Anti-scaling system of gasification furnace chilling ring and coal gasification system
By using an acoustic emission module to identify the scaling status and adjust the acoustic parameters in the quench ring of the gasifier, the scaling problem in the quench ring was solved, improving the safety and reliability of the coal gasification system.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-03
- Publication Date
- 2026-04-14
AI Technical Summary
The gasifier quench ring is prone to scaling under high temperature and high pressure, which leads to uneven distribution of quench water, increases the risk of burn-through of the downcomer, and reduces the operational safety of the coal gasification system.
An acoustic emission module is used to emit acoustic waves into the target area of the gasifier quench ring. The scaling status is identified by acoustic signature, and the acoustic emission parameters are adjusted to break up the aggregation of ash particles, form a continuous water film, and prevent scaling.
Reduce the scaling rate, ensure the formation of a continuous water film on the inner wall of the downcomer, improve the operational safety of the coal gasification system, and reduce unplanned shutdowns for maintenance.
Smart Images
Figure CN121852097A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of scaling prevention technology, and in particular to an anti-scaling system for a gasifier quench ring and a coal gasification system. Background Technology
[0002] The gasifier quench ring is a key safety component in the coal gasification system. Its core function is to evenly distribute quench water to the inner wall of the downcomer to form a continuous water film, thereby isolating the downcomer from the thermal shock of high-temperature gas and ash particles, and preventing the downcomer from being burned through due to overheating.
[0003] However, the gasifier quench ring consistently faces scaling problems during actual operation. The causes of scaling are mainly twofold: firstly, under high-temperature and high-pressure process conditions, ash particles easily adhere to and sinter on the surface of the gasifier quench ring, leading to scaling; secondly, when the quench water passes through the small holes, gaps, and flow channel turning points inside the gasifier quench ring, changes in flow state easily trigger particulate matter deposition, resulting in scaling.
[0004] Once scaling occurs, it directly disrupts the uniformity of the quench water distribution, causing the water film formed on the inner wall of the downcomer to become excessively thin or even disappear in some areas. This results in the downcomer section being subjected to abnormally high temperatures, potentially leading to serious accidents such as burn-through, and consequently reducing the operational safety of the coal gasification system.
[0005] Therefore, how to prevent scaling in the quench ring of the gasifier, thereby improving the operational safety of the coal gasification system, has become an urgent technical problem to be solved. Summary of the Invention
[0006] To address the aforementioned issues, this application provides an anti-scaling system for the quench ring of a gasifier and a coal gasification system, which can prevent scaling of the quench ring of the gasifier, thereby improving the operational safety of the coal gasification system.
[0007] The embodiments of this application disclose the following technical solutions: In a first aspect, this application discloses an anti-scaling system for the quench ring of a gasifier, the system comprising: a control module, an acoustic wave emitting module, and an acoustic wave acquisition module; the control module is communicatively connected to the acoustic wave emitting module and the acoustic wave acquisition module respectively. The acoustic wave emission module is used to emit acoustic waves with an anti-scaling effect into the target area of the gasifier quench ring; The acoustic wave acquisition module is used to acquire acoustic wave signals generated by the fluid flowing through the target area; The control module is used to determine the acoustic signature characteristics representing the scaling state based on the acoustic signal; input the acoustic signature characteristics into the scaling identification model to determine the scaling degree in the target area; and adjust the acoustic emission parameters of the acoustic emission module according to the scaling degree.
[0008] Optionally, the acoustic emission module includes a transducer module; the transducer module includes a transducer head made of a high-temperature and high-pressure resistant material; the transducer head is arranged at least at one of the outer wall of the distribution pipe box of the gasifier quench ring and the connection of the semi-ring pipe; the transducer module is used to convert electrical energy into directional acoustic energy to emit acoustic waves with anti-scaling effect to the target area of the gasifier quench ring.
[0009] Optionally, the acoustic wave emitting module also includes a power supply module; the power supply module uses an externally excited oscillating circuit and is powered by a hybrid power supply architecture consisting of a switching power supply circuit and a linear power supply circuit.
[0010] Optionally, the acoustic acquisition module includes an acoustic receiver; the acoustic receiver is arranged at least at one of the following locations: the outer wall of the distribution pipe box of the gasifier quench ring, the semi-ring pipe connection, and the outer wall of the downcomer; the acoustic receiver is used to acquire the acoustic signal generated by the fluid flowing through the target area.
[0011] Optionally, the acoustic wave acquisition module is specifically used to: acquire acoustic wave signals generated by the fluid flowing through the target area during the emission interval of the acoustic wave emitting module.
[0012] Optionally, the control module is specifically used for: performing pre-emphasis processing, noise reduction processing, and frame segmentation processing on the acoustic signal to obtain a processed signal set; performing fast Fourier transform on the signals in the processed signal set to obtain spectral morphology features; performing wavelet transform on the signals in the processed signal set to obtain time-frequency distribution features; performing Hilbert spectrum analysis on the signals or time-frequency distribution features in the processed signal set to obtain instantaneous energy features; and fusing the spectral morphology features, time-frequency distribution features, and instantaneous energy features to obtain voiceprint features.
[0013] Optionally, the acoustic emission parameters include output power; the degree of increase in output power is positively correlated with the degree of scaling.
[0014] Optionally, the acoustic emission parameters include the emission frequency; The control module is specifically used to adjust the emission frequency of the acoustic wave emission module according to the physical characteristics of the scale when the scale level is indicated as moderate or severe.
[0015] Secondly, this application discloses a coal gasification system, which includes an anti-scaling system for the gasifier quench ring as described in the first aspect.
[0016] Compared with the prior art, this application has the following beneficial effects: This application provides an anti-scaling system for the quench ring of a gasifier and a coal gasification system. This application uses a scaling identification model to perform real-time analysis of the acoustic signature characteristics of target areas prone to scaling. This allows for adjustment of the acoustic emission parameters of the acoustic emission module in the early stages of scaling, thereby disrupting the aggregation and adhesion of ash particles. This not only reduces the scaling rate but also ensures the formation of a continuous water film on the inner wall of the downcomer, thus improving the operational safety of the coal gasification system and reducing unplanned shutdown maintenance requirements. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 Signaling diagram of an anti-scaling system for a gasifier quench ring provided in this application embodiment; Figure 2 This is a schematic diagram of the structure of an ultrasonic generator provided in an embodiment of this application; Figure 3 A flowchart illustrating the determination of acoustic signature features characterizing scaling conditions is provided in an embodiment of this application. Figure 4 A flowchart illustrating a training model for scale recognition provided in an embodiment of this application. Detailed Implementation
[0019] As described earlier, the gasifier quench ring consistently faces scaling issues during actual operation. Scaling is primarily caused by two factors: firstly, under high-temperature and high-pressure conditions, ash particles easily adhere to and sinter on the surface of the gasifier quench ring, leading to scaling; secondly, when quench water passes through small holes, gaps, and flow channel bends within the gasifier quench ring, changes in flow patterns easily trigger particle deposition, resulting in scaling. Once scaling occurs, it directly disrupts the uniformity of quench water distribution, causing the water film formed on the inner wall of the downcomer to become excessively thin or even disappear. This means that the downcomer section will be subjected to abnormally high temperatures, potentially leading to serious accidents such as downcomer burn-through, thereby reducing the operational safety of the coal gasification system.
[0020] The inventors, through research, proposed an anti-scaling system for the quench ring of a gasifier and a coal gasification system. The anti-scaling system for the quench ring includes a control module, a sound wave emission module, and a sound wave acquisition module. The control module is communicatively connected to both the sound wave emission module and the sound wave acquisition module. The sound wave emission module emits sound waves with an anti-scaling effect towards the target area of the quench ring. The sound wave acquisition module acquires the sound wave signals generated by the fluid flowing through the target area. The control module determines the acoustic signature characteristics representing the scaling state based on the sound wave signals. The acoustic signature characteristics are input into a scaling identification model to determine the degree of scaling in the target area. The sound wave emission parameters of the sound wave emission module are adjusted according to the degree of scaling. This application uses a scaling identification model to perform real-time analysis of the acoustic signature characteristics of easily scaling target areas, enabling the adjustment of the sound wave emission parameters of the sound wave emission module in the early stages of scaling, thereby disrupting the aggregation and adhesion of ash particles. This not only reduces the scaling rate but also ensures the formation of a continuous water film on the inner wall of the downcomer, thus improving the operational safety of the coal gasification system and reducing unplanned shutdown maintenance requirements.
[0021] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.
[0022] See Figure 1 The figure is a signaling diagram of an anti-scaling system for a gasifier quench ring according to an embodiment of this application. The anti-scaling system 10 for the gasifier quench ring includes: an acoustic wave emitting module 101, an acoustic wave acquisition module 102, and a control module 103, wherein the control module 103 is communicatively connected to the acoustic wave emitting module 101 and the acoustic wave acquisition module 102, respectively.
[0023] The acoustic wave emitting module 101 can be a high-frequency acoustic wave generator or an ultrasonic wave generator. See also Figure 2 The figure is a schematic diagram of the structure of an ultrasonic generator provided in an embodiment of this application. Figure 2 As shown, the ultrasonic generator includes a power supply module, a control circuit module, and a transducer module, which together realize the efficient and controllable conversion of electrical energy into directional acoustic energy.
[0024] The power module uses an externally excited oscillator circuit as its core topology. Compared to a self-excited oscillator circuit, the externally excited oscillator circuit has higher output power stability and waveform purity, making it suitable for high-load industrial applications.
[0025] To optimize the power supply performance of the self-excited oscillator circuit, this application employs a switching power supply circuit and a linear power supply circuit as its power supply circuits. The switching power supply circuit improves the conversion efficiency of mains power to intermediate DC bus voltage, while the linear power supply circuit supports continuous and rapid changes in operating frequency. The power supply circuit achieves dual capabilities of wide-range power regulation (e.g., 200-600W) and wide-bandwidth rapid frequency switching (e.g., 20-100kHz). Furthermore, dynamic frequency adjustment effectively suppresses acoustic standing waves formed in complex flow channels due to fixed-frequency operation, thereby improving the uniformity and reliability of the acoustic anti-fouling effect.
[0026] The control circuit module integrates multiple safety protection mechanisms to ensure that the ultrasonic generator can operate safely and reliably under any abnormal conditions.
[0027] In one example, when the control circuit module determines that the ultrasonic generator is in an unloaded state (e.g., the transducer module is not properly connected or has become detached), it can actively trigger an audible and visual alarm and simultaneously perform a power cut-off operation to prevent the ultrasonic generator from being damaged due to the inability to release energy.
[0028] In another example, the control circuit module can also communicate with current sensors, voltage sensors, and temperature sensors to continuously acquire output current, bus voltage, and the temperature of critical power devices. When the real-time value of any parameter exceeds its corresponding preset safety threshold, the control circuit module will immediately trigger an audible and visual alarm and execute corresponding protection measures based on the specific over-limit parameter, such as dynamic current limiting, active voltage reduction, or immediate shutdown, thereby avoiding faults caused by overcurrent, overvoltage, or overheating.
[0029] The transducer head of the transducer module is made of Incoloy 825 alloy, which is resistant to high temperature and high pressure. It can stably withstand a system pressure of 6.5MPa and a continuous high temperature of 250℃, ensuring its long-term reliable operation in the harsh environment of the gasifier quench ring.
[0030] To optimize the anti-scaling effect of acoustic waves, transducer heads are typically positioned at least once in areas prone to scaling, such as the outer wall of the distribution pipe box of the gasifier quench ring and the connection of the semi-ring pipe, to achieve targeted coverage of acoustic energy. The transducer module is fixed by welding its base to the outer wall of the gasifier quench ring using pulsed arc welding, supplemented by a threaded base structure to prevent loosening caused by thermal vibration under high-temperature conditions. Furthermore, the sleeve of the transducer module is connected to the gasifier quench ring via circumferential welding, and heat sinks are added to reduce heat conduction from the wall to the transducer.
[0031] To ensure reliable sealing under high-temperature and high-pressure conditions, the interface between the transducer module and the gasifier quench ring features a multi-layered sealing structure: an internal sealing cavity filled with high-temperature resistant waveguide oil (such as silicone oil) to couple sound waves and aid heat dissipation; and an outer layer employing a dynamic seal combining a polytetrafluoroethylene (PTFE) slip ring and an austenitic stainless steel O-ring to achieve leak-free operation over long periods. Furthermore, the sealing gaskets are made of high-temperature resistant graphite composite material to withstand the high-pressure conditions between the quench ring and the support plate.
[0032] The acoustic acquisition module 102 can be an acoustic receiver. The acoustic receiver is typically located at at least one of the following critical locations: the outer wall of the distribution pipe box of the gasifier quench ring, the connection point of the semi-annular pipe, and the outer wall of the downcomer—locations prone to scaling or exhibiting significant flow characteristics. Furthermore, the installation location of the acoustic receiver needs to avoid fluid bends and non-metallic lining surfaces. Bends are prone to turbulence and additional vibration noise, while non-metallic materials have a strong absorption effect on sound waves; both of these factors interfere with the extraction of true scaling acoustic signatures.
[0033] In terms of mechanical installation, the acoustic receiver is rigidly connected to the wall of the gasifier quench ring via a threaded base. This method not only provides excellent vibration coupling, ensuring high-fidelity transmission of minute acoustic signals, but also significantly enhances connection stability and long-term reliability under high temperature, high pressure, and continuous vibration conditions, avoiding signal attenuation or monitoring failure due to loosening or displacement.
[0034] S101: The acoustic wave emitting module emits acoustic waves with an anti-scaling effect to the target area of the gasifier quench ring.
[0035] The principle behind the anti-scaling effect of sound waves is as follows: On the one hand, when sound waves propagate in a fluid, they cause periodic changes in the density of the local liquid, generating a large number of micron-sized cavitation bubbles. These bubbles oscillate violently under the influence of the sound field, grow, and eventually implode and collapse, generating localized high-temperature and high-pressure shock waves. The mechanical force generated in this process can destroy the aggregation and adhesion of ash particles. On the other hand, the radiation force and acoustic flow generated when sound waves propagate in a fluid can form a high-intensity shear flow field on the inner wall of the gasifier's quench ring and near the micropores, continuously scouring the surface and interfering with and hindering the aggregation and growth of ash, slag, crystals, and other scale particles.
[0036] In practical applications, the target area is usually selected from key parts with a high risk of scaling, such as one or more of the following: the outer wall of the distribution tube box of the gasifier quench ring, the connection of the semi-ring pipe, and the outer wall of the downcomer.
[0037] It should be noted that, to further optimize the uniformity and adaptability of the anti-scaling effect, multiple ultrasonic transducers with different frequencies can be set (e.g., 20kHz, 40kHz, and 60kHz respectively). Among them, low-frequency sound waves have high cavitation intensity and deep range of action, which is conducive to stripping thicker scale layers; high-frequency sound waves have good directionality and strong shearing effect, which is suitable for suppressing the initial deposition of fine particles.
[0038] S102: The acoustic wave acquisition module acquires the acoustic wave signals generated by the fluid flowing through the target area.
[0039] It should be noted that during the intervals between sound wave emission by the sound wave emitting module, the sound wave acquisition module acquires the sound wave signals generated by the fluid flowing through the target area. This is because if acquisition were performed simultaneously with sound wave emission, the high-intensity sound waves generated by the transducer module would mask the weak acoustic characteristics generated by the fluid itself and its structure, resulting in distorted sound wave signals.
[0040] S103: The control module determines the acoustic signature characteristics that characterize the scaling state based on the acoustic signal.
[0041] The acoustic wave signal acquired by the acoustic wave acquisition module is transmitted to the signal processing system built into the control module via a shielded high-frequency cable. The signal processing system digitizes the acoustic wave signal at a sampling frequency of not less than 40kHz, a setting that strictly follows the Nyquist sampling theorem.
[0042] See Figure 3 The figure is a flowchart illustrating how to determine acoustic signature features characterizing scaling conditions according to an embodiment of this application. The acoustic signature features characterizing scaling conditions can be determined through the following steps A1-A4: A1: The signal processing system performs noise reduction processing on the sound wave signal to obtain the first processed signal.
[0043] Signal processing systems utilize digital filters (such as bandpass filters) to filter out low-frequency mechanical vibration noise and specific high-frequency industrial interference that are unrelated to the scaling process, while retaining key frequency band signals that reflect the scaling state, thereby improving the signal-to-noise ratio of the signal.
[0044] A2: The signal processing system pre-emphasizes the first processed signal to obtain the second processed signal.
[0045] The pre-emphasis processing is achieved through a first-order high-pass digital filter, which aims to compensate for the high-frequency attenuation that naturally occurs during the generation and propagation of the sound wave signal, increase the proportion of high-frequency components, and make the signal spectrum flatter.
[0046] A3: The signal processing system performs frame-by-frame processing on the second processed signal to obtain a set of processed signals.
[0047] Frame segmentation refers to dividing a continuous, non-stationary second-processing signal into a series of segments (frames) using a windowing function (such as a Hamming window) to obtain a set of processed signals, so that stable spectral analysis can be performed on each segment.
[0048] A4: The multimodal signal analysis module performs multimodal time-frequency analysis on each frame of signal in the processed signal set to extract acoustic features that characterize the scaling state.
[0049] The signal processing system for the control signals transmits the processed signal set to the multimodal signal analysis module of the control module, which then performs subsequent steps: First, the multimodal signal analysis module performs a Fast Fourier Transform on each frame of the processed signal set, converting the signal from the time domain to the frequency domain to obtain the power spectrum. By analyzing the power spectrum, spectral characteristics such as the main resonant peak frequency, amplitude, bandwidth, and harmonic components can be obtained.
[0050] Next, the multimodal signal analysis module performs wavelet transform on each frame of signal in the processed signal set to obtain time-frequency distribution features such as wavelet packet node energy fraction and time-frequency plane entropy.
[0051] Subsequently, the multimodal signal analysis module performs Hilbert spectral analysis on the relevant frequency band components after wavelet decomposition or the original signal to obtain the Hilbert marginal spectrum. By analyzing the Hilbert marginal spectrum, instantaneous energy characteristics such as the mean instantaneous energy, fluctuation variance, and evolution trajectory complexity of a specific frequency band can be obtained.
[0052] Finally, the multimodal signal analysis module integrates the above-mentioned spectral morphology features, time-frequency distribution features, and instantaneous energy features to form a high-dimensional, multimodal acoustic signature characteristic of scaling.
[0053] S104: The control module inputs the acoustic signature features into the scaling identification model to determine the degree of scaling in the target area.
[0054] The control module inputs the voiceprint features into the trained scaling recognition model, which then automatically calculates and outputs the scaling level of the target area, including normal, slight, moderate, and severe. The scaling recognition model is a lightweight deep learning model.
[0055] See Figure 4 The figure is a flowchart illustrating a method for training a scale recognition model according to an embodiment of this application. The scale recognition model can be trained through the following steps B1-B2: B1: Obtain the sample dataset.
[0056] The sample dataset includes sample acoustic signature features collected under real or simulated working conditions, and corresponding labels for the actual degree of scaling (including normal, slight, moderate, and severe) calibrated by experiments or experts.
[0057] It should be noted that, in order to solve the problem of scarce labeled data in industrial scenarios, this application can use generative adversarial networks to learn the distribution pattern of sample voiceprint features and generate new sample voiceprint features, thereby augmenting the sample dataset.
[0058] It should also be noted that the sample dataset was obtained based on a sampling frequency of 40kHz or higher, which complies with the Nyquist sampling theorem and ensures the integrity of the acoustic information.
[0059] B2: Train a deep learning model based on the sample dataset to obtain a scale recognition model.
[0060] Using the sample voiceprint features from the sample dataset as input and the corresponding true scaling degree labels as output labels, a lightweight convolutional neural network is trained to obtain a scaling recognition model.
[0061] In one specific implementation, knowledge distillation techniques can be used to efficiently train lightweight deep learning models suitable for edge devices: First, a teacher model is trained based on the sample dataset. The output of the teacher model is not the degree of fouling, but rather a probability distribution of fouling degree (e.g., normal: 10%, mild: 72%, moderate: 17%, severe: 1%). This allows the teacher model to delve deeper into the complex nonlinear mapping relationship between sample voiceprint features and fouling degree.
[0062] Subsequently, using the teacher model as the knowledge source, a lightweight student model (i.e., the final deployed scaling identification model) is trained. The loss function of the student model is constructed as a multi-task objective, and the training objectives of the student model simultaneously include: minimizing the difference between the predicted results output by the student model and the true scaling severity labels, minimizing the difference between the predicted results output by the student model and the scaling severity probability distribution output by the teacher model, and minimizing the difference between the intermediate layer feature relationships of the student model and the teacher model. Through this joint optimization, the student model efficiently inherits the generalized knowledge and discrimination patterns extracted by the teacher model. Thus, knowledge distillation technology can greatly alleviate the dependence on large amounts of expensive and time-consuming manually labeled data, significantly reducing data preparation costs.
[0063] It should be noted that, to meet industrial requirements for real-time performance, reliability, and data security, the trained scale recognition model is typically deployed in on-site edge computing devices. Simultaneously, the cloud server continuously optimizes the model's parameters, enabling it to adapt to new operating conditions over time, maintaining and improving its accuracy and robustness.
[0064] S105: The control module adjusts the acoustic emission parameters of the acoustic emission module according to the degree of scaling.
[0065] In one specific implementation, the acoustic emission parameters include output power. For example, when the scaling level is normal, there is no need to adjust the acoustic emission parameters of the acoustic emission module. When the scaling level is light, the current output power is increased slightly (e.g., to 200W) to provide preventative acoustic energy and inhibit scale growth; when the scaling level is moderate, the current output power is increased significantly (e.g., to 400W) to remove the already attached soft scale layer by enhancing cavitation and shearing effects; when the scaling level is heavy, the maximum power (e.g., 600W) is activated for intensive treatment, aiming to slow the clogging process and buy time for planned maintenance.
[0066] In another specific implementation, the acoustic emission parameters include the emission frequency. For example, when the scaling is moderate or severe, the emission frequency of the acoustic emission module can be adjusted according to the physical characteristics of the scaling. For instance, by continuously or abruptly changing the emission frequency, the formation of standing waves in the sound field can be effectively disrupted, allowing the acoustic energy to be distributed more evenly within the cooling ring, avoiding dead zones in scaling prevention, and thus improving the overall scaling prevention effect.
[0067] It should be noted that the control module can also trigger alarm indications based on the degree of scaling. For example, when the scaling level is mild, an early warning can be issued and intervention suggestions can be provided (such as adjusting the acoustic power or water quality parameters).
[0068] In summary, this application provides an anti-scaling system for the quench ring of a gasifier. This application uses a scaling identification model to perform real-time analysis of the acoustic signature characteristics of target areas prone to scaling, enabling the adjustment of the acoustic emission parameters of the acoustic emission module in the early stages of scaling, thereby disrupting the aggregation and adhesion of ash particles. This not only reduces the scaling rate but also ensures the formation of a continuous water film on the inner wall of the downcomer, thus improving the operational safety of the coal gasification system and reducing unplanned shutdown maintenance requirements.
[0069] This application discloses a coal gasification system, which includes the aforementioned anti-scaling system for the quench ring of a gasifier, and has the beneficial effects of the aforementioned anti-scaling system for the quench ring of a gasifier.
[0070] It should be noted that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely exemplary forms of implementing the claims.
[0071] While several specific implementation details are included in the foregoing discussion, these should not be construed as limiting the scope of this application. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.
[0072] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.
Claims
1. A scaling prevention system for a gasifier quench ring, characterized in that, The system includes: a control module, a sound wave emitting module, and a sound wave acquisition module; the control module is communicatively connected to both the sound wave emitting module and the voiceprint acquisition module. The acoustic wave emitting module is used to emit acoustic waves with an anti-scaling effect toward the target area of the gasifier quench ring. The acoustic wave acquisition module is used to acquire acoustic wave signals generated by the fluid flowing through the target area; The control module is used to: determine acoustic signature features characterizing the scaling state based on the acoustic signal; input the acoustic signature features into the scaling identification model to determine the scaling degree of the target area; and adjust the acoustic emission parameters of the acoustic emission module according to the scaling degree.
2. The system according to claim 1, characterized in that, The acoustic wave emitting module includes a transducer module; the transducer module includes a transducer head made of high temperature and high pressure resistant material; the transducer head is arranged at least at one of the outer wall of the distribution pipe box and the connection of the semi-ring pipe of the gasifier quench ring; the transducer module is used to convert electrical energy into directional acoustic energy to emit acoustic waves with anti-scaling effect to the target area of the gasifier quench ring.
3. The system according to claim 2, characterized in that, The acoustic wave emitting module also includes a power supply module; the power supply module adopts an externally excited oscillation circuit and is powered by a hybrid power supply architecture consisting of a switching power supply circuit and a linear power supply circuit.
4. The system according to claim 1, characterized in that, The acoustic wave acquisition module includes an acoustic wave receiver; the acoustic wave receiver is arranged at least at one of the following locations: the outer wall of the distribution pipe box of the gasifier quench ring, the connection of the semi-ring pipe, and the outer wall of the downcomer; the acoustic wave receiver is used to acquire the acoustic wave signal generated by the fluid flowing through the target area.
5. The system according to claim 1, characterized in that, The acoustic wave acquisition module is specifically used to: acquire acoustic wave signals generated by the fluid flowing through the target area during the emission interval of the acoustic wave emitting module.
6. The system according to any one of claims 1-5, characterized in that, The control module is specifically used for: performing pre-emphasis processing, noise reduction processing, and frame segmentation processing on the acoustic signal to obtain a processed signal set; performing fast Fourier transform on the signals in the processed signal set to obtain spectral morphology features; performing wavelet transform on the signals in the processed signal set to obtain time-frequency distribution features; performing Hilbert spectrum analysis on the signals in the processed signal set or the time-frequency distribution features to obtain instantaneous energy features; and fusing the spectral morphology features, the time-frequency distribution features, and the instantaneous energy features to obtain the voiceprint features.
7. The system according to claim 1, characterized in that, The scale identification model was trained in the following manner: Obtain a sample dataset; the sample dataset includes sample voiceprint features and labels for the actual degree of scaling corresponding to the sample voiceprint features; Based on the sample dataset, a teacher model is trained; the teacher model is used to output the probability distribution of the degree of scaling. Using the teacher model as the knowledge source, a student model is trained through knowledge distillation. The student model is the scaling identification model. The training objectives of the student model include: minimizing the difference between the predicted result output by the student model and the actual scaling degree label, minimizing the difference between the predicted result output by the student model and the scaling degree probability distribution output by the teacher model, and minimizing the difference between the intermediate layer feature relationships between the student model and the teacher model.
8. The system according to claim 1, characterized in that, The acoustic emission parameters include output power; the degree of increase in output power is positively correlated with the degree of scaling.
9. The system according to claim 1, characterized in that, The acoustic wave emission parameters include the emission frequency; The control module is specifically used to adjust the emission frequency of the acoustic wave emission module according to the physical characteristics of the scale when the scale level is indicated as moderate or severe.
10. A coal gasification system, characterized in that, The coal gasification system includes an anti-scaling system for the gasifier quench ring as described in any one of claims 1-9.