Methods, systems, and apparatus, including computer programs encoded on a storage device, for performing leak detection. In one aspect, the method includes actions of obtaining water consumption data that is based on first sensor data generated by a connected water meter that is installed at a property, determining, based on the obtained water consumption data, (i) that a water leak is occurring at the property and (ii) a type of water leak that is occurring at the property, in response to determining (i) that a water leak is occurring at the property and (ii) a type of water leak that is occurring at the property, determining, based on a type of water leak that is determined to be occurring at the property, an operation to mitigate potential damages caused by the water leak, and initiating performance of the operation in order to mitigate potential damages caused by the water leak.

A monitoring device includes: a base information acquisition unit that acquires information on operation and fault of an equipment arranged at a base and position information relating to the equipment; a natural environment information acquisition unit that acquires natural environment information in a region; and an analysis unit that specifies a position of the equipment in which the fault has occurred from the information acquired by the base information acquisition unit, associates the position with a region of the natural environment information, and associates the equipment in which the fault has occurred with the natural environment information.

The disclosed embodiments provide a system that performs seasonality-compensated prognostic-surveillance operations for an asset. During operation, the system obtains time-series sensor signals gathered from sensors in the asset during operation of the asset. Next, the system identifies seasonality modes in the time-series sensor signals. The system then determines frequencies and phase angles for the identified seasonality modes. Next, the system uses the determined frequencies and phase angles to filter out the seasonality modes from the time-series sensor signals to produce seasonality-compensated time-series sensor signals. The system then applies an inferential model to the seasonality-compensated time-series sensor signals to detect incipient anomalies that arise during operation of the asset. Finally, when an incipient anomaly is detected, the system generates a notification regarding the anomaly.

A Fault Detection Diagnostic (FDD) correction method for increasing the cooling capacity delivered by an Air-Conditioning (AC) system with an economizer comprising: correcting/superseding at least one cooling fault/delay, the correcting/superseding selected from the group consisting of: correcting/superseding a High-limit-Shut-off-Temperature (HST) fault/delay based on detecting an Outdoor Air Temperature (OAT) is less than or equal to a High-limit-Control Temperature (HCT) during a thermostat call for cooling to enable economizer cooling otherwise delayed by the at least one HST fault/delay, superseding a thermostat second-stage time/temperature-deadband delay based on detecting an OAT is greater than or equal to an AC Control Temperature (ACT) during a call for cooling and energizing an AC compressor otherwise delayed by a thermostat second-stage time/temperature-deadband delay, superseding at least one economizer second-stage time/temperature delay based on detecting a thermostat second-stage cooling signal and energizing an AC compressor otherwise delayed by the at least one economizer second-stage time/temperature delay.

A system checks for abnormality in a machine tool and regardless of power interruption of the machine tool. A system for remote control of production equipment is installed in a management apparatus for the production equipment by receiving operational state information of a machine tool and transmitting the data thereof to a server. The system includes at least one sensor installed in the main body of the machine tool to collect operational information data thereof and transmit the same to the server. The sensor includes a dual power supply having a first external power source supplied with external power in communication with the machine tool and a second power source formed of a battery independent of the external power. A sensor communication network transmits the collected data to the server, whereby causes of failure may be judged by determining whether data communication with the server is executed.

A method for computer-aided processing of state messages in an automation installation, wherein state messages are generated by components and detected with their generation points in time, where causative states present at the generation point of the state message or beforehand in other components are determined for a multiplicity of state messages of a respective component and the current state in the generated state message, where the propagation time between occurrence of the respective causative state and the generation point of the state message is calculated for each causative state, where groups are formed from the causative states, where in a respective group all causative states have at least the common feature that they were determined for the same current state in the respective component, and where at least one statistical parameter is determined from the propagation times which belong to the causative states of the same group and stored.

A system for determining a priority of monitoring a machine is provided. The system includes a data acquisition module disposed in communication with a sensor. The data acquisition module is configured to generate data based on at least an operational parameter associated with the machine. The system further includes a server configured to determine a first factor indicative of a rate of usage of the machine, a second factor indicative of a number of exceptions of the machine at corresponding severities, a third factor indicative of a risk of unscheduled downtime of the machine, a fourth factor indicative of a distance from a preventive maintenance of the machine, a fifth factor indicative of an importance of a sub-system of the machine, and the priority of monitoring the machine based on at least the first factor, the second factor, the third factor, the fourth factor and the fifth factor.

A fault reporting device 8 for reporting a fault to a facility management arrangement 9, having a location module, wherein the location module is formed to determine a location position X(t) of the fault reporting device 8, having a position determining module, wherein the position determining module is formed to identify a fault position in a surrounding area of the location position X(t), having a transmission module for wirelessly transmitting a fault report, wherein the fault report comprises the fault position and fault information 12.

A fixed wing unmanned aircraft and a method for operating the same are provided. The fixed wing unmanned aircraft may include, but is not limited to, a failure detection system configured to detect faults in one or more of the plurality of components, a capability evaluation system communicatively coupled to the failure detection system, the capability evaluation system configured to determine a capability level of the fixed wing unmanned aerial vehicle based upon the faults in the one or more of the plurality of components, and a trajectory generation system communicatively coupled to the failure detection system and the capability evaluation system, the trajectory generation system configured to generate a touch down trajectory for the fixed wing unmanned aerial vehicle based upon the determined capability level of the fixed wing unmanned aerial vehicle, wherein when the determined capability level is below a predetermined threshold, the touch down trajectory comprising a stall maneuver configured to minimize a lateral energy of the fixed wing unmanned aerial vehicle.

Methods and systems for monitoring a brush holder assembly and/or detecting wear of a brush in a brush holder assembly are disclosed. One method includes sending data from a plurality of remote monitoring locations to a central control unit, where the data may be evaluated in order to monitor states of brushes at a plurality of remote electrical facilities. For example, multiple images of a marker tracking longitudinal movement of the brush may be acquired. A comparison of the images, for example, a comparative imaging technique, such as pixel-by-pixel comparison, may then be performed in order to evaluate a condition of the brush, such as the wear rate, wear state, or life expectancy of the brush.