9 results about "Transfer path analysis" patented technology

The present application relates to a kind of all-weather power grid equipment abnormal sound monitoring device and its sound source positioning method, belong to the technical field of power equipment online monitoring and fault diagnosis.The device includes: multiple microphone units, each microphone unit includes microphone body and the e-PTFE sound-permeable film covered on its surface, for efficiently permeating sound wave while blocking wind and rain erosion;Multiple three-legged stand poles with water-blocking umbrella covers, at least one microphone unit is arranged on each stand pole, and is distributed around the power grid equipment to be monitored;Data processing unit;And solar power supply module and protection cabin.The method includes: setting loudspeaker array at the suspected abnormal sound source position, using exponential sine sweep method to measure the frequency response function matrix of loudspeaker to microphone unit;After removing the loudspeaker, based on the measured frequency response function matrix and the sound pressure signal collected in real time, the abnormal sound source signal is extracted and the path contribution is calculated using the transfer path analysis method based on regularization.

This invention relates to the fields of data analysis and intelligent marketing technology. Specifically, it relates to a method and system for intelligently generating marketing strategies based on high-dimensional customer profiles. This invention combines event-driven and time-sliding window approaches to obtain category-differentiated decay functions. It updates demand intensity values ​​by setting dynamic decay rates based on product lifecycles and customer stickiness. Through cross-cycle behavior matching and spatiotemporal alignment of demand intensity waveforms, it identifies demand transfer logic chains and labels core demand tags. It aggregates tag strength and commercial factors to generate a list, triggers marketing resource migration with dual thresholds, collects response data, and compares conversion rate deviations to optimize parameters and complete self-calibration. The system includes a demand intensity calculation unit, a demand transfer path analysis unit, a strategy dynamic optimization unit, and a decay calibration feedback unit. This invention solves the problems of strategy lag and resource mismatch, improves marketing accuracy and resource utilization, and adapts to changing demand scenarios in the maternal and infant and home appliance industries.

The application discloses a kind of running conditions under vehicle interior structure road noise diagnostic test method, belong to automobile structure road noise diagnostic technical field, comprising the following steps: S1, establish vehicle transmission path analysis model: define unevenness of road as excitation source, rubber bushing of vehicle chassis suspension system is vibration energy transmission path, vehicle body is as vibration receiving structure;S2, transfer function test and acquisition: obtain two core transfer functions by vehicle body noise transfer function and origin dynamic stiffness test;S3, running condition simulation and sound pressure-acceleration transmission relationship derivation: S4, based on step S3 obtains sound pressure-acceleration transfer function.The running conditions under vehicle interior structure road noise diagnostic test method can be used for the diagnosis optimization of vehicle interior structure road noise, can shorten test cycle, improve transmission path analysis accuracy simultaneously, provide new ideas for transmission path analysis, with good engineering application value.

The application discloses a multi-shaft reducer vibration tracing method and system based on a transfer path analysis method, and belongs to the technical field of reducer vibration tracing analysis. The method comprises the following steps: arranging a vibration sensor array and a 1m radius microphone array on the surface of a reducer, and synchronously collecting sound and vibration signals; constructing a transfer function matrix through a reciprocity method; converting frequency domain signals through a short-time Fourier transform; reducing noise by using an improved adaptive hyperbolic compression threshold wavelet algorithm; screening effective transfer paths based on partial coherence-recoherence composite analysis, and perfecting a path set through a confidence level grading mechanism (A level γ 2 ≥0.85, B level 0.7≤γ 2 <0.85); and quantifying path contribution to realize vibration tracing. The method solves the problem of insufficient coverage of mixed paths from multiple sources, improves the main path recognition efficiency by more than 40%, and the contribution error is less than or equal to 3dB.

The invention relates to a noise reduction method of an intelligent electric appliance and the intelligent electric appliance thereof.The intelligent electric appliance is provided with an air inlet and an air outlet, the air inlet and the air outlet are each provided with a flow guide part, and the angle and height of each flow guide part are adjustable. The noise contribution amount from the air inlet to the target monitoring point and the noise contribution amount from the air outlet to the target monitoring point are calculated based on a working condition transmission path analysis method; according to the size relation and the positive and negative characteristics, the adjusting path and strategy of the flow guide part are determined, so that optimal control over the angle and height of the flow guide part is achieved. The noise reduction method has the advantages that the noise contribution of the air inlet and the noise contribution of the air outlet can be accurately distinguished, data support is provided for noise reduction optimization, and the noise reduction effect is better.

The application discloses an accelerating rough sound optimization method and system and a storage medium, which comprises the following steps: step one, arranging cylinder pressure, torsional vibration, vibration sensor and microphone on a whole vehicle; step two, the whole vehicle drives according to a set working condition, and first test data is collected; step three, the whole vehicle drives according to a problem working condition, and second test data is collected; step four, the second test data is analyzed to determine an excitation source of the accelerating rough sound in the vehicle; step five, a whole vehicle model is established by using an Operational Transfer Path Analysis module of LMS software, the first test data is imported into the whole vehicle model, and initial transfer functions on each transfer path are calculated; step six, the initial transfer functions and the second test data are imported into the whole vehicle model, and the main transfer path with the largest contribution to the noise in the vehicle under the problem working condition is calculated; and step seven, the excitation source and structural members on the main transfer path are optimized. The accelerating rough sound in the vehicle can be optimized from the excitation source and the transfer path, and the comfort is effectively improved.

The present application relates to the field of signal processing of mechanical system, and particularly relates to a working condition transmission path analysis method, comprising the following steps: establishing a finite element model at the passive end of a machine; arranging acceleration sensors and strain sensors at a reference point and a target point of the machine, and obtaining acceleration and strain information of the reference point and the target point respectively under the operating condition of the machine, and constructing a target point response matrix; estimating optimal state variables according to the acceleration and strain information of the reference point, wherein the optimal state variables contain interface forces of the reference point, and constructing an interface force matrix; performing fast Fourier transform on the target point response matrix and the interface force matrix; constructing a transmission rate function; and calculating total contribution of each transmission path. The present application can eliminate the influence of crosstalk to a certain extent, and improve the accuracy and stability of the transmission rate function.

The application provides a train running gear bearing fault real-time detection method and device and a train, which can be applied to the field of rail transit technology. The method comprises the following steps: acquiring a characteristic value of a real-time vibration acceleration signal of a train end running gear bearing; dynamically matching the characteristic value of the simulation vibration acceleration signal with the characteristic value of the real-time vibration acceleration signal to obtain a nonlinear relationship between the characteristic value of the real-time vibration acceleration signal and a test fault defect size; processing an estimated fault defect size obtained by inversion of the nonlinear relationship based on a fault displacement excitation, a bearing radial clearance and attribute parameters, real-time working condition parameters and a real-time load spectrum of the running gear bearing to obtain a vibration acceleration initial simulation signal, performing real-time transfer path analysis on the vibration acceleration initial simulation signal to obtain a vibration acceleration simulation signal; and performing real-time processing on the vibration acceleration simulation signal received by the train end to obtain a fault real-time detection result of the running gear bearing.

The application provides a structural engineering bearing capacity on-site detection method, and belongs to the technical field of structural engineering detection.The application installs multi-axial acceleration sensors and strain gauge arrays on the surface of a structure component to be detected, applies incremental load by using an intelligent loading device, collects vibration response data and strain response data in real time by using a mobile data collection terminal, extracts modal parameters based on a frequency domain analysis method to establish a load-modal parameter relationship curve, analyzes and calculates the bearing capacity of the component, optimizes a load transfer path analysis by using a graph theory shortest path algorithm, and accurately evaluates the bearing performance of the component by using a structure response prediction model based on a Transformer architecture, so that technical integration of multi-dimensional detection data fusion, intelligent loading control, quantitative bearing capacity evaluation and accurate performance prediction is realized, and the technical problem of insufficient detection precision of the bearing capacity of the structure component is solved.