Techniques regarding root cause analyses based on time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise maintenance component that can detect a cause of failure for a mechanical system by employing a greedy hill climbing process to perform a polynomial number of conditional independence tests to determine a Granger causality between variables from time series data of the mechanical system given a conditioning set.

Methods, systems, and devices for analyzing vibration data and for identifying and tracking vibration anomalies in industrial machines are described. In various embodiments, the system described herein collects, transforms, and analyzes sensor data from one or more machines, such as industrial machines. The system may identify one or more sensors that are experiencing vibrational anomalies. In various embodiments, the system: collects and analyzes vibration data for a set of one or more vibration-related sensors of one or more industrial machines; determines an occurrence of one or more anomalies based on the vibration data as compared to a threshold; tracks anomalies in collected vibration data for the one or more industrial machines of the facility; generates a report of vibration data for the one or more vibration-related sensors of the facility; and reports industrial machines in the facility that may deviate from a target performance.

Methods, systems, and devices for analyzing vibration data and for identifying and tracking vibration anomalies in industrial machines are described. In various embodiments, the system described herein collects, transforms, and analyzes sensor data from one or more machines, such as industrial machines. The system may identify one or more sensors that are experiencing vibrational anomalies. In various embodiments, the system: collects and analyzes vibration data for a set of one or more vibration-related sensors of one or more industrial machines; determines an occurrence of one or more anomalies based on the vibration data as compared to a threshold; tracks anomalies in collected vibration data for the one or more industrial machines of the facility; generates a report of vibration data for the one or more vibration-related sensors of the facility; and reports industrial machines in the facility that may deviate from a target performance.

The present disclosure includes a method for adapting functionalities of a field device, including a step of transmitting a configuration of the field device to a database. Further application programs, including additional functionality for the field device and basic programs for various field devices are stored on the database. The configuration of the field device has information about the basic program of the field device, any application programs already on the field device, the type of field device or the hardware of the field device. The method also includes a step of selecting a further application program. An installation package is created containing the further application program using a tool chain selected based on the configuration. The tool chain creates the installation package in a format executable on the field device. The installation packet is executed on the field device, thus transferring the further application program to the field device.

The present disclosure includes a method for adapting functionalities of a field device, including a step of transmitting a configuration of the field device to a database. Further application programs, including additional functionality for the field device and basic programs for various field devices are stored on the database. The configuration of the field device has information about the basic program of the field device, any application programs already on the field device, the type of field device or the hardware of the field device. The method also includes a step of selecting a further application program. An installation package is created containing the further application program using a tool chain selected based on the configuration. The tool chain creates the installation package in a format executable on the field device. The installation packet is executed on the field device, thus transferring the further application program to the field device.

Asset data is collected from one or more asset managers and stored in a known asset database. The known asset database enables tracking and maintenance of assets associated with each asset manager. One or more field technicians may also be associated with assets in the known asset database. A field technician is provided with access to a field asset management application on a mobile device, which allows the field technician to provide data associated with asset samples. Asset sample data is then correlated with asset data. Once an asset sample has been correlated with an asset, a field technician or other party is presented with an interface through an asset management application, allowing the party to place one or more requests for tests to be performed on one or more asset samples. Once the one or more tests are performed, test results data is provided.

This application relates to apparatus and methods for determining the integrity of data, such as sensor data, in systems. In some examples, a computing device receives input data for the system, and executes a physics-based model to generate a first output. The physics-based model may include a plurality of surrogate models that simulate various portions of the system. The computing device may further execute a machine learning model that operates on the first output to generate a second output. The computing device may generate a predicted output for the system based on the first output and the second output. In some examples, the computing device determines an error for the system based on the predicted output and sensor data received from sensors for the system. Based on the error, the computing device determines if the sensor data is valid. The computing device may then provide an indication of the determination.

Techniques regarding root cause analyses based on time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise maintenance component that can detect a cause of failure for a mechanical system by employing a greedy hill climbing process to perform a polynomial number of conditional independence tests to determine a Granger causality between variables from time series data of the mechanical system given a conditioning set.

A physical quantity measurement method acquires a plurality of measurement results corresponding to the passage of a plurality of vehicles based on the measurement performed by a sensor for physical quantity computation attached to a structure through which the plurality of vehicles pass. The physical quantity measurement method further identifies the vehicle corresponding to each of the plurality of measurement results based on measurement time information that is information on the time when the measurement is performed and operation information that is information on the operation status of the vehicle. The physical quantity measurement method then determines whether or not to use each of the plurality of measurement results in an abnormality evaluation process of evaluating abnormality of the structure based on a vehicle identification result that is the result of the identification of the vehicle.

Systems and methods for monitoring and diagnosis of equipment health. An example method may include commencing operation of a monitoring system of a well construction system to cause the monitoring system to receive sensor data facilitated by sensors disposed in association with a corresponding piece of equipment, detect an abnormal condition associated with a piece of equipment based on the sensor data, and output abnormal condition information indicative of the abnormal condition to a first communication device. The method may further include displaying on the first communication device to technical support personnel the abnormal condition information, receiving by the first communication device from the technical support personnel mitigation information indicative of mitigating action to be performed to mitigate the abnormal condition, and transmitting the mitigation information from the first communication device to a second communication device to be viewed by maintenance personnel who are to perform the mitigating action.