A sensor device using verification includes a sensor component and a verification component. The sensor component is configured to generate first data and second data. The verification component is configured to analyze the first data and the second data and generate verification data based on the first data and the second data.

A method for monitoring a primary variable is carried out in a device having access to a set of sensors. The method includes the steps of receiving, from a network service, a series of forecasted values for the primary variable, each forecasted value being associated with one of a series of future time points; for at least one of the future time points, predicting a value for the primary variable using data of at least one secondary variable captured by a subset of the set of sensors, comparing the predicted value to the forecasted value associated with the future time point, and switching to a different subset of the set of sensors, if the predicted value deviates from the forecasted value with more than a specified threshold value.

A method for providing output values with associated uncertainties for a flexible modular plant or machine comprising an arrangement of modular entities, wherein uncertainty information associated with an operation of the modular entity is assigned to a plurality of modular entities and input values are provided based on an operation of the modular entities, where a computing unit calculates an output value based on said input values, calculates an input value uncertainty for each input value based on the uncertainty information of the modular entity, and calculates at least one output value uncertainty associated with the output value based on propagation of uncertainty and using the input value uncertainties, and where the output value and the at least one output value uncertainty are output.

A detection system and detection method for the sensors of a robot. A detection system installs three sensors at the motor side and power output terminal of the robot. A detection unit detects the normal or abnormal state of three sensors to index the abnormal sensor for maintenance, and two normal sensors are selected for keeping the robot safety operation without stop.

In one embodiment, a system may include a multi-purpose sensor coupled to a machine operating in an industrial environment. The multi-purpose sensor may include a camera that obtains a first and second set of image data including images of the machine and an environment surrounding the machine. The first set of image data is associated with a baseline of the machine and the environment, and the second set of image data is acquired subsequent to when the first set is acquired. The system may include a computing device that may include a processor to receive the first and second set of image data, determine baseline positions of objects in the first set, determine subsequent positions of the objects in the second set, determine whether the subsequent positions vary from the baseline positions, and perform an action when the subsequent positions vary from the baseline positions.

A system and method for performing management and diagnostic functions in an advanced process control (APC) system. An APC management computer retrieves operating process data from an APC control computer and performs an iterative step test on the APC system. The iterative step test modifies at least one test parameter of the operating process data and identifies changes to a set of remaining parameters of the operating process data resulting from modification of the test parameter. The APC management computer determines at least one process variable from the iterative step test and generates at least one process model based on the process variable. The APC management computer transmits the process model to the APC control computer.

A method for providing output values with associated uncertainties for a flexible modular plant or machine comprising an arrangement of modular entities, wherein uncertainty information associated with an operation of the modular entity is assigned to a plurality of modular entities and input values are provided based on an operation of the modular entities, where a computing unit calculates an output value based on said input values, calculates an input value uncertainty for each input value based on the uncertainty information of the modular entity, and calculates at least one output value uncertainty associated with the output value based on propagation of uncertainty and using the input value uncertainties, and where the output value and the at least one output value uncertainty are output.

Semi-closed control or fully closed control is selected as a control system for a joint using a motor configured to drive a joint of a robot arm via a reduction gear, an input-side encoder, and an output-side encoder, the semi-closed control being control in which an output of the input-side encoder is used, the fully closed control being control in which an output of the output-side encoder is used. A test run is performed plural times in which the robot arm is caused to perform a specific operation while semi-closed control is being performed on the joint, and semi-closed control or fully closed control is selected using outputs of the output-side encoder obtained in the test runs or in accordance with the content of a task that the robot arm is to be caused to perform.

An exoskeleton comprising a plurality of support structures, and a plurality of joint mechanisms each joint mechanism rotatably coupling at least two of the plurality of support structures. A sensor suite discrepancy detection system can be operable to interrogate the suite of sensors within the exoskeleton, and can comprise a plurality of sensor groups, each associated with a respective joint mechanism, and each comprising a plurality of sensors from a suite of sensors. A controller can be configured to recruit at least one substitute sensor from a first sensor group of based on an identified discrepancy between the sensor output data of at least two sensors within the first sensor group and a target sensor within the first sensor group, and to execute a remedial measure associated with a safety mode of the exoskeleton for safe operation of the exoskeleton.

An exoskeleton operable in a safety mode comprises a plurality of support structures, and at least one joint mechanism rotatably coupling two of the plurality of support structures, and a plurality of sensors associated with the at least one joint mechanism. The exoskeleton comprises a controller configured to generate a plurality of command signals according to a plurality of respective control policies, and configured to generate each command signal based on sensor output data from at least one sensor of the plurality of sensors, and configured to control operation of the at least one joint mechanism according to a selected control policy, of the plurality of control policies, based on at least one of an identified discrepancy between at least some of the plurality of command signals or a determination whether each of the plurality of sensors satisfies at least one self-test defined criterion defined criterion or a comparison criterion between the output signal of two or more sensors of the plurality of sensors, or both of these.