59 results about "Statistical monitoring" patented technology

A tool for detecting potential impairment in an electronic device. The tool classifies the user input into various categories and determines some measurement, typically a rate of input per user or per time, for determining average use statistics of the electronic device. The tool then determines if a calculated measurement based on user inputs deviates from the average use statistics past some threshold level of deviation. In response to surpassing the threshold level of deviation, the tool identifies the electronic device as potentially impaired.

A statistical power indication monitor including a random pattern generator that generates random sample assertions of a sample signal, a total counter that counts a total number of the random sample assertions within a sample time interval, detect logic that provides a detection signal for each power indication signal that is asserted coincident with the sample signal, and counter logic that counts a number of assertions of each detection signal during the sample time interval. The assertion count of each power indication signal divided by the total count provides a statistical indication of power consumption of a corresponding system. A user may use the statistical monitoring information to adjust system or application operation. The random pattern generator may be a pseudo-random pattern generator including a linear feedback shift register and may have programmable seed and sample rate.

This specification discloses a method, device and electronic equipment for monitoring credit risk of an Internet financial platform, which relate to the technical field of Internet information processing. The method realizes distributed statistics on information flow based on server clusters, and the first statistics server serves as a distributed statistics processing request. The initiating end of the server can make the second statistics server perform synchronous processing with the first statistics server, thus improving the efficiency of information flow processing, and the first statistics server can determine the second statistics server in the process of receiving the second target information code. Whether the information security verification is passed, so as to ensure that the received second target information code is accurate and reliable, and performing reverse sharpening processing on the third pulse signal can effectively eliminate the configuration between the first statistics server and the second statistics server. Therefore, accurate and complete distributed statistical monitoring results can be determined, thereby ensuring the efficiency and reliability of information flow processing.

The invention relates to a statistical modeling, online monitoring and fault diagnosis technology of a superspeed carton packaging machine BV of the Italian G.D company and discloses a cigarette factory superspeed carton packaging machine multi-condition process online monitoring and fault diagnosis method. According to the method, a stable condition and a transition condition of stability factor identification are calculated based on a slide time window in an offline mode, the stable condition is divided to form a plurality of stable condition data clusters by use of an adaptive k-means cluster method, and then a statistical monitoring model is established independently for each stable condition data cluster by use of a PCA method. During online monitoring, a condition type is determined according to a stability factor of data in a current slide time window, under the stable condition, real-time monitoring is carried out by use of one PCA monitoring model corresponding to a cluster with a minimum distance, when any one statistical amount exceeds a limit, a major process variable causing a fault is determined by use of a contribution graph method, and finally, an effective feasible method is provided for online monitoring and fault diagnosis of the superspeed carton packaging machine BV.

The invention provides a cloud application fault diagnosis system based on statistical monitoring. The cloud application fault diagnosis system based on statistical monitoring comprises a monitoring agent, a running status tracker and a fault detection locator, wherein the monitoring agent is used for collecting monitoring information when a cloud application runs; the running status tracker is used for abstracting the running status of the system to be local outlier factors and correlation coefficients; the fault detection locator is used for analyzing the running status of the system according to monitoring data provided by the running status tracker so as to detect a fault and locate reasons of the fault. According to the method, the running status of the system is described from utilization and performance of system resources according to the monitoring data through the local outlier factor and kernel canonical correlation analysis method, the system fault is detected according to a control chart, and abnormal measurements are located through a feature selection method. The method has the advantages that related knowledge of the application such as a software system structure and parameter estimation is not needed, and the method is simple, easy to implement and wide in application range; various faults of the cloud application can be automatically detected without manual intervention, and the abnormal degrees of the measurements can be quantized.