Frequently Asked Questions
Questions about the Online Monitoring System or the TRACTIAN Maintenance Management Software? Check here.
Smart Trac Sensor
Learn more about which assets the TRACTIAN sensor monitors.
There are no size or power limitations, but the machine must be stationary. Its operating temperature can also be a limiting factor: the surface where the sensor is placed must not exceed 194°F/90°C.
After being placed on the machine and registered on the platform, the sensor immediately begins collecting data on the mechanical behavior and physical conditions of the asset.
This data is collected using a high-performance accelerometer that converts real-world data into its digital version. Then it is manipulated by the sensor's embedded processor and sent to TRACTIAN servers via the cloud.
The collected data refers to the acceleration arising from the vibration of the asset where the sensor is placed. Different filters are applied to ensure the quality and reliability of the signal, and data compression methods are used for sending and processing in the cloud.
The IoT sensor can be easily and efficiently installed on the machine in less than 5 minutes thanks to its plug & play technology. It does not require any specific training and can be done by clients themselves, as it does not require any electrical wiring or specific infrastructure for installation.
After installing the sensor, simply register the machine on the platform and associate each asset with a sensor code. The machine information will already be transmitted through the 3G/4G mobile network to the platform. It usually takes an average of 10 minutes per sensor to complete the activation.
There is no need for any Bluetooth or Wi-Fi communication configuration procedures. The sensor communicates using the Smart Receiver’s transmitters through a secure communication protocol from TRACTIAN. In addition, it operates on battery power, eliminating the need for electrical wiring or power outlets.
No - the acceptable limits for vibration are defined by the TRACTIAN proprietary Machine Learning algorithm which is highly accurate compared to laboratory-based standards and real-world factory conditions. The limits are continually improved by TRACTIAN's learning system based on the reality of your unit, ensuring insights with 89% accuracy.
If desired, manual limits or standards can still be activated for specifically desired applications.
The system recognizes the behavioral pattern (vibrational DNA) of the equipment using Machine Learning, a method that is not affected by random external vibrations. Therefore, nothing will interfere with the recognition of the signal from the monitored machine.
To differentiate the vibration signal of the monitored asset from other vibrations present in the environment, the system uses filters and digital signal processing techniques. Essentially, when measuring vibration, it is possible to differentiate noise from the signal of interest by considering the expected behavior of each of these phenomena. Mechanical noises have known and usually random distributions and levels within a range of values, as does the behavior of the machine. By using filters and statistical techniques, we can separate these signals and only monitor what really matters: the vibration related to the behavior of the machine.
Want to know more about how TRACTIAN sensors work? Check out this article.
The only required parameters are the power and RPM values of the machine, which help with the accuracy of the Machine Learning algorithms.
The more data about the machine and its components is entered into the system, the more accurate and descriptive the generated notifications will be. The essential values to be added are the asset model (motor, pump, compressor, etc.), its power and the operating RPM.
In addition to this data, you are able to enter information about other components such as gears, pulleys, belts and bearings. This information will be used by the more specialized models when diagnosing failures, which increases efficiency and accuracy in detecting different failure modes.
The sensor has an IP69K rating, making it completely dust and water jet proof.
Once the sensor is installed, the system begins to gather the spectral signature of the equipment which we call the ''vibration DNA of the equipment''. After that, any abnormalities in the usual vibrational behavior of the equipment or any unknown frequencies of its regular spectrum are immediately identified by the platform using the artificial intelligence incorporated in the sensor.
The intelligence of our system considers two principles: the individual behavior of the analyzed asset and the expected behavior of similar assets in the same group. Using statistical and Machine Learning techniques, the models learn the possible failure modes for individual assets and groups of assets through observation and examples over time. In other words, our intelligence is composed of several pieces, each responsible for identifying a type of behavior or indication of failure, whether in the spectrum, time, speed, acceleration or in temperature.
The information observed by these pieces is gathered and delivered to the diagnostic module, which acts like a human vibration analyst. The big difference is that this module is able to interpret enormous amounts of data quickly and continuously.
Yes, all TRACTIAN customers have total access to their collected data and can generate reports to thoroughly analyze the collected vibration spectra.
Our system's intention is to facilitate access to and visualization of the data acquired by the sensor. All collected and processed information is made available to the user in dedicated and clear graphs. If interested, a user may export this information.
Taking into consideration the equipment's operation and safety, the sensor's temperature operating range is from 14°F to 194°F (-10°C to 90°C). Temperatures outside of this range may cause damage to the sensor.
The sensor can collect with a minimum sampling frequency of 1 Hz or up to a maximum of 32 KHz. The default frequency is defined by the artificial intelligence of our system according to the chosen application.
The TRACTIAN system can identify over 70 different types of failures, including the most common and costly for maintenance teams:
- ● Unbalance
- ● Misalignment
- ● Bearing failures
- ● Gear wear
- ● Pump cavitation
- ● Saturation in filtering elements
- ● Lubrication failures
- ● Mechanical clearance (rotary and structural)
- ● Structural weakness
In addition to the highlighted failure modes, the sensor can identify several other behaviors that classify or indicate an asset is in a failure state.
Yes, you can monitor different assets in several units. Thanks to the easy-to-implement IoT technology, there are no restrictions on the physical distribution of your sensors.
In addition, the TRACTIAN platform has a series of tools that allow for easy comparison between the health of your assets in different locations, enabling remote management of all your units.
In the event that any anomaly is detected in your asset by the TRACTIAN system, you and your team will receive a notification through the app and by email. It will indicate the detected failure mode and the recommended action.
If the monitoring system is allied with the Tractian CMMS, it is also possible to follow each action taken by the team in order to remedy the failure.
There are no limits to the number of assets monitored by TRACTIAN in your unit or to the storage of data on our platform, which will always be available to our clients.
Assets with an operating temperature above 194°F (90°C) are outside the scope of the sensor's operation. Among the system limitations, the monitoring and detection of failures in assets with very low or very high rotation (less than 120 RPM or more than 25,000 RPM) implies lower accuracy. This happens due to the sensor's acquisition settings, which are not ideal for this type of machinery. Even so, despite having reduced accuracy, it is still possible to use the sensors on this type of asset.
The great distinction of the TRACTIAN system is the ability to constantly evolve and learn from customer feedback. All the Machine Learning techniques used are based on the principle of continuous learning. In other words, according to the responses the system receives, it improves its next inferences - in our case, its next insights.
To contribute to this process, the user must provide feedback on the failures identified through the insights on the platform, and detail the severity of the identified problem and the type of problem. In addition to helping improve future insights, these responses provide the maintenance team with valuable information for tracking and managing events that occur with the asset and are an essential part of effective maintenance planning, control and management.
Energy Trac Sensor
Energy Trac is the TRACTIAN electrical energy monitoring and diagnosis sensor. It monitors all the main electrical quantities of a panel or asset and uses this data to generate information on consumption, demand, energy quality and running time. This data can also be used to diagnose electrical problems.
Problems related to asset operating limits such as overvoltage and voltage drop, overload, reduction in power factor and current above the limit. Energy Trac can also diagnose energy quality problems such as current and voltage harmonics, voltage levels, etc.
The Energy Trac has a voltage monitoring range of 90 to 480 Vca, and a current range of 0 to 3000A.
Yes, through the modulation performed by the TP or TC commonly found in the cabins. Another possible solution is at the low voltage side of the MT/BT transformer after the cabin.
No. Currently, Energy Trac only monitors equipment in AC.
The sensor monitors voltage and current non-invasively, through a TC fixed around each phase and a direct attachment to a bus or circuit breaker.
The attachment of the sensor itself is done through a magnetic base on the back. It can be installed on DIN rails and metal parts of the electrical panel, both on the back and front as well as on the door.
Energy Trac monitors any and all assets that are connected to your electrical network. From electrical panels, transformers and generators to assets such as motors, compressors and loads.
The data from your assets is shared and stored via mobile network (3G/4G) or Industrial Wi-Fi, eliminating the use of cables (such as RS485, RJ45) and avoiding automation infrastructure in your plant.
You can see the electrical energy consumption in a desired period and other important metrics such as power factor and the specific consumption of each component through the TRACTIAN platform. You can even analyze energy expenditure through the platform with the Kwh cost data in your plant.
Yes, all TRACTIAN clients have total access to collected data and can generate reports and thoroughly analyze the energy indicators of the plant.
The intention of our system is to facilitate access and visualization of the data acquired by the sensors. All collected and processed information is made available to users in dedicated and clear graphs. If interested, a user may export this information.
There are no limits to the number of assets monitored by TRACTIAN in your unit, nor to the storage of data on our platform, which will always be available to our clients.
Yes, you can monitor different assets in various units. Thanks to the easy-to-implement IoT technology, there are no restrictions on the physical distribution of your sensors.
In fact, the TRACTIAN platform has a number of tools that allow for easy comparison of assets in different locations, enabling remote management of all your units.
In the event of any electrical failure signal being detected by the TRACTIAN system on your asset, you and your team will receive a notification through the app and email. It indicates the mode of failure detected and the recommended action. The history of these alerts is also accessible to system users.
After positioning in the electrical panel and registering on the platform, the sensor immediately begins collecting data on the electrical behavior of the asset.
Such collections are made as follows:
For the voltage signal, it occurs through a conductor that is connected in parallel to the bus (electrical point) you want to monitor.
The current signal has each phase monitored through Rogowski coils (TC's), which are native to Energy Trac. The principle of operation of this is that the coils collect electrical currents through induction by the magnetic field.
After collection, we convert the data into its digital version, where it is manipulated by the processor embedded in the sensor and sent to the TRACTIAN servers via the cloud.
The collected data refers to the voltage and current coming from the collection of the asset where the sensor is positioned. Different filters are applied to ensure the quality and reliability of the signal, and data compression methods are used for sending and processing in the cloud.
The nominal current values, operating voltage and nominal power are the only required parameters to ensure the accuracy of the Machine Learning algorithms.
The more data about the machine and its components that is entered into the system, the more accurate and descriptive the generated notifications will be. The essential values to be added are the model of the asset (Low Voltage General Board, Power Board, pump, motors, compressor, etc.) and its factory data.
In addition to this data, a user can enter information about the consumption in $/kwh paid for the calculation of consumption for better management of your unit.
As soon as the sensor is installed, the system starts gathering the spectral signature of the equipment, which we call ''Electrical Signature Analysis (ESA)''. After that, any abnormalities in the usual electrical behavior of the equipment or any unknown frequencies of its regular spectrum are immediately identified by the platform using the artificial intelligence incorporated into the sensor.
The intellegence of our system considers two things: the individual behavior of the analyzed asset and the expected behavior of similar assets in the same group.
Using statistical and Machine Learning techniques, the models learn the possible failure modes for the different individual assets and groups of assets through observation and examples over time. In other words, our intelligence is made up of several components, each designed to identify specific types of behavior or failure indicators, whether in the time spectrum of voltage and current or in the frequency spectrum through the analysis of harmonics.
The information observed by these pieces is gathered and delivered to the diagnosis module, which acts as an industrial maintenance electrician. The big difference is that this module is able to interpret huge amounts of data quickly and continuously.
For predictive models, the major advantage of the TRACTIAN system is its ability to continuously evolve and learn from customer feedback. All the Machine Learning techniques used are based on the principle of continuous learning, that is, according to the responses the system receives, it improves its next inferences - in our case, its next insights.
To contribute to this process, the user must provide feedback on the identified failures (including their type and severity). In addition to helping to improve future insights, the user's responses also serve to help the maintenance team effectively control and manage events occurring with the asset, making them an essential part of electrical maintenance planning, control, and management.
In addition to the aforementioned voltage and current ranges, we have limits such as operating temperature, -20°C to 60°C, maximum relative humidity of 95% and internal power supply current of up to 3.15A, protected by a fuse.
CMMS TracOS™
CMMS stands for Computerized Maintenance Management System, a specific software for planning, scheduling and managing maintenance routines, centralizing information in a single ecosystem. TracOS™ is therefore the TRACTIAN maintenance activity planning and management system.
Yes, you can use the software on any desktop computer through web browsers or on mobile devices such as tablets and smartphones through our app, available for all iOS and Android devices.
There is no storage limit in TracOS™. The information, data and history are unlimited, you can register any information you want according to your needs, regardless of the contracted plan.
TracOS™ is an online platform in the SaaS (software as a service) model, which means that your subscription occurs through a monthly subscription according to the contracted plan, with no contractual ties.
No. All costs are already included in the monthly fee for the plan, including the cloud platform, backups with redundancy compliant with ISO 27001, training, support, installation and integration.
Yes. We perform integrations through API and have a specialized team to assist with the entire process.
Yes. Our team of specialists are prepared to map all your business rules, map process flows, and ensure that all information is integrated with the main market ERPs, such as SAP and TOTVS.
Yes- It is possible to configure the access levels and respective permissions according to each user's activity in the maintenance routine.
Yes. Every action taken within TracOS™ is recorded on the platform. You can view all actions within the asset tree as well as see which maintenance plans exist for that equipment. Other notable records include metrics, service orders and technicians who’ve worked on the machine.
There are no limits to asset inclusion, you can register all your assets at no additional cost.
Yes, you can attach unlimited files to the platform, such as images, PDFs, and videos.
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