Noise control method, system and equipment for mobile crushing station and medium

Abstract

The invention relates to the technical field of crushing noise control, in particular to a noise control method, system and equipment for a mobile crushing station and a medium, and the method comprises the steps: obtaining a vibration noise signal of the crushing station, and carrying out the frequency domain conversion of the vibration noise signal to obtain spectrum analysis information; analyzing a frequency band with concentrated noise energy according to the spectrum analysis information to obtain distribution condition information and noise intensity information to generate first reverse sound wave information; historical information of a crushing station is obtained, and a sound wave prediction model is constructed according to the historical information of the crushing station; analyzing the distribution condition information, the noise intensity information and the working point position information according to a sound wave prediction model to obtain second reverse sound wave information; the first reverse sound wave information is adjusted according to the second reverse sound wave information, reverse sound wave output information acting on the loudspeaker is obtained, noise generated in multiple use environments and multiple working conditions of the mobile crushing station can be accurately and rapidly dealt with, and the operation stability of the mobile crushing station is improved.

Description

Technical Field

[0001] The present application relates to the technical field of crushing noise control, and in particular to a noise control method, system, equipment and medium for a mobile crushing station. Background Art

[0002] With the increasing demand for material processing in industries such as mining, construction, and waste recycling, crushing equipment plays an increasingly important role in modern industry.

[0003] When a conventional crushing station is working, due to the impact of the material in the crushing chamber and the operation of the equipment itself, it will produce more complex vibration noise. The noise sources include the impact sound of the material in the crushing chamber, the mechanical noise of various parts of the equipment, etc. These noise spectra usually contain low-frequency and high-frequency components. Low-frequency noise may appear as a rumble, while high-frequency noise is often sharp and harsh, causing potential damage to the structure of the equipment, thereby affecting the service life and stability of the equipment. In response to these noises, anti-vibration materials are usually added to the equipment based on usage experience to reduce vibration.

[0004] Compared with fixed crushing stations, mobile crushing stations have higher flexibility and adaptability and can operate at different construction sites. However, this flexibility also brings a more complex working environment. Mobile crushing stations usually operate in changing terrain and environments, resulting in significant changes in vibration modes and noise characteristics. For example, the unevenness of the road surface, the type of soil and its bearing capacity will affect the vibration state and noise generation of the equipment, and the operation mode of the mobile crushing station under different working conditions will also have a significant impact on its noise characteristics, such as crushing, screening, transportation and other working conditions. In view of the above-mentioned changing environment and working conditions, the mobile crushing station will generate different noises in different environments and working conditions. The traditional method of adding anti-vibration materials to the equipment based on usage experience cannot be well adapted to the mobile crushing station, affecting the effect and efficiency of noise treatment, and even affecting the operating stability and life of the mobile crushing station. The above problems need to be solved. Summary of the invention

[0005] In order to more accurately and quickly deal with the noise generated by the mobile crushing station in multiple usage environments and multiple working conditions and improve the operating stability of the mobile crushing station, the present application provides a noise control method, system, device and medium for a mobile crushing station, which adopts the following technical solutions:

[0006] In a first aspect, the present application provides a noise control method for a mobile crushing station, comprising:

[0007] Obtain the vibration and noise signals of the crushing station, perform frequency domain conversion on the vibration and noise signals, and obtain spectrum analysis information;

[0008] Analyze the frequency band where the noise energy is concentrated according to the spectrum analysis information to obtain the distribution information and noise intensity information;

[0009] Generate first reverse sound wave information according to the distribution information and the noise intensity information;

[0010] Obtain the historical information of the crushing station, and construct the acoustic wave prediction model based on the historical information of the crushing station;

[0011] Acquire the working point location information, analyze the distribution information, noise intensity information and working point location information according to the sound wave prediction model, and obtain the second reverse sound wave information;

[0012] The first reverse sound wave information is adjusted according to the second reverse sound wave information to obtain reverse sound wave output information acting on the speaker.

[0013] Preferably, it also includes:

[0014] When the reverse sound wave output information is generated, several vibration sensor signals of the vibration noise signal are analyzed to obtain the noise source azimuth information, and the loudspeaker used to play the reverse sound wave output information is matched according to the noise source azimuth information.

[0015] Preferably, it also includes:

[0016] Position adjustment processing is performed according to the noise source azimuth information and the corresponding loudspeaker position information to obtain angle adjustment information for adjusting the direction of the loudspeaker.

[0017] Preferably, it also includes:

[0018] Distance analysis is performed based on the noise source azimuth information and the corresponding loudspeaker position information to obtain distance information, and reverse sound wave output information is compensated based on the distance information and a pre-built sound wave attenuation model to obtain compensated reverse sound wave information acting on the loudspeaker.

[0019] Preferably, it also includes:

[0020] Obtain the structural parameters of the crushing station and build a physical model of the crushing station according to the structural parameters of the crushing station;

[0021] Obtain the operating parameters of the crushing station, perform vibration numerical simulation based on the crushing station physical model and the crushing station operating parameters, and obtain the natural frequency of the crushing station;

[0022] Compare the crushing station's natural frequency and spectrum analysis information to determine whether there are similar frequencies. If the frequencies are similar, select the resonant frequency for optimization reference;

[0023] The structural layout adjustment plan is matched according to the resonance frequency and the corresponding noise source orientation information.

[0024] Preferably, it also includes:

[0025] Determine the noise type according to the distribution information and the noise intensity information, and match the noise vibration threshold according to the noise type;

[0026] When outputting reverse sound wave output information, an updated noise signal is obtained in real time, and the updated noise signal is compared with a noise vibration threshold. When the updated noise signal is greater than the noise vibration threshold, updated azimuth information for issuing an alarm is obtained.

[0027] Preferably, it also includes:

[0028] The sound wave prediction model is updated according to the updated noise signal.

[0029] Preferably, the specific steps of analyzing the plurality of vibration sensor signals of the vibration noise signal are:

[0030] The time delay difference method is used to analyze several vibration sensor signals.

[0031] Preferably, the crushing station historical information includes historical noise distribution information, historical noise intensity information, historical crushing station location and historical environmental information.

[0032] In a second aspect, the present application provides a noise control system for a mobile crushing station, comprising:

[0033] The spectrum analysis module is used to obtain the vibration noise signal of the crushing station, perform frequency domain conversion on the vibration noise signal, and obtain spectrum analysis information;

[0034] A distribution analysis module is used to analyze the frequency band where the noise energy is concentrated according to the spectrum analysis information to obtain distribution information and noise intensity information;

[0035] A first reverse sound wave generating module, used to generate first reverse sound wave information according to the distribution information and the noise intensity information;

[0036] A prediction model building module is used to obtain historical information of the crushing station and build an acoustic wave prediction model based on the historical information of the crushing station;

[0037] A second reverse acoustic wave generating module is used to obtain the working point position information, analyze the distribution information, the noise intensity information and the working point position information according to the acoustic wave prediction model, and obtain the second reverse acoustic wave information;

[0038] The sound wave output module adjusts the first reverse sound wave information according to the second reverse sound wave information to obtain reverse sound wave output information acting on the speaker.

[0039] Preferably, it also includes:

[0040] The orientation recognition module is used to analyze several vibration sensor signals of the vibration noise signal when generating reverse sound wave output information, obtain the noise source orientation information, and match the loudspeaker used to play the reverse sound wave output information according to the noise source orientation information.

[0041] Preferably, it also includes:

[0042] The azimuth adjustment module is used to perform position adjustment processing according to the azimuth information of the noise source and the corresponding loudspeaker position information to obtain angle adjustment information for adjusting the direction of the loudspeaker.

[0043] Preferably, it also includes:

[0044] The distance compensation module is used to perform distance analysis based on the noise source orientation information and the corresponding speaker position information to obtain distance information, and to compensate the reverse sound wave output information based on the distance information and a pre-built sound wave attenuation model to obtain compensated reverse sound wave information acting on the speaker.

[0045] Preferably, it also includes:

[0046] The entity analysis module is used to obtain the structural parameters of the crushing station and build a physical model of the crushing station according to the structural parameters of the crushing station;

[0047] Obtain the operating parameters of the crushing station, perform vibration numerical simulation based on the crushing station physical model and the crushing station operating parameters, and obtain the natural frequency of the crushing station;

[0048] Compare the crushing station's natural frequency and spectrum analysis information to determine whether there are similar frequencies. If the frequencies are similar, select the resonant frequency for optimization reference;

[0049] The structural layout adjustment plan is matched according to the resonance frequency and the corresponding noise source orientation information.

[0050] Preferably, it also includes:

[0051] A noise type confirmation module determines the noise type according to the distribution information and the noise intensity information, and matches the noise vibration threshold according to the noise type;

[0052] When outputting reverse sound wave output information, an updated noise signal is obtained in real time, and the updated noise signal is compared with a noise vibration threshold. When the updated noise signal is greater than the noise vibration threshold, updated azimuth information for issuing an alarm is obtained.

[0053] Preferably, it also includes:

[0054] The model data updating module updates the data of the sound wave prediction model according to the updated noise signal.

[0055] Preferably, the specific steps of the orientation recognition module analyzing several vibration sensor signals of the vibration noise signal are:

[0056] The time delay difference method is used to analyze several vibration sensor signals.

[0057] Preferably, the historical information of the crushing station acquired by the prediction model building module includes historical noise distribution information, historical noise intensity information, historical crushing station location and historical environmental information.

[0058] In a third aspect, the present application provides a noise control device for a mobile crushing station, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the noise control method for the mobile crushing station as described above.

[0059] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program is configured to execute the noise control method for the mobile crushing station as described above when running.

[0060] In summary, compared with the prior art, the technical solution provided by this application has at least the following beneficial effects:

[0061] The present application collects the vibration noise signal corresponding to one of the working points of the mobile crushing station, converts it into the frequency domain, converts the time domain signal into the frequency domain to obtain spectrum analysis information, performs noise frequency band analysis on the spectrum analysis information, determines the distribution information of the low-frequency, medium-frequency and high-frequency components of the noise and the corresponding noise intensity information, thereby generating a first reverse sound wave information, and then constructs a model based on historical information, combines the working point location information to predict the second reverse sound wave information, and generates reverse sound wave output information by comprehensively generating information and prediction information, thereby suppressing the noise in the complex working environment of the mobile crushing station, so as to more accurately and quickly respond to the noise generated in multiple usage environments and multiple working conditions of the mobile crushing station, and improve the operating stability of the mobile crushing station. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a flow chart of a noise control method for a mobile crushing station described in an embodiment of the present application.

[0063] Figure 2 It is a schematic diagram of a further processing flow of the noise control method of the mobile crushing station described in the embodiment of the present application.

[0064] Figure 3 It is a module schematic diagram of a noise control system of a mobile crushing station described in an embodiment of the present application.

[0065] Figure 4 It is a schematic diagram of the modules of orientation recognition, orientation adjustment and distance compensation described in the embodiment of the present application.

[0066] Description of reference numerals:

[0067] 1. Spectrum analysis module; 2. Distribution analysis module; 3. First reverse sound wave generation module; 4. Prediction model construction module; 5. Second reverse sound wave generation module; 6. Sound wave output module; 7. Direction recognition module; 8. Direction adjustment module; 9. Distance compensation module. DETAILED DESCRIPTION

[0068] The following combination Figure 1-Figure 4 The present application is described in further detail. The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments and are not intended to be limiting.

[0069] Reference Figure 1 and Figure 2 The noise control method of a mobile crushing station involved in this application specifically includes:

[0070] Step S1: Obtain the vibration noise signal of the crushing station, perform frequency domain conversion on the vibration noise signal, and obtain spectrum analysis information;

[0071] Step S2: Analyze the frequency band where the noise energy is concentrated according to the spectrum analysis information to obtain distribution information and noise intensity information;

[0072] Step S3: generating first reverse sound wave information according to the distribution information and the noise intensity information;

[0073] Step S4: Obtain historical information of the crushing station, and construct a sound wave prediction model based on the historical information of the crushing station;

[0074] Step S5: obtaining the working point position information, analyzing the distribution information, the noise intensity information and the working point position information according to the sound wave prediction model, and obtaining the second reverse sound wave information;

[0075] Step S6: adjusting the first reverse sound wave information according to the second reverse sound wave information to obtain reverse sound wave output information acting on the speaker.

[0076] Specifically, the present application realizes signal collection and transmission by arranging multiple vibration sensors and speakers at different positions of the mobile crushing station. Multiple vibration sensors collect vibration and noise signals of the crushing station under actual working conditions to obtain comprehensive original data. The speaker feeds back reverse sound waves to actively suppress the noise. First, the vibration and noise signal corresponding to one of the working points of the mobile crushing station is collected by a vibration sensor, and the vibration and noise signal is converted into the frequency domain using a signal processing algorithm such as a fast Fourier transform, so as to convert it from a time domain signal to a frequency domain to obtain spectrum analysis information. The spectrum analysis information is subjected to noise frequency band analysis to determine the distribution information of the low-frequency, medium-frequency and high-frequency components of the noise and the corresponding noise intensity information, thereby generating the first reverse sound wave information based on the distribution information and the corresponding noise intensity information. Then, a sound wave prediction model is constructed based on historical information, and the second reverse sound wave information is predicted in combination with the working point position information. The reverse sound wave output information is generated by combining the generated information and the predicted information, thereby suppressing the noise in the complex working environment of the mobile crushing station. This allows a more accurate and rapid response to the noise generated by the mobile crushing station in multiple usage environments and multiple working conditions. This not only emphasizes the characteristics and flexibility of the mobile crushing station in noise control, but also forms a sharp contrast with the noise control of traditional fixed crushing stations. Comprehensive analysis and control measures will effectively improve the noise management capabilities of the mobile crushing station, ensuring that it can still comply with relevant noise standards in a changing working environment, improving overall operating efficiency, and improving the operating stability of the mobile crushing station.

[0077] As one of the implementation methods, the sensor can monitor and record the vibration noise signal of the equipment in real time during operation. The collected signal is usually a time domain signal, which contains the superposition of different frequency components and reflects the working status and noise characteristics of the equipment. The embodiment of the present application adopts a signal processing algorithm, such as a fast Fourier transform, and the FFT performs a frequency domain conversion on the collected time domain signal, converting the signal from a time domain signal and a waveform that changes with time into a frequency domain signal, that is, the amplitude and phase of each frequency component. After the Fourier transform, the spectrum analysis information obtained will show the energy distribution of different frequency components, including low frequency, medium frequency and high frequency parts.

[0078] Then, the embodiment of the present application analyzes the spectrum to determine the concentrated frequency band of the noise energy. For example, a specific frequency range can be set, such as low frequency 0-200Hz, medium frequency 200-2000Hz, and high frequency above 2000Hz, so as to identify the characteristics of the noise. It is necessary to extract the corresponding noise intensity information, clarify the noise intensity of different frequency bands, express it in decibels dB, and record the distribution points of the noise to obtain the spectrum analysis information.

[0079] The embodiment of the present application can accurately identify the frequency characteristics of noise through spectrum analysis, providing a scientific basis for the subsequent generation of reverse sound waves. It can obtain comprehensive noise data, which helps to understand the noise performance of the crushing station under different working conditions and provide support for the optimization of noise suppression solutions.

[0080] In one embodiment, during the crushing operation, after the time domain signal collected by the vibration sensor is processed by FFT, the spectrum shows that there is significant energy concentration in the frequency band of 100Hz to 300Hz. This means that the noise in this frequency band has a greater impact on the environment. Through further analysis, it is determined that this frequency band is medium-frequency noise, which provides data support for the reverse sound wave design.

[0081] In one embodiment, in another crushing operation scenario, when the equipment is crushing concrete, the spectrum information detected by the vibration sensor shows that the low frequency, that is, 50Hz-150Hz noise is significant. This information shows that the low-frequency vibration noise during operation may cause interference to nearby residents, so it is necessary to focus on the generation and output of reverse sound waves in the low frequency band to reduce the impact on the environment.

[0082] As one implementation method, the energy distribution of each frequency band is extracted from the obtained spectrum analysis information, including the amplitude values ​​of low frequency, medium frequency and high frequency. The spectrum data will be presented in the form of an amplitude-frequency curve, and the energy concentration of each frequency band will be displayed in the form of a chart.

[0083] By setting a threshold, such as a specific dB value, we can determine which frequency bands have higher noise intensity. Statistical methods, such as mean and standard deviation, are usually used to determine significant frequency bands. For example, if the noise amplitude in the mid-frequency band, i.e. 200Hz-2000Hz, is significantly higher than that in other frequency bands, then the mid-frequency band is determined to be the main noise band.

[0084] According to the determined frequency bands, the noise intensity of each frequency band is recorded and classified. For example, the average noise intensity and the maximum value of each frequency band are recorded, and then data visualization tools such as spectrograms or histograms are used to intuitively present the noise intensity distribution of different frequency bands.

[0085] Generate the corresponding reverse sound wave according to the noise frequency band information. The reverse sound wave refers to the sound wave with the opposite phase to the noise signal, and its frequency and intensity match the analyzed noise. Specifically, a DSP digital signal processing algorithm, such as a synthesis algorithm, is used to generate the reverse sound wave signal.

[0086] As one embodiment, the historical information of the crushing station includes historical noise distribution information, historical noise intensity information, historical crushing station location and historical environment information.

[0087] Specifically, to obtain the historical information of the crushing station and build the acoustic wave prediction model, we first collect relevant data from the historical records of the crushing station, including previous noise levels, equipment operating status, environmental factors such as location, weather, terrain, etc., and fault records, etc. The historical information data of the crushing station comes from sensor records, operator logs or maintenance records.

[0088] To build the acoustic wave prediction model, the collected historical data must first be cleaned to remove outliers and noise to ensure data accuracy. The data must also be standardized or normalized for subsequent analysis.

[0089] Statistical methods and machine learning techniques are then used to extract features in order to build effective predictive models and identify features associated with noise generation, such as workload, device type, and operating time.

[0090] Then select an appropriate sound wave prediction model, such as a regression model, decision tree or neural network, use the processed historical data to train the model, adjust the model parameters to improve the accuracy of the prediction, use a portion of the historical data as a test set, evaluate the model's prediction performance, and ensure its effectiveness in practical applications.

[0091] After the acoustic wave prediction model is constructed and trained, the noise distribution information, noise intensity information and working point location information are input into the constructed acoustic wave prediction model. The acoustic wave prediction model is used to analyze the input data and predict the noise situation under the given working point conditions.

[0092] The acoustic wave prediction model will consider the performance under similar conditions in historical data to generate second reverse acoustic wave information adapted to the current working environment. The generated second reverse acoustic wave information includes the expected spectrum and intensity of the noise, indicating the suppression measures to be taken at specific working points.

[0093] As one of the implementation methods, the frequency domain information of the first reverse acoustic wave signal and the key features of the second reverse acoustic wave signal are analyzed, the difference between the first reverse acoustic wave signal and the second reverse acoustic wave signal is calculated, and the adjustment factor is set according to the analysis result, usually gain, phase offset, etc.

[0094] The difference and adjustment factor are applied to the first reverse acoustic wave signal to generate a new signal output, the formula is:

[0095] S output =S1-kS2

[0096] Among them, S output is the adjusted reverse acoustic wave output information, S1 is the first reverse acoustic wave signal, S2 is the second reverse acoustic wave signal, and k is the adjustment factor.

[0097] The conditioned signal is digitally filtered, such as using an IIR or FIR filter, to ensure that the signal is stable and suitable for speaker output, and the signal is quantized and converted into an analog signal format suitable for the speaker.

[0098] The final adjusted signal is sent to the digital-to-analog converter DAC, converted into an analog signal, ready to act on the speaker, control the speaker drive signal, and ensure that the reverse sound wave can effectively offset the ambient noise.

[0099] Through real-time feedback mechanisms, such as using sensors to continuously monitor ambient noise, the reverse sound wave output signal is continuously adjusted to improve the noise reduction effect.

[0100] As one implementation mode, it also includes:

[0101] When the reverse sound wave output information is generated, several vibration sensor signals of the vibration noise signal are analyzed to obtain the noise source azimuth information, and the loudspeaker used to play the reverse sound wave output information is matched according to the noise source azimuth information.

[0102] The specific steps for analyzing several vibration sensor signals of vibration noise signals are:

[0103] The time delay difference method is used to analyze several vibration sensor signals.

[0104] Specifically, the embodiment of the present application converts the time domain signal into a frequency domain signal by using the fast Fourier transform (FFT), identifies the main frequency components, uses the time difference when the sensor receives the sound, estimates the direction of the noise source through a triangulation positioning algorithm, and determines the main direction of the noise source by comparing the signal strength of each sensor.

[0105] The time delay difference method requires multiple sensors. Multiple vibration sensors are arranged around the crusher. The noise source is located by using the time delay difference of the signals received by multiple sensors. The location of the noise source can be calculated by comparing the arrival time of the noise signals received by different sensors. If there are more than three sensors, the triangulation positioning method or super triangulation positioning method is included. Through the known sensor position and the measured time delay difference, the coordinates of the noise source can be determined by using geometric relationships.

[0106] In the embodiment of the present application, among several speakers that have been fixedly installed, the speaker with the least noise control task and closest to the noise source is matched for noise control. By setting a certain weight coefficient to weigh the relationship between the task amount and the distance, the most suitable speaker is selected to perform the output of the reverse sound wave, thereby improving the noise control effect.

[0107] As one implementation mode, it also includes:

[0108] Position adjustment processing is performed according to the noise source azimuth information and the corresponding loudspeaker position information to obtain angle adjustment information for adjusting the direction of the loudspeaker.

[0109] Specifically, when outputting reverse sound wave output information, since the fixed orientation of the speaker will cause loss of reverse sound wave output information, it is necessary to adjust the orientation of the speaker so that the output direction is directly facing the direction of the main noise source or the direction of the main noise source within a certain range.

[0110] The embodiment of the present application determines the selection of an appropriate number and type of speakers based on the position information between the selected speakers and the noise source, and plans the orientation of the speakers based on the orientation information of the noise source to ensure that they can cover the main noise source area.

[0111] The noise level changes are monitored in real time, and the angle of the speaker is adjusted dynamically based on the monitoring data. The required adjustment angle is calculated using an algorithm to ensure that the speaker is facing the main noise source, and PID control algorithms are used to achieve precise adjustment. The reverse sound wave is processed through digital signal processing DSP technology to ensure that its waveform is opposite to the phase of the noise to achieve a cancellation effect.

[0112] After the implementation of the embodiment of the present application, the effect of the system is evaluated by measuring the noise level again. If the noise level does not meet expectations, the angle or number of the speakers needs to be readjusted. The direction and output of the speakers are adjusted regularly according to environmental changes and working conditions to ensure the continuity of the noise control effect.

[0113] The embodiments of the present application reduce the loss of reverse sound wave output information caused by the fixed orientation of the speaker, thereby improving the noise processing effect of the mobile crushing station.

[0114] As one implementation mode, it also includes:

[0115] Distance analysis is performed based on the noise source azimuth information and the corresponding loudspeaker position information to obtain distance information, and reverse sound wave output information is compensated based on the distance information and a pre-built sound wave attenuation model to obtain compensated reverse sound wave information acting on the loudspeaker.

[0116] Specifically, in the process of using the speaker to output reverse sound wave output information for active noise reduction, the reverse sound wave needs a certain distance from the location where the speaker outputs to the noise source, and the reverse sound wave may be lost on the way, affecting the effect of active noise reduction. When the microphone picks up noise, there is an influencing factor of the distance between the noise source and the speaker.

[0117] The embodiment of the present application performs distance analysis based on the noise source orientation information and the corresponding speaker position information to obtain distance information, and compensates the reverse sound wave output information based on the distance information and the pre-built sound wave attenuation model. Among them, a sound wave propagation model is established to compensate for the reverse sound wave by considering distance attenuation and environmental factors such as air density and temperature.

[0118] As one implementation mode, it also includes:

[0119] Obtain the structural parameters of the crushing station and build a physical model of the crushing station according to the structural parameters of the crushing station;

[0120] Obtain the operating parameters of the crushing station, perform vibration numerical simulation based on the crushing station physical model and the crushing station operating parameters, and obtain the natural frequency of the crushing station;

[0121] Compare the crushing station's natural frequency and spectrum analysis information to determine whether there are similar frequencies. If the frequencies are similar, select the resonant frequency for optimization reference;

[0122] The structural layout adjustment plan is matched according to the resonance frequency and the corresponding noise source orientation information.

[0123] Specifically, the embodiment of the present application adopts numerical simulation technology to establish a three-dimensional solid model of the crushing station, simulate the vibration response of the crushing station under different working conditions, obtain the natural frequency of the crushing station, and determine whether there is a resonant frequency close to the main noise frequency. If a resonant frequency is found, it is necessary to avoid the resonant frequency and reduce the risk of noise amplification by optimizing the structural layout of the crushing station, adjusting the crushing cavity type, and other measures.

[0124] The embodiment of the present application specifically collects geometric parameters of the crushing station, such as size, shape, material properties, and structural parameters, such as the cross-section of the beam, support position, etc., through on-site measurement or obtaining design drawings, and organizes the collected data into the format required by the structural model, such as using CAD software for preliminary design of the model.

[0125] Then, a 3D solid model of the crushing station is constructed using finite element analysis software such as ANSYS, Abaqus, etc. The model is initially verified to ensure that it conforms to physical reality, which can be verified by comparing known parameters or conducting small-scale experiments.

[0126] The crushing station operation data is collected through sensors and data acquisition systems, including load, operating frequency, vibration data, noise level, etc. The above operating parameters are sorted into a database for subsequent analysis and simulation, thereby realizing numerical simulation.

[0127] Perform modal analysis in finite element analysis software to calculate the natural frequencies and vibration modes of the crushing station, input operating parameters to simulate the behavior under actual working conditions, extract the natural frequencies from the simulation results, and generate a correlation diagram between frequency and vibration mode.

[0128] Use fast Fourier transform to perform spectral analysis on the operation data, identify the main frequency components generated during the operation, compare the extracted natural frequency with the spectral analysis results, and determine whether there are similar frequencies. If there are similar frequencies, record the frequencies that may cause resonance.

[0129] Then, based on the results of similar frequencies, the most influential resonance frequency is selected as an optimization reference, and the structural layout adjustment plan is matched according to the resonance frequency and the corresponding orientation information, so as to accurately match the treatment method suitable for the scenario, thereby reminding the user to make structural adjustments to a certain part of the mobile crushing station.

[0130] The structural layout adjustment plan specifically includes increasing damping through structural improvement, adding damping materials to key parts of the stone crusher, such as the casing and supporting structure, to reduce the vibration amplitude and resonance peak. Common damping materials include rubber, polyurethane, etc. For example, optimizing the design of the stone crusher, increasing the stiffness of the structure or adjusting the shape to reduce the natural frequency and stay away from the noise frequency.

[0131] The structural layout adjustment scheme includes changing the shape or size of the crusher, changing the size or shape of certain components, such as the vibrating screen and hammer head, so that the natural frequency can avoid the main noise frequency. Or adding additional mass to certain components to change the vibration characteristics to adjust the natural frequency.

[0132] As one implementation mode, it also includes:

[0133] Determine the noise type according to the distribution information and the noise intensity information, and match the noise vibration threshold according to the noise type;

[0134] When outputting reverse sound wave output information, an updated noise signal is obtained in real time, and the updated noise signal is compared with a noise vibration threshold. When the updated noise signal is greater than the noise vibration threshold, updated azimuth information for issuing an alarm is obtained.

[0135] Also includes:

[0136] The sound wave prediction model is updated according to the updated noise signal.

[0137] Specifically, the embodiment of the present application uses a highly sensitive noise sensor to collect on-site noise data, analyzes the noise data according to parameters such as frequency and amplitude, and determines the type of noise, such as mechanical noise, impact noise, environmental noise, etc. Then, historical noise data is collected and analyzed to determine the noise level under normal operation, and noise vibration thresholds are set with reference to relevant industry standards and regulations to ensure compliance with safety and environmental requirements, and the collected noise signals are transmitted to the processing unit in real time for analysis and update.

[0138] The real-time updated noise signal is then compared with the preset noise vibration threshold. If the updated noise signal is greater than the noise vibration threshold, the system will identify it as an abnormal noise event.

[0139] When an abnormality is detected in the embodiment of the present application, an alarm will be triggered, which may include sound and light alarms, text message notifications, or system log records and other related information.

[0140] The embodiment of the present application also combines GPS or other positioning technologies to obtain the current location of the equipment and the direction of the noise source. When an abnormal situation occurs, the alarm information is updated and output in real time, including the specific direction of the noise source. All monitoring data, threshold comparison results and alarm information are stored in a database for subsequent analysis. The embodiment of the present application can effectively implement the noise processing and monitoring system of the mobile crushing station to ensure real-time monitoring and processing of noise during operation.

[0141] The embodiments of the present application are directed to mobile crushing stations. The noise conditions of mobile crushing stations under different working conditions in different locations will be different from those of ordinary fixed ones. For example, mobile crushing stations face different geographical environments. When operating in mobile crushing stations, different geographical environments, such as cities, villages, and mountainous areas, have a significant impact on the propagation of noise. Therefore, factors such as reflection, absorption, and diffusion of the surrounding environment need to be considered. Different environmental factors change dynamically. Natural factors such as wind speed, wind direction, and humidity will affect noise propagation. Therefore, during the noise monitoring process, a dynamic monitoring system should be established to record environmental changes in real time and correct noise data.

[0142] For complex environments, it is necessary to establish a dynamic acoustic model based on field data. Using real-time collected noise signals and environmental data, a dynamic acoustic model is constructed to predict the noise distribution under different working conditions and positions. The model also needs to be adaptively adjusted to adjust the model parameters in real time under different locations and working conditions to more accurately reflect the noise characteristics of the current mobile crushing station. In the process of locating the noise source, multiple noise monitoring points are set to accurately locate the noise contribution of different components, such as crushers, conveyor belts, vibrating screens, etc.

[0143] It is also necessary to analyze the noise characteristics under different working conditions. According to the noise characteristics of the mobile crushing station under different working conditions, such as crushing, screening, transportation, etc., analyze the noise intensity, spectrum characteristics and change rules of each working condition. Compare with the fixed crushing station to highlight the differences in noise characteristics of the mobile crushing station under different geographical locations and working conditions.

[0144] The present application aims at a mobile crushing station, and automatically adjusts the parameters of the reverse sound wave, such as frequency, phase and amplitude, according to the real-time noise monitoring results and environmental changes to achieve the best noise suppression effect. A reverse sound wave emission array is arranged around the mobile crushing station to form a noise control strategy for different directions and distances.

[0145] The above application scheme not only emphasizes the characteristics and flexibility of mobile crushing stations in noise control, but also forms a sharp contrast with the noise control of traditional fixed crushing stations. This comprehensive analysis and control measures will effectively improve the noise management capabilities of mobile crushing stations, ensure that they can still comply with relevant noise standards in a changing working environment, and improve overall operating efficiency.

[0146] Reference Figure 3 and Figure 4 , a noise control system for a mobile crushing station is provided for an embodiment of the present application, the system comprising:

[0147] The spectrum analysis module is used to obtain the vibration noise signal of the crushing station, perform frequency domain conversion on the vibration noise signal, and obtain spectrum analysis information;

[0148] A distribution analysis module is used to analyze the frequency band where the noise energy is concentrated according to the spectrum analysis information to obtain distribution information and noise intensity information;

[0149] A first reverse sound wave generating module, used to generate first reverse sound wave information according to the distribution information and the noise intensity information;

[0150] A prediction model building module is used to obtain historical information of the crushing station and build an acoustic wave prediction model based on the historical information of the crushing station;

[0151] A second reverse acoustic wave generating module is used to obtain the working point position information, analyze the distribution information, the noise intensity information and the working point position information according to the acoustic wave prediction model, and obtain the second reverse acoustic wave information;

[0152] The sound wave output module adjusts the first reverse sound wave information according to the second reverse sound wave information to obtain reverse sound wave output information acting on the speaker.

[0153] Specifically, by collecting the vibration noise signal corresponding to one of the working points of the mobile crushing station, it is converted into the frequency domain, so that the time domain signal is converted into the frequency domain to obtain spectrum analysis information, and the spectrum analysis information is subjected to noise frequency band analysis to determine the distribution information of the low-frequency, medium-frequency and high-frequency components of the noise and the corresponding noise intensity information, thereby generating the first reverse sound wave information, and then constructing a model based on the historical information, and combining the working point location information to predict the second reverse sound wave information, and generating reverse sound wave output information by comprehensively generating the generated information and the predicted information, thereby suppressing the noise in the complex working environment of the mobile crushing station, so that it can more accurately and quickly respond to the noise generated in multiple usage environments and multiple working conditions of the mobile crushing station, and improve the operating stability of the mobile crushing station.

[0154] As one implementation mode, it also includes:

[0155] The orientation recognition module is used to analyze several vibration sensor signals of the vibration noise signal when generating reverse sound wave output information, obtain the noise source orientation information, and match the loudspeaker used to play the reverse sound wave output information according to the noise source orientation information.

[0156] As one implementation mode, it also includes:

[0157] The azimuth adjustment module is used to perform position adjustment processing according to the azimuth information of the noise source and the corresponding loudspeaker position information to obtain angle adjustment information for adjusting the direction of the loudspeaker.

[0158] As one implementation mode, it also includes:

[0159] The distance compensation module is used to perform distance analysis based on the noise source orientation information and the corresponding speaker position information to obtain distance information, and to compensate the reverse sound wave output information based on the distance information and a pre-built sound wave attenuation model to obtain compensated reverse sound wave information acting on the speaker.

[0160] As one implementation mode, it also includes:

[0161] The entity analysis module is used to obtain the structural parameters of the crushing station and build a physical model of the crushing station according to the structural parameters of the crushing station;

[0162] Obtain the operating parameters of the crushing station, perform vibration numerical simulation based on the crushing station physical model and the crushing station operating parameters, and obtain the natural frequency of the crushing station;

[0163] Compare the crushing station's natural frequency and spectrum analysis information to determine whether there are similar frequencies. If the frequencies are similar, select the resonant frequency for optimization reference;

[0164] The structural layout adjustment plan is matched according to the resonance frequency and the corresponding noise source orientation information.

[0165] As one implementation mode, it also includes:

[0166] A noise type confirmation module determines the noise type according to the distribution information and the noise intensity information, and matches the noise vibration threshold according to the noise type;

[0167] When outputting reverse sound wave output information, an updated noise signal is obtained in real time, and the updated noise signal is compared with a noise vibration threshold. When the updated noise signal is greater than the noise vibration threshold, updated azimuth information for issuing an alarm is obtained.

[0168] As one implementation mode, it also includes:

[0169] The model data updating module updates the data of the sound wave prediction model according to the updated noise signal.

[0170] As one implementation method, the specific steps of the position recognition module analyzing several vibration sensor signals of the vibration noise signal are as follows:

[0171] The time delay difference method is used to analyze several vibration sensor signals.

[0172] As one implementation mode, the historical information of the crushing station obtained by the prediction model building module includes historical noise distribution information, historical noise intensity information, historical crushing station location and historical environmental information.

[0173] An embodiment of the present application provides a noise control device for a mobile crushing station, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the noise control method for the mobile crushing station as described above.

[0174] An embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the noise control method for a mobile crushing station as described above when running.

[0175] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described device and product can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0176] In several embodiments provided in this application, it should be understood that the disclosed methods, systems, devices and program products may be implemented in other ways.

[0177] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0178] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A noise control method for a mobile crushing station, characterized in that: include: Obtain the vibration and noise signals of the crushing station, perform frequency domain conversion on the vibration and noise signals, and obtain spectrum analysis information; Analyze the frequency band where the noise energy is concentrated according to the spectrum analysis information to obtain the distribution information and noise intensity information; Generate first reverse sound wave information according to the distribution information and the noise intensity information; Obtain the historical information of the crushing station, and construct the acoustic wave prediction model based on the historical information of the crushing station; Acquire the working point location information, analyze the distribution information, noise intensity information and working point location information according to the sound wave prediction model, and obtain the second reverse sound wave information; The first reverse sound wave information is adjusted according to the second reverse sound wave information to obtain reverse sound wave output information acting on the speaker.

2. The noise control method of a mobile crushing station according to claim 1, characterized in that: Also includes: When the reverse sound wave output information is generated, several vibration sensor signals of the vibration noise signal are analyzed to obtain the noise source azimuth information, and the loudspeaker used to play the reverse sound wave output information is matched according to the noise source azimuth information.

3. The noise control method of a mobile crushing station according to claim 2, characterized in that: Also includes: Position adjustment processing is performed according to the noise source azimuth information and the corresponding loudspeaker position information to obtain angle adjustment information for adjusting the direction of the loudspeaker.

4. The noise control method of a mobile crushing station according to claim 3, characterized in that: Also includes: Distance analysis is performed based on the noise source azimuth information and the corresponding loudspeaker position information to obtain distance information, and reverse sound wave output information is compensated based on the distance information and a pre-built sound wave attenuation model to obtain compensated reverse sound wave information acting on the loudspeaker.

5. The noise control method of a mobile crushing station according to claim 1, characterized in that: Also includes: Obtain the structural parameters of the crushing station and build a physical model of the crushing station according to the structural parameters of the crushing station; Obtain the operating parameters of the crushing station, perform vibration numerical simulation based on the crushing station physical model and the crushing station operating parameters, and obtain the natural frequency of the crushing station; Compare the crushing station's natural frequency and spectrum analysis information to determine whether there are similar frequencies. If the frequencies are similar, select the resonant frequency for optimization reference; The structural layout adjustment plan is matched according to the resonance frequency and the corresponding noise source orientation information.

6. The noise control method of a mobile crushing station according to claim 1, characterized in that: Also includes: Determine the noise type according to the distribution information and the noise intensity information, and match the noise vibration threshold according to the noise type; When outputting reverse sound wave output information, an updated noise signal is obtained in real time, and the updated noise signal is compared with a noise vibration threshold. When the updated noise signal is greater than the noise vibration threshold, updated azimuth information for issuing an alarm is obtained.

7. The noise control method of a mobile crushing station according to claim 6, characterized in that: Also includes: The sound wave prediction model is updated according to the updated noise signal.

8. The noise control method of a mobile crushing station according to claim 2, characterized in that: The specific steps of analyzing the several vibration sensor signals of the vibration noise signal are as follows: The time delay difference method is used to analyze several vibration sensor signals.

9. The noise control method of a mobile crushing station according to claim 1, characterized in that: The crushing station historical information includes historical noise distribution information, historical noise intensity information, historical crushing station location and historical environmental information.

10. A noise control system for a mobile crushing station, characterized in that: include: The spectrum analysis module is used to obtain the vibration noise signal of the crushing station, perform frequency domain conversion on the vibration noise signal, and obtain spectrum analysis information; A distribution analysis module is used to analyze the frequency band where the noise energy is concentrated according to the spectrum analysis information to obtain distribution information and noise intensity information; A first reverse sound wave generating module, used to generate first reverse sound wave information according to the distribution information and the noise intensity information; A prediction model building module is used to obtain the historical information of the crushing station and build an acoustic wave prediction model based on the historical information of the crushing station; A second reverse acoustic wave generating module is used to obtain the working point position information, analyze the distribution information, the noise intensity information and the working point position information according to the acoustic wave prediction model, and obtain the second reverse acoustic wave information; The sound wave output module adjusts the first reverse sound wave information according to the second reverse sound wave information to obtain reverse sound wave output information acting on the speaker.

11. The noise control system of the mobile crushing station according to claim 10, characterized in that: Also includes: The orientation recognition module is used to analyze several vibration sensor signals of the vibration noise signal when generating reverse sound wave output information, obtain the noise source orientation information, and match the loudspeaker used to play the reverse sound wave output information according to the noise source orientation information.

12. The noise control system of the mobile crushing station according to claim 11, characterized in that: Also includes: The azimuth adjustment module is used to perform position adjustment processing according to the azimuth information of the noise source and the corresponding loudspeaker position information to obtain angle adjustment information for adjusting the direction of the loudspeaker.

13. The noise control system of the mobile crushing station according to claim 12, characterized in that: Also includes: The distance compensation module is used to perform distance analysis based on the noise source orientation information and the corresponding speaker position information to obtain distance information, and to compensate the reverse sound wave output information based on the distance information and a pre-built sound wave attenuation model to obtain compensated reverse sound wave information acting on the speaker.

14. The noise control system of the mobile crushing station according to claim 10, characterized in that: Also includes: The entity analysis module is used to obtain the structural parameters of the crushing station and build a physical model of the crushing station according to the structural parameters of the crushing station; Obtain the operating parameters of the crushing station, perform vibration numerical simulation based on the crushing station physical model and the crushing station operating parameters, and obtain the natural frequency of the crushing station; Compare the crushing station's natural frequency and spectrum analysis information to determine whether there are similar frequencies. If the frequencies are similar, select the resonant frequency for optimization reference; The structural layout adjustment plan is matched according to the resonance frequency and the corresponding noise source orientation information.

15. The noise control system of the mobile crushing station according to claim 10, characterized in that: Also includes: A noise type confirmation module determines the noise type according to the distribution information and the noise intensity information, and matches the noise vibration threshold according to the noise type; When outputting reverse sound wave output information, an updated noise signal is obtained in real time, and the updated noise signal is compared with a noise vibration threshold. When the updated noise signal is greater than the noise vibration threshold, updated azimuth information for issuing an alarm is obtained.

16. The noise control system of the mobile crushing station according to claim 15, characterized in that: Also includes: The model data updating module updates the data of the sound wave prediction model according to the updated noise signal.

17. The noise control system of the mobile crushing station according to claim 11, characterized in that: The specific steps of the orientation recognition module analyzing the multiple vibration sensor signals of the vibration noise signal are as follows: The time delay difference method is used to analyze several vibration sensor signals.

18. The noise control system of the mobile crushing station according to claim 10, characterized in that: The historical information of the crushing station acquired by the prediction model building module includes historical noise distribution information, historical noise intensity information, historical crushing station location and historical environmental information.

19. A noise control device for a mobile crushing station, characterized in that: The invention comprises a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the noise control method for a mobile crushing station according to any one of claims 1 to 9.

20. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program is configured to execute the noise control method for a mobile crushing station according to any one of claims 1 to 9 when running.

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