139 results about "Diagnostic program" patented technology

The invention discloses an elevator control reminding and fault self-diagnosis method and system, and the method comprises the steps: installing acceleration, temperature, pressure and displacement sensors at preset parts of an elevator car, a motor, a steel wire rope and a door system, and collecting operation data in real time. Performing data preprocessing, cleaning wrong data, normalizing and extracting key feature parameters; and then, a state evaluation model constructed based on historical data and expert experience is used for judging the running state of the elevator, and normal, early warning and fault grades are divided. According to an evaluation result, the system executes corresponding control reminding operation, a fault diagnosis program is started when a fault occurs, fault types and reasons are accurately positioned, and part of faults can be self-repaired. Meanwhile, diagnosis and processing conditions are fed back, and a fault database is updated. The elevator running safety and reliability are remarkably improved, the maintenance cost is reduced, and the safety of elevator passengers is guaranteed.

An example of a distributed discernment system including a discernment server and a communications interface permitting bi-directional communications to and from the discernment server; and a plurality of human interface devices, each including a speaker, a microphone, a processor running a local processing program, and a system interface permitting bi-directional communications between the human interface device and the discernment server, where the diagnostic program running on the discernment server is adapted to generate interview instructions provided to the interface devices and the interface devices are adapted receive interview instructions from the discernment server, present a verbal question to a human interviewee; receive and process sensor data from the microphone to determine whether the microphone sensor data corresponds to a complete human voice response to the presented verbal question.

The machining diagnosis device (1) includes a data acquisition unit (11) that acquires a physical quantity related to the operating state of a machining machine (90) that machines a workpiece, and the machining conditions when the physical quantity is obtained, a feature quantity calculation unit (12) that calculates, for each machining condition, a statistical feature quantity of the physical quantity obtained during machining under the same machining conditions based on the physical quantity and the machining conditions, and an inference unit (16) that performs machining diagnosis based on the statistical feature quantity for each machining condition.

A distributed discernment system that includes discernment server including a processer running a diagnostic program and server interface permitting communications to and from the discernment server where the discernment system communicates with two or more human interface devices, where each human interface device includes display capable of presenting a video segment of a virtual human interviewer asking a question to an interviewee and sensors capable of detecting various responses of a human interviewee to each presented question where the discernment server includes a diagnostic that generates interview instructions to be provided to a plurality of human interface devices over the communications network, wherein the instructions provided to a given human interface device are intended to cause the human interface device to present certain questions to a human interviewee interacting with the device and wherein the discernment server is adapted to receive data from each of a plurality of the human interface devices and analyze such data to provide an assessment of the state of the human interviewee interacting with the human interface device.

To specify the abrasion loss of a centrifugal dehydrator.SOLUTION: A diagnosis system for diagnosing a centrifugal dehydrator including an outer body and an inner body that are coaxially disposed, are pivotally supported at two bearing portions provided at both ends in an extending direction, and rotate at different rotation speeds, the inner body having a screw spirally provided on an outer periphery thereof, the diagnosis system including measurement devices 2, 3, and 4 that measure a physical quantity related to the centrifugal dehydrator, and an arithmetic device 5, in which the arithmetic device 5 is capable of realizing a wear amount specifying function of specifying a wear amount of a tip portion of the screw based on the physical quantity.SELECTED DRAWING: Figure 2

According to the elevator diagnosis method and system based on functional safety, functional safety diagnosis is paused in the running stage of an elevator needing to be quickly responded, a control system can centralize resources to process related tasks, such as accurate control over elevator car leveling and timely response to door machine instructions, response delay caused by diagnosis program interference is avoided, and the service life of the elevator is prolonged. The probability of accidents caused by untimely response is reduced, and quick and accurate response in a key stage is guaranteed; secondly, by setting the threshold duration of pause function safety diagnosis and overtime forced recovery diagnosis, long-time non-monitoring in the quick response stage is avoided, and in the normal operation stage of the elevator, diagnosis is recovered and periodically executed, the elevator function is continuously detected, potential safety problems are found and early warned in time, so that maintenance and repair measures are taken, and the safety of the elevator is guaranteed. The response speed and safety monitoring are balanced, the safety monitoring effectiveness of the overall function of the elevator is guaranteed, and the operation safety is improved.

To simplify the display of a check result for an input item of DPC data.SOLUTION: A check program causes a computer to perform processing of: receiving an input of DPC (Diagnosis Procedure Combination) data, executing a check on an input item corresponding to an occupation of an account of a user who inputs the DPC data among input items included in the DPC data, and outputting an execution result of the check.SELECTED DRAWING: Figure 1

A diagnosis program (P) causes a processor (10) to use a battery degradation model formula (Ma) to specify a degradation factor of a battery module (2a), wherein the battery degradation model formula (Ma) is obtained by linear regression analysis in which the degradation amount of characteristic data (E) of the battery module (2a) is used as an objective variable (Y) and in which usage history data (D) of the battery module (2a) during measurement of the characteristic data (E) and the power (D') of the usage history data are used as explanatory variables (X), and through modeling in which the coefficient of each term of the explanatory variables (X) is predefined as positive or negative.

A fluid control apparatus 100 is provided with a second flow rate calculation unit 431 that calculates a flow rate flowing through a fluid resistor 33 based on a change over time in an upstream-side pressure P1 or a downstream-side pressure P2 in a state in which a fluid control valve 32 is closed, and with a diagnostic parameter calculation unit 432 that calculates a diagnostic parameter based on a first flow rate calculated by a first flow rate calculation unit 431, and on a second flow rate calculated by the second flow rate calculation unit 432 in a state in which the fluid control valve 32 is closed.

The invention provides a machine learning device capable of diagnosing the insulation state of a winding without stopping a shield motor pump. A machine learning device (4) generates a learning model (6) for an insulation state diagnosis device (5) for diagnosing the insulation state of a winding (31) of a stator (23) used in a shield motor pump (2). A machine learning device (4) uses unprocessed data or data obtained by pre-processing at least a portion of the unprocessed data as input data, and inputs learning data including at least the input data into a learning model (6). Therefore, the learning model learns the correlation between the input data and the diagnosis information of the insulation state of the winding. The unprocessed data is data of a voltage value and a current value supplied to the motor unit (20), data of a temperature of a winding (31) of the stator (23) or a temperature, a temperature difference, or a pressure related thereto, and data of an inflow temperature and a flow rate of the working fluid in the pump unit (10).

The invention relates to a method for operating a motor vehicle closure system (1), the motor vehicle closure system (1) having a drive (2) with an electric drive motor (3) and a control assembly (4) for actuating the drive (2) in order to provide an electric closure function for an adjustable closure element (5) of a motor vehicle (6), the control assembly (4) has a rechargeable electrical energy store (9) with at least one capacitor (10), the emergency supply voltage being provided by means of the energy store (9) during emergency operation, in particular in the event of a failure of the normal supply voltage. According to the invention, a diagnostic program is carried out by means of a control component (4), in which the capacitor (10) is subjected to a discharge and a charge from an initial state of charge in a chronological order, and a first electrical characteristic parameter of the capacitor (10) is determined on the basis of the discharge and a second electrical characteristic parameter of the capacitor (10) is determined on the basis of the charge by means of the control component (4).

[Problem] To provide an endoscope diagnosis program, an endoscope diagnosis device, a control method for an endoscope diagnosis device, and a program for generating an endoscope diagnosis trained model which each make it possible to use endoscope images that have been accumulated to date to diagnose the presence or absence of a lesion, without limitations on the type of endoscope device. [Solution] A computer is made to function as: a diagnostic-use image acquisition unit 66 that acquires a diagnostic-use image of a site that is subject to diagnosis which has been captured with an endoscope device 20; a color tone correction unit 67 that performs color tone correction on the diagnostic-use image in accordance with a reference color tone, which is a color tone of an image of a site subject to diagnosis having been captured in advance with the endoscope device; and a lesion presence / absence diagnosis unit 68 that inputs the corrected diagnostic-use image into a trained model and that performs a process for diagnosing the presence or absence of a lesion from a result output by the trained model, said trained model having being generated by machine learning of a plurality of training images which have been subjected to color tone correction with the reference color tone.

A diagnostic method, executable for example from remote computing devices or onboard control units for machines having various systems, each system having associated electronic controllers. For a specified machine and configuration, a hierarchical list is automatically generated comprising systems associated with the machine and one or more expected electronic controllers for each system. At least pursuant to initiation of a diagnostic program via an onboard control unit of the specified machine, respective input signals are obtained from present electronic controllers in functional communication with the onboard control unit. For each of any expected electronic controllers for which respective input signals are not obtained, a status alert is generated corresponding to a determined missing status or failure status, wherein the determined missing or failure status is based on an optionality of the respective expected electronic controller for which respective input signals are not obtained and / or an optionality of the corresponding system.

A diagnostic device for an exhaust gas aftertreatment device includes a temperature detection device that detects a filter inlet-side temperature and a filter outlet-side temperature, a differential pressure detection device that detects a differential pressure between a filter inlet-side pressure and a filter outlet-side pressure, an intake air pressure detection device that detects an intake air pressure of an engine, and a controller that determines a malfunction in an exhaust gas aftertreatment device based on values detected by the temperature detection device, the differential pressure detection device, and the intake air pressure detection device.

The application discloses a core system, device and method for vehicle diagnosis. The core system for vehicle diagnosis is connected with a vehicle and comprises an operating system layer, a protocol layer, a service layer and an application layer. The operating system layer comprises an operating system and a driver corresponding to diagnostic system hardware. The protocol layer comprises a hardware protocol stack corresponding to the diagnostic system hardware, and the hardware protocol stack is provided with multiple types of hardware protocols. The service layer is provided with multiple preset services corresponding to the types of the hardware protocols. The application layer comprises a diagnostic program used for performing a diagnostic operation on the vehicle. When the diagnostic program performs the diagnostic operation and generates a hardware calling request, the hardware calling request is sent to a preset service of a corresponding type. Each preset service determines a hardware scheduling strategy according to all currently received hardware calling requests, and schedules a hardware protocol of the corresponding type according to the hardware scheduling strategy, so that the diagnostic program completes control on the diagnostic system hardware in the diagnostic operation process.

The diagnostic system (1) includes a machining data acquisition unit (10) that acquires machining data from the start of machining by a machine tool (2) to the end of machining, a section extraction unit (11) that extracts a first section, which is a cutting section, and a second section, which is a section other than the first section, from the machining sections of the machining data, a feature calculation unit (13) that calculates a first feature value in the first section of the machining data and a second feature value in the second section of the machining data, a corrected feature calculation unit (14) that calculates a third feature value corresponding to an actual cutting load, which is a load of the cutting process, by subtracting the second feature value from the first feature value, and a machining diagnosis unit (17) that performs machining diagnosis based on the third feature value.

Provided is a secondary battery diagnostic method capable of evaluating a remaining service life of a secondary battery more accurately than in the past, without disassembling the secondary battery. This secondary battery diagnostic method includes: a parameter estimating step (step S1) for employing a predetermined model formula to estimate, on the basis of data obtained by measuring a load characteristic of a secondary battery being diagnosed, characteristic parameters, at a diagnosis time point, of the secondary battery being diagnosed, the characteristic parameters including an electrolytic solution diffusion coefficient Dn, at the diagnosis time point, of the secondary battery being diagnosed; a threshold estimating step (step S5) for employing a trained model to estimate, on the basis of input data, which are data including some of the characteristic parameters at the diagnosis time point, a threshold Dth of the electrolytic solution diffusion coefficient of the secondary battery being diagnosed; and a difference calculating step (step S4) for finding a difference ΔD between the threshold Dth and the electrolytic solution diffusion coefficient Dn at the diagnosis time point.

The invention discloses a DSM fault diagnosis test method and device and a medium, and the method comprises the steps: constructing a CANoe test environment, and generating a test case for testing a DSM fault diagnosis program; executing a fault clearing operation through a fault clearing program in the ECUTEST software to clear all historical fault codes stored in the VCU controller before the test case simulates a new fault state, so that the VCU controller is in a single fault code state; based on the single fault code state, running the test case through a CANoe test environment; and obtaining a fault diagnosis message sent by the DSM fault diagnosis program in response to the test case, and comparing an actual fault code in the fault diagnosis message with an expected fault code in the test case to generate a diagnosis test report.

A vehicle diagnostic device is provided with: a feature data acquisition unit that acquires a plurality of pieces of feature data included in a predetermined output mode of a vehicle; an actual data acquisition unit that acquires output data based on actual travel of the vehicle in a past predetermined period and actual measurement data indicating actual measurement of parameters required for vehicle diagnosis during travel of the vehicle in the predetermined period; an equivalent pattern generation unit that generates an equivalent output pattern that is considered to be equivalent to a predetermined output pattern by intercepting points or intervals similar to a plurality of pieces of feature data from the output data for a predetermined period; and an actual measurement extraction unit that extracts actual measurements for each point or each section included in the equivalent output pattern from the actual measurement data during the predetermined period.

Systems and methods are disclosed herein for mitigation of sensor obstructions or interference. The system can generate a first sensor map using a first sensor and a second sensor map using a second sensor. The system can detect a first representation of a first object in the first sensor map. The system can obtain first field-of-view information associated with the first sensor and second field-of-view information associated with the second sensor. The system can generate a prediction for an object position of the first object. The system can determine, in the second sensor map, a predicted sensor cell for the first object. The system can determine that the second sensor map does not include a second representation of the object. The system can generate a sensor operation status for the second sensor. The system can execute an interference diagnostic program according to the sensor operation status.

A diagnostic apparatus includes a diagnostic unit that diagnoses a database based on managing an operation history, a fault factor, and a fault countermeasure of a reference field device in an associated manner, and identifies a fault factor and a fault countermeasure of a diagnosis target field device based on the operation history of the diagnosis target field device.

A fault diagnosis procedure for detecting faulty components in a vehicle, wherein, for at least one identifiable fault cause of a faulty component, a system parameter of the vehicle that is influenced by the fault cause is determined and compared with a target value of the system parameter, and a determined signal deviation between the determined system parameter and the target value of the system parameter is compared with a stored fault characteristic signal deviation, and if the determined signal deviation matches the fault characteristic signal deviation, the fault cause and / or faulty component associated with the fault characteristic signal deviation is uniquely identified, wherein the entire development process for the fault diagnosis procedure essentially consists of the following six individual steps, which are executed sequentially: - Selection of faults to be diagnosed, whereby in this first step the various components of the vehicle are analyzed in such a way that the possible causes of faults are listed for each component; - Structural analysis, whereby in this second step it is checked whether there is a possibility in principle of model-based diagnostics of the system; - Creation of a nominal model, whereby in this third step, so-called nominal models are created for those system parameters that are used and evaluated for the identification of a faulty system component, in which a normal operation of the system component is depicted; - Sensitivity analysis, in which, in this fourth step, defined causes of failure are imprinted into the system and their effects on the relevant system size(s) are considered using the nominal model, thereby identifying a unique assignment of a cause of failure or a faulty system component to its effect on the relevant system size; - Creation of fault models, whereby in this fifth step the knowledge about the effect is stored in a reference source onboard in the vehicle, whereby, based on this reference source, a statement can be made at any time valid for the diagnosis as to whether this cause of fault is present or not and - Integration into a diagnostic system, whereby in this sixth step the developed diagnostic procedure is transferred to a corresponding target control unit in the vehicle.

A robot system including: a robot with one or more movable elements respectively rotatable about one or more rotation axes; a control device that controls the robot; and a visual sensor attached to any of the movable elements of the robot, where the control device uses any of the movable elements of the robot as a subject element, compares a position of a predetermined target in a first image at an arbitrary first orientation of the robot at which the target fixed at a predetermined position is disposed inside a field of view of the visual sensor, and the position of the predetermined target in a second image at a second orientation at which the subject element is rotated about a rotation axis of the subject element with respect to the first orientation, and determines that the visual sensor is attached to the subject element.

A technique is provided that enables bearing condition diagnosis to be performed in a simple manner. A monitoring device (200) according to an embodiment of the present disclosure comprises a detection unit (2001) configured to detect measurement data relating to a rotational speed of an electric motor (100), a calculation unit (2003) configured to extract a component of a monitoring frequency of the rotational speed of the electric motor (100) based on the measurement data relating to the rotational speed of the electric motor (100) detected by the detection unit (2001), and a diagnosis unit (2004) configured to diagnose a condition of a bearing (104, 104a, 104b, 104x) of the electric motor (100) based on the component of the monitoring frequency extracted by the calculation unit (2003).

A diagnostic mechanism includes: a valve leak difference calculation unit that calculates a valve leak difference that is a difference between a valve leak pressure change model indicating a pressure change due to a valve leak of a fluid control valve and an upstream pressure detected by an upstream pressure sensor or a downstream pressure detected by a downstream pressure sensor; a sensor shift difference calculation unit that calculates a sensor shift difference that is a difference between a sensor shift pressure change model indicating a pressure change due to a sensor shift of the upstream pressure sensor or the downstream pressure sensor and the upstream pressure or the downstream pressure; and a diagnostic unit that compares the valve leak difference with the sensor shift difference to diagnose whether the fluid control valve is abnormal or whether each of the pressure sensors is abnormal.

This control device comprises: a control unit that controls home equipment on the basis of a control instruction; and a communication unit that can communicate by first wireless communication and second wireless communication. The control unit acquires the control instruction for the home equipment by the first wireless communication with respect to an access point. The control unit performs device diagnosis by the second wireless communication when the first wireless communication is malfunctioning.

An oil property sensor (1 (1a, 1b)) detects at least one dielectric constant and one resistance value as physical property values ​​of oil. A control unit (50) estimates a metal concentration or an iron concentration in the oil from the physical property values ​​based on a relationship between the physical property values ​​of the oil detected by the oil property sensor (1 (1a, 1b)) and the metal concentration or iron concentration in the oil.

An apparatus configured to perform a network diagnostic procedure within a message-based protocol network comprising a plurality of nodes. The apparatus includes: a diagnostic test device configured to perform a diagnostic test; and a diagnosis control device. To execute a network diagnostic program, a diagnostic control device is configured to: receive a diagnostic request from a commander node, where the diagnostic request is directed to a target node, and where the diagnostic request includes a first message identifier; comparing the first message identifier with a predetermined diagnostic identifier; receiving a diagnostic response from the target node, wherein the diagnostic response includes a second message identifier and a test pattern; and comparing the second message identifier with a predetermined diagnostic identifier; if the first message identifier and the second message identifier are the same as the predetermined diagnostic identifier, a diagnostic test is performed using the diagnostic test device using the test pattern.

The application relates to a test simulation verification platform for reusing on-board diagnosis algorithms, which comprises the following modules: a diagnosis program generation module, which automatically generates an on-board diagnosis program according to diagnosis knowledge; a diagnosis program simulation module, which loads the on-board diagnosis program, receives telemetry data and performs fault diagnosis; a data playback module, which plays back historical data records required for test verification; and a test verification module, which compares real and detected fault labels and analyzes diagnosis accuracy. The application provides a test simulation verification platform for reusing on-board diagnosis algorithms, realizes automatic updating and deployment to verification, and improves the test verification efficiency of on-board diagnosis programs.