Abstract: An abnormality detection device detects an abnormality of a device based on time-series data acquired from a device having a movable part. The abnormality determination device determines whether time-series data at a specific time have increased or decreased with respect to time-series data from a certain time prior to the specific time as the specific time is shifted, indicates an increase or decrease of the time-series data by defined numerical values, and detects an abnormality of the device based on integrated values obtained by integrating the defined numerical values.

Abstract: A motor malfunction monitoring device for monitoring a malfunction of a drive motor, includes: vibration sensors for detecting for one or more components of the drive motor transverse vibration in a direction parallel to a mounting plane of the drive motor and perpendicular to a longitudinal direction of the drive motor or longitudinal vibration in a direction perpendicular to both the mounting plane and the longitudinal direction of the drive motor; a voltage sensor for detecting a voltage of the drive motor or a current sensor for detecting a current of the drive motor; and a data storage storing a database of normal operation spectrums of one of the transverse vibration or the longitudinal vibration during a normal operation of the drive motor, and of one of the voltage or the current during a normal operation of the drive motor.

Abstract: In one embodiment, a device comprises interface circuitry and processing circuitry. The processing circuitry receives, via the interface circuitry, a video stream captured by a camera during performance of an industrial process, wherein the video stream comprises a sequence of frames; detects, based on analyzing the sequence of frames, a degree of particle scatter that occurs during performance of the industrial process; and determines, based on the degree of particle scatter, that an anomaly occurs during performance of the industrial process.

Abstract: A method and device for controlling an air conditioner, and a computer readable storage medium. The method for controlling an air conditioner includes: upon detecting a power-on or power-off command corresponding to an internal unit of a central air conditioner, acquiring a current predicted load of the central air conditioner; determining whether the predicted load meets an external unit change condition; and if so, adjusting an operating state of an external unit of the central air conditioner on the basis of the predicted load.

Abstract: An air conditioner control method and apparatus, and a computer-readable storage medium. The air conditioner control method includes: determining whether a time interval between the current moment and a preset moment at which work is started is less than or equal to the maximum early start duration; if the time interval is less than or equal to the maximum early start duration, acquiring a preliminary demand load corresponding to a central air-conditioner, and acquiring a startup combination load corresponding to the central air-conditioner; and based on the startup combination load and the preliminary demand load, determining a start moment of a host to be started.

Abstract: Example implementations as described herein are directed to generate a fault tree with a design document and minimized rules or database. The fault tree generation system may utilize assembly data and ladder programs as input and generates a fault tree by connecting an upper part of the fault tree generated from an assembly tree structure in the assembly data and a lower part of a fault tree from control logic in the ladder program. The fault tree is generated by connecting the lower part of the tree of the fault tree from the logic.

Abstract: Drilling rig operations may be monitored using a variety of sensors and/or other data sources. Erroneous, faulty, and/or missing data may be cleansed prior to using the data for modeling and/or monitoring drilling operations. Erroneous, faulty, and/or missing data may be identified by comparing received data to anticipated values based on historical operations, other physically related sensor readings, and known operating ranges. Cleansing may comprise replacing erroneous, faulty, and/or missing data with a modeled value or omitting a reading entirely.

Abstract: A template for assigning the most probable root causes for wafer defects. The bin map data for a subject wafer can be compared with bin map data for prior wafers to find wafers with similar issues. A probability can be determined as to whether the same root cause should be applied to the subject wafer, and if so, the wafer can be labeled with that root cause accordingly.

Abstract: A method of managing system health is provided. The method includes calculating a reconstruction missing value with respect to the second domain data, determining a degree of degradation of the system on the basis of the reconstruction missing value, predicting a second remaining useful life (RUL) prediction value {tilde over (y)} of the system on the basis of the second domain data, based on a result of the determination of the degree of degradation, optimizing a degradation compensation function on the basis of a distribution of a first RUL prediction value y of the system predicted based on the first domain data in a pre-learning process of the diagnosis model, and predicting a final RUL prediction value {tilde over (y)}? obtained by compensating for the second RUL prediction value {tilde over (y)}, by using the optimized degradation compensation function.

Abstract: A vehicle health monitoring system monitors the health of components for ground vehicles and accounts for the impact of changing engine RPM, a multi ratio gearbox, and the variable ratio encountered in vehicles having a differential. The vehicle health monitoring system may incorporate regime recognition that determines the vehicle state, e.g., the engine RPM, transmission gear ratio, whether its accelerating (or turning), so that a decision can be made whether the vehicle is in an appropriate regime for data acquisition for a monitored vehicle of the component, and if so, what type of configuration to use for analyzing the component for determining a condition indicator for that component. The configuration describes the ratio from a given tachometer to a shaft under analysis, and which, if any, gears/bearings are associated with the shaft.

Abstract: Techniques are provided for adaptive sensor position determination for multiple mobile sensors.

Abstract: An automatic robot control system and methods relating thereto are described. These systems include components such as a touch screen panel (“TSP”) robot controller for controlling a TSP robot, a camera robot controller for controlling a camera robot and an audio robot controller for controlling an audio robot. The TSP robot operates inside a TSP testing subsystem, the camera robot operates inside a camera testing subsystem, and the audio robot operates inside an audio testing subsystem. Inside the audio testing subsystem, an audio signals measurement system, using a bi-directional coupling, controls the operation of the audio robot controller. In this control scheme, a test application controller is designed to control the different types of subsystem robots. Methods relating to TSP, camera, and audio robots, and their controllers, taken individually or in combination, for automatic testing of device functionalities are also described.

Abstract: A refuse vehicle includes multiple systems, each system including a sensor. The refuse vehicle also includes an automated check system. The automated check system includes processing circuitry configured to obtain sensor data from the sensor of each of the multiple systems, determine which of the multiple systems require manual inspection based on the sensor data, and operate a display screen to prompt a technician to manually inspect one or more of the multiple systems.

Abstract: A system, method, and computer readable storage device are provided for providing a dynamic tachometer. Based on various signal inputs from a plurality of data sources, a tachometer may be dynamically modified to include visual information and assistance to the driver in relation to the vehicle's engine speed (i.e., revolution speed of the vehicle's crankshaft). The tachometer may include one or a combination of: dynamic shift point indicators, a target engine speed range indicator, an overspeed indicator, and a power take-off mode indicator.

Abstract: Disclosed is a method for predicting collision severity, including: establishing a first learning model, and inputting vehicle data and collision accident scene feature data into the first learning model; obtaining a predicted collision acceleration curve outputted by the first learning model, the predicted collision acceleration curve being established based on a plane rectangular coordinate system; establishing a second learning model, and inputting the predicted collision acceleration curve, the occupant feature data and the restraint system feature data into the second learning model; obtaining a plurality of predicted collision kinematics and dynamics curves of human body parts outputted by the second learning model; generating a collision severity parameter according to the plurality of predicted collision kinematics and dynamics curves of the human body parts, the collision severity parameter being configured to evaluate the collision severity.

Abstract: A plant or a group of plants in a grow facility may be registered for tracking based on a corresponding unique plant identifier (UPI) feature set as extracted from one or more images captured by a plurality of image sensors monitoring the grow facility. One or more locations of the plant or the group of plants in the grow facility at one or more dates and times may be identified based on the corresponding UPI feature set as the plant or the group of plants grow in the grow facility. The plant or the group of plants may be de-registered from being tracked based on the corresponding UPI feature set when the plant or the group of plants reaches an end of a growth cycle in the grow facility. Alternatively, visual identifier devices and/or regions of interest (ROIs) may be used with or without UPI feature sets for such tracking.

Abstract: Well completion design data for completing plural stages of a well completion operation is accessed. Predicted component life intervals for each of a plurality of components of a frac fleet are accessed. Remaining component life intervals for each of the plurality of components of the frac fleet are determined based on the predicted component life intervals. A continuous completion event for the well completion operation is set based on the remaining component life intervals for each of the plurality of components. The continuous completion event includes a continuous pumping block identifying one or more contiguous stages from among the plurality of stages during which the well completion operation is performed with the frac fleet, and a maintenance block identifying one or more of the plurality of frac pumps to be subject to predetermined maintenance operations upon completion of the one or more contiguous stages of the continuous pumping block.

Abstract: A method for a metrology process, the method includes obtaining first measurement data relating to a first set of measurement conditions and determining a first measurement recipe based on the first measurement data. At least one performance indicator is determined from one or more components of the first measurement data obtained from a component analysis or statistical decomposition. Alternatively, at least one performance indicator is determined from a comparison of one or more first measurement values relating to the first measurement recipe and one or more second measurement values relating to a second measurement recipe, where second measurement recipe is different to the first measurement data and relates a second set of measurement conditions, the second set of measurement conditions being different to the first set of measurement conditions.

Abstract: Systems, methods, and computer-readable media are disclosed for monitoring and diagnosing power system assets. An example method may include triggering, by a gateway device and at a first time, a capture of a first waveform from a first intelligent electronic device (IED) associated with a first asset in a power system. The method may also include transmitting, by the gateway device, the capture of the waveform to a remote device. The method may also include extracting fault features from the first waveform corresponding to different failure modes associated with the asset of the power system. The method may also include determining, based on the features extracted from first waveform, that a fault of a first fault mode has occurred in the asset. The method may also include providing an alert that the fault has been identified, wherein the alert initiates or otherwise facilitates a control action in the power system.

Abstract: A method for collecting error code history includes detecting a fault caused by errors in a machine, initiating a dispatch request from the machine to a service location, generating a first quick response code in response to a first input signal from a technician, where the first quick response code encodes first configuration items that describe the machine and first error codes that characterize the detected errors, presenting a first graphical image of the first quick response code on a display, performing a self-test in the machine in response to a second input signal, generating a second quick response code after the self-test has been completed, where the second quick response code encodes second configuration items that describe the machine and second error codes, and presenting a second graphical image of the second quick response code on the display.

Abstract: A device (11) for providing audio and/or video content to a media rendering device over a physical connection and controlling one or more wireless lighting devices (31,32) to render light effects based on an analysis of the audio and/or video content is configured to obtain relative distance information (201-204). The relative distance information is indicative of distances between the device and each of a plurality of wireless lighting devices (31-34). The device is further configured to select, based on the relative distance information, the one or more wireless lighting devices from the plurality of wireless lighting devices, perform the analysis of the audio and/or video content, determine the light effects based on the analysis of the audio and/or video content, and control the selected one or more wireless lighting devices to render the light effects.

Abstract: A method performed by a first computing system includes receiving, from a second computing system, a message identifying a symptom of a first vehicle; and sending a repair tip to the second computing system. The repair tip includes a first phrase describing a first procedure performed on a second vehicle that exhibited the symptom, wherein the first procedure performed on the second vehicle yielded a result insufficient to determine that a component of the second vehicle associated with the symptom is defective. The repair tip also includes a second phrase describing a second procedure performed on a given vehicle, wherein the given vehicle is either (i) the second vehicle or (ii) a third vehicle that also exhibited the symptom, wherein the second procedure performed on the given vehicle yielded a result sufficient to determine that a component of the given vehicle associated with the symptom is defective.

Abstract: Technologies are provided for identifying individuals having a risk of non-adherence to or from a prescribed treatment program; for predicting and the risk, which may be determined as a forecast over a future time span; and evaluating it to further determine or invoke specific actions to mitigate the risk or otherwise improve likelihood of compliance. A singular spectrum analysis (SSA) is utilized to analyze temporal properties of a time series determined from measured or observational data to determine an emergent pattern. Based on this pattern, a risk of non-adherence, including relapse or absconding, over a future time interval by the individual may be determined and utilized to implement an intervening action.

Abstract: A graphical user interface of a medical patient monitoring system allows clinical personnel to view and manipulate historical patient data in ways not available in traditional patient monitoring systems. The graphical user interface allows zooming in or out on the historical patient data, with a format of the data adjusted at certain zoom levels. A plurality of lanes of displayed historical patient data may be displayed in the graphical user interface, and a plurality of signals may be displayed in a single lane. An electrocardiogram strip view may be enabled to present historical patient data in the form of a traditional strip view if desired.

Abstract: A method for configuring a modular industrial plant using an engineering tool includes using a plant engineering facility of the tool to create a representation of the modular industrial plant identifying modules to be orchestrated in the modular industrial plant. The modules include at least one function module that includes control software for the modular industrial plant. The method further includes using a module engineering facility of the tool to configure the function module for use in the modular industrial plant by editing a placeholder configuration file created by the tool for defining the configuration of the function module. Editing the configuration file causes a representation of the function module in the plant engineering facility to be automatically updated to reflect adaptations made to the function module using the module engineering facility. The method includes instructing the tool to assign the function modules so configured to the modular industrial plant.

Abstract: The disclosure herein describes enables new sensors to be added and maintained in an Internet of Things system without upgrading firmware for the end device. A sensor abstraction layer (SAL) manages the end sensors, and a sensor definition layer (SDL) in the cloud interfaces with the SAL. Sensor definition data of a sensor connected to the end device is identified in a sensor definition data store of the SDL including sensor configuration data. The sensor configuration data is sent to the SAL, wherein the SAL is configured to collect sensor data from the sensor via a sensor interface. Sensor data is received from the SAL via an established network connection and converted into converted sensor data based on a data conversion model of the sensor definition data. The converted sensor data is then provided to an application, connected to a sensor management device, for consumption.

Abstract: According to an embodiment, an information processing apparatus includes one or more processors. The processors are configured to: generate a plurality of shuffle maps obtained by randomly shuffling, from positions to others, at least some of subject values contained in a subject map having the subject values arrayed in N dimensions (N is an integer of 1 or more); generate a subject vector expressing features of a frequency domain of the subject map and random vectors expressing features of respective frequency domains of the shuffle maps; and derive, as an evaluation value for whether the subject map has a random characteristic, a testing result of statistical hypothesis testing on feature differences between the subject vector and the respective random vectors.

Abstract: An example method for outputting a PID filter list (PFL) includes: receiving RO data from one or more ROs that indicate particular vehicle identifying information (PVII), at least one symptom identifier, and a particular vehicle component; determining, symptom-to-parameter-identifier (PID) mapping data (MD) based on the received RO data and component-to-PID MD; determining, based on the set of available PIDs for the SOV and the symptom-to-PID MD, a PFL, wherein the PFL is associated with the PVII and the at least one symptom identifier, and wherein the PFL indicates a symptom-based subset of PIDs from the set of available PIDs for the SOV; receiving, a request sent over a communication network from a display device, wherein the request comprises the PVII and the at least one symptom identifier; and transmitting, over the communication network to the display device, a response to the request, the response comprising the PFL.

Abstract: A method, system, and computer program product for learning parameters of Bayesian network using uncertain evidence, the method comprising: receiving input comprising graph representation and at least one sample of a Bayesian network, the graph comprising plurality of nodes representing random variables and plurality of directed edges representing conditional dependencies, wherein each of the at least one sample comprising for each node a value selected from the group consisting of: a known value; an unknown value; and an uncertain value; and applying on the input a Bayesian network learning process configured for calculating estimates of conditional probability tables of the Bayesian network using probabilities inferred by applying on the input a Bayesian network uncertain inference process configured for performing inference in a Bayesian network from uncertain evidence.

Abstract: The invention relates to a rail system as a track for suitable running gears and also to the running gear for a carrier roller diagnostic system, wherein the rail system is formed from a closed profile or tube. The rail system according to the invention comprises at least one running rail (2), a multi-part track holder (1) and a holding element (14) which is arranged with a first region (A) in a running rail support (13) of the track holder (1) and is arranged with a second region (B) in the running rail (2) when the running rail (2) and the running rail support (13) are connected to one another in the longitudinal direction, wherein the second region (B) of the holding element (14) is arranged in a passage opening (21) of the running rail (2) or projects through it.

Abstract: The present disclosure relates to a device and method for detecting vertical misalignment of a vehicle radar device and vehicle radar device with the same. A radar device according to an embodiment determines a monitoring range including the ground in front by using the radar signal, determines an error of vertical angles for a number of ground distances within the monitoring range, and detects the vertical mounting misalignment of the radar device by using the error. According to embodiments, it is possible to accurately determine the vertical mounting misalignment of the radar device even if there is a road surface non-uniformity, road slope, or radar beam width change.

Abstract: A method of controlling an electronic apparatus is provided. The method includes the steps of receiving measurement values for the state of air displayed on a plurality of external electronic apparatuses from each of the plurality of external apparatuses, calculating rates of change of the measurement values for each of the plurality of external electronic apparatuses based on the received measurement values, identifying external electronic apparatuses of which differences of the calculated rates of change belong to a predetermined range among the plurality of external electronic apparatuses, correcting the measurement values received from at least one external electronic apparatus among the identified external electronic apparatuses such that the measurement values received from the identified external electronic apparatuses become the same as one another, and transmitting information related to the corrected measurement values to the at least one external electronic apparatus.

Abstract: Disclosed is an integrity index detecting method for a device by means of a control output signal including an integrity information collecting step S10 of measuring and collecting a time interval between a control output signal and a subsequent control output signal; a defect information collecting step S20 of measuring and collecting a time interval between a control output signal and a subsequent control output signal; a setting step S30 of setting an integrity reference value and a defect reference value for the time interval between the control output signals; a detecting step S40 of measuring and collecting the time interval value between a control output signal and a subsequent control output signal; and an outputting step S50 of outputting the integrity index value detected in the detecting step S40 to provide the integrity index value to the manager.

Abstract: An example method of enforcing granular access policy for embedded artifacts comprises: detecting an association of an embedded artifact with a resource container; associating the embedded artifact with at least a subset of an access control policy associated with the resource container; and responsive to receiving an access request to access the embedded artifact, applying the access control policy associated with the resource container for determining whether the access request is grantable.

Abstract: One or more processors may detect that an extreme event that occurred in a first region. One or more processors may determine that the extreme event creates a drift in a probability distribution that is an output of a model associated with the first region. One or more processors may retrain the model associated with the first region using data associated with the extreme event. One or more processors may identify a second region similar to the first region according to a defined correlation threshold. One or more processors may generate data representing potential extreme scenarios for the second region based on the detected extreme event in the first region. One or more processors may retrain a model associated with the second region based on the generated data representing potential extreme scenarios.

Abstract: A system and method for predicting maintenance and providing optimized operational performance in industrial operations on a Metaverse platform, is described. In one aspect, the system implements AI/ML engines for anomaly detection and predictive analytics to control future failures, facilitate planned maintenance, and provide actionable recommendations to control future failures. The system combines data with AR/VR-based digital twin solutions for real-time troubleshooting and maintenance training. The system detects anomalies in industrial assets using sensor and IIoT data and provides predictive analytics for capturing failures and actionable recommendations, provides improved overall equipment effectiveness, enhanced device and system utilization, simulation of processes using data, and prescription uptime plans, achieving superior productivity gains and predictable uptime.

Abstract: A system includes a processing device, operatively coupled to the memory device, to perform operations comprising obtaining a plurality of sensor values associated with a deposition process performed, according to a recipe, in a process chamber to deposit film on a surface of a substrate; generating a manufacturing data graph based on the plurality of sensor values; receiving, via a user interface, a selection of a data point on the manufacturing graph; receiving failure data associated with the data point; and storing, in a data structure, the failure data to be accessible via the user interface presenting the manufacturing data graph.

Abstract: The present disclosure relates to systems and methods for calculating noise distributions in an electric power system. In one embodiment, a system to calculate a noise distribution in an electric power system may comprise a measurement subsystem to obtain a plurality of raw measurements of a parameter in the electric power system. A noise distribution determination subsystem may be configured to generate a plurality of scaled raw measurements from the plurality of raw measurements, generate a power spectrum density from the plurality of scaled raw measurements, generate a cumulative distribution from the power spectrum density, and determine a noise distribution from the power spectrum density. A protective action subsystem may monitor the parameter in the electric power system to identify a signal of interest by utilizing, at least in part, the noise distribution and generating a control action in response to the signal.

Abstract: A method for estimating the aging of an electronic component, characterized in that it includes the following steps: —compiling a thermal specification of the electronic component in order to determine a reference lifetime, —determining a reference temperature quantity, —measuring the actual temperature of the electronic component in operation, —determining an actual temperature quantity, —determining an equivalent operating time at the actual temperature, —transposing this equivalent operating time to the reference temperature to obtain a transposed operating time, —summing the transposed operating times to obtain a consumed lifetime comparable to the reference lifetime.

Abstract: A system and method of variable velocity control of an instrument by a computer-assisted device includes a computer-assisted device that includes an actuator and one or more processors. To perform an operation with an instrument coupled to the computer-assisted device, the one or more processors are configured to set a velocity set point of the actuator to an initial velocity, monitor force or torque applied by the actuator to actuate the instrument, when the applied force or torque is above a first force or torque limit, determine whether a total duration of a set of pauses occurring during the operation of the instrument is below a maximum pause threshold, and in response to determining that the total duration is below the maximum pause threshold, pause the operation of the instrument.

Abstract: A system that includes one or more sensors installed in proximity to a machine configured to collect raw signals associated with an environment of the machine, are multi-layer spatial data that include time-stamp data. The system may include a processor in communication with the sensors and programmed to receive one or more raw signals, denoise the one or more raw signals to obtain a pre-processed signal, extract one or more features from the pre-processed signals, classify the one or more features to an associated class, wherein the associated class includes one or more of a normal class, abnormal class, or a potential-abnormal class, create fusion data by fusing the one or more features utilizing the associated class and the time-stamp data, and output a heat map on an overlaid image of the environment.

Abstract: A method for forecasting part sales, including collecting sales data for a part over a series of sales time periods and collecting activity data for a plurality of activity types over a series of activity time periods for a plurality of machines including the part. A mean activity time can be calculated for each activity type for each time period in the series of activity time periods based on the collected activity data. An activity probability density function of the mean activity times for each activity type is created and a machine learning model is trained using an expectation of activity derived from the probability density functions for each activity type and the collected sales data. Machine activity data for a set of machines can be fed into the trained model to derive a part sales probability density function for the set of machines.

Abstract: An information processing device includes a controller configured to acquire a record of a predetermined action for maintaining a commercial value of a first vehicle by a first user who rents the first vehicle from a first service that is a vehicle rental service, and provide an incentive to the first user when the record of the predetermined action is at a level equal to or higher than a predetermined reference.

Abstract: A system for monitoring cutting devices in a packaging production line having a line for supplying a material to be cut, an area of a predetermined type of cutting device, and a packaging output line is provided. The system includes means for counting cutting actions of the cutting device, configured to provide a time series of cutting action counting data, a video camera to frame an area of the output line, the video camera configured to provide video data of packaging elements in the output line, first code means, configured to run, on a computer, a first algorithm for recognizing cutting defects starting from video data, the first algorithm providing defect recognition data, and second code means, configured to run, on the computer, a trained expert algorithm to predict cutting performance degradation based on historical defect recognition data, time series of cutting action counting data, and type of cutting device.

Abstract: Techniques are provided that may include receiving sensor data from one or more machine sensors, the sensor data indicating machine failure. Informational data about current repair technician backlog, shop availability backlog, and parts availability are retrieved and inputted to a machine learning model for computing an estimated time to when the failed machine will be repaired. Customer data and dealer site data are retrieved and an estimated financial impact from a potential loaner machine is computed. The various computed and retrieved data are inputted to a decision tree algorithm, which computes an optimal solution for maintaining customer productivity. The network-accessible dealer site is notified of the optimal solution, which is intended for the customer.

Abstract: In various examples, upon receiving data comprising a plurality of key performance indicators (KPIs), an anomaly may be detected in a first KPI. An engine may apply rules associating two or more KPIs together to confirm, reject, or narrow the anomaly in the first KPI. Through this technology, the mean time for detecting an anomaly in a network may be reduced thereby preventing the potential for more serious anomalies in the network.

Abstract: An embodiment is power module including a plurality of first switching elements of a first type semiconductor on a first substrate, a plurality of second switching elements of a second type semiconductor and a third switching element of the first type semiconductor or the second type semiconductor on a second substrate, wherein the first substrate has a different thermal conductivity than the second substrate, and a connection spacer configured to electrically connect the first substrate and the second substrate.

Abstract: A computer-implemented method for determining an abnormal technical status of a technical system includes: receiving, from the technical system, a plurality of signals, each signal being sampled over time and reflecting the technical status of at least one system component; computing, for each signal with associated high and low alarm thresholds obtained from an alarm management system, at every sampling time point, a univariate distance to its associated alarm thresholds as a maximum of the distances between a value of the respective signal and its associated alarm thresholds to quantify a degree of abnormality for the respective at least one system component; computing, at every sampling time point, based on the univariate distances at the respective sampling time points, an aggregate abnormality indicator reflecting the technical status of the technical system; and providing, to an operator, a comparison of the aggregate abnormality indicator with a predetermined abnormality threshold.

Abstract: A system and method of variable velocity control of an instrument by a computer-assisted device includes a computer-assisted device that includes an actuator and one or more processors. To perform an operation with an instrument coupled to the computer-assisted device, the one or more processors are configured to set a velocity set point of the actuator to an initial velocity, monitor force or torque applied by the actuator to actuate the instrument, when the applied force or torque is above a first force or torque limit, determine whether a total duration of a set of pauses occurring during the operation of the instrument is below a maximum pause threshold, and in response to determining that the total duration is below the maximum pause threshold, pause the operation of the instrument.

Abstract: Examples of the present disclosure relate to a system, method, and computer-readable medium for link anomaly detection across an inter-processor link in an infotainment system of a vehicle. In an example, the system includes a first processor, a second processor, and an inter-processor link to connect the second processor to the first processor. The system may include an anomalous detector and corrector module (ADCM) located on at least one of the first processor and the second processor, the ADCM to monitor a data exchange over the inter-processor link and initiate a correction action in response to an identification that the data exchange over the inter-processor link is anomalous.