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604 results about "Moving average" patented technology

In statistics, a moving average (rolling average or running average) is a calculation to analyze data points by creating a series of averages of different subsets of the full data set. It is also called a moving mean (MM) or rolling mean and is a type of finite impulse response filter. Variations include: simple, and cumulative, or weighted forms (described below).

Method and Apparatus for Pump Control Using Varying Equivalent System Characteristic Curve, AKA an Adaptive Control Curve

The present invention provides, e.g., apparatus comprising at least one processor; at least one memory including computer program code; the at least one memory and computer program code being configured, with at least one processor, to cause the apparatus at least to: respond to signaling containing information about an instant pressure and a flow rate of fluid being pumped in a pumping system, and obtain an adaptive control curve based at least partly on the instant pressure and flow rate using an adaptive moving average filter. The adaptive moving average filter may be based at least partly on a system flow equation: SAMAt=AMAF(Qt/√{square root over (ΔPt)}), where the function AMAF is an adaptive moving average filter (AMAF), and the parameters Q and ΔP are a system flow rate and differential pressure respectively. The at least one memory and computer program code may be configured to, with the at least one processor, to cause the apparatus at least to obtain an optimal control pressure set point from the adaptive control curve with respect to an instant flow rate or a moving average flow rate as SPt=MA(Qt)/SAMAt, where the function MA is a moving average filter (MA), to obtain a desired pump speed through a PID control.

A CNN and LSTM-based rolling bearing residual service life prediction method

The invention discloses a CNN and LSTM-based rolling bearing residual service life prediction method, and relates to the field of rolling bearing life prediction. The method aims to solve the problemthat residual service life (RUL) prediction of a rolling bearing is difficult in two modes of performance degradation gradual change faults and sudden faults. The method comprises the following stepsof: firstly, carrying out FFT (Fast Fourier Transform) on an original vibration signal of the rolling bearing, then carrying out normalization processing on a frequency domain amplitude signal obtained by preprocessing, and taking the frequency domain amplitude signal as the input of a CNN (Convolutional Neural Network); The CNN is used for automatically extracting data local abstract informationto mine deep features, and the problem that a traditional feature extraction method depends too much on expert experience is avoided. the deep features are input into an LSTM network, a trend quantitative health index is constructed, and a failure threshold value is determined at the same time; And finally, smoothing processing is carried out by using a moving average method, eliminating local oscillation, and a future failure moment is predicted by using polynomial curve fitting to realize rolling bearing RUL prediction. And the prediction result can be well close to the real life value.

Dynamic reverse link rate limit algorithm for high data rate system

A method for determining the reverse link data Rate Limit for mobile stations active on the reverse link of a High Data Rate system is disclosed. In the ideal case, the Rate Limit is based on only the number of mobile stations located in a common sector that are actually active on the reverse link. Currently, the Rate Limit is determined from the total number of mobile stations in a common sector where the total includes mobiles that are transmitting and receiving. Thus, the current method includes mobile stations that are active on the forward link and may not be active on the reverse link. In this invention, a more optimum method of estimating the reverse link loading is obtained from calculations which includes only the mobile stations which are active on the reverse link. An estimate of the reverse link loading of the mobile stations in a common cell is obtained by adding together the data rates of the data sent from each mobile in a common sector during a common frame. This aggregate rate of data during the frame is filtered to minimize irregularities by using the moving average of an infinite impulse response filter and then normalized. The normalized result is a percentage of the maximum achievable aggregate reverse link rate. The final result is compared with a set of threshold values to obtain the maximum Rate Limit that is then set for each mobile station.

Method for reducing fetch time in a congested communication network

Congestion within a communication is controlled by rate limiting packet transmissions over selected communication links within the network and modulating the rate limiting according to buffer occupancies at control nodes within the network. Preferably, though not necessarily, the rate limiting of the packet transmissions is performed at an aggregate level for all traffic streams utilizing the selected communication links. The rate limiting may also be performed dynamically in response to measured network performance metrics; such as the throughput of the selected communication links input to the control points and/or the buffer occupancy level at the control points. The network performance metrics may be measured according to at least one of: a moving average of the measured quantity, a standard average of the measured quantity, or another filtered average of the measured quantity. The rate limiting may be achieved by varying an inter-packet delay time over the selected communication links at the control points. The control points themselves may be located upstream or even downstream (or both) of congested nodes within the network and need only be located on only a few of a number of communication links that are coupled to a congested node within the network. More generally, the control points need only be associated with a fraction of the total number of traffic streams applied to a congested node within the network.

Agile elastic telescoping method in cloud environment

The invention relates to the field of elastic computing of cloud computing, and discloses an agile elastic telescoping method in a cloud environment. The agile elastic telescoping method includes the specific steps: forecasting the load of a next time slice according to historical load data of a data center through an ARIMA (autoregressive integrated moving average) model and an ARMA (autoregressive moving average) model by taking the time slice as a cycle; performing saving operation and restoring operation on a virtual machine, saving the memory state of the virtual machine by the saving operation to hang up the virtual machine, and then restoring the memory state of the virtual machine by the restoring operation to restore use of the virtual machine; hanging up one or a plurality of application-ready virtual machines or rapidly placing the virtual machines into service through the forecasted load of the data center obtained by the load forecasting step and by the aid of the rapid supply step of the virtual machines to dynamically adjust resources of application clusters of the data center. The agile elastic telescoping method has the advantages that the sizes of the clusters are adjusted in real time according to current conditions of the application clusters, and energy consumption of the data center is reduced.

Indoor passive positioning method based on channel state information and support vector machine

The invention discloses an indoor passive positioning method based on channel state information and a support vector machine. The method comprises the following steps: firstly preprocessing the acquired channel state information data, performing de-noising and smoothness through the adoption of a density-based spatial clustering of applications with noise and a weight-based moving average algorithm, and then using the principal component analysis algorithm to extract the features. The data after the preprocessing and feature-extracting can reflect the signal change more accurately and the dimension is greatly reduced. The passive positioning adopts two-stage positioning. In the training stage, the large positioning space is divided into sub-regions, the support vector machine classification and regression model is established for each sub-region so as to acquire a statistic model for accurately representing the nonlinear relationship between the position and the signal. The two-stage positioning firstly determines the sub-regions through the classification of the support vector machine, and the precision position is determined in the sub-region through the regression of the support vector machine. The method disclosed by the invention has the beneficial effects that the passive positioning can be performed in the absence of the active participation of the target, and the indoor positioning precision is improved to sub-meter level.

Microgrid energy optimization method based hybrid energy storage dispatching under different time scales

InactiveCN104617590AIn line with actual operating conditionsMeet scheduling needsSingle network parallel feeding arrangementsForecastingMoving averageMicrogrid
The invention relates to a microgrid energy optimization method based hybrid energy storage dispatching under different time scales. Microgrid optimized dispatching is divided into day-ahead dispatching and real-time dispatching according to different time scales; for the day-ahead dispatching, the operation plan of future 24 hours is provided one day in advance, the time granularity is 1 hour, the connecting line interaction power and the fuel cell (FC) output are optimized according to the difference between the electricity prices in the peak and valley periods, and a storage battery (SB) is dispatched to achieve low-storage high-output interest arbitrage; the real-time dispatching coordinates with the day-ahead dispatching, the microsource output is allocated according to the day-ahead plan, the time granularity is 1 minute, the power fluctuation in the microgrid is smoothened by use of a first-order low-pass filtering algorithm, the filtered fluctuating power is distributed reasonably between storage battery energy accumulation and a super capacitor by use of a moving average filtering algorithm and then reference is provided for the optimized dispatching of hybrid energy storage.

Real-time navigation system and real-time navigation method for underwater structure detection robot

The invention discloses a real-time navigation system and a real-time navigation method for an underwater structure detection robot. The navigation system comprises a magnetic compass, a gyroscope, an accelerometer, a depth meter and a navigation microprocessor, wherein the magnetic compass, the gyroscope, the accelerometer and the depth meter are used for respectively collecting magnetic field intensity, an angular speed, a linear speed and submerged depth data and transmitting the magnetic field intensity, the angular speed, the linear speed and the submerged depth data to the navigation microprocessor; the navigation microprocessor is used for calculating attitude and position of the underwater robot according to the collected data. The navigation method comprises an attitude algorithm, a speed algorithm and a depth algorithm; according to the attitude algorithm, a complementary filtering method, a quaternion gradient descent method and a Kalman algorithm are combined for obtaining an attitude matrix and an attitude angle; the speed algorithm is used for calculating the speed and the position of the robot by using a three-order upwind scheme with rotary compensation; the depth algorithm is used for processing the data of the depth meter by using a moving average filter algorithm so as to obtain the submerged depth. By virtue of the real-time navigation system for the underwater structure detection robot and the method thereof, the navigation cost is reduced and a relatively good navigation precision is achieved.
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