A computer-implemented method of predicting vehicle failures comprises: receiving, at a processing stage: i) a vehicle diagnostics dataset, which records historic diagnostic warning events and an associated timing for each diagnostic warning event, and ii) a vehicle fault dataset, which records historic vehicle fault events and an associated timing for each vehicle fault event, wherein the diagnostic warning events and vehicle fault events are associated in their respective datasets with cooperating vehicle identifiers; wherein a predictive algorithm executed at the data processing stage determines whether or not each diagnostic warning event of a target type is time-associated with a diagnostic warning event in that its associated timing is within a predetermined time window relative to that of any vehicle fault event associated with a matching vehicle identifier, and computes, based thereon, a significance value for the target type of diagnostic warning event, the significance value denoting the likelihood of a vehicle fault event occurring should a diagnostic warning event of the target type occur.

An online monitoring device of 3D printing equipment includes a signal collection module, a signal processing module, a feature extraction module, a monitoring module and a knowledge base module. A vibration signal of a preset component of the 3D printing equipment is collected by a vibration sensor. The collected vibration signal of each preset component is converted from an analog signal to a digital signal and the spectrum characteristics are extracted. Based on the spectrum characteristics of each preset component, the operation state type of the preset component is obtained by a comparative analysis model. The knowledge base module is configured to store newly added samples and initial samples of the 3D printing equipment. The initial samples include spectrum characteristic information and corresponding fault category of known faults, and the newly added samples include spectrum characteristic information and corresponding fault category of new faults.

The systems and methods provide an action recognition and analytics tool for use in manufacturing, health care services, shipping, retailing, restaurants and other similar contexts. Machine learning action recognition can be utilized to determine cycles, processes, actions, sequences, objects and or the like in one or more sensor streams. The sensor streams can include, but are not limited to, one or more video sensor frames, thermal sensor frames, infrared sensor frames, and or three-dimensional depth frames. The analytics tool can provide for establishing traceability.

An estimating device includes a storage unit that stores in association with each other state history information showing, as a history, a state of electrical equipment in which an abnormality has occurred, and cause history information showing, as a history, a cause of the abnormality, an acquisition unit that acquires state information indicating the state of the electrical equipment in which the abnormality has occurred, a detection unit that detects, from among a plurality of the state history information stored in the storage unit, at least one of the state history information that is similar to the state information acquired by the acquisition unit, and a notification unit that issues a notification concerning the cause of the abnormality, on the basis of the cause history information that is associated with the state history information detected by the detection unit.

A monitoring system for a heating, ventilation, and air conditioning (HVAC) system of a building receives, from a monitoring device located at the building, a frequency domain representation and a time domain current value that are based on an aggregate current supplied to a plurality of components of an indoor air handler of the HVAC system. The monitoring system assesses, based on the received frequency domain representation and time domain current value, whether a first fault has occurred in a first component of the plurality of components of the indoor air handler and whether a second fault has occurred in a second component of the plurality of components of the indoor air handler. The monitoring system generates and transmits an alert in response to assessing occurrence of at least one of the first fault and the second fault. The monitoring system is located remotely from the building.

A valve controller for controlling a valve and a valve comprising the valve controller are disclosed. The valve comprises an actuator and a flow controlling unit. The valve controller comprises equipment for controlling the function of at least one of the actuator and the flow controlling unit. The valve controller is further configured to obtain one or more first parameter values indicative of a functionality of the equipment at startup of the valve controller. The valve controller is configured to monitor the equipment during operation of the valve controller for determining one or more second parameter values indicative of the functionality of the equipment and determining if a change in functionality of the equipment has occurred based on a comparison of the one or more second parameter values with the one or more first parameter values.

An industrial machine is an industrial machine which has a history recording function, and includes: a manual pulse generator which includes a handle for manually operating the position of a drive axis in the industrial machine by an operator; a drive axis control unit which controls the drive axis according to the operation of the handle; a handle operation determination unit which determines the operation of the handle; and an operation history recording unit which records, as an operation history, the operation of the handle determined with the handle operation determination unit, and when the number of rotations of the handle exceeds a threshold value, the handle operation determination unit determines the operation of the handle, and the operation history recording unit records, as the operation history, the operation of the handle.

A process device with diagnostics for use in an industrial process includes a process variable sensor or controller element which is configured to sense or control a process variable of a process fluid of the industrial process. Circuitry is coupled to the process variable sensor or control element and configured to measure or control a process variable of the industrial process. A wireless communication adapter includes wireless communication circuitry configured to communicate in the industrial process. The wireless communication circuitry is further configured to receive a process signal from another process device. Diagnostic circuitry is configured to diagnose operation of the industrial process as a function of the sensed process variable and the received process signal.

A communications module for a household device includes a sensor device that is configured to be attached in the region of a device housing of the household device, a wireless data interface and a processor. The sensor device is configured to scan an emission signal, penetrating outwards through the device housing, of a component of the household device carrying out the operating process of the household device. The processor is configured to determine an operating state of the household device based on measurement values of the sensor device and to provide same by means of the data interface. In addition, the communications module can be used optionally in different types of household devices.

Disclosed herein are techniques for automatically distributing device identification amongst components of a process control loop in a process plant while the loop is communicatively disconnected from the plant's back-end environment or control room. A field device's identification is stored in a memory of a component of the loop (which may be the field device or a proxy) and is used for commissioning the field device. While the loop remains disconnected, the field device's identification is distributed to the memory of another component of the loop and used for commissioning a portion of the loop including the field device and the another component. Additional distribution to other components for commissioning other loop portions is possible. Distribution may be triggered by the completion of certain commissioning activities, the establishment of communicative connections between components, and/or other conditions. Other parameters and/or information descriptive of the field device may be similarly distributed.