A method for determining an anomalous operating state in a charging infrastructure system for batteries is proposed. For a charging process at a charging station, the method includes obtaining target characteristics of the charging process, determining process parameters for the charging process, performing the charging process, determining a performance metric for the performed charging process, generating and storing a data set for the performed charging process in a database. For multiple charging processes, the method includes calculating and storing at least one first set of statistic data for a first time interval and at least one second set of statistic data for a second time interval, comparing the first set of statistic data with the second set of statistic data to compute a set of difference values for each stored data set, and determining whether the charging infrastructure system operates in an anomalous operating state.

A system and method for data collection and frequency analysis with self-organization functionality includes analyzing with a processor a plurality of sensor inputs, sampling with the processor data received from at least one of the plurality of sensor inputs at a first frequency, and self-organizing with the processor a selection operation of the plurality of sensor inputs.

One embodiment provides a method and a system for diagnosing faults in a physical system. During operation, the system can obtain a model of the physical system comprising a plurality of components and can perform a structural analysis on the model to decompose the model into multiple independent subsystem models. A subsystem model corresponds to a subsystem comprising a subset of the plurality of components. The system can then perform, in parallel, a fault-diagnosis operation on each subsystem based on the corresponding subsystem model and can generate a diagnostic output indicating one or more components within the physical system being faulty based on outcomes of the fault-diagnosis operation on each subsystem.

The present subject matter describes a method to detect anomaly in an environment based on AI techniques. The method comprises receiving one or more data representations of one or more objects present in an environment. A first-type of information is captured from a first-area within the one or more data representations. A second-type of information from a second-area different than the first area in the data representations is also captured. A third information is generated from the first information, said third information corresponding to predicted information for the second area using one or more artificial-intelligence models for evaluating the second information. The third information is compared with the second information to determine abnormality with respect to state or operation of one or more objects within the environment.

Systems, apparatuses, and methods disclosed provide for tailoring responses to fault data generated during a service event. A method includes determining that a service event for a vehicle has started based on an indication from an off-board diagnostic service tool, interrupting transmission of a fault message during a time period after the service event for the vehicle has started and before the service event for the vehicle has ended, and determining that the service event for the vehicle has ended.

A glucose level control system can access a manufacturer specification that is configured to establish a minimum operating parameter of an associated ambulatory medicament pump. The control system can determine, via a pump monitoring system, a functional state of at least one of a plurality of pump components of the ambulatory medicament pump. The control system can determine, in response to determining the functional state of the at least one of the plurality of pump components, that the ambulatory medicament pump fails to meet the manufacturer specification and automatically generate a replacement alert that is configured to indicate that the ambulatory medicament pump may need to be replaced. The control system can transmit a request to a remote electronic device for a replacement ambulatory medicament pump.

There is described a zone controller and method for identifying a root cause failure at a zone. The zone controller determines whether a temperature measurement deviates from a temperature setpoint of the temperature sensor, and generates a first repair code, a second repair code, and/or a third repair code. The first repair code replaces a temperature sensor in response to detecting that a reading of the temperature sensor has failed. The second repair code releases an operator override on the reading of the temperature sensor in response to detecting that the reading of the temperature sensor has been overridden. The third repair code releases an operator override on a setpoint of the temperature sensor in response to detecting that the setpoint of the temperature sensor is outside the predetermined setpoint range. One or more of these repair codes are provided to a remote device.

A system for automatic application of fault detection and diagnostics (FDD) rules within a building management system (BMS) includes a memory having instructions stored thereon and a processor configured to execute the instructions. The processor, in executing the instructions, may retrieve from a plurality of BMS devices, a first BMS device having at least one attribute. The processor may identify, from a plurality of FDD rules based on the at least one attribute, an FDD rule associated with the at least one attribute. The processor may apply the FDD rule to the data point of the first BMS device corresponding to the at least one attribute. The processor may, responsive to determining a second BMS device from the plurality of BMS devices shares the at least one attribute, automatically apply the FDD rule to the second BMS device.

The present invention related to the technical field of industrial automation, in particular to a method and apparatus for generating a fault diagnosis database of a CNC machine tool, intended to conveniently provide comprehensive fault diagnosis information. The method comprises: setting a fault condition of the CNC machine tool; running a simulation model of the CNC machine tool under each set fault condition to generate fault, and recording a fault phenomenon of the fault; backtracking a possible fault generating each fault phenomenon, to establish an association between the fault phenomenon and a possible fault generating the fault phenomenon; generating a fault diagnosis database of the CNC machine tool according to the association established. Due to the fact that what is being run is a simulation model of the CNC machine tool, various fault conditions can be conveniently set. The fault diagnosis database established by the method has the advantage of comprehensive coverage of fault situations and abundant fault diagnosis information. The result of performing fault diagnosis on the basis of such a fault diagnosis database is more accurate.

A manufacturing device monitoring system includes a plurality of manufacturing devices and a remote monitoring device. The manufacturing device includes a work unit, an equipment notifier, an error detector, and an error notifier. The error notifier determines whether or not an error detected by the error detector may be corrected by an operation from the remote monitoring device, notifies the remote monitoring device of the occurrence of the error in a case where the error can be corrected, and operates the equipment notifier to notify a first notification pattern in a case where the error cannot be corrected.