Mechanical transmission optimization and evaluation method of industrial sound insulation composite board

Abstract

The application discloses a kind of mechanical transmission optimization and evaluation method of industrial sound insulation composite board, and the application relates to the technical field of mechanical transmission state monitoring and water pollution control and treatment synergic optimization, the vibration acceleration signal and torque signal of the transmission gear box of heavy roller press are collected, the mechanical load characteristic vector is extracted, the digital twin mapping prediction model is constructed by convolutional neural network and long short-term memory network, the wastewater toxicity load is predicted in advance and the early warning signal is output, before pollutants reach biochemical treatment tank, the feedforward adjustment of the dosing amount of special functional microorganisms and aeration ratio is carried out using the buffer time of adjusting tank, while the residual vibration energy is safety evaluated, the vibration energy within the safety range is guided into biochemical treatment tank through acoustic waveguide tube, and mass transfer efficiency is strengthened.The application realizes dynamic synergic mapping and energy coupling utilization of mechanical transmission system and sewage treatment and its regeneration system.

Description

Technical Field

[0001] This invention relates to the field of synergistic optimization technology of mechanical transmission status monitoring and water pollution control and treatment, specifically a method for optimizing and evaluating the mechanical transmission of industrial sound insulation composite panels. Background Technology

[0002] Industrial sound insulation composite panel production lines typically consist of heavy-duty roller presses, hot presses, and other main equipment. Power is supplied by a transmission gearbox via a drive shaft, driving rollers or pressure plates to complete the forming and hot-pressing of the panels. During production, adhesives, primarily composed of polymers such as phenolic resin, are applied to bond the various layers of the panel. Wastewater generated during production mainly contains resin monomers formed from the volatilization or extrusion of the adhesive, such as free phenol and free formaldehyde. This type of wastewater usually first enters an equalization tank for water quantity and quality homogenization, and then enters a biological treatment tank. By adding specialized functional microbial agents and using an aeration system, pollutants are biodegraded, thus achieving wastewater treatment and reuse. Currently, health monitoring of mechanical transmission systems typically relies on installing vibration acceleration sensors and torque sensors in transmission gearboxes, bearing housings, and other parts to collect vibration and torque signals during operation for equipment fault diagnosis, such as determining bearing wear or abnormal gear meshing.

[0003] The closest existing technical solution to this invention is to manage the mechanical transmission system monitoring and the end-of-pipe wastewater biochemical treatment system as two completely independent subsystems. The mechanical transmission health monitoring system collects vibration and torque signals at a fixed sampling frequency, and determines whether there are potential faults in the equipment through threshold comparison or spectrum analysis. The output results are only used for equipment maintenance alarms and do not have any linkage with any downstream process links.

[0004] The wastewater biological treatment system is equipped with online monitoring instruments for chemical oxygen demand, pH, etc. at the effluent end of the biological treatment tank or the equalization tank. The operator or a simple proportional-integral-derivative feedback controller adjusts the functional microbial agent dosing pump and aerator air volume after the fact according to the current measured concentration value and preset rules. There is no data interaction or signal transmission relationship between the two systems. The load fluctuation information of the mechanical system is not used for prediction and intervention at the water pollution control and treatment end.

[0005] Because the existing mechanical transmission monitoring system only focuses on diagnosing equipment faults and has not established a mapping relationship between transmission load characteristics and pollutant concentrations in end-of-pipe wastewater, when a load transient in the transmission system causes an increase in adhesive extrusion, this information cannot be identified and transmitted to the downstream wastewater treatment process.

[0006] Because this information is not transmitted, the wastewater biological treatment system can only respond after the pollutants actually arrive and are detected by online instruments to have exceeded the concentration limit. At this time, the pollutants have already entered the biological treatment tank, causing the activated sludge and dedicated functional microorganisms to be directly exposed to a sudden high concentration of toxic load, resulting in inhibition or even irreversible inactivation. This leads to a sharp drop in the operating efficiency of the entire biological treatment system, seriously affecting the stability of wastewater treatment and its reuse in meeting standards. In addition, the existing technology regards the low-frequency vibration generated by the mechanical transmission system as only an energy loss that needs to be suppressed or consumed, without considering its resource utilization value under the condition of meeting the safety threshold. This results in the long-term waste of this mechanical energy, failing to form an energy coupling with the end-of-pipe water pollution control and treatment links, resulting in low overall system energy efficiency. Summary of the Invention

[0007] The technical problem to be solved by this invention is that during the production of industrial sound insulation composite panels, fluctuations in the operating conditions of the mechanical transmission system directly cause changes in the physical extrusion and volatilization of the adhesive on the panels, which in turn leads to drastic and unpredictable fluctuations in the toxicity concentration of resin pollutants in the final production wastewater.

[0008] The existing mechanical transmission assessment methods are independent and disconnected from the end-of-pipe wastewater biochemical treatment system. Mechanical monitoring only serves the health diagnosis of the equipment itself, and the wastewater biochemical treatment system can only respond passively and with a lag based on the actual measured concentration at the end. This results in high-concentration toxic wastewater directly impacting the biochemical tank without warning, causing large-scale poisoning and inactivation of dedicated functional microorganisms, and making the operation of the wastewater treatment and recycling system unstable.

[0009] Meanwhile, the low-frequency mechanical vibration energy generated during the operation of the heavy-duty transmission system of the sound insulation board has been wasted for a long time, failing to achieve synergistic utilization with the end-of-pipe water pollution control and treatment process.

[0010] To solve the above technical problems, the present invention provides a mechanical transmission optimization and evaluation method for industrial sound insulation composite panels. The overall technical solution includes: collecting vibration acceleration signals at the bearing housing of the transmission gearbox of a heavy-duty roller press and torque signals of the transmission shaft; extracting time-domain features and statistical features from the above signals; and combining them to form a mechanical load feature vector.

[0011] By combining convolutional neural networks and long short-term memory networks, a digital twin mapping prediction model is established between the mechanical load feature vector and the terminal wastewater toxicity load index after a delay through the pipeline network, so as to realize the advance prediction of wastewater toxicity load in future periods.

[0012] The predicted value is compared with the preset toxicity load safety threshold. If the threshold is exceeded, an early warning signal is output.

[0013] Based on the early warning signal, during the buffer time window of the equalization tank before the pollutants reach the biochemical treatment tank, the dosage of the dedicated functional microbial agent and the aeration ratio of the aerator are adjusted in a feedforward adaptive manner.

[0014] At the same time, the residual vibration energy of the mechanical transmission system is assessed for safety threshold. When it is determined to be within the safe redundancy range, the vibration energy is directed to the biochemical treatment tank through an acoustic waveguide, and converted into fluid mechanical disturbance, which is used to enhance the gas-liquid-solid three-phase mass transfer efficiency and promote the renewal and shedding of aging biofilm.

[0015] In addition, the actual effluent water quality indicators of the biochemical treatment system are fed back to the mapping prediction model, and the model parameters are periodically corrected to form a complete closed loop of perception, prediction, regulation and effect verification.

[0016] Correspondingly, the present invention also provides a mechanical transmission optimization and evaluation system for industrial sound insulation composite panels that implements the above method, including a mechanical transmission state sensing module, a digital twin mapping and early warning module, a biochemical system feedforward control execution module, and a vibration energy cross-system guidance module. The modules are interconnected through a data bus and control signal lines, and together they constitute a complete technical path from sensing to prediction, from prediction to control, and then from control to energy utilization.

[0017] Compared with the prior art, the beneficial effects of the present invention by adopting the above technical solution are as follows:

[0018] 1. This invention constructs a feedforward mapping prediction model between mechanical load characteristics and wastewater toxicity load, which can provide early warning before pollutants reach the biological treatment tank, avoid the biological system from being subjected to sudden toxic shocks, and thus improve the operational stability of wastewater treatment and reuse systems.

[0019] 2. This invention achieves precise on-demand allocation of biochemical treatment resources by adaptively adjusting the dosage and aeration ratio of dedicated functional microorganisms through feedforward, thereby reducing waste of chemicals and energy and improving the efficiency of water pollution control and treatment.

[0020] 3. This invention uses an acoustic waveguide to direct mechanical vibration energy within a safe threshold to a biochemical tank, thereby enhancing the gas-liquid-solid three-phase mass transfer efficiency and promoting the renewal and shedding of aging biofilms without significantly increasing additional energy consumption, thus realizing the cross-system resource reuse of mechanical waste energy. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the overall system architecture in an embodiment of the present invention;

[0022] Figure 2 This is a flowchart of the core algorithm in an embodiment of the present invention;

[0023] Figure 3 This is a schematic diagram of the vibration energy guiding structure in an embodiment of the present invention. Detailed Implementation

[0024] The following is in conjunction with the appendix Figure 1-3 The specific embodiments of the present invention will be further described below. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0025] The technical solution of the present invention will be further described in detail below with reference to specific embodiments, so that those skilled in the art can fully understand and implement the present invention.

[0026] The mechanical transmission optimization and evaluation method and system for industrial sound insulation composite panels provided by this invention are generally composed of four parts: a mechanical transmission state perception layer, a digital twin mapping and early warning layer, a biochemical system feedforward control execution layer, and a vibration energy cross-system guidance layer.

[0027] The mechanical transmission state sensing layer includes a vibration acceleration sensor installed on the bearing seat of the transmission gearbox of the heavy-duty roller press in the sound insulation board production line, a torque sensor installed on the transmission shaft, and a process data acquisition unit that collects process parameters such as roller pressing speed and hot pressing temperature. The output signals of the above three are uniformly integrated into the data bus and transmitted to the upper edge computing module. The vibration acceleration sensor collects the vibration acceleration signal in real time and records it as the vibration acceleration signal.

[0028] The torque sensor collects the torque signal of the drive shaft in real time and records it as the torque signal;

[0029] The process data acquisition unit synchronously records the current process parameters, including roller speed, hot pressing temperature, and designed adhesive application amount, to provide auxiliary working condition information for subsequent feature extraction and model training.

[0030] The digital twin mapping and early warning layer includes a feature extraction module for extracting time-frequency domain features from vibration and torque signals;

[0031] A mapping prediction model combining convolutional neural networks and long short-term memory networks is used to output predicted values ​​of future wastewater toxicity loads.

[0032] The system includes a toxicity warning and determination module, which compares the predicted value with a preset threshold and outputs a warning level signal. A feature extraction module calculates the root mean square value and kurtosis of the vibration acceleration signal within a sliding time window as time-domain features, and calculates the mean, variance, and volatility of the torque signal as statistical features. These features are combined to form a mechanical load feature vector, denoted as the feature vector, and denoted by the symbol... The root mean square value is calculated as follows:

[0033] ;

[0034] In the formula, It represents the root mean square value of the vibration signal, used to characterize the overall energy level of the vibration signal;

[0035] This indicates the total number of sampling points within the sliding window;

[0036] Indicates the first in the window One vibration acceleration sample value.

[0037] The kurtosis index is calculated as follows:

[0038] ;

[0039] In the formula, This represents the kurtosis value of the vibration signal, which is used to characterize the impact characteristics of the vibration signal. The higher the value, the more obvious the transient impact component in the signal.

[0040] This represents the mean value of the vibration acceleration samples within the window;

[0041] The meanings of the remaining symbols are the same as in the previous formula.

[0042] After feature extraction, mechanical load feature vector sequences from historical production cycles are collected. These sequences, along with wastewater toxicity load indicators (e.g., total phenol concentration, chemical oxygen demand) measured at corresponding times after pipeline delay, are used as label data to construct a training sample set. During training, a convolutional neural network is used to extract local correlation features from the feature vectors. A long short-term memory network is then used to model the temporal dependencies of the feature sequences. Supervised training of the model parameters yields a digital twin mapping prediction model. The inference relationship of this model can be expressed as:

[0043] ;

[0044] In the formula, Representing the model's prediction of the future Predicted values ​​of wastewater toxicity load at any given time;

[0045] Indicates the current The mechanical load feature vector at time t;

[0046] This represents the feature mapping function of a convolutional neural network;

[0047] Represents the set of parameters of a convolutional neural network;

[0048] A time-series modeling function representing a long short-term memory network;

[0049] The set of parameters representing a Long Short-Term Memory (LSTM) network;

[0050] This indicates the physical delay time of the pipeline network required for wastewater to travel from the production workshop to the biochemical treatment pond. This delay time can be obtained in advance by calibrating the actual process distance and flow rate of the plant's drainage pipeline network.

[0051] The mechanical load feature vectors collected and extracted in real time are input into the trained digital twin mapping prediction model to obtain the future... Predicted values ​​of wastewater toxicity load after the specified period ;

[0052] The toxicity warning and judgment module compares the predicted value with the preset toxicity load safety threshold. The comparison is performed. If the predicted value exceeds the threshold, a warning signal of the corresponding level is triggered and output to the feedforward control execution layer. If the predicted value does not exceed the threshold, the biochemical treatment pool continues to operate according to the baseline parameters.

[0053] The feedforward control execution layer of the biochemical system includes a regulating tank, which has a drainage delay buffer function;

[0054] Adaptive dosing pump for microbial agents;

[0055] Adjustable frequency aerator;

[0056] Biochemical treatment tank;

[0057] The controller, after processing the warning signal output by the toxicity warning judgment module, drives the adaptive dosing pump and the adjustable frequency aerator respectively. Before the pollutants reach the biological treatment tank, the buffer time window provided by the equalization tank is used to adjust the dosage and aeration ratio of the dedicated functional microbial agent in advance, thereby realizing the transformation of the biological system from passive response to active defense. The aeration air volume of the adjustable frequency aerator is adjusted by setting the current output air volume as the sum of the aerator's baseline operating air volume and the adjustment amount. The adjustment amount is the product of the preset proportional adjustment coefficient and the excess amount. The excess amount is the difference between the predicted wastewater toxicity load and the safe threshold for toxicity load, which can be specifically expressed as:

[0058] ;

[0059] In the formula, express The output air volume of the aerator is adjusted by feedforward at specific times;

[0060] This indicates the reference operating air volume of the aerator;

[0061] This represents the proportional adjustment coefficient, which is determined from historical calibration data;

[0062] and The meaning is the same as before. The dosage of the special functional microbial agent can adopt the same proportional control logic as the above-mentioned aeration air volume feedforward adjustment, that is, based on the baseline dosage of the agent, the adjustment amount is added in proportion to the excess amount. The formula will not be repeated here.

[0063] The vibration energy cross-system guidance layer includes a vibration safety threshold assessment module, which is used to assess the energy of measured vibration signals from mechanical transmission systems.

[0064] An acoustic waveguide, one end of which is connected to the vibration damping structure of the transmission gearbox, and the other end extends into the bottom of the biochemical treatment tank;

[0065] In addition to the fluid disturbance zone, the vibration safety threshold assessment module determines the residual usable vibration energy using the following method:

[0066] ;

[0067] In the formula, This indicates residual usable vibrational energy;

[0068] This represents the total measured vibration energy of the transmission system.

[0069] This indicates the threshold of vibration energy required to ensure the safe operation of the transmission system. When the residual usable vibration energy is greater than zero and lower than the upper limit of the rated conduction capacity of the acoustic waveguide, it is determined to be in a safe and exportable state. At this time, the vibration safety threshold assessment module triggers the acoustic waveguide to conduct this part of the residual vibration energy to the biochemical treatment tank in a directional manner. In the fluid disturbance zone, it is transformed into fluid mechanical disturbance, which is used to enhance the gas-liquid-solid three-phase mass transfer efficiency and promote the renewal and shedding of aging biofilm.

[0070] To achieve cross-system targeted guidance of mechanical vibration energy, the acoustic waveguide specifically includes a transmission gearbox vibration damping base;

[0071] The vibration pickup and coupling interface is fixedly connected to the vibration damping base and is used to couple the residual vibration energy of the transmission system into the waveguide.

[0072] The acoustic waveguide body has a closed internal cavity structure and is laid along the plant's pipe corridor to the vicinity of the biochemical treatment pool.

[0073] An energy regulating valve, located in the middle section of the waveguide body, is used to adjust the amount of vibration energy introduced into the biochemical treatment tank based on the vibration energy safety assessment results.

[0074] The terminal diffuser nozzle is installed at the bottom of the biochemical treatment tank to uniformly release the transmitted vibration energy into the water in the tank in the form of fluid mechanical disturbance. The vibration pickup and coupling interface is fixedly connected to the vibration damping base. The main body of the acoustic waveguide is a closed pipe structure laid along the pipe gallery. The energy regulating valve is set in the middle section of the pipe to regulate the amount of energy transmission. The terminal diffuser nozzle is fixedly installed at the bottom of the biochemical treatment tank. All components are connected in sequence to form a complete vibration energy transmission path from the transmission gearbox to the biochemical treatment tank. There are no moving parts in the transmission path that require additional power to drive. The vibration energy is transmitted along the closed pipe cavity in the form of elastic waves without changing the original power output relationship of the mechanical transmission system.

[0075] During actual operation, the controller also feeds back the actual effluent quality indicators of the biochemical treatment system, such as measured chemical oxygen demand and activated sludge concentration, to the digital twin mapping prediction model. The model parameters are then updated through online incremental learning. , Periodic corrections are made to form a complete technical closed loop, from mechanical state perception to toxicity prediction, then to feedforward control, and finally to treatment effect verification, so that the mapping prediction model can continuously optimize prediction accuracy as production conditions change.

[0076] As a specific embodiment, during a certain production shift, the roller pressure of an industrial sound insulation composite board production line increased due to the adjustment of the process cycle. The vibration acceleration sensor and torque sensor detected a significant increase in the root mean square value of vibration and the torque fluctuation rate, respectively. Based on this, the feature extraction module generated a corresponding mechanical load feature vector and input it into the mapping prediction model. The predicted value of future wastewater toxicity load output by the model exceeded the preset toxicity load safety threshold, and the toxicity early warning judgment module then output an early warning signal.

[0077] Within the buffer time window of the regulating tank before pollutants arrive at the biological treatment tank, the controller increases the dosage of the adaptive dosing pump for bacterial agents and adjusts the aeration volume of the adjustable frequency aerator. This ensures that the biological treatment tank is already in an enhanced treatment state when the pollutants actually arrive, thus preventing the specialized functional microorganisms from being subjected to sudden toxic shocks. At the same time, the vibration safety threshold assessment module determines that the residual usable vibration energy under this operating condition is within the safe redundancy range, triggering the acoustic waveguide to introduce this part of the vibration energy into the biological treatment tank, further enhancing the treatment effect.

[0078] As one of the alternative embodiments capable of achieving the objectives of the present invention, in scenarios where computing resources are limited or the accumulation of historical training data is restricted, the mapping prediction model combining a convolutional neural network and a long short-term memory network may not be adopted. Instead, a simplified empirical relationship established based on process mechanisms, combined with a historical operating condition hierarchical table lookup method, is used to divide the mechanical load characteristics into several grade intervals. A corresponding wastewater toxicity load compensation coefficient is pre-calibrated for each grade, and hierarchical switching of feedforward regulation parameters is performed accordingly. This alternative approach can also achieve the technical effect of judging the wastewater toxicity load in advance based on the mechanical load characteristics, and is suitable for small and medium-sized production enterprises with relatively stable production operating conditions.

[0079] As the second alternative embodiment capable of achieving the objectives of the present invention, under the condition that the layout of the pipe gallery in some plant areas is not convenient for directly laying acoustic wave conduits, a piezoelectric vibration energy harvesting device can be installed at the vibration damping base of the transmission gearbox to convert mechanical vibration energy into electric energy, which is used to drive the low-power stirring or aeration micro-power equipment supporting the biochemical treatment tank, thereby also realizing the resource conversion of mechanical waste energy to the improvement of biochemical treatment efficiency, as an effective supplement to the direct physical conduction scheme of the acoustic wave conduit.

[0080] Although the present invention is disclosed above with the preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible variations and modifications without departing from the spirit and scope of the present invention. Therefore, any modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for optimizing and evaluating the mechanical transmission of industrial sound-insulating composite panels, characterized in that, Includes the following steps: Collect vibration acceleration signals at the bearing housing of the transmission gearbox of the heavy-duty roller press in the industrial sound insulation composite board production line; Collect the torque signal of the transmission shaft that is matched with the transmission gearbox; The vibration acceleration signal is subjected to time-domain features within a sliding time window, and the torque signal is subjected to statistical features. The time-domain features and the statistical features are combined to form a mechanical load feature vector. The mechanical load feature vector of the historical period and the wastewater toxicity load index measured at the corresponding time after pipeline delay are used as training samples. A convolutional neural network is used to extract the local correlation features in the mechanical load feature vector, and a long short-term memory network is used to model the time dependency of the local correlation features to train a digital twin mapping prediction model. The mechanical load feature vector, which is collected and extracted in real time, is input into the digital twin mapping prediction model to obtain the predicted value of wastewater toxicity load at the corresponding time after the delay through the pipeline network. The predicted wastewater toxicity load is compared with a preset toxicity load safety threshold. When the predicted wastewater toxicity load exceeds the toxicity load safety threshold, an early warning signal is output. Energy assessment is performed on the measured vibration signal of the mechanical transmission system to obtain the residual usable vibration energy, which is the difference between the total vibration energy of the transmission system and the vibration energy threshold required to ensure the safe operation of the transmission system. When the residual available vibration energy is greater than zero and lower than the upper limit of the rated conduction capacity of the acoustic waveguide, it is determined to be in a safe and exportable state. The residual available vibration energy is then conducted to the biochemical treatment tank through the acoustic waveguide, where it is converted into fluid mechanical disturbance to enhance the gas-liquid-solid three-phase mass transfer efficiency.

2. The method according to claim 1, characterized in that, The extraction of time-domain features from the vibration acceleration signal within a sliding time window includes calculating the root mean square value and kurtosis value of the vibration acceleration signal; The extraction of statistical features from the torque signal includes calculating the mean, variance, and volatility of the torque signal.

3. The method according to claim 1, characterized in that, Also includes: Based on the warning signal, during the buffer time window of the regulating tank before the pollutants reach the biochemical treatment tank, the dosage of the dedicated functional microbial agent for the biochemical treatment tank and the aeration ratio of the aerator are adjusted forward.

4. The method according to claim 3, characterized in that, The feedforward adjustment of the aeration ratio of the aerator includes: setting the output air volume of the frequency-adjustable aerator at the current moment to be the sum of the reference operating air volume of the frequency-adjustable aerator and the adjustment amount, wherein the adjustment amount is the product of a preset proportional adjustment coefficient and an excess amount, and the excess amount is the difference between the predicted value of the wastewater toxicity load and the safe threshold value of the toxicity load.

5. The method according to claim 1, characterized in that, Also includes: Energy assessment is performed on the measured vibration signal of the mechanical transmission system to obtain the residual usable vibration energy, which is the difference between the total vibration energy of the transmission system and the vibration energy threshold required to ensure the safe operation of the transmission system. When the residual available vibration energy is greater than zero and lower than the upper limit of the rated conduction capacity of the acoustic waveguide, it is determined to be in a safe and exportable state.

6. The method according to claim 5, characterized in that, Also includes: When the state is determined to be safe and exportable, the residual available vibration energy is transmitted to the biochemical treatment tank through an acoustic waveguide, which is converted into fluid mechanical disturbance to enhance the gas-liquid-solid three-phase mass transfer efficiency and promote biofilm renewal and shedding.

7. The method according to claim 1, characterized in that, Also includes: The actual effluent water quality indicators of the biochemical treatment tank are fed back to the digital twin mapping prediction model, and the parameters of the digital twin mapping prediction model are periodically corrected.

8. A mechanical transmission optimization and evaluation system for industrial sound insulation composite panels, characterized in that, It includes a mechanical transmission state sensing module, a digital twin mapping and early warning module, a biochemical system feedforward regulation and execution module, and a vibration energy cross-system guidance module; The mechanical transmission state sensing module includes a vibration acceleration sensor mounted on the bearing housing of the transmission gearbox of the heavy-duty roller press, a torque sensor mounted on the transmission shaft, and a process data acquisition unit, used to acquire vibration acceleration signals, torque signals, and process parameters. The digital twin mapping and early warning module includes a feature extraction unit, a mapping prediction model, and a toxicity early warning determination unit. The feature extraction unit is used to extract mechanical load feature vectors based on the vibration acceleration signal and the torque signal. The mapping prediction model is used to predict future wastewater toxicity load based on the mechanical load feature vectors. The toxicity early warning determination unit is used to output early warning signals. The biochemical system feedforward control execution module includes an adjustment tank, an adaptive dosing pump for microbial agents, a frequency-adjustable aerator, a biochemical treatment tank, and a controller. The controller is used to drive the adaptive dosing pump for microbial agents and the frequency-adjustable aerator to adjust the operating parameters of the biochemical treatment tank according to the early warning signal. The vibration energy cross-system guidance module includes a vibration safety threshold assessment unit, an acoustic waveguide, and a fluid disturbance zone. One end of the acoustic waveguide is connected to the vibration damping structure of the transmission gearbox, and the other end extends into the biochemical treatment tank to guide residual vibration energy within a safe range into the biochemical treatment tank.

9. The system according to claim 8, characterized in that, The acoustic waveguide includes a transmission gearbox vibration damping base, a vibration pickup and coupling interface, an acoustic waveguide body, an energy regulating valve, and an end diffuser nozzle; The vibration pickup and coupling interface is fixedly connected to the vibration damping base and is used to couple the residual vibration energy of the transmission system into the acoustic waveguide body. The acoustic waveguide has a closed tubular structure inside and is laid along the plant's pipe corridor to the vicinity of the biochemical treatment pool. The energy regulating valve is located in the middle section of the acoustic waveguide body and is used to regulate the magnitude of the vibration energy introduced into the biochemical treatment tank. The terminal diffusion nozzle is installed at the bottom of the biochemical treatment tank to release the transmitted vibration energy into the water body in the form of hydromechanical disturbance.

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