47 results about "Time to diagnosis" patented technology

The invention discloses an industrial process fault diagnosis method based on multiple classifiers and D-S evidence fusion. The method comprises the steps that firstly, independent repeated sampling is conducted according to fault data in the industrial process; secondly, the multiple classifiers are applied to new training data, respective off-line modeling models are obtained, and meanwhile the properties of all the classifiers are represented in the form of a fusion matrix; thirdly, different types of elementary probability valuation functions are calculated according to the D-S evidence theory, decisions of the multiple classifiers are selectively integrated and synthesized according to the similarity index, a combined elementary probability valuation function is obtained, and a final classified diagnosis result is obtained by means of comparison. Compared with other methods in the prior art, the industrial process fault diagnosis method can greatly improve the diagnosis effect of the industrial process, shorten delayed diagnosis time and increase the diagnosis accuracy rate, improves the monitoring performance to a great extent, enhances the comprehension ability and operation confidence of process operators in the process, and is more beneficial to automatic implementation of the industrial process.

Infusion systems, infusion devices, and related operating methods are provided. An exemplary method of operating an infusion device to deliver fluid to a user in accordance with an operating mode involves obtaining operational information pertaining to one or more prior instances of the operating mode, obtaining status information pertaining to the infusion device, and determining a diagnosis time based at least in part on the operational information. The diagnosis time is prior to a subsequent instance of the operating mode. At the diagnosis time, the method automatically determines the viability of the subsequent instance of the operating mode based at least in part on the status information and automatically generates a notification indicative of a recommended action for the user based at least in part on the viability.

The invention belongs to the technical field of medical information, and particularly relates to a medical image multi-stage classification method based on a symmetry theory. The method comprises the following steps that: images to be classified provide classification requests, wherein the images to be classified need to be original medical image data; and an image preprocessing process comprises the steps of image-based modeling, multi-stage classification and result display. The concepts of weak symmetry and high symmetry provided by the invention belong to redefinition on the medical images. A weak symmetry judging algorithm and a high symmetry judging algorithm are provided for realizing the multi-stage classification of the medical images. The classification accuracy of the multi-stage classification is very high, and the direct connection and layer-by-layer deep classification is realized in each stage, so the diagnosis precision of a doctor is improved, and the diagnosis time of the doctor is shortened. The medical image classification is realized by adopting the symmetry theory, so that the medical image multi-stage classification method based on the symmetry theory has higher accuracy.

The invention discloses a deep learning-based intelligent X-ray film diagnosis method. The method comprises the following steps: image data of chest X-ray films stored in a preset memory are acquired;the image data of the chest X-ray films are augmented in a preset mode; the augmented image data are subjected to preprocessing operation to enable data features to meet a standard; the preprocessedimage data are classified to form a plurality of classification models, and model training is designed for each classification model to generate a model training prediction result; a final CNN featuremap is acquired, and according to the CNN feature map, a thermodynamic map is generated; and according to the model training prediction result of each classification model, an integration result is calculated and obtained. Deep learning on pulmonary disease characteristics in a large number of chest X-ray films can be carried out, multiple pulmonary diseases can be accurately predicted, a diagnosis basis is provided, the prediction time is greatly less than manual diagnosis time, and the time of a doctor is saved.

The invention discloses a method and a system for predictive maintenance based on motor parameters. The method starts from the local operation condition of the motor; two non-electrical acquisition parameters of temperature and vibration of the motor without direct connection are acquired for cross calculation. The real-time working state of the motor is mapped by adopting the matrix eigenvalue vector; the function relationship among the temperature, the vibration and the health degree of the motor can be realized, the linear change relationship between the local and comprehensive health degrees of the motor can be obtained, predictive maintenance is realized by judging the change trend of the health degree within a period of time, the diagnosis time of traditional motor fault diagnosis isadvanced, and irreversible damage to the motor can be well prevented. According to the method, the abnormal working state of the motor can be obtained more accurately, the statistical calculation flow is independent of the real-time calculation flow, the edge calculation pressure of acquisition equipment is reduced, and unnecessary hardware cost is avoided; and predictive maintenance can be positioned to a part of the motor, so that the manual detection cost is reduced.

The invention discloses an intelligent auscultation system. The system comprises an electronic stethoscope, a patient terminal, a doctor terminal and a server; the server comprises a data acquisition module, a data processing module, an auscultation database, a preliminary judgment module, a data sending module, a data receiving module and a notification module; the preliminary judgment module is used for comparing and analyzing the auscultation data of the patient, the auscultation data of the normal person and various pathological feature information to obtain a preliminary judgment result; the data sending module is used for sending an audio signal detected by a patient and a preliminary judgment result to the doctor terminal; and the data receiving module is used for receiving the diagnosis result sent by the doctor terminal. The system can automatically perform preliminary judgment on the audio signal of the patient of the user to obtain a preliminary judgment result, provide a diagnosis direction for a doctor and reduce the diagnosis difficulty and diagnosis time of the doctor. When the disease degree in the preliminary judgment result or the diagnosis result is serious, the relatives of the patient are timely notified, so that the relatives can timely take response measures.

An apparatus and a method for diagnosing actuators in a vehicle can improve accuracy and reliability of a failure diagnosis by allowing a diagnostic control apparatus in a vehicle to measure power data and implementing a fast diagnosis by reducing a separation time and a diagnosis time of a measurement apparatus.

The invention discloses a rapid diagnosis and detection test paper card for detecting swine fever as well as a preparation and application method of the rapid diagnosis and detection test paper card. The rapid diagnosis and detection test paper card comprises a PVC base plate, a sample pad, a gold-labelled antibody glass fiber membrane, a nitrocellulose coating membrane, water absorption paper, a detection line and a quality control line. The rapid diagnosis and detection test paper card is applied based on a colloidal gold immunochromatography technology; in a detection process, a swine fever antigen in a sample is combined with a colloidal gold coated antibody to form an antigen-antibody complex, the antigen-antibody complex flows to the other end of an NC membrane along test paper, and when the complex flows to a detection line area on the membrane, a specific antibody fixed on the membrane can capture the complex and gradually coagulate the complex to form a visible detection line, an uncombined colloidal gold antibody flows through the detection line area and is captured by a second antibody of the quality control line to form a visible quality control line, and if the quality control line appears, the occurrence of immunochromatography can be determined, namely, the test paper is valid; and if the detection line appears, a swine fever virus can be determined to exist in the sample. The rapid diagnosis and detection test paper card disclosed by the invention can be used for judging results within 5 minutes, and has the characteristics of short diagnosis time and strong specificity.

The invention provides a novel missile fault prediction device which is widely used in the aerospace automation measurement and control technical field. The device is mainly composed of a PXI measurement and control system, a KVM integral machine, a printer, a test cable, a historic fault database, and missile fault prediction software. By combining virtual apparatus technologies and automatic measurement and control technologies, the device is in direct butt joint with the missile fault prediction software. All previous missile fault diagnosis results are automatically stored in the historic database, and by employing a prediction algorithm, a next possible fault position is predicted, and a part most likely to break down is found, thereby helping the missile fault prediction software to rapidly determine a fault scope, and avoiding a diagnosis mode starting diagnosis from a fixed source. The device can effectively reduce diagnosis time and improve test efficiency, possesses higher use values, and is already applied to the test and fault diagnosis filed of missiles in various tactical models.

The invention discloses a 3G wireless communication-based colostomy complication remote diagnosis system which comprises a plurality of medical centers; all the medical centers are communicated with 3G wireless network base stations by serial ports or networks; the 3G wireless network base stations are respectively connected with a 3G public wireless network; each medical center comprises a diagnosis control terminal which comprises a central processing unit (CPU); the CPUs are connected with the 3G wireless network base stations by routers; each CPU is also connected with a display device, a data storage device and a data acquisition device; and the CPUs are also connected with a computer used for expert consultation diagnosis. The 3G wireless communication-based colostomy complication remote diagnosis system has the advantages of greatly shortening the diagnosis time, reducing the financial burden on a patient, and being convenient for the patient to go to the nearest hospital.

The invention makes it an object to provide a memory fault diagnostic device and a memory fault diagnostic method which can diagnose a memory fault at a minimum time using an interim time after the execution of an application in a predetermined control cycle, and can minimize a fault diagnostic time for the whole memories in a diagnostic object area. An area of a memory has a diagnosis area (41) and a non diagnosis area (42), with the diagnosis area divided into a plurality of Row areas which do not overlap each other, and each of the Row areas is divided into a plurality of Cell areas which do not overlap each other. A memory fault diagnostic method has a diagnostic step in a Row area to diagnose between Cell areas with respect to all the combinations of a set of Cell areas in the Row area, and a diagnostic step between Row areas to diagnose between Row areas with respect to all the combinations of a set of Row areas in the diagnosis area. A Row area size is determined to be a size in which a time of the diagnosis in a Row area becomes equal to a time of the diagnosis between Row areas.