Firmware version 2.0 is now available.
To upgrade, follow the procedure:
Version 2.0 allows faster data download and processing, in addition to providing new features and enhancements:
Through the Gateway (Cassia X1000 model), it is possible to transfer sensor data to the WEG IoT Platform automatically. The Gateway has IP65 protection rating and is certified by the Brazilian National Telecommunications Agency (ANATEL). Gateway installation and operation information can be viewed in the full manual (www.weg.net/wegmotorscan).
To save energy, in firmware version 2.0 or later, all sensors will be shipped from the factory disabled. Therefore, before installing the sensor on the motor, it is necessary to activate it. This is done using the app that can be downloaded directly from the App Store and Google Play Store.
To download it, search for the term WEG MOTOR SCAN or use the QR Code:
After installation and registration on WEG IoT Platform, follow the steps described directly in the app or as indicated in the procedure:
1 - If necessary, log in again - “Log in”
2 - Press “NEW DEVICE” and then “SELECT”. On the device selection screen, press ""Enable."
3 - Place the sensor in the horizontal position as shown in the app, and press “START”. Wait for 15 seconds, turn over the sensor, leaving it with the WEG logo facing downwards, as shown in the app. Press "CONTINUE" and wait for 15 seconds again.
4 - After 15 seconds, the app will direct you to the manual or NFC pairing screen, if your smartphone model has such functionality.
To perform manual pairing, position the sensor to be configured as close as possible to the smartphone, ensuring that no other sensors are nearby. Select the first sensor from the list.
To perform the pairing using the NFC, press “SCAN SENSOR”. Bring the back of the sensor close to the smartphone NFC region, as indicated in the app. After the NFC reading, the sensor will be paired with the smartphone and activation will be automatically completed.
In firmware version 2.0 and later, the sensor performs one hourly vibration measurement, in a total of 24 fixed daily measurements.
In previous versions, the sensor made up to 12 daily vibration measurements.
Frequency analysis can be performed via the WEG IoT Platform or WEG Motor Scan app in all three vibration directions. Maximum frequency is approximately 3 kHz with acquisition rate of 3.3 Hz. The figures show, respectively, the FFT graph directly in the app and in the Portal.
Instant measurement through the app can be made after pairing it with the sensor. Frequency, rotational speed and temperature analyses are some of the main measurements made in this feature.
Figure shows instant quantities on the app screen.
In firmware version 2.0 or later, the rotational speed and load are estimated, enabling the monitoring of the motor performance in the application.
The estimation of these quantities is based on data acquired by the sensor and rated data informed during the motor registration process in the plant. Ensuring that all identification fields are correctly filled out is critical for proper estimation.
Rotational speed [rpm]:The estimated rotational speed can be viewed in the mobile app and in the WEG IoT Platform.
Load [%, kW]:
NOTE! Load estimation will only be available on motors that not driven by frequency inverters. Load estimation is in BETA phase, with improvements and continuous development.
The load estimation applied to the motor in percentage of the rated load and in kW depends on several factors, such as: estimated rotational speed, supply voltage and frequency, temperature and rated values informed on the nameplate.
In the application, rated values vary over time within standardized limits. Therefore, the estimated load value has certain deviations from the actual value, measured, for example, indirectly through a torsion bar. Taking that into account, the deviation from the estimated value may vary by an average of 10% from the rated point.
Estimated load values can be viewed on the mobile app and in the WEG IoT Portal. The figure shows the estimated performance of a certain motor based on data obtained from a WEG Motor Scan sensor. Estimated performance values are always related to the last acquisition made by the sensor. The next figure shows the load graph in percentage for a given time period. Mousing over the graph displays a text box with information on the day, time and estimated load values with their permissible variation (minimum and maximum).
The minimum and maximum values of the estimated load indicate that the load value may be within this range – due to all possible variations for the motor rated values.
NOTE!
The diagnosis is in the BETA phase, with improvements and continuous development.
The diagnosis may be affected for motors powered by frequency inverters.
The diagnosis only acts on measurements in which the motor is running.
Firmware version 2.0 or later, through the use of artificial intelligence, provides advanced motor diagnosis in the application. The view is available on the WEG IoT Portal.
Generated information:
system operation patterns
analysis of possible motor failures
The Diagnosis field informs the motor present condition. If the motor is not healthy, a brief description of the problem accompanies the condition. The Events tab records all events generated for the motor. In addition to temperature and vibration events, by checking the Advanced events option, you can see the details of the learning period, operating patterns and failure analysis.
The Learn button, available only for plant administrator users, is used to restart the diagnosis process. In this case, a new learning period will start with the analysis of its operating patterns.
Before providing any diagnosis information, a 15-day learning period is required. During this time, an analysis is made to learn the operating patterns of the system (motor + application). If the motor is part of a system with many variations/operating patterns, the learning period may automatically extend. The following image shows an example of a learning period with the patterns found.
During this period, the user will be informed of the operating patterns found, and if any pattern with vibration levels above the values set by ISO10816-3 is found, the user will also be notified.
In addition, whenever the users understand that there have been inconsistent measurements, they can restart the learning, thereby ensuring a better diagnosis process.
WEG Motor Scan, through Artificial Intelligence algorithms, identifies operating patterns. Not only during the learning period, but also any time there is a change in the system through the vibration and rotation measurements. Thus, the user can check changes in the system dynamics and, if necessary, take appropriate actions. The following image shows an example of a change in the system operating pattern.
With firmware version 2.0 or later, WEG Motor Scan adds WEG knowledge gained over the years to Artificial Intelligence in order to be able to detect potential motor failures based on the history of vibration data collected by the sensor.
Possible failures assessed: