MQTT Broker CONNECTING
Live Stream OFFLINE
Online Sensors 0 / 0
Selected Sensor --
Sensor State UNKNOWN
Data Quality NO DATA
Last Update --
Alarm Severity --
Sensor Health UNKNOWN
System Time --:--:--
Online 0
Stale 0
Offline 0
Selected State --
Velocity RMS --
Acceleration RMS --
Displacement RMS --
Sensor Frequency --
Alarm State --
Data Quality --
Sensor Fleet Normalized telemetry consumers
Asset ID Status Model Last Acquisition Overall RMS Severity
No monitored assets have published vibration telemetry.
Acceleration RMS — X
--
NORMAL
Acceleration RMS — Y
--
NORMAL
Acceleration RMS — Z
--
NORMAL
Sensor-calculated Frequency X
--
Source: --
Sensor-calculated Frequency Y
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Source: --
Sensor-calculated Frequency Z
--
Source: --
Sensor Condition
--
Trend: --
Sensor Condition Status Highest Severity Of All Metrics
Acceleration Status NORMAL --
Velocity Status NORMAL --
Displacement Status NORMAL --
Overall Asset Health NORMAL --
Selected Sensor Measurements Velocity RMS, acceleration diagnostics, confidence
Velocity RMS
--
Acceleration RMS
--
Peak Acceleration
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Peak-to-Peak
--
Frequency
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Temperature
--
Confidence
--
Alarm Reason
--
Sensor Profile Normalized telemetry
Sensor Type
--
Vendor
--
Model
--
Available Metrics
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Frequency Source
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Frequency Confidence
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Frequency Validation
--
Last Update
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Maintenance Notes Engineering Review
    Fault Indicators Stability Metrics — Last 30 acquisitions
    Signal
    Moving Avg
    Std Dev
    Peak / Avg
    Spike
    X Axis
    --
    --
    --
    --
    Y Axis
    --
    --
    --
    --
    Z Axis
    --
    --
    --
    --
    Overall
    --
    --
    --
    --
    Engineering Trend Analysis Acceleration: m/s² RMS | Velocity: mm/s RMS | Displacement: µm RMS

    Waiting for samples from selected sensor.

    Acceleration RMS Trend
    X Window s
    Scale
    Y-Range
    Y min max
    Velocity RMS Trend
    X Window s
    Scale
    Y-Range
    Y min max
    Displacement RMS Trend
    X Window s
    Normalized sensor-provided RMS | unit: µm
    Scale
    Y-Range
    Y min max
    Sensor-calculated Frequency Trend
    X Window s
    Normalized source and confidence metadata
    Scale
    Y-Range
    Y min max
    Selected Window Statistics For selected sensor and selected time window
    Latest overall RMS
    --
    Latest X
    --
    Latest Y
    --
    Latest Z
    --
    Mean overall RMS
    --
    Maximum overall RMS
    --
    Standard deviation
    --
    Peak-to-mean ratio
    --
    Sample count
    --
    Last acquisition time
    --
    Bearing Frequency Reference Reference calculator only
    Enter bearing geometry above to calculate BPFO, BPFI, BSF, and FTF reference frequencies.
    Threshold Configuration No sensor selected
    Sensor ID--
    Sensor Type--
    Location--
    State--

    Alarm limits apply to the selected sensor. Threshold comparisons use raw normalized engineering values, not smoothed display curves.

    Acceleration RMS Magnitude
    Warning Alarm m/s²
    Velocity RMS Magnitude
    Warning Alarm mm/s RMS
    Displacement RMS Magnitude
    Warning Alarm µm RMS
    Sensor-calculated Frequency X/Y/Z
    Warning Alarm Hz
    Baseline idle

    Each metric is evaluated independently with NORMAL / WARNING / CRITICAL severity.

    CSV Acquisition Recorder Backend stream writer

    Records normalized backend samples to CSV without storing data in the browser.

    Status
    Idle
    Rows
    0
    Elapsed
    0s
    Backpressure
    0
    File
    --
    Download
    --
    System Logs Latest platform events
    System Health Ingestion, rendering, and data validity
    MQTT
    --
    Live Stream
    --
    Selected Sensor
    --
    Sensor State
    --
    Data Quality
    --
    Receive Rate
    --
    Stored Samples
    --
    Dropped Display Samples
    --
    Queue Length
    --
    Invalid Payloads
    --
    Last Payload Timestamp
    --
    Recorder
    --
    AI Pattern Recogniser Stable result from recorded patterns
    Not Trained
    --
    Awaiting prediction
    --
    No pattern recogniser trained yet.
    Decision Explanation
    Awaiting pattern distances.
    Raw Window--
    Similarity--
    Stable Status--
    Last Updated--
    Decision Status--
    Model Version--
    Recent Windows: --
    Recorded Patterns Labels used when recording examples
    Select a sensor to manage labels.

    Abnormal / unrecognised pattern is automatic - never add it as a label. Pattern recogniser training requires at least 2 labels and 20 samples per label.

    Record Pattern Example Capture live data under the selected label
    Dataset Summary Recorded training samples per label
    No dataset yet.

    Model Training Learn recorded vibration signatures
    Status Idle
    Stage --
    Samples --
    Labels --
    Message --
    AI Settings Simple learning and update controls

    Signals Used For Learning

    Choose which live signals the recogniser should learn from.

    1 signal selected for learning

    The recogniser compares the live vibration with examples you recorded. Use fewer signals for a simpler, steadier model.

    Changing signals requires clearing old examples, recording new windows, and retraining.

    Recognition Behaviour

    Sensitivity changes require retraining. Status confirmation and analysis interval apply immediately.

    Settings version: -- | Last saved: -- | Sync: offline