46results about How to "High precision diagnosis" patented technology

A first irradiation portion that radiates white light onto a subject, a second irradiation portion that radiates narrow bandwidth light having a narrower wavelength bandwidth than the white light, and an observation window used to observe the subject are respectively disposed on a leading end surface of an endoscope insertion portion. Each of the first and second irradiation portions includes a pair of irradiation windows for emitting light therefrom. A straight line passing through a center point of the observation window and bisecting the leading end surface is defined as a boundary line. The pair of irradiation windows of the first irradiation portion are disposed on both sides of the boundary line. The pair of irradiation windows of the second irradiation portion are disposed on the both sides of the boundary line. Spectra of lights radiated from the irradiation windows of the second irradiation portion can be changed individually.

A computer (16) for capturing a colored moving image photographed by photographing means (14, 15) has an extraction means for extracting images having necessary swing postures as check-point images from a large number of still images constituting the color moving image; a means for obtaining a coordinate of a position of each of attention-focused points, which operate, in each of the check-point images, while a golfer (11) is swinging; a means for diagnosing a golfer's swing form by setting a plurality of diagnosis items for each trajectory pattern obtained by a ball motion measuring apparatus (20) to classify behavior of a golf ball and by comparing numerical data generated from data of the coordinate of the position of each of the attention-focused points with a judgement value set in each of a plurality of diagnosis items; and a means for outputting an advice drill corresponding to a result of a diagnosis.

A machine tool diagnostic method includes: an initial acquisition step for acquiring initial measurement data by measuring multiple parameters of the machine tool while operating the machine tool in a predetermined operating pattern; a generating step for generating a normal area in a mapping space of a 1 class support vector machine method using the initial measurement data as training data; a reacquisition step in which, after operating the machine tool, the multiple parameters are measured to acquire re-measured data while again operating the machine tool in the predetermined operating pattern; and a diagnostic step for diagnosing the machine tool using the re-measured data as test data, based on whether or not the test data is contained in the normal area of the mapping space in the 1 class support vector machine method.

A failure detection apparatus for an internal combustion engine includes failure detecting means (S22-S30) for detecting abnormality of fresh air quantity detecting means (air flow sensor) based on the result of comparison between a fresh air quantity detected by the fresh air quantity detecting means (air flow sensor) and a reference value for the fresh air quantity set by fresh air quantity reference value setting means (S20), and an EGR device (EGR passage, EGR valve, target opening setting means, EGR valve control means). The fresh air quantity reference value setting means sets the reference value (S16) in accordance with not only the operating state (engine speed N_e, fuel injection quantity Q_f, etc.) of the engine but also a target EGR valve opening set by target opening setting means (S12, S14).

A control apparatus capable of separately detecting an unexpected fluctuation in the amount of NOx discharged from an engine (combustion chamber), separately from deterioration of lean NOx catalyst performance, thereby avoiding incorrect diagnosis of deterioration of the lean NOx catalyst, and ensuring the optimum control of the catalyst. A control apparatus of an engine wherein a lean NOx catalyst having a function of storing the NOx discharged from a combustion chamber in the lean operation mode, and desorbing and cleaning the stored NOx in the rich operation mode is provided in an exhaust path. This control apparatus comprises: a sensor for detecting the amount or concentration of NOx downstream from the lean NOx catalyst; calculation means A for calculating the amount of NOx downstream from the lean NOx catalyst in the lean operation mode, based on the output from this sensor, calculation means B for calculating the amount of NOx stored in the lean NOx catalyst; and means for calculating the NOx storage capacity of the lean NOx catalyst and the amount of NOx discharged from the combustion chamber in the lean operation mode, based on the results of calculations by the calculation means A and B.

A fault diagnosis apparatus is provided with a machine learning device, and the machine learning device observes at least one of fault time point data including information at the occurrence of a fault of a motor drive apparatus to be repaired, and operating environment data indicating an operating environment, operating history data indicating an operating history, as a state variable representing the present state of the environment; acquires repaired and/or replaced part data indicating a part that has been repaired and/or replaced in the motor drive apparatus as label data; and performs learning by associating the observed state variable with the acquired label data.

The invention provides a safety diagnosis system for structure, which comprises one GNSS receiver installed on an upper floor of a structure, a control device having a storage unit for storing a program which prepares an absolute displacement curve of the structure based on an absolute coordinate measured by the GNSS receiver and a displacement of the absolute coordinate, calculates a maximum inter-layer displacement and a maximum inter-layer deformation angle per each floor based on the absolute displacement curve and prepares an inter-layer deformation angle curve and a judging unit for performing a diagnosis of the safety of the structure based on the maximum inter-layer displacement and the maximum inter-layer deformation angle, and a display unit, wherein the control device calculates the maximum inter-layer displacement and the maximum inter-layer deformation angle per each floor and the inter-layer deformation angle curve based on a displacement of the absolute coordinate and the program and makes the display unit display a diagnosis result of the structure as evaluated by the judging unit based on at least one of the maximum inter-layer displacement and the maximum inter-layer deformation angle or the inter-layer deformation angle curve.

The invention discloses an OPGW lightning strike site polarization state waveform signal processing method. According to the method, a polarization demodulation device is adopted to acquire OPGW lightning strike site polarization state signals, and a wavelet denoising method is adopted to perform denoising preprocessing on sampling signals, so that wavelet denoised polarization state signals x(t)can be obtained; EMD decomposition is performed on the signals x(t), an equation described in the descriptions in the invention is obtained, rn in the equation is called a residual function, and ci inthe equation is the i-th component of the signals x(t) that satisfies an IMF condition; HHT (Hilbert-Huang) transformation is performed on each intrinsic mode function ci(t) of the polarization statesignals, and then analytical signals are constructed, and a lightning strike point can be accurately located on the basis of optical polarization state signals extracted by the final Hilbert-Huang transformation; and therefore, the problem of low accuracy of the analysis and processing of optical polarization state signals in an OPGW in the prior art can be solved, and the problem of inaccurate fault location caused by the low accuracy, and other problems can be also solved.

The invention intends to provide a technology which makes it possible to diagnose with higher accuracy whether or not abnormality occurs in a filter regeneration system causing excessive execution frequency of a regeneration process. The filter regeneration system initiates execution of the regeneration process, incase an estimated particulate matter (PM) accumulation amount at the filter reaches a pre-determined regeneration requiring accumulation amount; or in case the pressure upstream of the filter or the differential pressure across the filter reaches a pre-determined regeneration requiring value, the value being larger than the pressure or the differential pressure corresponding to the regeneration requiring accumulation amount. Then, the diagnosis is carried out based on a ratio of an estimated PM accumulation amount at the initiation of the execution of the regeneration process to the regeneration requiring accumulation amount.

An object of the invention is to diagnose a failure of an addition valve provided in the exhaust system of an internal combustion engine. To achieve the object, post injection through a fuel injection valve of the internal combustion engine and reducing agent addition through the reducing agent addition valve are performed at different timings, the quantity of fuel injected through the fuel injection valve when the post injection is performed and the quantity of reducing agent added through the reducing agent addition valve when the reducing agent addition is performed are estimated based on a same parameter, and it is diagnosed that the reducing agent addition valve has a failure on condition that the difference between the estimated fuel quantity and the estimated reducing agent quantity exceeds a predetermined quantity.

Disclosed are an apparatus and a method for diagnosing a state of a fuel cell stack with high accuracy by reducing the deviation of a harmonic component although the voltage variation of the fuel cell stack is substantial. According to the present invention, a harmonic component is detected by converting the difference between the voltage of the fuel cell stack and a moving average voltage to a frequency and the state of the fuel cell stack is diagnosed based on the size of the detected harmonic component.

An object is to provide an internal abnormality diagnosis method, an internal abnormality diagnosis system and a decision tree generation method for internal abnormality diagnosis of an oil-filled electric apparatus utilizing gas concentration in oil and having a diagnostic accuracy equal to or higher than that of a diagnostic specialist having reached a certain level. The present invention provides a method for generating a decision tree for determining the type of an internal abnormality of an oil-filled electric apparatus using a computer. In the decision tree generation method, the computer generates a standardized data group by converting concentrations of a plurality of gas species dissolved in an insulating oil in an oil-filled electric apparatus into ratios for each abnormality case, generates a discretized data group by converting the ratios of the concentrations of the gas species, the ratios constituting the standardized data group, into a plurality of discretized attributes using predetermined thresholds which are set for the respective gas species, and generates a decision tree for determining the type of an internal abnormality of the oil-filled electric apparatus by analysis using specific formulae on the basis of the discretized data group.

The present invention discloses an in vivo spectrometric inspection system. The system of the present invention is encapsulated in a swallowable capsule. After a testee swallows the capsule, an optical system inside the capsule generates a light source to illuminate an object. The light source hits the object to excite a light, or the light source is partially absorbed and partially reflected by the object. The excited light or the reflected light is received by the optical system and sent to a spectrometric system also inside the capsule. The spectrometric system disperses the wavelength components of the excited light or the reflected light into spectra, and then, the spectrometric system further analyzes the spectra to obtain a spectrum data. The spectrum data is sent out to the exterior of the testee body by a data-transmission device and received by an external receiver system. Otherwise, the spectrum data may be stored in a storage device inside the capsule, and after the capsule is excreted out, the spectrum data can be obtained too. Therefore, the in vivo spectrometric inspection system disclosed in the present invention can provide the information of the full-waveband spectral responses of the inspected object and promote the resolution of diagnostic inspections.

The present application relates to a kit for diagnosing pancreatic cancer, a method for providing information for diagnosing pancreatic cancer using the kit, and a method for diagnosing pancreatic cancer using same, wherein the kit includes an antibody specifically binding to complement factor B protein and an antibody specifically binding to carbohydrate antigen 19-9 protein. According to the present application, it is possible to provide a marker for diagnosing pancreatic cancer having enhanced sensitivity and specificity.

A power supply unit for an aerosol suction device includes: a power supply capable of discharging to a load for generating an aerosol from an aerosol generation source; and a controller capable of controlling charging and discharging of the power supply. The controller is capable of operating in a charging mode for controlling charging of the power supply, a first mode different from the charging mode, and a second mode different from the charging mode and the first mode, and is capable of executing diagnosis processes of the power supply in each of the first mode and the second mode.

The invention provides a gearbox fault detection method based on deep transfer learning, and the method comprises the steps: collecting original signal data of a gearbox, carrying out the noise reduction and data cleaning of an original signal, carrying out the extraction through a feature extractor, obtaining a new image, building a model, and carrying out the result analysis and verification of the model through training data and verification data. According to the method, the technical problem that the type of gearbox fault diagnosis is single is solved, the image data of the vibration signals, the temperature signals and the oil liquid signals of the gearbox are innovatively combined in a crossed mode, multiple sets of composite image data are obtained, a composite fault model is finally constructed, and the fault diagnosis accuracy is improved. The obtained convolutional neural network model is migrated to gearbox diagnosis detection data, the migration diagnosis fault rate is calculated, the diagnosis rate is 94%-100%, high-precision diagnosis is achieved, and rapid fault detection of the gearbox under the composite fault condition is achieved.