstream receive level for ONU 7. During the same interval, ONU 7 has intermittent ranging failures and repeated LOS indications. 16:52: ONU 7 goes offline. The PON port remains free of LOS, and the other ONUs remain online. The declining level is the earliest reported change and is associated with the later instability of this single ONU.","The likely root cause is the ONU-specific optical-path impairment suggested by the declining receive level. The ranging failures, repeated LOS indications, and eventual offline state are symptoms of the resulting unstable link. The absence of a port LOS and the continued operation of the other ONUs argue against a PON-wide failure.",{"id":666,"relate_table":643,"relate_id":667,"file_size":573,"file_name":8,"path":8,"duration":573,"cate":483,"file_format":8,"audio_rate":8,"audio_channel":522,"audio_bit_depth":522,"quality":8,"annotation":668,"cate_name":646,"case_input":669,"root_cause":670,"final_answer":671,"downstream_effects":672,"reasoning_rationale":673,"related_alarm_chain":674,"symptom_classification":675},14625,2116761672,"{\"case_input\": \"At 09:14:02, OLT-1 on PON 1\u002F3 reports a sudden drop in upstream receive optical level, followed by an upstream LOS alarm. Between 09:14:03 and 09:14:07, all 18 ONUs previously online on PON 1\u002F3 transition to ranging timeout or offline. No individual ONU alarm precedes the port alarm. ONUs on adjacent PON ports remain online. What alarm sequence is most likely related, what is the probable initiating fault, and which events are symptoms rather than the root cause?\", \"root_cause\": \"The most likely initiating fault is a loss or severe impairment in the shared optical path serving PON 1\u002F3. The simultaneous port-level receive loss occurs before all 18 ONU ranging timeouts, while adjacent PON ports remain online. The available events do not identify the precise location or component.\", \"final_answer\": \"The alarms form a common sequence: upstream receive optical level drops on PON 1\u002F3, the port raises LOS, and its 18 ONUs subsequently fail ranging and go offline. The most likely initiating fault is a severe impairment or loss on the shared optical path serving that PON. The ONU timeouts and offline states are consequences, not separate root causes. Adjacent ports are unaffected, and the available evidence does not pinpoint the damaged component or location.\", \"downstream_effects\": \"The OLT can no longer reliably receive upstream transmissions on PON 1\u002F3. The ONUs then fail to complete ranging and transition offline, interrupting service for the ONUs on that port. No impact on the adjacent PON ports is indicated.\", \"reasoning_rationale\": \"The port-level receive-level drop and LOS are the earliest reported events. All affected ONUs are on the same PON and transition afterward, whereas ONUs on adjacent ports remain online. This timing and shared scope favor a common-path impairment over independent ONU failures; the timeline alone cannot locate the physical fault.\", \"related_alarm_chain\": \"09:14:02: The upstream receive optical level at PON 1\u002F3 drops suddenly. 09:14:02: The port raises an upstream LOS alarm. 09:14:03–09:14:07: The ONUs on that port successively time out during ranging and go offline. The port-level optical loss precedes the ONU state changes and affects the full PON group, linking the events to a shared path or port-level impairment.\", \"symptom_classification\": \"The initiating fault is the shared-path or port-level optical impairment indicated by the sudden receive-level drop and upstream LOS. The subsequent ONU ranging timeouts and offline states are downstream symptoms. The evidence does not support assigning the fault to a specific fiber segment, splitter, or connector.\"}","At 09:14:02, OLT-1 on PON 1\u002F3 reports a sudden drop in upstream receive optical level, followed by an upstream LOS alarm. Between 09:14:03 and 09:14:07, all 18 ONUs previously online on PON 1\u002F3 transition to ranging timeout or offline. No individual ONU alarm precedes the port alarm. ONUs on adjacent PON ports remain online. What alarm sequence is most likely related, what is the probable initiating fault, and which events are symptoms rather than the root cause?","The most likely initiating fault is a loss or severe impairment in the shared optical path serving PON 1\u002F3. The simultaneous port-level receive loss occurs before all 18 ONU ranging timeouts, while adjacent PON ports remain online. The available events do not identify the precise location or component.","The alarms form a common sequence: upstream receive optical level drops on PON 1\u002F3, the port raises LOS, and its 18 ONUs subsequently fail ranging and go offline. The most likely initiating fault is a severe impairment or loss on the shared optical path serving that PON. The ONU timeouts and offline states are consequences, not separate root causes. Adjacent ports are unaffected, and the available evidence does not pinpoint the damaged component or location.","The OLT can no longer reliably receive upstream transmissions on PON 1\u002F3. The ONUs then fail to complete ranging and transition offline, interrupting service for the ONUs on that port. No impact on the adjacent PON ports is indicated.","The port-level receive-level drop and LOS are the earliest reported events. All affected ONUs are on the same PON and transition afterward, whereas ONUs on adjacent ports remain online. This timing and shared scope favor a common-path impairment over independent ONU failures; the timeline alone cannot locate the physical fault.","09:14:02: The upstream receive optical level at PON 1\u002F3 drops suddenly. 09:14:02: The port raises an upstream LOS alarm. 09:14:03–09:14:07: The ONUs on that port successively time out during ranging and go offline. The port-level optical loss precedes the ONU state changes and affects the full PON group, linking the events to a shared path or port-level impairment.","The initiating fault is the shared-path or port-level optical impairment indicated by the sudden receive-level drop and upstream LOS. The subsequent ONU ranging timeouts and offline states are downstream symptoms. The evidence does not support assigning the fault to a specific fiber segment, splitter, or connector.","{\"case_input\":\"At 11:06:18, ONU 12 on OLT-3 PON 4\\\u002F2 sends a dying-gasp alarm. At 11:06:20, the OLT marks ONU 12 offline after it stops responding. The PON port has no LOS alarm, and the other 31 ONUs remain online. The last recorded optical levels for ONU 12, at 11:05:50, were within their previously stable range. What is the most likely initiating event, how are the later state changes related, and what can and cannot be concluded from this timeline?\",\"root_cause\":\"The most likely initiating event is a local power interruption or loss affecting ONU 12. Its dying-gasp alarm precedes the offline state, while the PON port and other ONUs remain operational. The timeline does not establish whether the cause is the ONU's power supply, its power feed, or another local condition.\",\"final_answer\":\"The most likely sequence is a local power-related interruption at ONU 12, signaled by its dying-gasp alarm, followed by loss of communication and the OLT marking it offline. The offline state is a consequence, not the initiating fault. The healthy PON port and other 31 online ONUs argue against a port-wide outage. The timeline supports a local power-related cause but does not reveal whether the ONU, its power supply, or its power feed is responsible.\",\"downstream_effects\":\"After the dying-gasp alarm, ONU 12 stops responding and is marked offline, interrupting service to that ONU. No port-wide LOS or outage affecting the other 31 ONUs is reported.\",\"reasoning_rationale\":\"The dying-gasp alarm is the first event in the sequence and is followed two seconds later by the OLT's offline state. The event is confined to one ONU, the port remains free of LOS, and the last recorded optical levels were stable. These facts favor a local power-related interruption, but they do not identify its exact physical cause.\",\"related_alarm_chain\":\"11:06:18: ONU 12 sends a dying-gasp alarm. 11:06:20: The OLT marks ONU 12 offline after it stops responding. The PON port has no LOS alarm, and the other 31 ONUs remain online. The dying-gasp event precedes the loss of communication and is limited to ONU 12.\",\"symptom_classification\":\"The likely initiating fault is the local power-related event indicated by ONU 12's dying-gasp alarm. The subsequent loss of communication and offline state are consequences. The absence of a port LOS and the continued operation of the other ONUs make a shared optical-path outage less consistent with the observed sequence.\"}","MOBIUSI INC","https:\u002F\u002Fstatic.mobiusi.com\u002Fmobiwusi\u002F20250829\u002F7bf4ac62b4533e2b809998a6f1c5491e.png?Expires=1792463130&OSSAccessKeyId=LTAI5tH8MQqhgeiAtrzCHrxM&Signature=v6Tr8jBrdm4s5wU1SnnyGsYg%2Bhw%3D&x-oss-process=image%2Fresize%2Cm_fill%2Cw_35%2Ch_35",[680,686],{"type":681,"title":682,"count_data":683},"bar","Length distribution",[684],{"name":685,"value":483},"1k lower",{"type":687,"title":688,"count_data":689},"pie","Language distribution",[690],{"name":691,"value":483},"English"]