270 results about "Continuous analysis" patented technology

The invention relates to the technical field of communication data analysis, and discloses a communication network service health degree analysis method, system and device and a medium, and the method comprises the steps: obtaining real-time link state data, carrying out the quantitative analysis, and judging whether the link jitter exceeds a preset threshold value or not; when abnormality is detected, abnormal points can be positioned and the influence range of the abnormal points can be analyzed, so that the influence degree of nodes on the abnormal diffusion path can be identified; calculating a service quality index change value, and determining a starting point and a diffusion direction of chain degradation; by analyzing historical traffic data of the key nodes, a service traffic change trend and traffic dense area distribution characteristics are obtained. According to the method, the bandwidth allocation strategy is dynamically optimized, the bandwidth resources at the junction are reconfigured, and the regional service health degree is evaluated. And if the degradation is not effectively controlled, monitoring and detection mechanism parameters can be adaptively adjusted, and continuous analysis and control of link abnormity are realized, so that the network performance and the service quality are effectively improved.

The invention provides a coal mining digital twinning method based on multi-level dynamic deviation correction and AI optimization. The method comprises the steps of monitoring data acquisition and dynamic preprocessing, and performing denoising and space consistency detection on data; constructing and pre-processing the coal mine digital twinborn body; generating a nonlinear deviation field by adopting a high nonlinear variable interpolation and model mapping method; performing Kalman filtering error analysis and correction under the continuous analysis step, and marking an optimization model state in combination with a space mutation step; performing staged sliding window long-time-sequence fluctuation analysis, and classifying and marking regions according to an absolute value of an error and fluctuation; performing multi-level weighted error optimization based on a genetic algorithm, and adjusting material parameters and boundary conditions; carrying out material constitutive rectification based on dynamic Bayesian, and gradually enhancing the adaptability and accuracy of the model; and constructing a hybrid network structure AI optimization prediction model based on deep data driving, capturing the dynamic change of the material constitutive and the characteristic difference of the model constitutive, and realizing the precise digital twinborn simulation of the whole coal mining process.

Described herein are variations of an analyte monitoring system, including an analyte monitoring device. For example, an analyte monitoring device may include an implantable microneedle array for use in measuring one or more analytes (e.g., glucose), such as in a continuous manner. The microneedle array may include, for example, at least one microneedle including a tapered distal portion having an insulated distal apex, and an electrode on a surface of the tapered distal portion located proximal to the insulated distal apex. At least some of the microneedles may be electrically isolated such that one or more electrodes is individually addressable.

Described herein are variations of an analyte monitoring system, including an analyte monitoring device. For example, an analyte monitoring device may include an implantable microneedle array for use in measuring one or more analytes (e.g., glucose), such as in a continuous manner. The microneedle array may include, for example, at least one microneedle including a tapered distal portion having an insulated distal apex, and an electrode on a surface of the tapered distal portion located proximal to the insulated distal apex. At least some of the microneedles may be electrically isolated such that one or more electrodes is individually addressable.

The invention relates to the technical field of agricultural intelligent monitoring, in particular to a crop growth detection system and method based on machine vision, and the system comprises an image collection module, a morphological feature capture module, a growth trend judgment module, an abnormal region marking module and a state information output module. According to the method, crop images are collected through a multi-angle camera, leaf contours, stem bending and plant spacing are extracted, multi-dimensional modeling of morphology is realized, structural change identification is enhanced, time sequence comparison of key morphological characteristics is realized, identification precision and time efficiency are improved, leaf and stem change trends are continuously analyzed, offset is quantified, and growth abnormity is early warned in advance; health degradation identification is combined with fluctuation area marking, dynamic monitoring is achieved, high-risk positioning is carried out on a time overlapping area, time-space locking is enhanced, precise management is assisted, the process is from image analysis to abnormal focusing, an information reasoning chain is established, and the monitoring precision and response efficiency are remarkably improved.

Described herein are variations of an analyte monitoring system, including an analyte monitoring device. For example, an analyte monitoring device may include an implantable microneedle array for use in measuring one or more analytes (e.g., glucose), such as in a continuous manner. The microneedle array may include, for example, at least one microneedle including a tapered distal portion having an insulated distal apex, and an electrode on a surface of the tapered distal portion located proximal to the insulated distal apex. At least some of the microneedles may be electrically isolated such that one or more electrodes is individually addressable.

Described herein are variations of an analyte monitoring system, including an analyte monitoring device. For example, an analyte monitoring device may include an implantable microneedle array for use in measuring one or more analytes (e.g., glucose), such as in a continuous manner. The microneedle array may include, for example, at least one microneedle including a tapered distal portion having an insulated distal apex, and an electrode on a surface of the tapered distal portion located proximal to the insulated distal apex. At least some of the microneedles may be electrically isolated such that one or more electrodes is individually addressable.

The invention relates to the technical field of soil organic carbon monitoring, and particularly discloses a monitoring method and system for soil organic carbon, and the method comprises the steps: dividing a monitoring region, fusing an unmanned aerial vehicle and a remote sensing image, analyzing an attribute parameter set, and dynamically judging and adjusting an initial image collection process to ensure the data quality; sub-region division is carried out based on the target region fusion image, and whether a region division strategy is optimized or not is dynamically decided by evaluating image feature parameters of each sub-region; and finally, after region division is completed, collecting and marking the soil organic carbon content of each sub-region, and judging and optimizing a subsequent monitoring scheme through comparative analysis with historical data. According to the method, a feedback workflow including three core links of data acquisition, space dynamic division, monitoring result calibration and scheme optimization is established. Wherein the key parameters of each link are continuously analyzed, and the subsequent steps are dynamically judged and adjusted, so that a self-perfect dynamic optimization mechanism is formed.

AI-powered data breach detection and prevention system that includes: a threat monitoring module for continuous analysis of network traffic, system logs and user activities; an AI-powered anomaly detection module that uses machine learning to detect threats, including zero-day attacks and insider threats; a behavioral analysis module that tracks user authentication, access patterns, and privilege escalations; an automated incident response module that isolates threats, blocks unauthorized access, and alerts security teams; a threat intelligence module that integrates global cybersecurity databases for proactive risk mitigation; a multi-layered security system with endpoint protection, encryption and role-based access control; a privacy-preserving mechanism that uses homomorphic encryption and federated learning to protect sensitive data; a compliance and audit module that ensures compliance with cybersecurity regulations.

The invention discloses a micro-reagent ammonia nitrogen on-line continuous analyzer and an analysis method, and belongs to the technical field of water quality ammonia nitrogen monitoring, the micro-reagent ammonia nitrogen on-line continuous analyzer comprises a first injection pump, a second injection pump, a multi-channel valve, a liquid storage ring and a reaction tank; liquid outlets of the first injection pump and the second injection pump are respectively connected with one end of the liquid storage ring and a circulating port of the reaction tank through different channels of the multi-channel valve; a circulating port of the reaction tank is connected with a first peristaltic pump; the other end of the liquid storage ring is connected with a second peristaltic pump; liquid outlets of the first injection pump and the second injection pump are connected with a third peristaltic pump; a first reagent and a second reagent for ammonia nitrogen analysis are respectively stored in the first injection pump and the second injection pump; different channels of the multi-channel valve are respectively connected with a standard sample and a water sample which are used for ammonia nitrogen analysis, and cleaning water. The micro-reagent ammonia nitrogen on-line continuous analyzer provided by the invention can reduce cross contamination of reagents, reduce reagent consumption and realize short-interval continuous analysis.

The invention relates to the field of data processing, in particular to a positioning data processing method and device, electronic equipment and a storage medium. According to the embodiment of the invention, a plurality of positioning points and longitude and latitude parameters in the current acquisition period are firstly obtained, and the data volume is increased. The error influence of a single positioning point caused by instantaneous factors such as satellite signal quality fluctuation and a multipath effect can be reduced. Secondly, the positioning points are constructed into a positioning point sequence in a time sequence, the positioning point sequence is input into a sliding window, and continuous analysis can be carried out on positioning data in a period of time; furthermore, the first target positioning point is updated by acquiring the target positioning point and the target longitude and latitude parameters in the sliding window, and the whole positioning point sequence is updated in sequence, so that a data smoothing effect is realized. According to the updating mode, information of surrounding positioning points which are close in time is utilized, and the positioning points which may drift are corrected.

The invention provides a cardiac autonomic neurodynamics quantitative evaluation method based on a phase ordering signal averaging technology. The cardiac autonomic neurodynamics quantitative evaluation method comprises an ECG signal preprocessing step, a QRS wave detection and processing step, a phase ordering signal averaging step and an autonomic neurodynamics quantitative analysis step. According to the cardiac autonomic neurodynamics quantitative evaluation method based on the phase ordering signal averaging technology, on the basis of inhibiting aperiodic interference and improving index stability in a complex physiological environment, continuous analysis of cardiac sympathetic nerve activity and cardiac parasympathetic nerve activity is carried out; time-varying CSI and CPI indexes are extracted to realize quantification of cardiac autonomic neurodynamics, and a lightweight algorithm framework is designed to adapt to real-time monitoring requirements of portable equipment.

The invention relates to the technical field of distribution boxes, in particular to a distribution box cloud management-based fault diagnosis system, which comprises a sensing module used for sensing operation state parameters and environmental parameters of a distribution box; the analysis module is used for receiving the distribution box operation state parameters and the environment parameters sensed by the sensing module, analyzing the distribution box fault risk by using the distribution box operation state parameters, and analyzing the distribution box fault tendency by using the distribution box operation environment parameters; according to the method, the operation state parameters and the environment parameters of the distribution box are collected, the fault risk and the fault tendency of the distribution box are continuously analyzed, continuous fault diagnosis is carried out on the distribution box by combining the two analysis results, and a certain prediction effect is achieved in the diagnosis process; therefore, the system has certain predictability for fault diagnosis of the distribution box.

The invention discloses an oil abrasive particle enrichment chip based on sound control and an LIBS (laser-induced breakdown spectroscopy) detection system and method.The enrichment chip is internally provided with an enrichment flow channel, and enrichment of oil abrasive particles is achieved through sound field driving; the detection system comprises a driving device, an enrichment chip, a detection chip, a pulse pump and an LIBS spectral analysis module, the driving device is used for sending out an electric signal with a preset frequency to excite piezoelectric ceramics to form a preset sound field in an enrichment flow channel, and oil abrasive particles are directionally gathered under the action of the sound field; the pulse pump is used for pumping the oil liquid enriched by the enrichment chip into the detection chip; the detection chip is used for carrying out secondary dispersion on the enriched oil liquid; the LIBS spectrum analysis module is used for carrying out breakdown detection on the oil liquid dispersed by the detection chip so as to obtain oil liquid spectrum data. Through a closed-loop system of sound field dynamic enrichment, pulse pump time sequence conveying and LIBS high-frequency detection, real-time continuous analysis of oil abrasive particle components is achieved, and the limitation of a traditional static sampling mode is broken through.

The invention discloses an automatic attendance checking, abnormal behavior detection and classroom condition analysis device based on computer vision, and relates to the technical field of intelligent education, the device comprises a front-end user interface, a rear-end server and a database; the system integrates attendance checking, abnormal behavior monitoring and classroom condition analysis functions, the classroom attendance checking module is provided with a dynamic window, a comparison algorithm is optimized, caching and early warning are combined, accurate non-inductive attendance checking and abnormity reminding are achieved, the abnormal behavior detection module fuses multiple algorithms and a dynamic threshold value, behaviors are recognized, instantaneous actions are filtered, continuous analysis is achieved, and the classroom attendance checking system is suitable for being popularized and applied. The method fills the blank of abnormal behavior analysis, realizes visual display of attendance and abnormal behavior detection results by superposing state labels through a front-end real-time monitoring panel and supporting historical data calling, automatically generates a classroom condition analysis report containing analysis data according to the detection results, provides real-time behavior feedback, assists teachers in mastering classroom dynamic conditions in real time, and improves the teaching efficiency. And support is provided for teaching decision making.

The invention discloses a landslide geological disaster deduction method and system based on an MPM method, and the method comprises the steps: collecting the multi-source data of a disaster scene, and synchronously constructing a digital twinborn model; a qualitative and quantitative two-stage inversion calibration model is adopted; a qualitative layer combines a monitored displacement direction and a deformation mode, and preliminarily inverts key parameters such as slip band cohesive force and an internal friction angle; the quantitative layer comparison model calculates the actual deformation range, collapse position and displacement, and parameters are optimized to match the actual landslide state; in landslide long-term evolution deduction, a rock-soil body aging characteristic model is embedded, an exponential function is used for describing annual scale parameter deterioration, prediction is divided into continuous analysis steps, MPM calculation is carried out based on a material point method, full-cycle simulation from the current year to the future years is completed, and deformation range, displacement and outburst risk results are output. And reliable decision support is provided for disaster prevention and reduction.

The invention provides a decision-making method and system for the influence of water and sand linkage above a slope on the erosion amount below the slope. The system comprises an experiment control unit, an REE element layout unit, a dynamic monitoring network unit and a data acquisition and analysis unit. The experiment control unit comprises a parameterization experiment design module and a process sample dynamic sampling module, and the REE element laying unit comprises a layering marking module and a tracer agent selection and stability control module; the method not only objectively describes the temporal and spatial change rule of relative erosion amounts of different parts of the slope in the erosion occurrence process, but also can continuously analyze the influence of water and sand coming from the upper part of a certain section of the slope on the erosion process below, thereby dynamically judging and measuring the slope sediment source and analyzing the influence of water and sand linkage above on the erosion process below. The purpose of monitoring the sediment source and the soil erosion amount of different terrain parts is achieved.

The invention relates to the technical field of resistance adjustment, in particular to a multifunctional spinning and a multifunctional spinning system, and the system comprises a pedaling frequency recognition module, a state judgment module, a stage control module, a load adjustment module and an output response module. According to the invention, through continuous analysis of the pedaling frequency and time information, accurate recognition of the rhythm fluctuation state, and combination of the linkage change of the flywheel rotation speed and the pedal pressure, the dynamic judgment of the motion stability and the matching mechanism of the training time and stage setting are realized; a resistance adjusting strategy is deduced according to the relation between flywheel acceleration and pedal pressure, the sensitivity and precision of regulation and control response are enhanced, the load weight is set by fusing the heart rate change trend, the resistance output is more matched with the individual physiological state, the load rhythm matching degree is optimized, and the training efficiency is improved. And the rhythm following capability, the resistance adjustment rationality and the training individuation level are integrally improved.

The invention discloses an automatic ship collision avoidance decision-making system, and relates to the technical field of ships, and the technical scheme is characterized in that the method comprises the steps: collecting environment data of a target ship in a navigation region and target ship dynamic data of the target ship in a navigation process; dividing the navigation area into navigation area blocks according to the risk level and the environmental data, and performing feature extraction on the dynamic data of the target ship to obtain dynamic feature parameters; analyzing and determining the normal variation range of the influence coefficients of the navigation region blocks with different risk levels to obtain a reference interval value; according to the reference interval value, performing statistics on influence coefficients between the current target ship and the surrounding environment and between the current target ship and other ships in the sailing process to obtain a statistical result, and comparing the statistical result with the reference interval value to obtain a collision avoidance risk early warning or continuous analysis instruction; the method has the effects of reducing the occurrence rate of collision accidents and improving the safety and orderliness of marine navigation.

The invention relates to the technical field of online psychological counseling, in particular to a verbal skill reply method and system for online psychological counseling, and the method comprises the following steps: based on original data of emotional states and psychological counseling demands, carrying out symbol distribution on differentiated states and demands, carrying out initialization coding processing on the data, and generating a symbol set initial framework; according to the method, the verbal skill strategy is accurately mapped through initialization coding and symbol optimization, loss in the information transmission process is effectively avoided, information exchange in the consultation process is smoother and more accurate, continuous analysis and iterative adjustment of the information transmission efficiency are beneficial to continuously optimizing the reply strategy, the overall consultation quality is improved, and the consultation efficiency is improved. By simulating the psychological influence of the differentiated verbal skill strategy and drawing the influence map, potential psychological risks can be accurately predicted and avoided, it is ensured that the consultation service can better meet the actual needs of the help seeker, implementation of personalized services is enhanced, and psychological health of the user is promoted.

The present invention relates to a self-propelled forage harvester (1) comprising a height-adjustable header (4) for receiving crop (2), working units (20) for processing the received crop (2), an unloading device (15) for discharging the processed crop (2), a camera system (16) for capturing images (41) of a crop flow (21) passing through the forage harvester (1), an image evaluation device (27) for evaluating the images (41), and a driver assistance system (17) for controlling the header (4), the working units (20), and the unloading device (15), wherein the driver assistance system (17) has a memory (40) for storing data and a computing device (39) for processing the data stored in the memory (40), wherein the image evaluation device (27) together with the driver assistance system (17),The front attachment (4) and the working units (20) form an automatic setting system, in that the image evaluation device (27) is configured to continuously analyze the images (41) of the crop flow (21) for the proportion of, in particular inorganic, impurities contained in the crop flow (21) by means of a machine learning algorithm and to transmit a derived degree of contamination (DC) to the driver assistance system (17), which autonomously and continuously adapts a setting of the front attachment (4) and / or at least one of the working units (20) depending on the degree of contamination (DC).

According to the building intelligent monitoring method and system provided by the invention, the same target person is locked through target detection / target tracking, and continuous analysis is carried out in a detection period, so that the misjudgment risk caused by other persons, shielding and instantaneous noise can be remarkably reduced, and the evaluation stability is improved. By fusing the deviation (abnormal sight value during walking) of the sight, the head orientation and the walking direction with abnormal gravity center and upper limb action (abnormal walking value), an early risk signal can be captured before the abnormal behavior is upgraded, and the sensitivity and the recognition timeliness of the abnormal state are improved. And an abnormal total value is formed by using weighted average and is compared with a threshold value, so that the balance of false alarm and missing alarm can be realized in different building scenes, and the alarm result has higher availability and credibility. Finally, by marking the target personnel and pushing the warning command, security personnel can obtain clear risk objects and early warning prompts in the first time, the response time is shortened, and the field disposal efficiency and the overall security level are improved.

The invention relates to a cerebrospinal fluid dynamic monitoring management method. Comprising the following steps: performing mode identification by using dynamic characteristics of cerebrospinal fluid pressure and flow velocity; by monitoring the flow velocity and pressure fluctuation of cerebrospinal fluid in real time, a comparison library of a normal mode and an abnormal mode is established; deep learning is carried out by using a fluid mechanics model and a neural network, and abnormal points of non-linear change are identified; through combination of a pressure sensor array and a flow velocity sensor, dynamic flow changes are captured in different areas of a cerebrospinal fluid system including a ventricle and a subarachnoid space, and abnormal fluctuations are identified through continuous analysis of time sequence data; by analyzing the interaction between the intracranial flow mode of cerebrospinal fluid and the compression expansion effect of brain tissues, an intelligent adjustment mechanism based on the flow pressure coupling effect is introduced; under the influence of cerebrospinal fluid pressure changes, deformation of brain tissue including ventricular expansion influences blood flow and tissue pressure in other intracranial areas.

The invention discloses a modification method of NAD (P), which comprises the following steps: S1, reacting Br <-> (CH2) x-NH2. HBr with NAD (P) to obtain N1-(x-(CH2) xNH2)-NAD (P) < + >; s2, carrying out rearrangement reaction on the N1-(x-(CH2) xNH2)-NAD (P) < + > to obtain N6-(x-(CH2) xNH2)-NAD (P) < + >; wherein x is equal to 2-6. The invention further provides a method for fixing the modified NAD (P) and a continuous analysis sensor. The method provided by the invention is environment-friendly and harmless, amino groups are modified and added on the NAD (P), and the NAD (P) can be effectively fixed, so that the stability of the sensor is effectively enhanced, and the service life of the sensor is prolonged.

The invention relates to a sampling device, in particular to a sampling device for real-time continuous analysis of end expired gas. Comprising first to fourth three-way valves, a first sampling ring, a second sampling ring, an air pump, a purging pipeline, an exhalation pipeline, a carbon dioxide sensor and an analysis detector, the air inlets of the first sampling ring and the second sampling ring are connected with a purging pipeline through a first three-way valve and are connected with an exhalation pipeline provided with a carbon dioxide sensor through a second three-way valve; air outlets of the first sampling ring and the second sampling ring are connected with an analysis detector through a third three-way valve and are connected with an air pump through a fourth three-way valve; through linkage switching of the first three-way valve, the second three-way valve and the third three-way valve, the fourth three-way valve and the fourth three-way valve, the first sampling ring and the second sampling ring alternately conduct sampling and sample injection, and real-time accurate sampling and continuous sample injection analysis of tail end expired gas in each respiratory cycle are achieved. The device is high in time resolution, accurate in terminal expired gas sampling, constant in volume and good in detection result consistency.

A continuous analyte monitoring device includes an outer housing, a cover, a puncture unit, and a monitoring unit. The outer housing has first and second ends opposite to each other in a first direction. The second end has an implantation opening. The cover is detachably connected to the outer housing. A driving unit is movable along the first direction to perform an implantation operation. The puncture unit is movable along a second direction to perform a needle withdrawal operation. The monitoring unit includes a first monitoring component including a sensor and a second monitoring component including a signal processing module. Prior to use, remove the cover and perform a single trigger to enable the driving unit to move along the first direction, thereby partially inserting the sensor into a host and establishing an electrical connectivity between the first and the second monitoring components.

The invention relates to a micro-fluidic chip for efficient separation of a micro gas chromatograph, the micro-fluidic chip for efficient separation of the micro gas chromatograph comprises a silicon wafer, a water cooling structure arranged above the silicon wafer and a heating element and a temperature measuring element arranged below the silicon wafer, and the water cooling structure is manufactured by adopting the micro-nano machining bonding process. And the water cooling structure is tightly connected with the upper part of the silicon wafer in an attached manner by adopting an anodic bonding mode. According to the micro-fluidic chip for efficient separation of the micro-gas chromatograph, the water cooling structure is prepared on the silicon wafer in a bonding manner, so that the micro-fluidic chip for efficient separation of the micro-gas chromatograph is applied to form a micro-chromatographic column through the water cooling structure after analysis is completed under the condition that the size of the chip is not increased; the cooling waiting time during continuous analysis can be greatly shortened, the power consumption is reduced, and the problem of high power consumption caused by poor cooling effect due to the fact that the power consumption is reduced by a natural cooling mode of an existing miniature gas chromatograph is solved.

The invention relates to the technical field of network security, and discloses an enterprise data security management system based on a cloud platform, which comprises a data acquisition module, a data analysis module, a security evaluation module and an operation management module, the encryption state and the backup frequency of enterprise data stored in each resource pool of the cloud platform by a target enterprise are periodically acquired, behavior logs in the storage and reading process of the enterprise data in each resource pool are acquired in real time, and the behavior logs comprise an access behavior log, a transmission behavior log and a processing behavior log. Encryption states, backup frequencies and behavior logs in the resource pools are comprehensively obtained through regular collection and real-time collection of enterprise data in the resource pools, and static risk scores, dynamic risk trend scores and comprehensive risk scores in the resource pools are calculated by dividing a monitoring period into a plurality of continuous analysis windows. And identifying high-risk data in the resource pool.

The invention relates to the technical field of frequency matching, in particular to a frequency matching method of an interphone and the interphone, and the method comprises the following steps: based on an interphone frequency signal, measuring the signal intensity of each channel, counting the intensity change of the signal in a target time period, and evaluating the signal interference level of the interphone. According to the method, the channel with the best performance is effectively screened out through careful measurement and ratio calculation of the signals and the interference of the interphone channels, the communication quality is improved, interference suppression and channel performance adjustment are more accurate through analysis of the interference source and accurate identification and classification of the interference, and through continuous analysis of the signals and the interference, the communication quality is improved. According to the invention, stable channel performance can be realized, the communication efficiency of the interphone can be improved, and through frequent monitoring and dynamic adjustment of channel configuration, the working environment change can be adapted, so that the communication path is continuously optimized, the influence of interference is reduced, and the stability and reliability of interphone communication are ensured.

The invention relates to the technical field of data processing, and discloses an inspection management method for a power distribution network, which is used for improving the inspection management efficiency of the power distribution network. The method comprises the following steps: collecting and preprocessing multi-source data of a plurality of distribution network inspection nodes of a distribution network to obtain de-noised multi-dimensional image data; performing feature extraction processing on the multi-dimensional image data to obtain equipment abnormal feature data of a plurality of distribution network inspection nodes; performing data fusion processing on the equipment anomaly feature data of the plurality of distribution network inspection nodes to obtain time-space associated equipment anomaly comprehensive data; performing continuous analysis processing on the equipment abnormal comprehensive data through a space-time tracking algorithm to obtain equipment abnormal space-time change data; performing intelligent positioning processing on the equipment abnormal spatial-temporal change data to obtain equipment fault spatial coordinate data; and performing anomaly level evaluation processing on the equipment fault space coordinate data based on a priority ranking algorithm to obtain equipment anomaly priority information.