A method including measuring vibrations of a rotating machine during its operation, using a vibration sensor. Next, from the signal measured by the sensor, automatically extracting, using an electronic detection device, a first signal representative of components of a first frequency range of the measured vibration signal, and a second signal representative of a second frequency range of the measured vibration signal. Then, from the first signal, calculating a first data set belonging to a time domain of the first signal, and extracting first calculation elements therefrom. Next, from the second signal, calculating a second data set belonging to a frequency domain of the second signal, and extracting second calculation elements therefrom. Lastly, determining a health index of the bearing from each of the extracted calculation elements.

A method including measuring vibrations of a rotating machine during its operation, using a vibration sensor. Next, from the signal measured by the sensor, automatically extracting, using an electronic detection device, a first signal representative of components of a first frequency range of the measured vibration signal, and a second signal representative of a second frequency range of the measured vibration signal. Then, from the first signal, calculating a first data set belonging to a time domain of the first signal, and extracting first calculation elements therefrom. Next, from the second signal, calculating a second data set belonging to a frequency domain of the second signal, and extracting second calculation elements therefrom. Lastly, determining a health index of the bearing from each of the extracted calculation elements.

Systems for self-organizing data collection and storage in a refining environment are disclosed. An example system may include a swarm of mobile data collectors structured to interpret a plurality of sensor inputs from sensors in the refining environment, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of a plurality of refining system components disposed in the refining environment, and wherein the plurality of refining system components is structured to contribute, in part, to refining of a product. The self-organizing system organizes a swarm of mobile data collectors to collect data from the system components, and at least one of a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs.

Systems for self-organizing data collection and storage in a refining environment are disclosed. An example system may include a swarm of mobile data collectors structured to interpret a plurality of sensor inputs from sensors in the refining environment, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of a plurality of refining system components disposed in the refining environment, and wherein the plurality of refining system components is structured to contribute, in part, to refining of a product. The self-organizing system organizes a swarm of mobile data collectors to collect data from the system components, and at least one of a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs.

Methods and systems for sensor fusion in a production line environment are disclosed. An example system for data collection in an industrial production environment may include an industrial production system comprising a plurality of components, and a plurality of sensors each operatively coupled to at least one of the components; a sensor communication circuit to interpret a plurality of sensor data values in response to a sensed parameter group; and a data analysis circuit to detect an operating condition of the industrial production system based at least in part on a portion of the sensor data values; and a response circuit to modify a production related operating parameter of the industrial production system in response to the detected operating condition.

Methods and systems for sensor fusion in a production line environment are disclosed. An example system for data collection in an industrial production environment may include an industrial production system comprising a plurality of components, and a plurality of sensors each operatively coupled to at least one of the components; a sensor communication circuit to interpret a plurality of sensor data values in response to a sensed parameter group; and a data analysis circuit to detect an operating condition of the industrial production system based at least in part on a portion of the sensor data values; and a response circuit to modify a production related operating parameter of the industrial production system in response to the detected operating condition.

A method for detecting defects in a rotational element of a machine based on changes in measured vibration energy includes: (a) collecting vibration data over an extended period of time using vibration sensors attached to the machine; (b) processing the vibration data to generate a time waveform comprising processed vibration values sampled during sequential sampling time intervals within the extended period of time; (c) detecting multiple time blocks within the extended period of time during which the processed vibration values exhibit sustained increases at progressively increasing rates; and (d) generating alerts based on detection of the multiple time blocks during which the processed vibration values exhibit sustained increases at progressively increasing rates. The multiple time blocks may include a first time block during which the processed vibration values increase at a first rate, and a second time block occurring after the first time block during which the processed vibration values increase at a second rate that is greater than the first rate.

A method for detecting defects in a rotational element of a machine based on changes in measured vibration energy includes: (a) collecting vibration data over an extended period of time using vibration sensors attached to the machine; (b) processing the vibration data to generate a time waveform comprising processed vibration values sampled during sequential sampling time intervals within the extended period of time; (c) detecting multiple time blocks within the extended period of time during which the processed vibration values exhibit sustained increases at progressively increasing rates; and (d) generating alerts based on detection of the multiple time blocks during which the processed vibration values exhibit sustained increases at progressively increasing rates. The multiple time blocks may include a first time block during which the processed vibration values increase at a first rate, and a second time block occurring after the first time block during which the processed vibration values increase at a second rate that is greater than the first rate.

A method for analyzing the condition of a machine, and an apparatus for analyzing the condition of a machine are described.

A method for analyzing the condition of a machine, and an apparatus for analyzing the condition of a machine are described.