18 results about "Industrial noise" patented technology

The invention relates to the technical field of audio signal processing, and discloses an industrial noise identification method and system, and the method comprises the steps: obtaining an audio signal, and carrying out the time-frequency decomposition, and obtaining preliminary decomposition data; classifying the coupling features of the preliminary decomposition data to obtain a coupling region boundary value; if the boundary value of the coupling region exceeds a preset boundary threshold value, performing filtering processing to obtain separated noise spectrum data; calculating an overlapping proportion of the separated noise spectrum data and a preset target sound; if the overlapping proportion causes extraction deviation, extracting dynamic change characteristics of the separated noise spectrum data and fusing the dynamic change characteristics into a spectrum extraction process to obtain an accurate noise spectrum; calculating an intensity value according to the accurate noise spectrum, and determining an intensity evaluation result; and comparing the intensity evaluation result with a preset pollution threshold, calculating a noise pollution degree and outputting a noise identification result. The method is suitable for industrial environment noise monitoring, and can accurately extract the noise spectrum.

The invention discloses a device for exciting ion sound waves for noise reduction, and belongs to the technical field of vibration reduction and noise reduction. The device comprises a cathode structure, an anode structure, a noise source, a square pipeline and a high-voltage power supply device, the frequency, phase and amplitude characteristics of the ion sound wave are directly modulated through the preset combination of applied voltage, electrode gap and discharge position parameters; the cathode structure and the anode structure are composed of three kinds of electrodes, namely a cathode of a needle electrode structure, an anode of a metal wire structure and a perforated plate-shaped grounding electrode. The high-voltage power supply device is used for applying negative high voltage to the needle electrode and grounding the perforated plate, or applying positive high voltage to the metal wire electrode and grounding the cathode so as to generate corona discharge; and ion sound waves generated by corona discharge and industrial noise emitted by the noise source are subjected to sound wave superposition in the square pipeline so as to realize sound pressure counteracting. Ion sound waves are directly generated through corona discharge and are superposed and counteracted with noise sound waves, and passive noise reduction is achieved.

This invention discloses a low-frequency noise reduction and sound insulation device for industrial applications, belonging to the field of noise control technology. The device includes an outer soundproof cover, an inner composite sound-absorbing structure, and an active noise control system. The outer soundproof cover is constructed of high-density board. The inner composite sound-absorbing structure is located on the inner wall of the outer soundproof cover and includes an acoustic metamaterial layer and a micro-perforated plate layer, which are spaced apart to form a first resonant cavity. The active noise control system includes: an error microphone embedded in the inner wall of the outer soundproof cover; a controller electrically connected to the error microphone; and a secondary sound source electrically connected to the controller and installed on the inner wall of the outer soundproof cover. This invention achieves broadband passive sound absorption through the composite structure of acoustic metamaterial and micro-perforated plate, providing a high signal-to-noise ratio environment for the active control system. Furthermore, the active control system based on the FxLMS algorithm precisely cancels residual low-frequency line spectra, achieving efficient and stable low-frequency noise reduction.

The application relates to the technical field of industrial earmuffs, and provides an industrial noise reduction earmuff with working condition self-adaptive adjustment, which comprises a supporting block arranged on a safety cap shell, an adjusting unit arranged on the outer surface of the supporting block and used for adjusting the sealing effect of the earmuff and the human body, an earmuff shell fixedly connected to the bottom of the adjusting unit, a decibel detector fixedly connected to the outer side of the earmuff shell, a detection ring connected to the decibel detector through an electric wire, sound-absorbing cotton placed in the interlayer of the earmuff shell, and an air inflation air bag fixedly connected to the inner side of the earmuff shell; a first adjusting unit and a second adjusting unit arranged on the inner wall of the earmuff shell; the sound-absorbing cotton can absorb part of the noise from the outside, and the detection ring can detect the size of the external noise so as to drive the adjusting unit, the first adjusting unit and the second adjusting unit to work, and the noise reduction effect is self-adjusted according to the actual working condition.

This invention discloses a composite sound insulation and vibration damping board, its preparation method, and its application, belonging to the field of building and industrial noise control materials. The board comprises, from top to bottom, an upper sound insulation layer, a middle matrix layer, and a lower vibration damping layer, which are bonded together using a water-based adhesive; the upper sound insulation layer has a density of 30-60 kg / m³. 3 The polyurethane foam board has an intermediate matrix layer composed of cement-based cloth, fiber cloth, non-woven fabric, plastic film, or aluminized film, and a lower shock-absorbing layer with a density of 15-25 kg / m³. 3 EPP foam board. This board combines the sound insulation and heat preservation properties of polyurethane, the sound insulation enhancement of the middle matrix layer, and the shock absorption and cushioning properties of EPP through a three-layer composite material. It has good sound insulation, shock absorption and heat preservation performance, and is suitable for building and industrial applications with requirements for comprehensive performance.

The invention relates to the technical field of industrial noise control and monitoring, and discloses a large air compression station noise analysis and control system, which comprises a sensor array, a data acquisition module, a spectrum analysis module and the like, and is characterized in that the sensor array acquires original signals in an air compression station and in a factory boundary, and transmits the original signals to the data acquisition module for preprocessing and packaging a data packet; the spectrum analysis module receives the data packet, extracts data characteristics through FFT and 1 / 3 octave analysis, and transmits the data characteristics to the central intelligent control module; the central intelligent control module generates a control strategy in combination with the noise feature database, sends an instruction to the related execution module, and sends state data to the man-machine interaction early warning module; and each execution and interaction module receives the instruction and the data as required, and completes corresponding display and adjustment operations. Noise reduction and heat dissipation are achieved by integrating the functions of noise analysis, noise elimination, sound insulation, vibration reduction and intelligent ventilation, the treatment strategy can be dynamically adjusted along with the load of the air compressor, and collaborative optimization of environment noise control and equipment operation safety is achieved.

The invention relates to an industrial noise source positioning and separating method and device, equipment and a storage medium, and the method comprises the steps: collecting a multi-channel audio signal, and carrying out the preprocessing and local feature extraction of the multi-channel audio signal, and obtaining a local feature vector packet; carrying out sound source localization based on the local feature vector packet by adopting a hybrid localization strategy to generate space position information of a sound source, and calculating localization confidence; sound source separation is carried out on the multi-channel audio signals, and separated audio signals and sound source separation quality confidence coefficients of all independent sound sources are obtained; collaborative management is carried out on the output of each agent through the arbitration agent, and confidence fusion and conflict judgment are carried out; and when the confidence coefficient is lower than a first preset threshold value, triggering an artificial verification process or scheduling a mobile detection unit to carry out auxiliary measurement so as to determine target sound source positioning and separation data, and storing the target sound source positioning and separation data in a vector database. The method has the advantages of high-precision positioning and reliable separation of the industrial noise source, and can adapt to the change of a complex acoustic environment.

This invention belongs to the field of industrial noise control technology and discloses an active noise control method for vibration noise in precast beam factories. The method includes the following steps: S1, signal preprocessing and frequency band focusing; S2, secondary path identification and modeling; S3, calculation of the filtered reference signal; S4, initialization of control parameters; S5, calculation of the desired signal for the main path; S6, main loop processing. The beneficial effects of this invention are as follows: 1. An adaptive divergence detection mechanism based on error signal energy monitoring is introduced into the traditional SAS-FxLMS algorithm. When the error energy exceeds a preset multiple of the original energy, the algorithm is determined to be diverging, and a recovery mechanism is automatically triggered. 2. When the norm exceeds a preset threshold, the weight vector is scaled proportionally to reduce its norm to within the threshold range, ensuring the numerical stability of the algorithm. 3. The transfer function models of the main path and secondary paths are optimized according to the characteristics of the target frequency band center frequency (150Hz); the algorithm parameters are dynamically adjusted according to the peak factor, RMS value, and other characteristic parameters of the input signal.

The application relates to the technical field of audio signal processing, and discloses an industrial noise identification method and system.The method comprises the following steps: acquiring an audio signal and performing time-frequency decomposition to obtain preliminary decomposition data; classifying coupling features of the preliminary decomposition data to obtain a coupling region boundary value; if the coupling region boundary value exceeds a preset boundary threshold value, performing filtering processing to obtain separated noise spectrum data; calculating an overlap ratio of the separated noise spectrum data and a preset target sound; if the overlap ratio leads to extraction deviation, extracting dynamic change characteristics of the separated noise spectrum data and integrating the dynamic change characteristics into a spectrum extraction process to obtain an accurate noise spectrum; calculating an intensity value according to the accurate noise spectrum to determine an intensity evaluation result; comparing the intensity evaluation result with a preset pollution threshold value, calculating a noise pollution degree, and outputting a noise identification result.The method is suitable for industrial environment noise monitoring and can realize accurate extraction of a noise spectrum.

This application relates to a method and apparatus for constructing an equipment noise detection model based on industrial noise analysis technology, belonging to the technical field of equipment noise detection. The method includes: acquiring sound sampling data in response to a request; processing the sound sampling data to obtain sound reconstruction data; acquiring first volume information and first density information of the sound reconstruction data in each frequency band over any time period; and constructing an equipment noise detection model based on the first volume information and the first density information. This application has the effect of detecting abnormal sound frequency bands and the volume and density distribution relationships existing in each frequency band.

The utility model relates to the technical field of noise isolation earmuffs, and discloses an adjustable industrial noise isolation earmuff which comprises a safety helmet, the left side and the right side of the safety helmet are both connected with mounting plates through connecting mechanisms, the far sides of the two mounting plates are both fixedly connected with head hoops, the head hoops are connected with adjusting rods through adjusting mechanisms, and the adjusting rods are fixedly connected with the safety helmet. The bottom end of the adjusting rod is rotatably connected with a connecting frame, the bottom end of the connecting frame is provided with a shell, the connecting mechanism comprises a mounting rod, the interior of the mounting rod is slidably connected with an extrusion rod, the exterior of the extrusion rod is fixedly connected with a limiting disc, and the exterior of the extrusion rod is sleeved with a strong spring. Threaded blocks are rotationally connected to the sides, far away from each other, of the multiple extrusion rods. According to the safety helmet, the safety risk that the head of a worker is hit by a falling object due to the fact that the safety helmet is not stably worn or taken down is greatly reduced, and the overall safety of the working environment is improved.

The application discloses an easy-to-clean industrial noise reduction earmuff and belongs to the technical field of earmuffs. The earmuff comprises an earmuff main body and an ear pad arranged on the earmuff main body, and the ear pad is composed of a flexible base material and a fabric layer wrapped on the outer surface of the flexible base material. The fabric layer is prepared through a specific process: the fabric is immersed in a treatment liquid, and then cross-linked and dried to obtain the fabric layer. The treatment liquid comprises 5-10% of polyacrylic acid, 3-8% of nanocellulose, 0.3-0.7% of a cross-linking agent, 0.1-0.5% of an additive and the balance of deionized water. The industrial noise reduction earmuff prepared by the application has the characteristics of easy cleaning, can effectively block the penetration of sweat and significantly improves the sanitary safety, wearing comfort and service life of the earmuff.

The invention relates to an integrated silencing grille door, and belongs to the technical field of industrial noise control and ventilation equipment. The grille door comprises a door frame assembly, a grille assembly, a composite sound absorption assembly and an intelligent control assembly. The door frame assembly is connected with a wall through a nitrile rubber damping rubber mat, and a modular interface is reserved to be matched with a special-shaped door opening. According to the grating assembly, grating blades are driven to rotate through a rope-rope wheel transmission system, and opening adjustment is achieved. The composite sound absorption assembly comprises a metal cover, a metal framework and three sound insulation layers (rock wool, a damping sound insulation plate and hydrophobic glass fiber cotton), and the noise path is prolonged through honeycomb-shaped protrusions. The intelligent control assembly monitors in real time through the noise sensor, the microcontroller controls the motor to adjust the blade angle according to the noise frequency band, medium-high frequency noise is mainly used for horizontal wide-angle ventilation of the blade, and low-frequency noise is mainly used for the blade in a 45-degree silent mode. According to the invention, 100-4000 Hz full-band noise reduction is realized, and the ventilation efficiency, vibration isolation and intelligent regulation and control functions are realized.

This utility model discloses a shuttle lifting mechanism, comprising: a frame, a set of support frames vertically mounted on the frame, a first gear rotatably mounted above the support frames, a second gear rotatably mounted on the frame, a toothed belt connecting the first gear and the second gear, and a first drive assembly for driving the second gear to rotate. By combining reliability and quiet performance, the self-healing toothed assembly extends the life of the toothed belt to more than four times that of traditional toothed belts, significantly reducing replacement costs. The quiet component eliminates industrial noise pollution while maintaining high torque transmission, meeting stringent requirements for the working environment. Compared to existing chain or ordinary toothed belt solutions, it completely avoids the risk of wire rope breakage and the hidden danger of gear disengagement.

The invention discloses a man-machine interaction welding method and system based on multi-modal fusion and natural language, and the method comprises the steps: synchronously collecting voice, gesture and environment signals in real time, and preprocessing the obtained multi-modal data; based on the preprocessed multi-modal data, deep fusion of the multi-modal data is carried out, and the intention of an operator is accurately identified and confirmed; when the user intention is determined, continuously optimizing an adaptive speech recognition model, performing deep analysis on the user intention in a natural language form, and extracting task logic and parameters; based on the analyzed intention logic and parameters, an executable macro instruction sequence is generated, and the welding robot is driven to complete a task; in the task execution process, the task execution condition is continuously monitored to provide safety feedback, subsequent optimization is performed, and it is guaranteed that the task is safely and efficiently completed. The method provided by the invention can adapt to industrial noise and operator accent, solve the problem of single modal ambiguity, understand complex task instructions, and realize low delay and data security.

The invention discloses a noise reduction optimization system for a desulfurization fan room based on sound field simulation. The noise reduction optimization system comprises a data acquisition module, a sound field simulation module, a noise analysis module, a noise reduction scheme optimization module and a scheme output and execution module. By integrating a sound field simulation technology and a modular optimization system, accurate prediction and active optimization of the noise of the desulfurization fan room are realized, and the system can perform high-precision sound field simulation and identify a main noise source and a propagation path on the basis of actual equipment parameters and a machine room structure, so that a targeted noise reduction scheme is generated; according to the method, the blindness of a traditional method is effectively avoided, the noise reduction effect is remarkably improved, the treatment cost is reduced, the long-term effectiveness of measures is guaranteed through real-time monitoring and dynamic optimization functions, meanwhile, the equipment operation efficiency and the machine room safety are both considered, and a scientific and intelligent solution is provided for industrial noise treatment.

The utility model belongs to the technical field of organic fertilizer, especially an organic fertilizer grinding device, including frame and fixed on the frame's grinding jar, the inside setting of grinding jar has grinding mechanism, the grinding mechanism includes the breaker plate with bevel gear, the rotation of breaker plate carries out preliminary crushing to fertilizer, through setting monitoring mechanism, the pressure that produces in real time monitoring grinding, pressure sensor and round plate fixed mounting, its fixed, pressure sensor is located in the protection frame inside, its protection, the model of pressure sensor can select piezoelectric sensor, and it is suitable for high frequency pressure change, and response speed is fast, and it is suitable for dynamic pressure monitoring in the grinding process, and the model of siren can adopt Honeywell XLS100 series audible -visual alarm, and its sound pressure is greater than or equal to 120dB, and visible distance is greater than or equal to 10 meters, and it is suitable for industrial noise environment.

The invention discloses a noise artifact dynamic identification method based on multi-scale feature modeling and deep learning. The method comprises the following steps: S1, continuously collecting complete noise signals in an environment; s2, preprocessing the digital signal; s3, identifying whether the short-time frames contain artifact noise or not and removing the short-time frames containing the artifact noise; s4, maintaining and updating an artifact signal pattern library and a deep learning recognition model; s5, post-processing is carried out on the noise signal after artifact noise identification is completed; and S6, calculating indexes such as a continuous equivalent sound pressure level for the post-processed noise signal. The invention discloses a noise artifact dynamic identification method based on multi-scale feature modeling and deep learning, and aims to realize accurate identification and removal of artifact signals in an industrial noise acquisition process through combination of multi-scale time-frequency feature analysis and a deep learning algorithm.