Abstract: A method includes receiving an input signal containing information associated with a rolling element bearing and/or a piece of equipment containing the rolling element bearing. The method also includes decomposing the input signal into a frequency-domain signal and determining at least one family of frequencies corresponding to at least one failure mode of the rolling element bearing. The method further includes generating a reconstructed input signal using the at least one family of frequencies and the frequency-domain signal. In addition, the method includes determining, using the reconstructed input signal, an indicator identifying an overall health of the rolling element bearing. The indicator could be determined using a baseline signal associated with either (i) normal operation of the rolling element bearing and/or the piece of equipment or (ii) defective operation of the rolling element bearing and/or the piece of equipment (where a severity of the defective operation will increase over time).

Abstract: A system includes more sensors configured to measure one or more characteristics of rotating equipment and a blind fault detection device. The blind fault detection device includes an input interface configured to receive at least one input signal from the one or more sensors. The blind fault detection device also includes a processing unit configured to identify a fault in the rotating equipment using the at least one input signal. The blind fault detection device further includes an output interface configured to provide an indicator identifying the fault. The processing unit is configured to identify the fault by determining at least one family of frequencies related to at least one sensor point, determining an average energy for the at least one sensor point based on the at least one family of frequencies, and comparing the average energy to a baseline value.

Abstract: A system includes at least one sensor and an equipment health monitoring (EHM) unit. The at least one sensor is configured to measure one or more characteristics of an asset, where the asset includes a piece of equipment. The EHM unit includes at least one sensor interface configured to receive at least one input signal associated with the asset from the sensor(s). The EHM unit also includes at least one processing unit operable to be pre-configured to identify a specified fault in the asset using the input signals and an asset-specific model that includes a combination of standard subsystem models. The EHM unit further includes at least one output interface configured to provide an indicator identifying the fault. The standard subsystem models could include standardized fault models configured to identify faults for standard assets.

Abstract: A method includes receiving wireless signals from a wireless network at a handheld device located at a specified site. The wireless signals are associated with a network connection at the specified site. The method also includes determining one or more metrics related to a reliability of the network connection at the specified site. In addition, the method includes determining that a class of application or device is supported by the network connection using the one or more metrics. The one or more metrics could include signal strength, bandwidth, latency, average number of channels available, number of routing elements visible, and/or average latency. Determining that the class of application or device is supported by the network connection could include determining that each of the one or more metrics is suitable for the class of application or device based on a criticality of the class of application or device.

Abstract: A system includes more sensors configured to measure one or more characteristics of rotating equipment and a blind fault detection device. The blind fault detection device includes an input interface configured to receive at least one input signal from the one or more sensors. The blind fault detection device also includes a processing unit configured to identify a fault in the rotating equipment using the at least one input signal. The blind fault detection device further includes an output interface configured to provide an indicator identifying the fault. The processing unit is configured to identify the fault by determining at least one family of frequencies related to at least one sensor point, determining an average energy for the at least one sensor point based on the at least one family of frequencies, and comparing the average energy to a baseline value.

Abstract: A system includes at least one sensor and an equipment health monitoring (EHM) unit. The at least one sensor is configured to measure one or more characteristics of an asset, where the asset includes a piece of equipment. The EHM unit includes at least one sensor interface configured to receive at least one input signal associated with the asset from the sensor(s). The EHM unit also includes at least one processing unit operable to be pre-configured to identify a specified fault in the asset using the input signals and an asset-specific model that includes a combination of standard subsystem models. The EHM unit further includes at least one output interface configured to provide an indicator identifying the fault. The standard subsystem models could include standardized fault models configured to identify faults for standard assets.

Abstract: A method includes receiving wireless signals from a wireless network at a handheld device located at a specified site. The wireless signals are associated with a network connection at the specified site. The method also includes determining one or more metrics related to a reliability of the network connection at the specified site. In addition, the method includes determining that a class of application or device is supported by the network connection using the one or more metrics. The one or more metrics could include signal strength, bandwidth, latency, average number of channels available, number of routing elements visible, and/or average latency. Determining that the class of application or device is supported by the network connection could include determining that each of the one or more metrics is suitable for the class of application or device based on a criticality of the class of application or device.

Abstract: A method includes receiving an input signal containing information associated with a rolling element bearing and/or a piece of equipment containing the rolling element bearing. The method also includes decomposing the input signal into a frequency-domain signal and determining at least one family of frequencies corresponding to at least one failure mode of the rolling element bearing. The method further includes generating a reconstructed input signal using the at least one family of frequencies and the frequency-domain signal. In addition, the method includes determining, using the reconstructed input signal, an indicator identifying an overall health of the rolling element bearing. The indicator could be determined using a baseline signal associated with either (i) normal operation of the rolling element bearing and/or the piece of equipment or (ii) defective operation of the rolling element bearing and/or the piece of equipment (where a severity of the defective operation will increase over time).

Abstract: A system and method for a wireless preprocessing sensor are provided. An analysis application is operable to communicate wirelessly. The wireless preprocessing sensor includes a sensor, a processor and a wireless communication interface. The sensor is operable to measure a vibration of a rotating mechanism. The processor is operable to receive measurements of vibration from the sensor, analyze a plurality of vibration measurements to produce information representing a characteristic of the vibration of the rotating mechanism, and send the information to the analysis application via the wireless communication interface.