The invention involves the automated testing of HVAC units using an energy management system. The automated HVAC test is performed to understand if one or more HVAC units are operational across one or more locations. If an HVAC unit is not operational, HVAC testing could be performed to understand which component or stage of the HVAC unit is not working as designed. The automated HVAC test is also used to calculate the efficiency of the HVAC unit(s) being tested. The various HVAC tests are performed on all HVAC units as a form of preventative maintenance and diagnostics. These tests can be scheduled on-demand, for a future date and time, or on a recurring schedule (monthly or quarterly). A report is generated for each HVAC test and can be viewed and exported from a cloud-based energy management platform.

The control apparatus 1 includes a control unit 21 that controls execution of a workflow including a handling execution process when an alarm indicating a failure is occurred, and an instruction unit that instructs the control unit 21 to stand by execution of the handling execution process when the handling execution process is capable of being executed before a monitoring period started in response to occurrence of an alarm indicating the failure or a recovery expires, and when the monitoring period expires, execute the handling execution process in a case where an alarm that is occurred most recently indicates the failure, and cancel the execution of the handling execution process in a case where the alarm that is occurred most recently indicates the recovery.

A method may include obtaining, at a server or analysis device, sensor data comprising at least one of vibration data and impulse data from one or more sensor devices coupled to a first utility infrastructure; obtaining training sensor data associated with at least one of the first utility infrastructure from a previous time period and one or more second utility infrastructures; comparing the sensor data with the training sensor data associated with the at least one of the first utility infrastructure from the previous time period and the one or more second utility infrastructures; and identifying or predicting a fault occurrence associated with the first utility infrastructure based on the comparing the sensor data associated with the first utility infrastructure to the training sensor data associated with the at least one of the first utility infrastructure from the previous time period and the one or more second utility infrastructures.

A method and system for localizing faults in an industrial process is proposed. The industrial process includes a plurality of components. The method includes receiving structural plant data from an industrial plant. A structured model of the process is generated from the structural plant data. Sensor data measuring characteristics of the plurality of components is also received. Parameters of the structured model are identified from the received sensor data and stored. Faults are detected during operation of the industrial plant utilizing the identified parameters and detecting changes in the parameters by comparing current parameters to stored parameters. The fault information is then displayed via a display to an operator.

A system with a self-test function has at least one system component which has at least one technical function, a fault simulation unit integrated in the system, a self-test unit integrated in the system, and a verification control unit integrated in the system, wherein the at least one system component is coupled to the fault simulation unit, wherein the fault simulation unit is designed to influence the operation of the system component to the effect that the at least one technical function is selectively impaired, wherein the self-test unit is designed to monitor operating parameters of the system component and to respectively generate a warning signal which indicates impairment of the respective at least one technical function, and wherein the verification control unit is designed to compare the warning signals generated by the self-test unit with expected warning signals on the basis of the impaired technical functions.

An abnormality detection method of an encoder includes an output step, a control step, an information acquisition step, and an abnormality determination step. The abnormality determination step compares command position information with detection position information of a motor calculated based on an output signal, and determines that the encoder is abnormal in a case where a difference between the command position information and the detection position information of the motor is equal to or more than a predetermined value.

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.

An arc detection and intervention system for a solar energy system. One or more arc detectors are strategically located among strings of solar panels. In conjunction with local management units (LMUs), arcs can be isolated and affected panels disconnected from the solar energy system.

A fault notification system comprises a plurality of tower sensor units and a central processing element. Each tower sensor unit includes a tower safety sensor and a tower processing element. The tower safety sensor monitors a rotation angle of a mobile tower and output a signal that varies according to the rotation angle. The tower processing element is configured to receive the signal, compare a signal level of the signal with a range of signal levels indicating a normal rotation angle, and transmit a message that a fault has occurred and request that each drive motor shut down if the level of the signal is out of the range indicating a normal rotation angle. The central processing element is configured to receive the message from the tower processing element and transmit a signal to each tower processing element to output a signal to instruct each drive motor to shut down.

In the disclosure, a failure of a device performing work while moving is more reliably detected while the data amount of failure diagnosis data is reduced. The disclosure includes a frequency analyzing part which performs a frequency analysis on acquired data from an acceleration sensor; a maximum frequency detecting part which detects a maximum frequency from a result of the frequency analysis; and a failure diagnosis data generating part which sets a frequency twice or more of the maximum frequency as a sampling frequency, samples the acquired data from the acceleration sensor, and generates the failure diagnosis data.