8 results about "Alarm filtering" patented technology

A system capable of optimizing early alarm operation by introducing an alarm filtering technology so as not to cause false alarm to an abnormal signal due to signal noise is disclosed. The system comprises: a data acquisition unit for selectively acquiring historical data according to the operation of a electric power facility by selecting a preset multivariate input tag; a recommendation unit for generating learning data, which is a multivariate signal for machine learning, based on a preset similarity from the historical data; a compression unit for generating re-sampling data by compressing the learning data; a learning unit for performing real-time monitoring by using the re-sampling data as input data of a pre-designed early warning learning model; and a calculation unit for generating a final warning when a predetermined condition predefined through the real-time monitoring is satisfied.

The application relates to the field of liquid treatment, in particular to a negative pressure self-alarming filter device which comprises a rigid vertical cylinder, a quick-release inner filter is arranged in the inside of the rigid vertical cylinder, a feeding pipe is arranged on the outer sidewall of the rigid vertical cylinder at the upper portion of the quick-release inner filter; a plugging bottom cover is tightly screwed on the bottom of the rigid vertical cylinder, a discharging pipe is arranged on the outer sidewall of the lower portion of the rigid vertical cylinder, a plugging top cover is arranged on the upper connecting flange of the top of the rigid vertical cylinder, one side of the plugging top cover is connected with the upper connecting flange through a lifting lug bolt, a pressure reference control component is arranged at the center hole of the plugging top cover, and an output end pressure component matched with the pressure reference control component is arranged on the rear sidewall of the lower portion of the rigid vertical cylinder.

The application discloses a method and system for alarm screening display based on power plant working conditions and operation tasks, and the method comprises the following steps: establishing a power plant working condition alarm list corresponding to each power plant working condition according to different power plant working conditions, and screening alarm contents of the power plant working condition alarm list according to different state characteristics of different working conditions; establishing a self-defined alarm list according to operation tasks, and inputting alarm contents of the self-defined alarm list according to the operation tasks, which are different from the alarm contents of the power plant working condition alarm list; when an alarm is triggered, identifying whether the alarm is the alarm content of the power plant working condition alarm list or the self-defined alarm list, if yes, locating the position of the alarm in the two lists, and displaying the alarm on an interface. Through implementation of the application, the task load of alarm response of operators can be reduced in the work of the nuclear power plant, the performance of the operators is improved, and the risk of human error is reduced.

The embodiment of the invention provides an automatic task alarm filtering method based on a multi-layer dynamic threshold value, and belongs to the technical field of data processing, and the method specifically comprises the following steps: retrieving all task data which is completed in a time window based on pre-configuration and has a final state of a preset completion state from a database; screening the task data by using a predefined normal state code set, and screening out the task data of which error codes exist in the normal state code set; sequentially executing at least three rounds of filtering based on a predefined static blacklist rule on the screened task data; distributing a real-time counter in a time window for each task type-error code combination, and taking the task data as target data when a count value of the real-time counter exceeds a threshold value of the corresponding combination; and assembling the target data into a structured alarm message, and pushing the structured alarm message based on the dynamically determined on-duty person information. By means of the scheme, the filtering precision and adaptability are improved.

In various embodiments, a process for alert filtering based on service to facilitate triage includes receiving an alert, identifying a configuration item of a computer information technology configuration management system associated with the alert, and identifying a property of the configuration item stored separately from one or more properties included in the alert. The process includes enabling filtering of the alert based on the property of the configuration item.

The invention belongs to the technical field of monitoring systems, and particularly relates to a data machine room environment dynamic monitoring system which comprises an intelligent sensing layer, an edge computing layer, a cloud analysis layer and a user interaction layer. The edge computing layer and the cloud analysis layer cooperatively execute three-level alarm filtering: in the first level, sensor data transient noise filtering is performed at an edge computing node; the second stage executes multi-sensor correlation analysis at an edge computing node to locate a root cause fault; and the third level verifies the alarm effectiveness in a cloud analysis layer through a dynamic threshold model trained by historical data, and the dynamic threshold model is associated with an equipment aging factor to correct an alarm triggering condition. The sensor data is preprocessed in real time through the edge calculation layer, the data transmission amount is reduced, the network delay is reduced, the real-time performance of the system is remarkably improved, and abnormal changes of the machine room environment can be quickly responded.

The invention discloses a host security fine management and control system of an industrial control system, which comprises an application layer, a data transmission and analysis layer and an acquisition and terminal protection layer, and is characterized in that the application layer comprises a security instrument panel, a log analysis unit, a security alarm unit and a peripheral management unit; the data transmission and analysis layer comprises a log centralized convergence engine, a security baseline check engine, a user state management engine and an alarm optimization engine; and the acquisition and terminal protection layer comprises enhanced host Agent clients deployed at the industrial control nodes. According to the host security fine management and control system of the industrial control system disclosed by the invention, by constructing the enhanced host Agent client and a multi-engine collaborative architecture, log collection comprehensiveness, data processing high efficiency, baseline check refinement, account management and control precision and alarm filtering intellectualization are realized, and the host security protection capability of the Eimeson industrial control system is improved.

This invention discloses a method for analyzing the causes of alarm filtering failures in a network management system, including: S1. Retrieving relevant alarms and rules through an interface query, selecting one alarm and one rule as input parameters and passing them to the controller; S2. A verification environment generator searches for the filtering conditions of a rule based on its rule ID and dynamically compiles and generates a corresponding verification simulation environment; S3. Passing the alarm into the verification simulation environment to match each filtering sub-condition and obtain the filtering result; S4. Passing the filtering result into a filtering result analyzer to obtain an analysis report; S5. Displaying the analysis report on the interface. This invention transforms the problem analysis process from manual to code-based, improving analysis efficiency, reducing the probability of errors, and increasing the accuracy of problem analysis. Through interface interaction and the provision of precise and detailed analysis reports, it not only provides a user-friendly and intuitive way to locate the causes of filtering failures for specific alarms and rules but also reduces learning costs and labor costs.