type: multiagent

text: For asset hp_1, using sensor data from the last 50 days leading up to and including 2023-01-28, can we detect that the valve condition is approaching total failure? What trends in the sensor data over this 50-day window indicate the degradation?

hint: IoT Agent collects multi-sensor data over the fixed window; TSFM Agent examines temporal feature shifts; FMSR Agent validates the trajectory to fault state; WO Agent plans action based on bounded trend analysis.

category: Fixed-Window Condition Detection (50 days)

characteristic_form: Detection should integrate pressure, flow, vibration, and temperature trends across dates 2022-12-10 to 2023-01-28. TSFM Agent flags sustained deviations; FMSR Agent matches the fixed window anomalies to valve degradation profiles; WO Agent uses detection output for timely maintenance scheduling.

failure_event: Valve close to total failure at date 2023-01-28

asset_component: valve

labels: valve, fixed-window, pre-failure

relevant_sensors: PS1, PS2, PS3, PS4, PS5, PS6, FS1, FS2, VS1


text: For asset hp_1, using sensor data from the last 50 days leading up to and including 2024-03-13, can we detect the valve nearing total failure? Which sensor patterns over this window support this diagnosis?

hint: IoT aggregates valve-related sensor streams over the 50-day window; TSFM identifies evolving valve anomalies; FMSR confirms failure progression; WO recommends timely maintenance.

characteristic_form: Detection is based on multi-day feature trends including pressure sensors PS1–PS6, flow sensors FS1/FS2, and vibration VS1. The agents jointly identify and confirm progressive valve degeneration in dates 2024-01-24 to 2024-03-13.

failure_event: Valve close to total failure at date 2024-03-13


text: For asset hp_1, analyzing the last 50 days leading up to and including 2026-05-14, can the sensor data reveal a worsening valve condition approaching failure? What temporal indicators support this?

hint: Multi-sensor sequence analysis performed over 2026-03-26 to 2026-05-14; TSFM and FMSR Agents detect and validate valve failure signatures; WO Agent plans repair.

characteristic_form: Consistent anomalies in valve-switching-related sensor signals detected over the last 50 days before 2026-05-14 enable agents to detect failure onset and prioritize maintenance.

failure_event: Valve close to total failure at date 2026-05-14


text: For asset hp_1, can severe internal pump leakage onset at 2023-01-27 be detected by analyzing sensor data from the last 100 days? Which sensor trends and patterns within this window indicate leakage development?

hint: IoT and TSFM Agents analyze pressure, flow, vibration, and motor power sensor data from days 2022-10-20 to 2023-01-27; FMSR Agent diagnoses leakage severity; WO Agent recommends intervention based on trend detection.

category: Fixed-Window Condition Detection (100 days)

characteristic_form: The agents jointly detect escalating pump leakage signatures manifested as temporal deviations in sensors PS1–PS6, FS1/FS2, EPS1, and VS1 across the 100-day window before date 2023-01-27, enabling timely maintenance action recommendations.

failure_event: Severe pump leakage onset at date 2023-01-27

asset_component: pump

labels: pump, fixed-window, pre-failure

relevant_sensors: PS1, PS2, PS3, PS4, PS5, PS6, FS1, FS2, EPS1, VS1


text: For asset hp_1, using sensor data from the last 100 days leading up to and including 2023-06-09, can severe internal pump leakage be detected? What sensor evidence within this window is most critical for diagnosis?

hint: Pressure, flow, motor power, vibration, and temperature sensors are analyzed temporally over dates 2023-03-02 to 2023-06-09; Agents collaborate for fault classification and maintenance planning.

characteristic_form: Multi-sensor signatures of pump leakage are tracked and interpreted from a 100-days historical window ending at 2023-06-09, supporting confident fault detection and prioritization of corrective action.

failure_event: Severe pump leakage onset at day 2023-06-09


text: For asset hp_1, can severe internal pump leakage on 2024-01-31 be detected using sensor data from the preceding 100 days? Which sensor trends provide key clues within this timeframe?

hint: Agents monitor sensor streams representing pump performance and anomalies over the window from 2023-10-24 to 2024-01-31; FMSR and WO Agents localize fault and maintenance needs.

category: Fixed-Window Condition Detection (100-day window)

characteristic_form: Joint analysis of sensor deviations over the 100-day period before 2024-01-31 allows agents to support reliable detection of severe leakage and guide corresponding repairs.

failure_event: Severe pump leakage onset on 2024-01-31


text: For asset hp_1, using the last 100 days up to and including 2027-01-30, can sensor data reveal the onset of severe internal pump leakage? Which sensor anomalies support this?

hint: Integrated multi-sensor data monitoring from 2026-10-22 to 2027-01-30 assists TSFM and FMSR Agents in detecting and classifying severe leakage; WO Agent coordinates timely maintenance intervention.

characteristic_form: Agents utilize densely sampled trends over the 100-day window to detect severe leakage onset reliably and recommend appropriate repair schedules.

failure_event: Severe pump leakage onset on 2027-01-30


text: For asset hp_1, is the hydraulic accumulator’s pressure near total failure detectable in sensor data from the prior 50 days leading up to and including 2024-01-22? What temporal sensor features indicate critical pressure decline?

hint: Pressure sensors monitored over the window from 2023-12-04 to 2024-01-22 provide key data; TSFM detects critical trends; FMSR assesses failure risk; WO advises urgent maintenance.

category: Fixed-Window Condition Detection (50-day window)

characteristic_form: Agents detect significant pressure decrease alongside corroborative anomalies in temperature and flow across 50 days, confirming the accumulator’s critical condition and enabling timely maintenance decision-making.

failure_event: Accumulator close to failure on 2024-01-22

asset_component: accumulator

labels: accumulator, fixed-window, pre-failure

relevant_sensors: PS1, PS2, PS3, PS4, PS5, PS6, TS1, TS2, TS3, TS4, FS1, FS2


text: For asset hp_1, using sensor data from the 50 days preceding and including 2026-03-23, can we detect critically low hydraulic accumulator pressure? Which sensor trends support this detection?

hint: Multi-sensor temporal analysis including pressure, flow, and temperature over the window from 2026-02-02 to 2026-03-23 supports multi-agent failure confirmation.

characteristic_form: Degradation patterns in pressure sensors and supporting data confirm near failure of the accumulator, prompting maintenance planning.

failure_event: Accumulator close to failure on 2026-03-23


text: For asset hp_1, can sensor data covering the 50 days before and including 2028-03-11 confirm that the hydraulic accumulator is close to total failure? What temporal sensor signals are most indicative?

hint: Agents analyze sustained pressure drops and supporting temperature and flow trends over the window from 2028-01-21 to 2028-03-11; WO Agent plans detection-based intervention.

characteristic_form: Temporal sensor trends over the fixed window clearly reflect critical accumulator degradation, enabling agents to confirm failure mode and recommend immediate maintenance.

failure_event: Accumulator close to failure on 2028-03-11


text: For asset hp_1, using sensor data spanning the days leading up to and including 2023-01-28, can we detect that the valve condition is approaching total failure? What evolving sensor trends support this diagnosis?

hint: IoT Agent aggregates multi-days sensor data; TSFM Agent analyzes valve switching anomalies over time; FMSR Agent confirms failure progression; WO Agent maps findings to maintenance scheduling.

category: Open-Window Condition Detection

characteristic_form: Agents integrate all relevant sensor data prior to and including 2023-01-28 to detect progressive valve degradation, emphasizing temporal patterns and cumulative anomalies supporting fault detection.

failure_event: Valve close to total failure around 2023-01-28

labels: valve, open-window, pre-failure


text: For asset hp_1, can severe internal pump leakage at 2023-01-27 be detected by reviewing historical sensor data over the days leading up to this event? Which sensor anomalies are key?

hint: Multi-agent analysis aggregates pump-related sensor streams over an unbounded prior window to identify leakage onset and severity.

characteristic_form: Detection capitalizes on extended temporal context leveraging all available days before 2023-01-27, focusing on identifying trends in flow, pressure, motor power, and vibration signaling leakage onset.

failure_event: Severe pump leakage onset around 2023-01-27

labels: pump, open-window, pre-failure


text: Consider asset hp_1. Is valve near-total failure detectable in sensor data across the days leading up to and including 2024-03-13? How do sensor patterns evolve during this period?

hint: Agents review all available sensor data prior to and including 2024-03-13 to detect valve degradation and failure patterns.

characteristic_form: Temporal anomaly detection integrates long-term sensor trends, enabling confident detection of valve near-failure states informed by multiple data streams.

failure_event: Valve close to total failure around 2024-03-13


text: Consider asset hp_1. At 2024-01-22, can the hydraulic accumulator close to total failure be detected by analyzing sensor data spanning previous days? What sensor signatures confirm this state?

hint: All pressure and supporting sensor data from prior days are evaluated; agents detect critical pressure decline and associated anomalies.

characteristic_form: Agents leverage as much historical data as needed to observe pressure degradation, ensuring reliable identification of accumulator failure risk and informing urgent maintenance.

failure_event: Accumulator close to failure around 2024-01-22

labels: accumulator, open-window, pre-failure


text: Consider asset hp_1. Can sensor data over the days leading up to and including 2026-03-23 confirm that the hydraulic accumulator pressure has critically dropped? Which sensor patterns support this finding?

hint: Pressure, flow, and temperature data aggregated across preceding days; multi-agent collaboration interprets failure risk.

characteristic_form: Agents utilize flexible-length temporal context to corroborate failure mode activation and prioritize intervention.

failure_event: Accumulator close to failure around 2026-03-23


text: For asset hp_1, is the hydraulic accumulator close to total failure on 2028-03-11 detectable using sensor data from all available prior days? What sensor evidence indicates this condition?

hint: Agents analyze long-term pressure sensor trends plus supporting signals to detect critical hydraulic accumulator failure.

characteristic_form: A complete historical view enables agents to detect and confirm the degradation leading to failure and to recommend timely preventive maintenance.

failure_event: Accumulator close to failure around 2028-03-11


text: For asset hp_1, at 2023-06-09, can severe internal pump leakage be detected by considering sensor data over an extended window leading to this point? What sensor trends are most indicative?

hint: Agents combine multi-day sensor inputs for robust trend detection and classification of pump leakage severity.

characteristic_form: Use of long-term temporal context helps accurately identify leakage onset and severity from anomalies in pressure, flow, motor power, vibration, and temperature records.

failure_event: Severe pump leakage onset around 2023-06-09