8 results about "Noise assessment" patented technology

The invention relates to the technical field of noise evaluation, in particular to a self-ventilation motor fan aerodynamic noise simulation evaluation method. According to the technical scheme, the method comprises the steps of data acquisition and processing, deep learning model construction, simulation and optimization of a multi-physics coupling model and result fusion. According to the method, the hybrid deep learning model combining the convolutional neural network and the recurrent neural network is adopted, so that the noise prediction precision is remarkably improved, and the evaluation result is closer to the actual noise condition; a multi-physics coupling model is adopted to reflect the comprehensive influence of multiple factors on aerodynamic noise under actual working conditions, a noise generation mechanism is analyzed through a CFD model and an acoustic FEM model, a reliable physical basis is provided for noise evaluation, and errors are reduced; besides, the Bayesian fusion method is combined with the results of the deep learning model and the multi-physics field coupling model, the advantages of the two methods are comprehensively considered, the limitation of a single method is made up, and the reliability and stability of the evaluation result are further improved.

The invention relates to the technical field of noise detection, in particular to a high-precision equipment noise detection method, which comprises a mobile vehicle, a protective frame is fixedly connected to the surface of the mobile vehicle, a master control box is fixedly mounted on the surface of the mobile vehicle, a damping mechanism is arranged on the surface of the mobile vehicle, and the damping mechanism comprises a damping spring. The damping springs are fixedly connected to the surface of the moving vehicle, a telescopic damper is fixedly connected to the surface of the moving vehicle, a damping plate is fixedly connected to a telescopic rod of the telescopic damper, and an adjusting mechanism is arranged on the surface of the damping plate. According to the invention, the sound source is positioned through the sound source positioning instrument, after the noise source is determined, the adjusting mechanism is started to detect the detection equipment, and then the height and angle of the noise detector are changed, so that the detection precision is improved, and the noise can be better evaluated.

The invention relates to a noise evaluation method, device and equipment of a compressor, a medium and a program product. The method comprises the steps that a multi-body dynamics simulation model corresponding to the compressor is established based on geometric structure parameters of all parts in the compressor and the motion relation between all the parts; the multi-body dynamics simulation model comprises a plurality of body units and kinematic pairs among the body units; on the basis of the multi-body dynamics simulation model and corresponding preset driving of the compressor under the preset working condition, dynamic response of the compressor is predicted, and a prediction result is obtained; and based on the prediction result, the knocking noise risk of the compressor is evaluated, and an evaluation result is obtained. Thus, the actual running state of the compressor can be effectively simulated, the potential knocking problem can be recognized in advance, the knocking abnormal sound problem of the compressor product can be effectively found or predicted without depending on test and error, and the risk prediction capacity and optimization efficiency in the design stage are improved.

The present invention discloses an intelligent construction project operation and maintenance management platform and method, which relates to the technical field of intelligent construction projects. The present invention includes: a shopping mall information acquisition module, a shopping mall noise assessment module, a shopping mall noise processing module, a display terminal, and a database. The present invention determines the noise abnormality solution types of each noise-abnormal sub-region in the shopping mall, classifies and processes equipment noise and human flow noise, effectively ensures the rationality of the noise processing method in the shopping mall, improves the quality of noise processing, improves customer satisfaction, ensures the proportion of repeat customers, and avoids health problems such as hearing loss, increased stress, and sleep disorders among employees. The present invention generates group labels for noise-abnormal sub-regions inside the shopping mall, analyzes the urgency of noise processing in each region of the shopping mall, ensures the rationality of the order of noise processing in each region of the shopping mall, optimizes the balance of noise inside the shopping mall, and improves the efficiency of noise processing in the shopping mall.

The invention discloses a noise robustness auditory decoding method and system based on an adversarial domain adaptation network, and relates to the technical field of auditory decoding, and the method comprises the steps: obtaining a multi-channel electroencephalogram signal, and carrying out the parallel analysis and feature fusion; inputting the multi-dimensional signal integrity feature vector into a noise evaluation model, and outputting a noise complexity score; calling a feature decoupling module, and outputting a task-related feature vector and a noise-related feature vector; inputting the task related feature vectors into an attention decoder to obtain auditory attention distribution probability distribution; and an auditory attention distribution probability distribution and noise traceability and influence report is used as a noise robustness auditory decoding result of the target user. The technical problems that an existing auditory decoding method is low in decoding precision and insufficient in robustness in a noisy scene are solved.

This invention relates to the field of noise environmental impact assessment technology, and discloses a method and related apparatus for assessing the noise environmental impact of onshore wind farms. The method first constructs a discretized representation containing spatial coordinates, calculates noise propagation attenuation and directional parameters, and establishes a propagation path feature association array; it then matches the wind turbine sound power level with hourly meteorological data of the assessment benchmark year, determines the directivity correction amount, and forms a complete propagation array containing time-varying sound source parameters; it calculates and superimposes the hourly noise contribution value of each wind turbine, obtains the daily continuous equivalent sound level through energy averaging, and extracts the maximum continuous equivalent sound level as an evaluation index; based on the index, it generates a spatial distribution report of noise impact. This invention constructs a dynamic sound source intensity model, uses a gridded array algorithm to improve computational efficiency, comprehensively considers multiple attenuation mechanisms and the superposition effect of multiple wind turbines, accurately reflects the actual operating conditions of the wind farm, and significantly improves the accuracy and scientific nature of the noise assessment results.

The invention discloses an intelligent hearing aid noise reduction method combined with environmental noise evaluation, and relates to the technical field of hearing aid signal processing, comprising the following steps: collecting an audio signal and converting the audio signal to a frequency domain to obtain a frequency domain signal; extracting noise features from the frequency domain signal, calculating a noise time-varying index and spectrum flatness, and identifying an environmental noise type; estimating a noise power spectrum, determining a noise tracking parameter according to the environment noise type, and updating the noise power spectrum; calculating a signal-to-noise ratio parameter corresponding to the noise power spectrum, determining a noise reduction intensity factor according to the environmental noise type and the hearing characteristics of the user, and calculating a noise reduction gain based on the signal-to-noise ratio parameter and the noise reduction intensity factor; and performing noise reduction processing on the frequency domain signal by using the noise reduction gain, and converting the frequency domain signal to a time domain to output a processed audio signal. According to the invention, the noise tracking parameter is adaptively adjusted by identifying the environmental noise type, and the noise reduction intensity is determined in combination with the hearing characteristics of the user, so that the noise reduction effect and the user suitability of the hearing aid in a complex environment are improved.

The application discloses a noise robustness hearing decoding method and system based on an adversarial domain adaptation network, relates to the technical field of hearing decoding, and comprises the following steps: acquiring a multi-channel electroencephalogram signal, and performing parallel analysis and feature fusion; inputting a multi-dimensional signal integrity feature vector into a noise evaluation model to output a noise complexity score; calling a feature decoupling module to output a task-related feature vector and a noise-related feature vector; inputting the task-related feature vector into an attention decoder to obtain a hearing attention allocation probability distribution; and taking the hearing attention allocation probability distribution and a noise tracing and influence report as a noise robustness hearing decoding result of a target user. The technical problem of low decoding accuracy and insufficient robustness of existing hearing decoding methods in a noisy scene is solved.