Abstract: A device for assisting molding condition determination includes a molding state data adjustment amount obtaining unit and a molding condition element adjustment amount obtaining unit. The molding state data adjustment amount obtaining unit obtains, using a first learning model, a molding state data adjustment amount having a value equivalent to a difference between molding state data detected by a sensor and a molding state data target value. The molding condition element adjustment amount obtaining unit obtains, using a second learning model, an adjustment amount for a molding condition element corresponding to the molding state data adjustment amount.

Abstract: A method for analyzing data provided by a robot system located in a plant. The method includes operating a plurality of robots in the robot system and collecting first level data concerning operating parameters of each robot while they are being operated. The method further includes analyzing the first level data in a first data collection device located in the plant using first level analyzation software, analyzing the analyzed first level data collected in a second data collection device using second level analyzation software, and analyzing the analyzed second level data collected in a third data collection device in the cloud using third level analyzation software. A web portal outside of the plant can be used to gain access to the analyzed third level data.

Abstract: An embodiment of the present disclosure discloses a method of process variation compensating through activation value adjustment of an analog binarized neural network circuit that may recover a decrease in recognition rate performance up to an almost perfect level, even if a binarized neural network is implemented as an analog circuit such that recognition rate performance is decreased due to process variation.

Abstract: A mobile vehicle diagnostic device (MVDD) for acquiring data about a vehicle, the device comprising: a housing configured to be mechanically coupled to the vehicle so that, when the housing is mechanically coupled to the vehicle, vibration generated by the vehicle during its operation causes the housing to vibrate; acoustic sensors disposed within the housing and configured to acquire sound generated by the vehicle during its operation, the acoustic sensors comprising first and second acoustic sensors respectively oriented in first and second directions, wherein the first and second directions are at least 30 degrees apart; at least one dampening device disposed in the housing and positioned to dampen vibration of the acoustic sensors caused by operation of the vehicle; and at least one vibration sensor disposed within the housing and configured to sense vibration in the housing caused by the operation of the vehicle.

Abstract: A failure diagnosing device diagnoses failure of a plurality of reduction gears of a mechanical apparatus which includes a plurality of operation parts, a plurality of motors, and the plurality of reduction gears. The failure diagnosing device includes an acceleration/deceleration period identifying module configured to identify an acceleration/deceleration period of operation of one of the plurality of operation parts, a motor current processing module configured to acquire a peak value of an amplitude of a frequency component of motor current in a specific frequency band of one motor that drives the one operation part, in the acceleration/deceleration period, and a determining module configured to determine whether a sign of failure exists in one of the reduction gears.

Abstract: A control apparatus includes: a management unit that updates internal state values for each control period with a state value generated in a subject to be controlled; a feature quantity extraction unit that calculates a feature quantity from a change of a second internal state value for each unit section determined according to a value of a first internal state value; and an abnormality detection unit that generates detection results indicating whether any abnormality has occurred in a subject to be monitored included in the subject to be controlled, on the basis of the feature quantity. The feature quantity extraction unit and the abnormality detection unit output the values of the first internal state value used to determine the unit section, in correspondence with the corresponding unit section.

Abstract: A method is provided for maintaining an onboard reasoner for diagnosing failures on an aircraft that includes aircraft systems configured to report faults to the onboard reasoner. The method includes accessing diagnostic data received from an onboard computer of the aircraft that includes the onboard reasoner. An off-board reasoner builds an off-board diagnostic causal model that describes causal relationships between the failed tests and the diagnosed failure modes. The off-board diagnostic causal model is compared to the diagnostic data. Based thereon, a discrepancy is identified between the graph of the off-board diagnostic causal model, and the other graph of the onboard diagnostic causal model, to determine a new causal relationship relative to the known causal relationships. The onboard diagnostic causal model is updated to further describe the new causal relationship, including producing an updated model, and uploading the updated model to the onboard computer.

Abstract: A method is provided for diagnosing a failure on an aircraft that includes aircraft systems configured to report faults to an onboard reasoner. The method includes receiving a fault report at an onboard computer of the aircraft from an aircraft system of the aircraft systems, the fault report indicating failed tests reported by the aircraft system. The onboard reasoner accesses an onboard diagnostic causal model represented by a graph describing known causal relationships between possible failed tests reported by the respective ones of the aircraft systems, and possible failure modes of the respective ones of the aircraft systems. The onboard reasoner diagnoses a failure mode of the aircraft system or another of the aircraft systems, from the failed tests, and using a graph-theoretic algorithm and the onboard diagnostic causal model. A maintenance action is determined for the failure mode, and a maintenance message is generated including the maintenance action.

Abstract: A method for calculating a remaining useful life of an apparatus comprises the following steps. Time-series of previous runs and a current run of the apparatus are provided containing data of sensors configured to monitor parameters of the apparatus. An error occurs when a parameter breaches a threshold. Cumulative counts of errors occurring during a run are calculated. A linearly decreasing remaining useful life is calculated for previous runs. Breakdowns of the apparatus are mapped in an error space. Each dimension of the error space refers to one type of an error. The breakdown points are mapped at coordinates which represent cumulative error counts at the time of the breakdowns. A test point representing cumulative error counts of the current run is mapped. At least two nearest breakdown points to the test point are identified. The remaining useful life of the apparatus is calculated based on the nearest breakdown points.

Abstract: A system for predicting remaining useful life of a component implements a set of estimation models that generate future damage estimates for the component. The system detects damage to the component and estimates the magnitude of the current damaged. An error processor estimates the between each future damage estimate and the magnitude of current damage. A weight calculator calculates weights for the future damage estimates, wherein each weight is inversely proportional to the error. A fusion processor applies the weights respectively to future damage estimates of the estimators and combines the weighted future damage estimates.

Abstract: A system for monitoring rotating equipment. The system includes a sensor device that acquires vibration data, acoustic emission data, temperature data, and magnetic flux data of the rotating equipment. The sensor device includes base, holding frame, first integrated circuit, housing, and power source. The first integrated circuit includes a plurality of sensors and a microcontroller configured to receive vibration data, acoustic emission data, temperature data, magnetic flux data from plurality of sensors and determine anomalies of the rotating equipment. The system further comprises an application server that receives vibration data and magnetic flux data, determines revolutions per minute (RPM) data for rotating equipment, and diagnose faults based on processed vibration data and RPM data. The application server further generates a set of features and corresponding feature values and analyzes them to diagnose faults, and predict remaining useful life of the rotating equipment.

Abstract: Method for detecting at least one critical defect in a ceramic rolling element providing the steps of capturing a plurality of two-dimensional digital radiographic images of the ceramic rolling element; digitally filtering each radiographic image; delineating, on the basis of the filtered image, at least one region liable to comprise the critical defect; constructing stereoscopically a virtual model of the ceramic rolling element having the region; comparing the dimensions of the delineated region with a plurality of predetermined threshold values, and, when the dimensions are greater than the threshold values, generating an alarm signal.

Abstract: A method for monitoring at least one machine including causing at least a first sensor to acquire at least a first non-stationary signal from at least one machine operating in a non-stationary manner during at least one operational time frame, the at least first sensor providing at least a first non-stationary output, causing at least a second sensor to acquire at least a second non-stationary signal from the at least one machine during the operational time frame, the at least second sensor providing at least a second non-stationary output, fusing the at least first non-stationary output with the at least second non-stationary output to produce a fused output, extracting at least one feature of at least one of the first and second non-stationary signals based on the fused output, analyzing the at least one feature to ascertain a state of health of the at least one machine and performing at least one of a repair operation, maintenance operation and modification of operating parameters of the at least one machi

Abstract: This disclosure relates to a method and system for monitoring health and predicting failure of an electro-mechanical machine. In an embodiment, the method may include receiving a plurality of operational parameters with respect to the electro-mechanical machine and determining a set of features and a set of events, based on the plurality of operational parameters. The method may further include detecting one or more fault signatures associated the electro-mechanical machine based on at least one of the plurality of operational parameters, the set of features, or the set of events. The method may further include determining at least one of a time to the possible failure and a remaining useful life of the electro-mechanical machine based on at least one of the plurality of operational parameters, the set of features, the set of events, or the one or more fault signature, by using a hybrid machine learning model.

Abstract: The present technology relates to an image processing apparatus and method that allow to more accurately identify image processing target areas in an image. An image processing apparatus of the present technology includes a determination unit that determines, on the basis of reliability information indicating reliability of depth information, whether to make a determination on the basis of the depth information, the determination being as to whether an area is a target area for predetermined image processing, and the depth information indicating a depth of an image. The present technology can be applied to, for example, an imaging apparatus that captures a subject, a server that processes a captured image, etc.

Abstract: A method for operating a condition monitoring system of a vibrating machine in the form of a vibrating conveyor or a vibrating screen, it is provided that the condition monitoring system has at least one sensor designed for motion detection and/or acceleration detection, which is mounted on the vibrating machine. The sensor generates measurement data, which is further processed into characteristic values in a processing unit associated with the sensor. The characteristic values are stored as a data set or a plurality of data sets. The data sets and/or the data sets expanded to include metadata are transferred to a data storage and stored there. A knowledge base for an expert system is generated taking into account the information provided by the data sets and/or built on theoretical models.

Abstract: A method and system for monitoring a condition of a machine are provided. The machine monitoring system includes a housing mounted to a surface of a machine, a plurality of sensors configured to generate respective output signals for a parameter indicative of a condition of the machine, and a voting module positioned within the housing and configured to generate a corrected output based on the respective output signals. The machine monitoring system also includes a memory device including a store location configured to store manual input functions relating to a construction of the machine, a life calculator communicatively coupled to the voting module and the memory device wherein the life calculator is configured to determine a life remaining in the machine using the corrected output and the manual input functions, and a display positioned within the housing and configured to display the life remaining in the machine.

Abstract: A system and method for detecting a rotor fault condition in an AC induction machine is disclosed. The system includes a processor programmed to receive voltage and current data from an AC induction machine, generate a current frequency spectrum from the current data, and identify rotor-fault related harmonics in the current frequency spectrum. The processor is also programmed to calculate a fault severity indicator using the voltage and current data, identified rotor-fault related harmonics, and motor specifications, analyze the fault severity indicator to determine a possibility of rotor fault. The processor generates an alert based on the possibility of rotor fault.

Abstract: An evaluation method of a progressive-addition lens is provided. First, powers of the progressive-addition lens at a plurality of measurement points are measured to obtain an actually measured power distribution. Next, a comparison power distribution created based on the actually measured power distribution and a defective power distribution prepared in advance are compared with each other to perform similarity search between the both. Thereafter, whether or not the comparison power distribution and the defective power distribution are similar to each other is determined based on the result of the similarity search step, and if it is determined that the comparison power distribution and the defective power distribution are similar to each other, then the progressive-addition lens is evaluated as defective.

Abstract: A robotic system includes a humanoid robot with multiple compliant joints, each moveable using one or more of the actuators, and having sensors for measuring control and feedback data. A distributed controller controls the joints and other integrated system components over multiple high-speed communication networks. Diagnostic, prognostic, and health management (DPHM) modules are embedded within the robot at the various control levels. Each DPHM module measures, controls, and records DPHM data for the respective control level/connected device in a location that is accessible over the networks or via an external device. A method of controlling the robot includes embedding a plurality of the DPHM modules within multiple control levels of the distributed controller, using the DPHM modules to measure DPHM data within each of the control levels, and recording the DPHM data in a location that is accessible over at least one of the high-speed communication networks.

Abstract: A control systems and methods are presented for controlling a production system, in which a model-based planner includes a formulation, such as a SAT formulation representing possible actions in the production, with a solver being used to provide a solution to the formulation based at least partially on production and diagnostic goals and the current plant condition, and a translation component translates the solution into a plan for execution in the plant.

Abstract: A process for monitoring a machine, within the framework of a FMEA process for at least one component of the machine for at least one predetermined fault which can be diagnosed by means of a diagnosis diagram and a diagnosis system with sensors for detecting physical parameters of the machine, a diagnosis priority number being determined which is the product of the following index quantities: severity of the effect of occurrence of the fault with respect to the serviceability of the machine; expected machine-specific consequential costs when a fault occurs, and the possibility of correction of the fault. The diagnosis priority number is used in the evaluation of the diagnosis diagram, the diagnosis system, the current machine state, the necessary maintenance measures and/or the failure risk of the machine.

Abstract: A diagnostics system comprising a topological map of a target system that has nodes (38, 40, 42, 44, 46, 48) that correspond to components (29, 30, 32, 34, 36) of the target system and links that correspond to connections between the components. Associated with the topological map is a knowledge store (50) that has a structure that reflects or corresponds to that of the topological map. Included in this store (50) is a plurality of sections or libraries each of which is provided for storing design specific data associated with one of the nodes (38, 40, 42, 44, 46, 48) of the topological map. Data received from one or more sensors on the target system is included in the topological map, and used together with the design specific information in the knowledge store to diagnose faults.

Abstract: There is provided with a data analysis method, including: providing a database storing for each of devices an example that includes inspection time, the degradation level, operation characteristics, and replacement information; providing a evaluation maintenance strategy including an evaluative inspection time, an evaluation time and evaluative replacement condition; providing a prediction model for predicting the degradation level of a device from operation characteristics thereof; estimating by using the database an estimated number of devices that have already been replaced before the evaluation time, evaluating the degradation level at the evaluative inspection time of each of as many devices as estimated number and devices subjected to inspection of same periodic inspection time as the evaluation time; and evaluating the degradation level at the evaluation time of devices whose degradation level at the evaluation inspection time does not satisfy the replacement condition.

Abstract: A method and system for diagnosing a fault that includes a decision tree having a plurality of decision points wherein at least some of the plurality of decision points terminate in a resolution point representing a diagnosis for the fault. Also included is a plurality of queries each having at least a first response and a second response where each of the plurality of queries being associated with one of the plurality of decision points. The system also includes a knowledge base that includes a plurality of first images where each of the plurality of first images illustrate one of the first responses. A user interface is included for presenting the plurality of queries and the illustrative first images to a user. The user navigates the decision tree by responding to at least some of the plurality of queries by viewing the illustrative first images and basing a selection between the first response and the second response associated with said at least some of said queries on said illustrative first images.

Abstract: A system (830) and method (800) for diagnosing a malfunctioning machine. A fault event is selected (806) together with sequential operating parameter data (808) from a selectively focused time interval about the fault event for evaluation of a machine (810). The selectively focused time interval may include data occurring just before, just after, or spanning the fault event. Characterizing information such as slope, rate of change, and absolute sign of the data may be derived (809) from the operating parameter data over the selectively focused time interval and used in the diagnosis. The fault event and operating parameter data may be compared to existing cases in a case database (834). A set of rules (817) or candidate anomalies (841) may be executed over the operating parameter data to further improve the accuracy of the diagnosis.

Abstract: A method of improving the quality of manufactured modules includes logging manufacturing information to a database and utilizing a knowledge base to determine defects of a manufactured module. A quality ticket is issued for defective modules that is used to log and store defect symptom information in the database. Defects may be determined based on the quality ticket and by utilizing the knowledge base. Repair suggestions may be made and logged to the quality ticket based on the defect determination. Repairs are performed and repair actions logged to the quality ticket. Tests are then performed on the repaired modules. Based on the test results, the knowledge base is updated. In other words, the knowledge base learns over time as more modules, symptoms, defects and actions are tracked. The knowledge base aids during troubleshooting by providing a list of repair actions and frequency of such repair actions that successfully repaired the defect identified in the quality ticket.

Abstract: Control apparatus for a horizontal boring tool is described which drives a boring lance via boring rods. The tool includes an input interface for receiving actual values of controlled variables of the horizontal boring tool, and an output unit for issuing control signals for controlling the horizontal boring tool. Between the input interface and the output unit is provided a fuzzy control unit which determines the control signals for activation of the horizontal boring tool from the actual values of the controlled variables and the desired values for the controlled variables by fuzzy logic while taking into account heuristic process values. The control apparatus permits automatic operation of the horizontal boring tool with good course steering and high precision.

Abstract: A method and a system are described for determining the effectiveness of production installations, significant fault events that bring about deviations from a desired effectiveness and the causes of fault events. The production installation is connected to a data acquisition device, which is set up for continuous acquisition and ready-to-call-up storage of installation and production-related data. A service device is connected to the data acquisition device and has an input device for the input of additional installation and production-related descriptive data that cannot be called up from the data acquisition device. An online system part is set up for calling up installation and production-related data from the data acquisition device, calculating the effectiveness, detecting fault events, determining significant fault events by fault event evaluation, and determining in each case the causes of faults. An offline system part is provided and contains a number of generic fault models and assessment models.

Abstract: A fault detection system for determining whether a fault exists with a rotating element of a vehicle. The system includes a transducer, a diagnosis sampler, a sensor, and a controller. The transducer may be a microphone located in the vehicle for converting sounds to an electrical signal. The electrical signal includes a noise component generated from the rotating element. The diagnosis sampler is connected to the transducer and provides a sample of the electrical signal from the transducer to the controller. The sensor obtains data relating to the rotating element. The controller has functional aspects such as a synchronous resample, a spectrum analysis, and a fault detect. The synchronous resample has the capability of synchronizing the sample of the electrical signal with the data from the sensor to form a synchronized envelope.

Abstract: The present invention provides a method utilizing evolutionary processes for solving partial constraint satisfaction problems in order to produce a near-optimal or optimal sequence of products for manufacture.

Abstract: The invention is directed to a system and a method for the configuration and/or parameterization of diagnostic devices for test objects. The system includes a first data object having a collection of technological test object parameters of the test object and its components, and a second data object having a collection of technological parameters of hardware components of the diagnostic device. The system further includes a first program object containing data sentences for the assignment of at least test object parameters and technological parameters of hardware components, and a second program object for processing the data sentences assigned in the first program object. Via the data and program objects, a knowledge base is created that results in a configuration mainly automatically controlled by the knowledge of the system and/or parameterization of the diagnostic device including the test structure and evaluation. In this manner, the cost of such preparations is significantly reduced.

Abstract: A method of predicting the properties (e.g., mechanical and/or processing properties) of an injection-molded article is disclosed. The method makes use of a hybrid model which includes at least one neural network. In order to forecast (or predict) properties with respect to the manufacture of a plastic molded article, a hybrid model is used in the present invention, which includes: one or more neural networks NN1, NN2, NN3, NN4, . . . , NNk; and optionally one or more rigorous models R1, R2, R3, R4, . . . , which are connected to one another. The rigorous models are used to map model elements which can be described in mathematical formulae. The neural networks are used to map processes whose relationship is present only in the form of data, as it is in effect impossible to model such processes rigorously. As a result, a forecast relating to properties including the mechanical, thermal and Theological processing properties and relating to the process time of a plastic molded article is obtained.

Abstract: A method of determining properties relating to the manufacture of an injection-molded article is described. The method makes use of a hybrid model which includes at least one neural network and at least one rigorous model. In order to forecast (or predict) properties relating to the manufacture of a plastic molded part, a hybrid model is used which includes: one or more neural networks NN1, NN2, NN3, NN4 , . . . , NNk; and one or more rigorous models R1, R2, R3, R4, . . . , which are connected to one another. The rigorous models are used to map model elements which can be described in mathematical formulae. The neural model elements are used to map processes whose relationship is present only in the form of data, as it is typically impossible to model such processes rigorously. As a result, a forecast (or prediction) relating to properties including, for example, the mechanical, thermal and rheological processing properties and relating to the cycle time of a plastic molded part can be made.

Abstract: A distributed diagnostic system in which a plurality of local monitoring devices collect local information concerning various machines and process that information, according to redefined diagnostic parameters, for diagnostic purposes. The local information collected by the plurality of local monitoring devices is provided to a global processor that globally processes the collected information to provide updated diagnostic parameters to the local monitoring devices.