Abstract: The present invention provides a process for the preparation of crystalline Lorcaserin hydrochloride hemihydrate of Formula (Ia), which comprises, Formula (Ia) (i) providing a solution of Lorcaserin base in a solvent; (ii) if water is present, removing water from the reaction mixture; (iii) adding hydrogen chloride to the reaction mixture; (iv) combining the reaction mixture with a suitable anti-solvent; and (v) isolating the crystalline Lorcaserin hydrochloride hemihydrate of Formula (Ia).

Abstract: The present invention provides a process for the preparation of crystalline Lorcaserin hydrochloride hemihydrate of Formula (1a), which comprises, Formula (1a) (i) providing a solution of Lorcaserin base in a solvent; (ii) if water is present, removing water from the reaction mixture; (iii) adding hydrogen chloride to the reaction mixture; (iv) combining the reaction mixture with a suitable anti-solvent; and (v) isolating the crystalline Lorcaserin hydrochloride hemihydrate of Formula (1a).

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 method includes parsing configuration data of multiple applications associated with an industrial process control and automation system. The method also includes generating first models associated with the applications based on the parsed configuration data. The method further includes identifying relationships between the first models to thereby identify relationships between information associated with the applications. In addition, the method includes generating a second model based on the identified relationships, where the second model identifies the relationships between the information associated with the applications. Parsing the configuration data could include identifying input and output variables associated with each application. The first models could include input-output models mapping the input variables versus the output variables of the applications.

Abstract: A system includes multiple sensors configured to measure one or more characteristics of a rotating o reciprocating systems. The system also includes a monitoring system configured to monitor a health of the rotating system. The monitoring system includes an input interface configured to receive multiple input signals from the sensors. The monitoring system also includes a processing unit configured to identify a fault in the rotating system using the input signals. The monitoring system further includes an output interface configured to provide an indicator identifying the fault. The processing unit is configured to identify the fault by (i) generating a pressure-volume diagram from a fusion of the input signals and comparing the pressure-volume diagram to a previous diagram to determine changes in the diagrams and/or (ii) normalizing the input signals and using the normalized input signals to identify a defect and calculate a confidence level of the defect.

Abstract: A system includes multiple sensors configured to measure one or more characteristics of a rotating o reciprocating systems. The system also includes a monitoring system configured to monitor a health of the rotating system. The monitoring system includes an input interface configured to receive multiple input signals from the sensors. The monitoring system also includes a processing unit configured to identify a fault in the rotating system using the input signals. The monitoring system further includes an output interface configured to provide an indicator identifying the fault. The processing unit is configured to identify the fault by (i) generating a pressure-volume diagram from a fusion of the input signals and comparing the pressure-volume diagram to a previous diagram to determine changes in the diagrams and/or (ii) normalizing the input signals and using the normalized input signals to identify a defect and calculate a confidence level of the defect.

Abstract: A system includes a subsystem interaction module device, which includes at least one interface configured to receive input signals associated with multiple components of a system. The subsystem interaction module device also includes at least one processing unit configured to identify a potential fault in one or more of the components using the input signals and to provide an indicator identifying the potential fault. The at least one processing unit is configured to identify the potential fault by: identifying conflicting frequencies that are associated with different faults in the components of the system; and determining a confidence level associated with the potential fault based on the conflicting frequencies.

Abstract: A system includes a plurality of sensors configured to measure one or more characteristics of a gearbox. The system also includes a subsystem interaction module device, which includes at least one interface configured to receive input signals associated with multiple components of a system. The subsystem interaction module device also includes at least one processing unit configured to identify a potential fault in one or more of the components using the input signals and to provide an indicator identifying the potential fault. The at least one processing unit is configured to identify the potential fault by: identifying conflicting frequencies that are associated with different faults in the components of the system; and determining a confidence level associated with the potential fault based on the conflicting frequencies.