An intelligent processing system for metal products

Abstract

The present invention relates to the technical field of metal product processing, and specifically to an intelligent processing system for metal products, including an intelligent sensing module, a data analysis module, a noise control module, a vibration suppression module, a system optimization module, and an environmental impact assessment module; wherein: the intelligent sensing module: is used to capture the sound waves and vibration waveforms generated by mechanical equipment during operation; the data analysis module: analyzes the sources of noise and vibration, and calculates their intensity and frequency characteristics; the noise control module: controls the deployment of sound wave cancellers or sound wave absorbing materials according to the analysis results of the data analysis module; the vibration suppression module: adjusts the parameters of the vibration reduction device according to the analysis results of the data analysis module. The present invention, by real-time monitoring and automatic adjustment of noise and vibration control parameters, not only significantly improves the comfort and safety of the working environment, but also ensures the environmental compliance of industrial activities and promotes the sustainable development of enterprises.

Description

Technical Field

[0001] The present invention relates to the technical field of metal product processing, and in particular to an intelligent processing system for metal products. Background Art

[0002] During the processing of metal products, mechanical operation is often accompanied by significant noise and vibration, which not only affects the working environment of operators, but may also have an adverse impact on the surrounding environment. With the tightening of environmental protection regulations and the public's increasing concern about the impact of industrial environment, how to effectively control the noise and vibration generated by industrial equipment during operation has become an urgent problem to be solved. Traditional noise and vibration control methods often rely on passive protection measures, such as sound insulation covers and shock pads. Although these measures can reduce noise and vibration to a certain extent, they are often difficult to adapt to the ever-changing industrial environment and complex mechanical operating conditions.

[0003] The main problem with existing noise and vibration control technologies is that they lack sufficient flexibility and adaptability, and cannot automatically adjust control strategies according to real-time working conditions. Therefore, it is difficult to effectively deal with the variable noise and vibration generated by mechanical equipment under different working conditions. In addition, these traditional methods usually fail to fully consider the long-term impact of noise and vibration on the ecological environment, and how to ensure that industrial activities meet increasingly stringent environmental standards.

[0004] Therefore, developing an intelligent machining system that can monitor and automatically adjust control strategies in real time can not only optimize the operating environment and reduce health risks caused by noise and vibration, but also ensure the protection of the ecological environment through accurate environmental impact assessment and meet regulatory requirements. Summary of the invention

[0005] Based on the above objectives, the present invention provides an intelligent processing system for metal products.

[0006] An intelligent processing system for metal products, comprising an intelligent sensing module, a data analysis module, a noise control module, a vibration suppression module, a system optimization module and an environmental impact assessment module; wherein:

[0007] Intelligent sensing module: equipped with a variety of sensors to capture the sound and vibration waveforms generated by mechanical equipment during operation and convert them into noise and vibration data of digital signals;

[0008] Data analysis module: receives and processes the noise and vibration data from the intelligent sensing module, analyzes the source of noise and vibration through the preset noise and vibration reduction algorithm, and calculates its intensity and frequency characteristics;

[0009] Noise control module: controls the deployment of sound wave cancellers or sound wave absorbing materials according to the analysis results of the data analysis module to achieve optimal noise control;

[0010] Vibration suppression module: according to the analysis results of the data analysis module, adjust the parameters of the vibration reduction device, including adjusting the configuration of the mechanical elements of the damper and the spring, so as to reduce the vibration generated in the mechanical movement;

[0011] System optimization module: It is connected to the noise control module and the vibration suppression module respectively, continuously collects the operation data of each module, and optimizes the noise control and vibration control strategies through the particle swarm optimization algorithm based on the long-term operation data;

[0012] Environmental impact assessment module: used to evaluate the impact of system operation on the surrounding environment, including analysis of the long-term impact of noise and vibration on the surrounding environment, as well as the potential impact on the ecological environment, to ensure that the system operation meets environmental protection standards.

[0013] Furthermore, the intelligent sensing module includes a sound wave sensing unit, a vibration sensing unit, a signal processing unit and a data transmission unit; wherein:

[0014] Sound wave sensing unit: including electret microphone and condenser microphone, used to capture the sound waves generated during the operation of mechanical equipment. The microphone can detect the change of sound pressure by converting the mechanical vibration of the sound wave into a change of capacitance or charge, and then converting this change into an electrical signal through the internal circuit. The electrical signal represents the intensity and frequency characteristics of the sound wave;

[0015] Vibration sensing unit: including acceleration sensor and piezoelectric sensor, used to capture the vibration waveform generated during the operation of mechanical equipment. Acceleration sensor converts mechanical motion into electrical signal by detecting the acceleration change of the object when it vibrates; piezoelectric sensor converts mechanical stress into electrical signal by generating charge change when piezoelectric material vibrates. The captured signal is expressed as the amplitude and frequency of vibration.

[0016] Signal processing unit: connected to the sound wave sensing unit and the vibration sensing unit, used to receive the output analog electrical signal, and convert the analog signal into a digital signal through an analog-to-digital converter so that it can be read and analyzed by the subsequent data processing system. The signal processing unit also includes a filter for removing noise and interference signals;

[0017] Data transmission unit: connected to the signal processing unit, used to transmit the generated digital signal to the data analysis module. The data transmission unit adopts a high-speed communication interface, including SPI or I2C, to ensure real-time transmission and processing of data.

[0018] Furthermore, the data analysis module includes a data receiving unit, a preprocessing unit, a feature extraction unit, a source analysis unit, an intensity calculation unit and a frequency characteristic calculation unit; wherein:

[0019] Data receiving unit: used to receive digital signals from the intelligent sensing module, including noise and vibration data, and store them in the internal memory for subsequent processing;

[0020] Preprocessing unit: connected to the data receiving unit, used to preprocess the received digital signal, including removing noise and interference signals, using digital filtering technology, including low-pass filter and high-pass filter, to ensure the purity and accuracy of the signal;

[0021] Feature extraction unit: connected to the preprocessing unit, used to extract features from the preprocessed signal, including calculating the signal's intensity, frequency and time domain characteristics, and using fast Fourier transform and wavelet transform algorithms to convert the time domain signal into a frequency domain signal in order to analyze its spectrum characteristics;

[0022] Source analysis unit: connected to the feature extraction unit, used to analyze the source of noise and vibration according to the extracted signal features, and specifically determine the specific location and cause of noise and vibration by comparing the preset equipment running noise and vibration models;

[0023] Intensity calculation unit: connected to the source analysis unit, used to calculate the intensity of noise and vibration signals. Specifically, the integration and averaging processing methods are used to calculate the effective value of the signal to quantify the energy intensity of noise and vibration;

[0024] Frequency characteristic calculation unit: connected to the intensity calculation unit, used to calculate the frequency characteristics of noise and vibration signals, identify frequency components and harmonic components by performing spectrum analysis on the signals, and generate a frequency characteristic report to provide reference data for subsequent noise and vibration control.

[0025] Furthermore, the source analysis unit specifically includes:

[0026] Model library subunit: used to store preset equipment operation noise and vibration models, which are pre-established based on actual operation data and experimental data, including the noise and vibration characteristics of different mechanical parts in normal and abnormal conditions;

[0027] Feature matching subunit: connected to the model library subunit, used to match the noise and vibration features collected in real time with the features in the model library. The feature matching unit uses the Euclidean distance and dynamic time warping method to calculate the distance between feature vectors to determine the similarity and then perform matching;

[0028] Position identification subunit: connected to the feature matching subunit, used to determine the specific location of noise and vibration based on the matching results. Specifically, a weighted average algorithm is used to weight the locations corresponding to the features with high matching degrees to determine the final location of the noise and vibration source. The specific formula is: ,in, To determine the source of noise and vibration, For the The weight of the matching features, For the The part corresponding to each feature;

[0029] Cause analysis subunit: connected to the location identification subunit, used to analyze and determine the specific causes of noise and vibration. By combining the matching model features and real-time data change trends, Bayesian network reasoning is used to determine the potential causes of noise and vibration. The specific formula is:

[0030] ,in, It represents the probability of occurrence of the cause of noise and vibration given the evidence. represents the conditional probability of evidence when a certain cause occurs, represents the prior probability of the cause, Represents the prior probability of the evidence.

[0031] Furthermore, the intensity calculation unit specifically includes:

[0032] Data acquisition subunit: used for receiving pre-processed noise and vibration signals from the feature extraction unit;

[0033] Integral calculation subunit: used to perform integration processing on the received signal and calculate the total energy of the noise and vibration signal. The integral calculation formula is: ,in, represents the total energy of the signal, For time The signal strength at the moment, is the total duration of the signal;

[0034] Average calculation subunit: used to average the integration results and calculate the root mean square value of the signal. The root mean square value calculation formula is: ,in, Indicates the effective value of the signal, For time The signal strength at the moment, is the total duration of the signal;

[0035] Energy quantization subunit: used to quantize the calculated signal effective value to represent the energy intensity of noise and vibration.

[0036] Furthermore, the frequency characteristic calculation unit includes:

[0037] Data receiving subunit: used for receiving the pre-processed noise and vibration signals from the feature extraction unit;

[0038] Spectrum analysis subunit: connected to the data receiving subunit, used to perform spectrum analysis on the received signal, using the fast Fourier transform algorithm to convert the time domain signal into the frequency domain signal. The formula is:

[0039] ,in, is the frequency domain signal, is the time domain signal, is the frequency, For time, is an imaginary unit;

[0040] Harmonic identification subunit: connected to the spectrum analysis subunit, used to identify frequency components and harmonic components from the frequency domain signal, specifically by detecting the peak value and its integer multiple frequency components in the spectrum to determine the predetermined frequency and harmonics; the harmonic identification formula is: ,in, represents the set of harmonic frequencies, Indicates frequency The spectrum value at is the threshold for harmonic identification, is a positive integer;

[0041] Characteristic report generation subunit: connected with the harmonic identification subunit, used to generate a frequency characteristic report, which includes frequency components, harmonic components and their corresponding amplitude information.

[0042] Furthermore, the noise control module includes a noise data receiving unit, a sound wave cancellation unit, a sound wave absorption unit and a control instruction generation unit; wherein:

[0043] Noise data receiving unit: used to receive noise characteristic data from the data analysis module, including the frequency, intensity and source information of the noise;

[0044] Sound wave cancellation unit: used to generate a sound wave cancellation signal that matches the noise characteristic data and send it out through the sound wave canceller. The sound wave cancellation unit adjusts the frequency and phase of the sound wave cancellation signal in real time according to the received noise frequency and intensity information;

[0045] Sound wave absorption unit: used to adjust the deployment position and quantity of sound wave absorption materials according to noise characteristic data, and automatically adjust the position and quantity of absorption materials by adopting movable sound wave absorption plates and intelligent material control systems;

[0046] A control instruction generating unit is connected to the sound wave cancellation unit and the sound wave absorption unit respectively, and based on the received noise data, uses a preset noise control algorithm to calculate the optimal sound wave cancellation and absorption scheme, and generates specific control instructions, and sends the corresponding control instructions to the sound wave cancellation unit and the sound wave absorption unit.

[0047] Further, the vibration suppression module includes a vibration data receiving unit, a damping adjustment unit and a spring adjustment unit; wherein:

[0048] Vibration data receiving unit: used to receive vibration characteristic data from the data analysis module, including frequency, intensity and source information of vibration;

[0049] Damping adjustment unit: connected to the vibration data receiving unit, used to adjust the damping coefficient of the damper in real time according to the received vibration characteristic data to achieve the best vibration suppression effect. The damping adjustment unit controls the damping coefficient by adjusting the viscosity of the fluid inside the damper or changing the structural parameters of the damper. The required damping coefficient Calculated by the following formula: ,in, is the mass of the mechanical system, is the spring stiffness;

[0050] Spring adjustment unit: connected to the vibration data receiving unit, used to adjust the stiffness and preload of the spring according to the received vibration characteristic data. The spring adjustment unit controls the stiffness of the spring by changing the material properties or preload of the spring. The required spring stiffness

[0051] Calculated by the following formula: ,in, is the vibration period, The quality of the mechanical system.

[0052] Furthermore, the system optimization module includes a data collection unit, a data storage unit, an optimization calculation unit and a strategy update unit; wherein:

[0053] Data collection unit: used to continuously collect operation data from the noise control module and the vibration suppression module, including the frequency, intensity, and control effect parameters of noise and vibration;

[0054] Data storage unit: used to store long-term collected operation data and provide a data basis for subsequent optimization calculations;

[0055] Optimization calculation unit: Based on the collected long-term operation data, the noise control and vibration control strategies are optimized through the particle swarm optimization algorithm. The specific steps of the optimization calculation unit include:

[0056] Particle initialization: The position and velocity of each particle are randomly initialized. Each particle represents a control strategy combination, including sound wave cancellation and absorption parameters, damping and spring parameters;

[0057] Fitness calculation: According to the position of each particle, calculate the corresponding noise and vibration control effect. Let the fitness function be , the calculation formula is: ,in, For the sound wave cancellation effect, For the sound wave absorption effect, For the damping effect, For the spring effect, the optimization goal is to minimize the fitness function value;

[0058] Speed ​​and position update: According to the particle swarm optimization algorithm, the speed and position of each particle are updated. The speed update formula is: ,in, For particles In time speed, For particles In time location, For particles The best location in history, is the global optimal position of all particles, is the inertia weight, and is the acceleration constant, and is a random number; the position update formula is: ;

[0059] Iterative update: Repeat the fitness calculation and speed and position update until the preset convergence condition or the maximum number of iterations is reached;

[0060] Strategy update unit: used to update the noise control and vibration control strategies according to the optimization calculation results, and send the new strategy parameters to the relevant modules for implementation.

[0061] Furthermore, the environmental impact assessment module includes an environmental data collection unit, a long-term impact analysis unit, an ecological environmental impact unit, a compliance assessment unit and a report generation unit; wherein:

[0062] Environmental data acquisition unit: Through noise sensors and vibration sensors installed at predetermined locations, it captures the noise and vibration levels during system operation, as well as the background noise and vibration conditions of the surrounding environment;

[0063] Long-term impact analysis unit: used to conduct long-term analysis of the collected environmental data, evaluate the impact of noise and vibration on the surrounding environment, and evaluate the long-term cumulative effect of noise and vibration through time series analysis and statistical analysis. Specific methods include mean analysis, variance analysis and spectrum analysis to determine the continuous impact of noise and vibration on the environment;

[0064] Ecological and Environmental Impact Unit: It is used to evaluate the potential impact of noise and vibration on the ecological environment. Through model simulation and field testing, it analyzes the impact of noise and vibration on flora, fauna and the ecosystem, and compares the actual measured values ​​with the model predicted values. The Ecological and Environmental Impact Unit can determine the potential threat of noise and vibration to the ecological environment and whether there is an over-limit situation;

[0065] Compliance assessment unit: used to compare the assessment results with environmental standards to ensure that the system operation complies with relevant environmental laws and regulations. According to environmental standards and regulations, the noise and vibration assessment results are compared with the statutory standards, a compliance report is generated, and whether improvements are needed to ensure that the system meets environmental requirements;

[0066] Report generation unit: used to generate environmental impact assessment reports, including long-term impact analysis of noise and vibration, ecological environmental impact assessment and compliance reports, for review and filing by relevant departments.

[0067] Beneficial effects of the present invention:

[0068] The present invention, through the integrated intelligent control module, can not only monitor the noise and vibration data in real time, but also automatically adjust the parameters of the sound wave cancellation and vibration suppression device according to the real-time data, so as to effectively reduce the generation of noise and vibration under variable working conditions. This automatic adjustment mechanism greatly improves the adaptability and efficiency of noise and vibration control, provides operators with a quieter and more stable working environment, and reduces the health risks of long-term exposure to high noise and strong vibration environments.

[0069] The present invention, through long-term monitoring and data analysis, the evaluation module can provide environmental impact reports in a timely manner to ensure that the impact of noise and vibration on the surrounding environment is minimized. This not only helps companies comply with strict environmental regulations, but also promotes the realization of corporate social responsibility and enhances the public's trust in corporate environmental protection behavior, thereby enhancing the company's brand image and market competitiveness. The implementation of this system is an important step in the transformation of industrial production to green and sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0071] Figure 1 A schematic diagram of an intelligent processing system for metal products according to an embodiment of the present invention;

[0072] Figure 2 Schematic diagram of a system optimization module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0073] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0074] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0075] like Figure 1-Figure 2 As shown, an intelligent processing system for metal products includes an intelligent sensing module, a data analysis module, a noise control module, a vibration suppression module, a system optimization module and an environmental impact assessment module; wherein:

[0076] Intelligent sensing module: equipped with a variety of sensors to capture the sound and vibration waveforms generated by mechanical equipment during operation and convert them into noise and vibration data of digital signals;

[0077] Data analysis module: receives and processes the noise and vibration data from the intelligent sensing module, analyzes the source of noise and vibration through the preset noise and vibration reduction algorithm, and calculates its intensity and frequency characteristics;

[0078] Noise control module: controls the deployment of sound wave cancellers or sound wave absorbing materials according to the analysis results of the data analysis module to achieve optimal noise control;

[0079] Vibration suppression module: according to the analysis results of the data analysis module, adjust the parameters of the vibration reduction device, including adjusting the configuration of the mechanical elements of the damper and the spring, so as to reduce the vibration generated in the mechanical movement;

[0080] System optimization module: It is connected to the noise control module and the vibration suppression module respectively, continuously collects the operation data of each module, and optimizes the noise control and vibration control strategies through the particle swarm optimization algorithm based on the long-term operation data to improve the overall system performance;

[0081] Environmental impact assessment module: used to evaluate the impact of system operation on the surrounding environment, including analysis of the long-term impact of noise and vibration on the surrounding environment, as well as the potential impact on the ecological environment, to ensure that the system operation meets environmental protection standards.

[0082] The intelligent sensing module includes an acoustic wave sensing unit, a vibration sensing unit, a signal processing unit and a data transmission unit; wherein:

[0083] Sound wave sensing unit: including electret microphone and condenser microphone, used to capture the sound waves generated during the operation of mechanical equipment. The microphone can detect the change of sound pressure, convert the mechanical vibration of the sound wave into the change of capacitance or charge, and then convert this change into an electrical signal through the internal circuit. The electrical signal represents the intensity and frequency characteristics of the sound wave;

[0084] Vibration sensing unit: including acceleration sensor and piezoelectric sensor, used to capture the vibration waveform generated during the operation of mechanical equipment. Acceleration sensor converts mechanical motion into electrical signal by detecting the acceleration change of the object when it vibrates; piezoelectric sensor converts mechanical stress into electrical signal by generating charge change when piezoelectric material vibrates. The captured signal is expressed as the amplitude and frequency of vibration.

[0085] Signal processing unit: connected to the sound wave sensing unit and the vibration sensing unit, used to receive the output analog electrical signal, and convert the analog signal into a digital signal through an analog-to-digital converter (ADC) so that it can be read and analyzed by the subsequent data processing system. The signal processing unit also includes a filter to remove noise and interference signals to ensure the accuracy of the signal;

[0086] Data transmission unit: connected to the signal processing unit, used to transmit the generated digital signal to the data analysis module. The data transmission unit adopts a high-speed communication interface, including SPI or I2C, to ensure real-time transmission and processing of data to achieve efficient operation of the system. Through the design of the above-mentioned intelligent sensing module, the sound waves and vibration waveforms generated by the mechanical equipment during operation can be accurately captured, and they can be efficiently converted into noise and vibration data of digital signals. These data provide a reliable basis for subsequent data analysis and control, ensuring that the source of noise and vibration can be accurately located and processed, thereby improving the overall performance and intelligence level of the system.

[0087] The data analysis module includes a data receiving unit, a preprocessing unit, a feature extraction unit, a source analysis unit, an intensity calculation unit and a frequency characteristic calculation unit; wherein:

[0088] Data receiving unit: used to receive digital signals from the intelligent sensing module, including noise and vibration data, and store them in the internal memory for subsequent processing;

[0089] Preprocessing unit: connected to the data receiving unit, used to preprocess the received digital signal, including removing noise and interference signals, using digital filtering technology, including low-pass filter and high-pass filter, to ensure the purity and accuracy of the signal;

[0090] Feature extraction unit: connected to the preprocessing unit, used to extract features from the preprocessed signal, including calculating the signal's intensity, frequency and time domain characteristics, and using the fast Fourier transform (FFT) and wavelet transform algorithms to convert the time domain signal into a frequency domain signal in order to analyze its spectrum characteristics;

[0091] Source analysis unit: connected to the feature extraction unit, used to analyze the source of noise and vibration according to the extracted signal features, and specifically determine the specific location and cause of noise and vibration by comparing the preset equipment running noise and vibration models;

[0092] Intensity calculation unit: connected to the source analysis unit, used to calculate the intensity of noise and vibration signals. Specifically, the integration and averaging processing methods are used to calculate the effective value (RMS) of the signal to quantify the energy intensity of noise and vibration;

[0093] Frequency characteristic calculation unit: connected to the intensity calculation unit, used to calculate the frequency characteristics of noise and vibration signals, identify the frequency components and harmonic components by performing spectrum analysis on the signals, and generate a frequency characteristic report to provide reference data for subsequent noise and vibration control; through the design of the above data analysis module, it is able to efficiently receive and process the noise and vibration digital signal data from the intelligent sensing module. The module uses advanced signal processing and analysis algorithms to accurately identify the sources of noise and vibration, and accurately calculate their intensity and frequency characteristics, providing reliable technical support for the system's noise and vibration control, thereby improving the overall performance and intelligence level of the system.

[0094] The source analysis unit specifically includes:

[0095] Model library subunit: used to store preset equipment operation noise and vibration models, which are pre-established based on actual operation data and experimental data, including the noise and vibration characteristics of different mechanical parts in normal and abnormal conditions;

[0096] Feature matching subunit: connected to the model library subunit, used to match the noise and vibration features collected in real time with the features in the model library. The feature matching unit uses the Euclidean distance (Euclidean Distance) and dynamic time warping (Dynamic Time Warping, DTW) methods to determine the similarity by calculating the distance between feature vectors, and then perform matching. The Euclidean distance formula is:

[0097] ,in, is the noise or vibration feature vector collected in real time, is the feature vector in the model library, and Respectively represent eigenvalues, Represents the distance between feature vectors;

[0098] The DTW formula is: ,in, and There are two sets of time series, represents their minimum matching distance, and is the characteristic value in the time series, is the length of the matching path;

[0099] Position identification subunit: connected to the feature matching subunit, used to determine the specific location of noise and vibration based on the matching results. Specifically, a weighted average algorithm is used to weight the locations corresponding to the features with high matching degrees to determine the final location of the noise and vibration source. The specific formula is: ,in, To determine the source of noise and vibration, For the The weight of the matching features, For the The part corresponding to each feature;

[0100] Cause analysis subunit: connected to the location identification subunit, used to analyze and determine the specific causes of noise and vibration. By combining the matching model features and real-time data change trends, the Bayesian Network is used for reasoning to determine the potential causes of noise and vibration. The specific formula is:

[0101] ,in, It represents the probability of occurrence of the cause of noise and vibration given the evidence (real-time data), represents the conditional probability of evidence when a certain cause occurs, represents the prior probability of the cause, Represents the prior probability of evidence; through the design of the above-mentioned source analysis unit, it is possible to accurately determine the specific location and cause of noise and vibration by comparing the preset equipment operation noise and vibration model, and adopt algorithms such as Euclidean distance, dynamic time warping, weighted average and Bayesian network to ensure the efficiency and accuracy of the analysis process, provide a scientific basis for the noise and vibration control of the system, and improve the overall performance and intelligence level of the system.

[0102] The intensity calculation unit specifically includes:

[0103] Data acquisition subunit: used for receiving pre-processed noise and vibration signals from the feature extraction unit;

[0104] Integral calculation subunit: used to perform integration processing on the received signal and calculate the total energy of the noise and vibration signal. The integral calculation formula is: ,in, represents the total energy of the signal, For time The signal strength at the moment, is the total duration of the signal;

[0105] Average calculation subunit: used to average the integration results and calculate the root mean square value (RMS) of the signal. The formula for calculating the root mean square value is: ,in, Indicates the effective value of the signal, For time The signal strength at the moment, is the total duration of the signal;

[0106] Energy quantization subunit: used to quantify the calculated signal effective value (RMS) to represent the energy intensity of noise and vibration for subsequent analysis and control; the specific quantification steps are as follows:

[0107] Determination of calibration coefficients: During initial system installation and periodic maintenance, the system is calibrated using a known standard signal to determine the calibration coefficients. , which is used to convert the RMS value into the energy intensity value in standard units. The calibration factor is determined according to the following formula: ,in, is the energy intensity of the known standard signal, The RMS value when the system measures the standard signal;

[0108] RMS value conversion: The real-time calculated RMS value is compared with the calibration coefficient Multiply to get the energy intensity value in standard units , the calculation formula is: ,in, Indicates the converted standard unit energy intensity value, is the effective value of the signal calculated in real time, is the calibration factor;

[0109] Unit conversion: The energy quantization unit converts the calculated energy intensity value into appropriate units, such as sound power level, according to the specific application scenario. Or vibration intensity level , ensuring the consistency and comparability of data in subsequent analysis and control; through the design of the above-mentioned intensity calculation unit, the effective value (RMS) of the noise and vibration signals can be accurately calculated, thereby quantifying the energy intensity of noise and vibration. The integration and averaging processing methods are used to ensure the accuracy and reliability of the signal intensity calculation, providing key data support for the noise and vibration control of the system.

[0110] The frequency characteristic calculation unit includes:

[0111] Data receiving subunit: used for receiving the pre-processed noise and vibration signals from the feature extraction unit;

[0112] Spectrum analysis subunit: connected to the data receiving subunit, used to perform spectrum analysis on the received signal, using the fast Fourier transform (FFT) algorithm to convert the time domain signal into the frequency domain signal. The spectrum analysis formula is: ,in, is the frequency domain signal, is the time domain signal, is the frequency, For time, is an imaginary unit;

[0113] Harmonic identification subunit: connected to the spectrum analysis subunit, used to identify frequency components and harmonic components from the frequency domain signal, specifically by detecting the peak value and its integer multiple frequency components in the spectrum to determine the predetermined frequency and harmonics; the harmonic identification formula is: ,in, represents the set of harmonic frequencies, Indicates frequency The spectrum value at is the threshold for harmonic identification, is a positive integer;

[0114] Characteristic report generation subunit: connected to the harmonic identification subunit, used to generate a frequency characteristic report, which includes frequency components, harmonic components and their corresponding amplitude information; through the design of the above-mentioned frequency characteristic calculation unit, the frequency characteristics of noise and vibration signals can be accurately calculated, and a detailed frequency characteristic report can be generated. The fast Fourier transform algorithm is used to convert time domain signals into frequency domain signals, and the main frequency components and harmonic components are identified, which provides key reference data for the noise and vibration control of the system, and further improves the overall performance and intelligence level of the system.

[0115] The noise control module includes a noise data receiving unit, a sound wave cancellation unit, a sound wave absorption unit and a control instruction generation unit; wherein:

[0116] Noise data receiving unit: used to receive noise characteristic data from the data analysis module, including the frequency, intensity and source information of the noise;

[0117] Sound wave cancellation unit: used to generate a sound wave cancellation signal that matches the noise characteristic data and send it out through the sound wave canceller. The sound wave cancellation unit adjusts the frequency and phase of the sound wave cancellation signal in real time according to the received noise frequency and intensity information to achieve effective noise cancellation.

[0118] Sound wave absorption unit: used to adjust the deployment position and quantity of sound wave absorption materials according to noise characteristic data. By adopting movable sound wave absorption plates and intelligent material control system, the position and quantity of absorption materials are automatically adjusted to optimally absorb noise within a specific frequency range.

[0119] The control instruction generating unit is connected to the sound wave cancellation unit and the sound wave absorption unit respectively, and based on the received noise data, uses the preset noise control algorithm to calculate the optimal sound wave cancellation and absorption scheme, and generates specific control instructions, and sends the corresponding control instructions to the sound wave cancellation unit and the sound wave absorption unit. The calculation process of the control instruction includes:

[0120] First, based on the received noise frequency and strength , conduct frequency and intensity distribution analysis;

[0121] Then, a sound wave cancellation signal matching the noise characteristics is generated, and the calculation formula is:

[0122] ,in, To generate the acoustic wave cancellation signal, The phase is adjusted so that the cancellation signal is in opposite phase to the noise signal to achieve noise cancellation.

[0123] Next, the location and amount of optimal absorption material deployment are calculated, assuming that the noise frequency range is , the sound wave absorption efficiency function is , then the total absorption effect for:

[0124] ,in, For frequency The noise intensity at

[0125] Finally, based on the optimization calculation results, specific control instructions are generated, including the frequency and phase adjustment parameters of the sound wave canceller and the deployment position and quantity of the sound wave absorbing material. Through the design of the above-mentioned control instruction generation unit, the preset noise control algorithm can be used to accurately calculate the optimal sound wave cancellation and absorption scheme, and generate specific control instructions. These control instructions achieve the best noise control effect of the system by accurately adjusting the frequency and phase of the sound wave cancellation signal and optimizing the deployment of the sound wave absorbing material, thereby improving the overall performance and intelligence level of the system.

[0126] The vibration suppression module includes a vibration data receiving unit, a damping adjustment unit and a spring adjustment unit; wherein:

[0127] Vibration data receiving unit: used to receive vibration characteristic data from the data analysis module, including frequency, intensity and source information of vibration;

[0128] Damping adjustment unit: connected to the vibration data receiving unit, used to adjust the damping coefficient of the damper in real time according to the received vibration characteristic data to achieve the best vibration suppression effect. The damping adjustment unit controls the damping coefficient by adjusting the viscosity of the fluid inside the damper or changing the structural parameters of the damper. The required damping coefficient Calculated by the following formula: ,in, is the mass of the mechanical system, is the spring stiffness, and the damper parameters are adjusted to meet the calculated value, thereby achieving optimal damping;

[0129] Spring adjustment unit: connected to the vibration data receiving unit, used to adjust the stiffness and preload of the spring according to the received vibration characteristic data. The spring adjustment unit controls the stiffness of the spring by changing the material properties or preload of the spring. The required spring stiffness

[0130] Calculated by the following formula: ,in, is the vibration period, is the mass of the mechanical system, and the material properties or preload of the spring are adjusted to achieve the calculated The vibration suppression module can be designed to accurately adjust the parameters of the vibration isolation device according to the vibration characteristic data provided by the data analysis module, including adjusting the configuration of the damper and the spring, thereby effectively reducing the vibration generated during mechanical movement.

[0131] The system optimization module includes a data collection unit, a data storage unit, an optimization calculation unit and a strategy update unit; wherein:

[0132] Data collection unit: used to continuously collect operation data from the noise control module and the vibration suppression module, including the frequency, intensity, and control effect parameters of noise and vibration;

[0133] Data storage unit: used to store long-term collected operation data and provide a data basis for subsequent optimization calculations;

[0134] Optimization calculation unit: Based on the collected long-term operation data, the noise control and vibration control strategies are optimized through the particle swarm optimization algorithm (PSO). The specific steps of the optimization calculation unit include:

[0135] Particle initialization: The position and velocity of each particle are randomly initialized. Each particle represents a control strategy combination, including sound wave cancellation and absorption parameters, damping and spring parameters;

[0136] Fitness calculation: According to the position of each particle, calculate the corresponding noise and vibration control effect. Let the fitness function be , the calculation formula is: ,in, For the sound wave cancellation effect, For the sound wave absorption effect, For the damping effect, For the spring effect, the optimization goal is to minimize the fitness function value;

[0137] Speed ​​and position update: According to the particle swarm optimization algorithm, the speed and position of each particle are updated. The speed update formula is: ,in, For particles In time speed, For particles In time location, For particles The best location in history, is the global optimal position of all particles, is the inertia weight, and is the acceleration constant, and is a random number; the position update formula is: ;

[0138] Iterative update: Repeat the fitness calculation and speed and position update until the preset convergence condition or the maximum number of iterations is reached;

[0139] Strategy updating unit: used to update the noise control and vibration control strategies according to the optimization calculation results, and send the new strategy parameters to the relevant modules for implementation; through the design of the above system optimization module, it can continuously collect the operation data of the noise control module and the vibration suppression module, and optimize the noise control and vibration control strategies based on the long-term operation data through the particle swarm optimization algorithm (PSO). The optimization calculation unit uses the PSO algorithm to dynamically adjust the control strategy, so that the system always maintains the best control effect under different operating conditions, thereby improving the overall performance and intelligence level of the system.

[0140] The environmental impact assessment module includes an environmental data collection unit, a long-term impact analysis unit, an ecological environmental impact unit, a compliance assessment unit, and a report generation unit; among which:

[0141] Environmental data acquisition unit: Through noise sensors and vibration sensors installed at predetermined locations, it captures the noise and vibration levels during system operation, as well as the background noise and vibration conditions of the surrounding environment;

[0142] Long-term impact analysis unit: used to conduct long-term analysis of the collected environmental data, evaluate the impact of noise and vibration on the surrounding environment, and evaluate the long-term cumulative effect of noise and vibration through time series analysis and statistical analysis. Specific methods include mean analysis, variance analysis and spectrum analysis to determine the continuous impact of noise and vibration on the environment;

[0143] Ecological and Environmental Impact Unit: It is used to evaluate the potential impact of noise and vibration on the ecological environment. Through model simulation and field testing, it analyzes the impact of noise and vibration on flora, fauna and the ecosystem, and compares the actual measured values ​​with the model predicted values. The Ecological and Environmental Impact Unit can determine the potential threat of noise and vibration to the ecological environment and whether there is an over-limit situation;

[0144] Compliance assessment unit: used to compare the assessment results with environmental standards to ensure that the system operation complies with relevant environmental laws and regulations. According to environmental standards and regulations, the noise and vibration assessment results are compared with the statutory standards, a compliance report is generated, and whether improvements are needed to ensure that the system meets environmental requirements;

[0145] Report generation unit: used to generate environmental impact assessment reports, including long-term impact analysis of noise and vibration, ecological environmental impact assessment and compliance reports, for review and filing by relevant departments; through the design of the above-mentioned environmental impact assessment module, it is possible to comprehensively evaluate the impact of system operation on the surrounding environment, ensure that the long-term impact of noise and vibration on the surrounding environment and the potential impact of the ecological environment are effectively analyzed and controlled, and through real-time monitoring, long-term analysis, model simulation and compliance assessment, ensure that the system operation complies with environmental protection standards, provide scientific basis and improvement suggestions, and improve the system's environmental performance and sustainable development capabilities.

[0146] The present invention is intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An intelligent processing system for metal products, characterized in that: It includes intelligent sensing module, data analysis module, noise control module, vibration suppression module, system optimization module and environmental impact assessment module; among which: Intelligent sensing module: equipped with a variety of sensors to capture the sound and vibration waveforms generated by mechanical equipment during operation and convert them into noise and vibration data of digital signals; The intelligent sensing module includes a sound wave sensing unit, a vibration sensing unit, a signal processing unit and a data transmission unit; wherein: Sound wave sensing unit: including electret microphone and condenser microphone, used to capture the sound waves generated during the operation of mechanical equipment. The microphone can detect the change of sound pressure by converting the mechanical vibration of the sound wave into a change of capacitance or charge, and then converting this change into an electrical signal through the internal circuit. The electrical signal represents the intensity and frequency characteristics of the sound wave; Vibration sensing unit: including acceleration sensor and piezoelectric sensor, used to capture the vibration waveform generated during the operation of mechanical equipment. Acceleration sensor converts mechanical motion into electrical signal by detecting the acceleration change of the object when it vibrates; piezoelectric sensor converts mechanical stress into electrical signal by generating charge change when piezoelectric material vibrates. The captured signal is expressed as the amplitude and frequency of vibration. Signal processing unit: connected to the sound wave sensing unit and the vibration sensing unit, used to receive the output analog electrical signal, and convert the analog signal into a digital signal through an analog-to-digital converter so that it can be read and analyzed by the subsequent data processing system. The signal processing unit also includes a filter for removing noise and interference signals; Data transmission unit: connected to the signal processing unit, used to transmit the generated digital signal to the data analysis module. The data transmission unit adopts a high-speed communication interface, including SPI or I2C, to ensure real-time transmission and processing of data; Data analysis module: receives and processes the noise and vibration data from the intelligent sensing module, analyzes the source of noise and vibration through the preset noise and vibration reduction algorithm, and calculates its intensity and frequency characteristics; The data analysis module includes a data receiving unit, a preprocessing unit, a feature extraction unit, a source analysis unit, an intensity calculation unit and a frequency characteristic calculation unit; wherein: Data receiving unit: used to receive digital signals from the intelligent sensing module, including noise and vibration data, and store them in the internal memory for subsequent processing; Preprocessing unit: connected to the data receiving unit, used to preprocess the received digital signal, including removing noise and interference signals, using digital filtering technology, including low-pass filter and high-pass filter, to ensure the purity and accuracy of the signal; Feature extraction unit: connected to the preprocessing unit, used to extract features from the preprocessed signal, including calculating the signal's intensity, frequency and time domain characteristics, and using fast Fourier transform and wavelet transform algorithms to convert the time domain signal into a frequency domain signal in order to analyze its spectrum characteristics; Source analysis unit: connected to the feature extraction unit, used to analyze the source of noise and vibration according to the extracted signal features, and specifically determine the specific location and cause of noise and vibration by comparing the preset equipment running noise and vibration models; Intensity calculation unit: connected to the source analysis unit, used to calculate the intensity of noise and vibration signals. Specifically, the integration and averaging processing methods are used to calculate the effective value of the signal to quantify the energy intensity of noise and vibration; Frequency characteristic calculation unit: connected to the intensity calculation unit, used to calculate the frequency characteristics of noise and vibration signals, identify frequency components and harmonic components by performing spectrum analysis on the signals, and generate a frequency characteristic report to provide reference data for subsequent noise and vibration control; Noise control module: controls the deployment of sound wave cancellers or sound wave absorbing materials according to the analysis results of the data analysis module to achieve optimal noise control; The noise control module includes a noise data receiving unit, a sound wave cancellation unit, a sound wave absorption unit and a control instruction generation unit; wherein: Noise data receiving unit: used to receive noise characteristic data from the data analysis module, including the frequency, intensity and source information of the noise; Sound wave cancellation unit: used to generate a sound wave cancellation signal that matches the noise characteristic data and send it through the sound wave canceller. The sound wave cancellation unit adjusts the frequency and phase of the sound wave cancellation signal in real time according to the received noise frequency and intensity information; Sound wave absorption unit: used to adjust the deployment position and quantity of sound wave absorption materials according to noise characteristic data, and automatically adjust the position and quantity of absorption materials by adopting movable sound wave absorption plates and intelligent material control systems; A control instruction generating unit: connected to the sound wave cancellation unit and the sound wave absorption unit respectively, and based on the received noise data, using a preset noise control algorithm, calculates the optimal sound wave cancellation and absorption scheme, generates specific control instructions, and sends the corresponding control instructions to the sound wave cancellation unit and the sound wave absorption unit; Vibration suppression module: according to the analysis results of the data analysis module, adjust the parameters of the vibration reduction device, including adjusting the configuration of the mechanical elements of the damper and the spring, so as to reduce the vibration generated in the mechanical movement; The vibration suppression module includes a vibration data receiving unit, a damping adjustment unit and a spring adjustment unit; wherein: Vibration data receiving unit: used to receive vibration characteristic data from the data analysis module, including frequency, intensity and source information of vibration; Damping adjustment unit: connected to the vibration data receiving unit, used to adjust the damping coefficient of the damper in real time according to the received vibration characteristic data to achieve the best vibration suppression effect. The damping adjustment unit controls the damping coefficient by adjusting the viscosity of the fluid inside the damper or changing the structural parameters of the damper. The required damping coefficient Calculated by the following formula: ,in, is the mass of the mechanical system, is the spring stiffness; Spring adjustment unit: connected to the vibration data receiving unit, used to adjust the stiffness and preload of the spring according to the received vibration characteristic data. The spring adjustment unit controls the stiffness of the spring by changing the material properties or preload of the spring. The required spring stiffness Calculated by the following formula: ,in, is the vibration period, is the quality of the mechanical system; System optimization module: It is connected to the noise control module and the vibration suppression module respectively, continuously collects the operation data of each module, and optimizes the noise control and vibration control strategies through the particle swarm optimization algorithm based on the long-term operation data; The system optimization module includes a data collection unit, a data storage unit, an optimization calculation unit and a strategy update unit; wherein: Data collection unit: used to continuously collect operation data from the noise control module and the vibration suppression module, including the frequency, intensity, and control effect parameters of noise and vibration; Data storage unit: used to store long-term collected operation data and provide a data basis for subsequent optimization calculations; Optimization calculation unit: Based on the collected long-term operation data, the noise control and vibration control strategies are optimized through the particle swarm optimization algorithm. The specific steps of the optimization calculation unit include: Particle initialization: The position and velocity of each particle are randomly initialized. Each particle represents a control strategy combination, including sound wave cancellation and absorption parameters, damping and spring parameters; Fitness calculation: According to the position of each particle, calculate the corresponding noise and vibration control effect. Let the fitness function be , the calculation formula is: ,in, For the sound wave cancellation effect, For the sound wave absorption effect, For the damping effect, For the spring effect, the optimization goal is to minimize the fitness function value; Speed ​​and position update: According to the particle swarm optimization algorithm, the speed and position of each particle are updated. The speed update formula is: ,in, For particles In time speed, For particles In time location, For particles The best location in history, is the global optimal position of all particles, is the inertia weight, and is the acceleration constant, and is a random number; the position update formula is: ; Iterative update: Repeat the fitness calculation and speed and position update until the preset convergence condition or the maximum number of iterations is reached; Strategy update unit: used to update noise control and vibration control strategies according to the optimization calculation results, and send new strategy parameters to related modules for implementation; Environmental impact assessment module: used to assess the impact of system operation on the surrounding environment, including the long-term impact analysis of noise and vibration on the surrounding environment, as well as the potential impact on the ecological environment, to ensure that the system operation meets environmental protection standards; The environmental impact assessment module includes an environmental data collection unit, a long-term impact analysis unit, an ecological environmental impact unit, a compliance assessment unit and a report generation unit; wherein: Environmental data acquisition unit: Through noise sensors and vibration sensors installed at predetermined locations, it captures the noise and vibration levels during system operation, as well as the background noise and vibration conditions of the surrounding environment; Long-term impact analysis unit: used to conduct long-term analysis of the collected environmental data, evaluate the impact of noise and vibration on the surrounding environment, and evaluate the long-term cumulative effect of noise and vibration through time series analysis and statistical analysis. Specific methods include mean analysis, variance analysis and spectrum analysis to determine the continuous impact of noise and vibration on the environment; Ecological and Environmental Impact Unit: It is used to evaluate the potential impact of noise and vibration on the ecological environment. Through model simulation and field testing, it analyzes the impact of noise and vibration on flora, fauna and the ecosystem, and compares the actual measured values ​​with the model predicted values. The Ecological and Environmental Impact Unit can determine the potential threat of noise and vibration to the ecological environment and whether there is an over-limit situation; Compliance assessment unit: used to compare the assessment results with environmental standards to ensure that the system operation complies with relevant environmental laws and regulations. According to environmental standards and regulations, the noise and vibration assessment results are compared with the statutory standards, a compliance report is generated, and whether improvements are needed to ensure that the system meets environmental requirements; Report generation unit: used to generate environmental impact assessment reports, including long-term impact analysis of noise and vibration, ecological environmental impact assessment and compliance reports, for review and filing by relevant departments.

2. The intelligent processing system for metal products according to claim 1, characterized in that: The source analysis unit specifically includes: Model library subunit: used to store preset equipment operation noise and vibration models, which are pre-established based on actual operation data and experimental data, including the noise and vibration characteristics of different mechanical parts in normal and abnormal conditions; Feature matching subunit: connected to the model library subunit, used to match the noise and vibration features collected in real time with the features in the model library. The feature matching unit uses the Euclidean distance and dynamic time warping method to calculate the distance between feature vectors to determine the similarity and then perform matching; Position identification subunit: connected to the feature matching subunit, used to determine the specific location of noise and vibration based on the matching results. Specifically, a weighted average algorithm is used to weight the locations corresponding to the features with high matching degrees to determine the final location of the noise and vibration source. The specific formula is: ,in, To determine the source of noise and vibration, For the The weight of the matching features, For the The part corresponding to each feature; Cause analysis subunit: connected to the location identification subunit, used to analyze and determine the specific causes of noise and vibration. By combining the matching model features and real-time data change trends, Bayesian network reasoning is used to determine the potential causes of noise and vibration. The specific formula is: ,in, It represents the probability of occurrence of the cause of noise and vibration given the evidence. represents the conditional probability of evidence when a certain cause occurs, represents the prior probability of the cause, Represents the prior probability of the evidence.

3. The intelligent processing system for metal products according to claim 2, characterized in that: The intensity calculation unit specifically includes: Data acquisition subunit: used for receiving pre-processed noise and vibration signals from the feature extraction unit; Integral calculation subunit: used to perform integration processing on the received signal and calculate the total energy of the noise and vibration signal. The integral calculation formula is: ,in, represents the total energy of the signal, For time The signal strength at the moment, is the total duration of the signal; Average calculation subunit: used to average the integration results and calculate the root mean square value of the signal. The root mean square value calculation formula is: ,in, Indicates the effective value of the signal, For time The signal strength at the moment, is the total duration of the signal; Energy quantization subunit: used to quantize the calculated signal effective value to represent the energy intensity of noise and vibration.

4. The intelligent processing system for metal products according to claim 3, characterized in that: The frequency characteristic calculation unit comprises: Data receiving subunit: used for receiving the pre-processed noise and vibration signals from the feature extraction unit; Spectrum analysis subunit: connected to the data receiving subunit, used to perform spectrum analysis on the received signal, using the fast Fourier transform algorithm to convert the time domain signal into the frequency domain signal. The formula is: ,in, is the frequency domain signal, is the time domain signal, is the frequency, For time, is an imaginary unit; Harmonic identification subunit: connected to the spectrum analysis subunit, used to identify frequency components and harmonic components from the frequency domain signal, specifically by detecting the peak value and its integer multiple frequency components in the spectrum to determine the predetermined frequency and harmonics; the harmonic identification formula is: ,in, represents the set of harmonic frequencies, Indicates frequency The spectrum value at is the threshold for harmonic identification, is a positive integer; Characteristic report generation subunit: connected with the harmonic identification subunit, used to generate a frequency characteristic report, which includes frequency components, harmonic components and their corresponding amplitude information.

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