A control method and device for safe transportation of a reactor vibration isolation device

Abstract

The present disclosure provides a control method and system for safe transportation of a reactor vibration reduction device, which comprises obtaining sensor information, operating parameters and environmental parameters of the reactor vibration reduction device in real time during transportation; judging whether an emergency has occurred or is about to occur based on at least the sensor information, and triggering a release mechanism to make the reactor vibration reduction device release from a transport tool when it is judged that an emergency has occurred or is about to occur; adjusting the trigger threshold and response time of the release mechanism based on the sensor information, operating parameters and environmental parameters of the reactor vibration reduction device after release. The present disclosure improves the safety of the reactor vibration reduction device during transportation through automatic judgment of emergency and fast release mechanism, and adjusts the trigger threshold and response time of the release mechanism to reduce the probability of false triggering events, maintains stability during normal transportation, does not trigger accidentally, and ensures the safety performance of transportation.

Description

Technical Field

[0001] This disclosure relates to the field of reactor vibration reduction and isolation system technology, and in particular to control methods and devices for the safe transportation of reactor vibration reduction and isolation devices. Background Technology

[0002] Reactor vibration damping and isolation devices are typically installed on transport vehicles using automated equipment. During transport, accidents or emergencies such as collisions or overturning may occur. In these situations, the reactor vibration damping and isolation devices must be able to quickly detach from the transport vehicle to prevent further damage. However, frequent detachment in non-emergency situations can also affect transport efficiency and device performance. Therefore, how to quickly and reliably detach in emergency situations while maintaining stability under normal conditions becomes a key problem that needs to be solved. Summary of the Invention

[0003] This disclosure aims to at least address the technical problem in the prior art of how to quickly and reliably detach in emergency situations while remaining stable under normal conditions.

[0004] Therefore, one objective of this disclosure is to provide a control method for the safe transportation of reactor vibration damping and isolation devices, which includes:

[0005] Real-time acquisition of sensor information, operating parameters, and environmental parameters of the reactor vibration reduction and isolation device during transportation;

[0006] At least based on the sensor information, it is determined whether an emergency has occurred or is about to occur. When it is determined that an emergency has occurred or is about to occur, the release mechanism is triggered to release the reactor vibration damping and isolation device from the vehicle.

[0007] Based on the sensor information, operating parameters, and environmental parameters after the reactor vibration reduction and isolation device is disengaged, the trigger threshold and response time of the disengagement mechanism are adjusted.

[0008] In some embodiments, determining whether an emergency has occurred or is about to occur based at least on the sensor information includes comparing the sensor information with a safety threshold to determine whether an emergency has occurred.

[0009] In some embodiments, the security threshold is determined in the following manner:

[0010] Based on the structural characteristics and material properties of the reactor vibration reduction and isolation device, the safety threshold is determined.

[0011] In some embodiments, the step of determining whether an emergency has occurred or is about to occur based at least on the sensor information further includes:

[0012] Based on the sensor information, the operating parameters, and the environmental parameters, characteristic factors for characterizing emergency situations are determined.

[0013] Based on the aforementioned characteristic factors, the probability of an impending emergency is determined;

[0014] When the probability exceeds a preset probability threshold, an emergency is determined to be imminent.

[0015] In some embodiments, after triggering the disengagement mechanism to disengage the reactor vibration damping and isolation device from the vehicle when an emergency is determined to have occurred or is about to occur, the method further includes:

[0016] Obtain sensor information after the reactor vibration reduction and isolation device is disconnected, and compare the sensor information after disconnection with the sensor information before disconnection;

[0017] Based on the comparison results, it is determined whether the reactor vibration reduction and isolation device has been damaged and a corresponding maintenance method is generated.

[0018] In some embodiments, adjusting the trigger threshold and response time of the disconnection mechanism based on sensor information, operating parameters, and environmental parameters after the reactor vibration damping and isolation device has disconnected includes:

[0019] Based on the sensor information, operating parameters, and environmental parameters after the reactor vibration reduction and isolation device is disconnected, the key parameters for the disconnection event are determined.

[0020] Based on the aforementioned key parameters, determine the correlation between the trigger threshold and response time of the detachment mechanism and the detachment frequency;

[0021] The trigger threshold of the escape mechanism is adjusted based on the correlation to reduce the probability of false triggering events.

[0022] In some embodiments, the sensor information includes at least one of vibration acceleration and impact acceleration.

[0023] One object of this disclosure is to provide a control device for the safe transportation of a reactor vibration damping and isolation device, comprising:

[0024] The acquisition module is used to acquire sensor information, operating parameters, and environmental parameters of the reactor vibration reduction and isolation device in real time during transportation.

[0025] The detachment module is used to determine, at least based on the sensor information, whether an emergency has occurred or is about to occur. When it is determined that an emergency has occurred or is about to occur, the detachment mechanism is triggered to detach the reactor vibration damping and isolation device from the vehicle.

[0026] The adjustment module is used to adjust the trigger threshold and response time of the disconnection mechanism based on the sensor information, operating parameters and environmental parameters after the reactor vibration reduction and isolation device is disconnected.

[0027] One object of this disclosure is to provide a storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described control method.

[0028] One object of this disclosure is to provide an electronic device, including at least a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-described control method when executing the computer program in the memory.

[0029] The control method and control device for safe transportation of reactor vibration reduction and isolation devices provided in this disclosure have the following beneficial effects:

[0030] The control method for safe transportation of the reactor vibration damping and isolation device has an automatic judgment and rapid release mechanism for emergencies, which improves the safety of the reactor vibration damping and isolation device during transportation, reduces the risk of damage caused by accidental impact or vibration, reduces unnecessary maintenance costs and time, and thus optimizes the overall transportation efficiency and device performance.

[0031] The control method for safe transportation of the reactor vibration reduction and isolation device reduces the probability of false triggering events by adjusting the trigger threshold of the release mechanism, maintaining stability during normal transportation and preventing accidental triggering due to vibration or other factors, thus ensuring the safety performance of transportation. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of this disclosure 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 recorded in this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a flowchart of the control method for safe transportation of the reactor vibration reduction and isolation device in the embodiments of this disclosure;

[0034] Figure 2 This is a flowchart of the control method for safe transportation of the reactor vibration reduction and isolation device in the embodiments of this disclosure;

[0035] Figure 3 This is a flowchart of the control method for safe transportation of the reactor vibration reduction and isolation device in the embodiments of this disclosure. Detailed Implementation

[0036] Various embodiments and features of this disclosure are described herein with reference to the accompanying drawings.

[0037] It should be understood that various modifications can be made to the embodiments described herein. Therefore, the above description should not be considered as limiting, but merely as an example of embodiments. Other modifications within the scope and spirit of this disclosure will be apparent to those skilled in the art.

[0038] The accompanying drawings, which are included in and form part of this specification, illustrate embodiments of the present disclosure and, together with the general description of the disclosure given above and the detailed description of the embodiments given below, serve to explain the principles of the disclosure.

[0039] These and other features of this disclosure will become apparent from the following description of preferred forms of embodiments given as non-limiting examples, with reference to the accompanying drawings.

[0040] It should also be understood that although this disclosure has been described with reference to some specific examples, many other equivalent forms of this disclosure can be definitively implemented by those skilled in the art, which have the features of the claims and are therefore within the scope of protection defined herein.

[0041] The above and other aspects, features and advantages of this disclosure will become more apparent when taken in conjunction with the accompanying drawings and in view of the following detailed description.

[0042] Specific embodiments of this disclosure are described thereafter with reference to the accompanying drawings; however, it should be understood that the claimed embodiments are merely examples of this disclosure, which may be implemented in various ways. Well-known and / or repeated functions and structures are not described in detail to avoid unnecessary or redundant details that could obscure this disclosure. Therefore, the specific structural and functional details claimed herein are not intended to be limiting, but merely to serve as the basis and representative basis for the claims to teach those skilled in the art to use this disclosure in a variety of substantially any suitable detailed structures.

[0043] The first embodiment of this disclosure provides a control method for the safe transportation of a reactor vibration damping and isolation device, such as... Figures 1-3 As shown, the control method for safe transportation of the reactor vibration damping and isolation device includes:

[0044] S1: Real-time acquisition of sensor information, operating parameters, and environmental parameters of the reactor vibration reduction and isolation device during transportation.

[0045] Specifically, multiple sensors are installed on the reactor vibration damping and isolation device to collect sensor information in real time during the device's transportation process. This sensor information includes vibration signals and impact signals. The amplitude of the vibration signal refers to the vibration acceleration, and the amplitude of the impact signal refers to the impact acceleration. After acquiring the sensor information, it is transmitted to the central processing unit for preprocessing (denoising and filtering). Preprocessing improves data quality and lays the foundation for subsequent analysis. By using sensors on the reactor vibration damping and isolation device to collect both vibration and impact signals, compared to collecting only vibration or only impact signals, the judgment results are more accurate in subsequent emergency situations.

[0046] Operating parameters refer to various data generated by the device during normal operation. These data reflect the device's working status, performance, and potential abnormalities. Operating parameters may include, but are not limited to, voltage, current, temperature, pressure, rotational speed, vibration frequency, load conditions, and power output.

[0047] Environmental parameters refer to changes in the external environment in which the device operates, which may affect the device's operating status and performance. Environmental factors may include, but are not limited to, temperature, humidity, dust, oil, electromagnetic interference, vibration, load changes, and power grid fluctuations.

[0048] For example, six triaxial accelerometers were installed on the reactor vibration damping and isolation device to collect vibration and impact signals. The sampling frequency was set to 1000Hz, and the data was transmitted to the central processing unit via an RS-485 bus. The central processing unit preprocessed the collected sensor information, using a 5th-order Butterworth low-pass filter with a cutoff frequency of 500Hz to remove high-frequency noise. Simultaneously, wavelet transform was used to denoise the data, employing the Daubechies 4 wavelet basis function with a decomposition level of 5, effectively eliminating impulse interference in the signal.

[0049] S2: At least based on sensor information, determine whether an emergency has occurred or is about to occur. When an emergency is determined to have occurred or is about to occur, trigger the release mechanism to release the reactor vibration damping and isolation device from the vehicle.

[0050] At least based on sensor information to determine whether an emergency has occurred or is about to occur, including comparing sensor information with safety thresholds to determine whether an emergency has occurred.

[0051] The safety threshold is determined in the following way:

[0052] Based on the structural characteristics and material properties of the reactor vibration reduction and isolation device, a safety threshold is determined.

[0053] Specifically, based on the structural characteristics and material properties of the reactor vibration reduction and isolation device, finite element analysis and modal analysis methods, combined with experimental data and theoretical calculations, are used to establish threshold models for vibration and shock signals, determining the normal operating range and threshold boundaries under abnormal conditions. In determining the safety threshold, factors such as the device's material properties, structural characteristics, and working environment are comprehensively considered, along with relevant industry standards and expert experience. This approach helps improve the accuracy of safety threshold setting and reduces the probability of false triggering events.

[0054] The safety threshold includes the vibration threshold and the impact threshold. The vibration threshold is the boundary value of vibration acceleration within the normal vibration range and under abnormal vibration conditions, while the impact threshold is the boundary value of impact acceleration within the normal impact range and under abnormal impact conditions.

[0055] During real-time monitoring, the threshold model and machine learning algorithm are continuously optimized, and model parameters are constantly updated and optimized through an adaptive learning mechanism. Based on newly acquired sensor information, the threshold model and machine learning algorithm are adjusted in real time using methods such as online learning or incremental learning, so that they can adapt to changes during the transportation of the reactor vibration reduction and isolation device, thereby improving the accuracy and reliability of anomaly detection.

[0056] In the application of Support Vector Machine (SVM) algorithms, by selecting appropriate algorithm types and adjusting algorithm parameters, such as the kernel function type of the SVM, the number of layers and nodes in the neural network, algorithm performance can be optimized, improving the accuracy and reliability of anomaly detection. If abnormal vibration or impact events are detected, the system automatically generates alarm information and transmits the alarm to the monitoring center and relevant personnel via wireless communication modules, enabling timely response measures. Monitoring data and analysis results are stored in a cloud database, using either a relational or non-relational database. In database design, a reasonable data table structure is designed, indexes are established, and query performance is optimized. Simultaneously, a data backup and recovery mechanism is established, with regular data backups to ensure data security and recoverability. By mining and analyzing the stored monitoring data, abnormal patterns and potential risks during the transportation of reactor vibration damping and isolation devices can be identified, providing data support for equipment maintenance and fault diagnosis.

[0057] During real-time monitoring, vibration and impact thresholds, as well as support vector machine algorithms, are continuously optimized. An adaptive learning mechanism is used to improve the accuracy and reliability of anomaly detection. Monitoring data and analysis results are stored in a cloud database.

[0058] For example, based on the finite element model of the reactor vibration reduction and isolation device, the first 10 natural frequencies and mode shapes were obtained through modal analysis. Combined with experimental data, threshold models for vibration and impact signals were established. During operation, the vibration threshold was set to 2g, and the impact threshold to 5g. A support vector machine (SVM) algorithm was used to analyze the processed sensor data in real time. A radial basis function kernel was selected, with a penalty factor C=10, kernel function parameter γ=0.1, 1000 training samples, and 500 test samples. The anomaly detection accuracy reached over 95%. When an abnormal vibration or impact event was detected, the system sent an alarm message via a wireless communication module. The alarm message included the event time, sensor location, maximum vibration acceleration, and maximum impact acceleration recorded during the entire monitoring period. Monitoring center personnel could quickly locate the problem and take countermeasures based on the alarm message. During monitoring, every hour, 100 newly collected samples were used to incrementally learn the threshold model and the SVM model, continuously optimizing the model parameters. Monitoring data and analysis results are stored in a MySQL relational database. The data tables are designed using a star schema, with time and sensor location as the primary keys and composite indexes to improve query efficiency. Additionally, data backups are performed daily at 2 AM, with backup files retaining the most recent month's data to ensure data security and recoverability.

[0059] Comparing sensor information with safety thresholds to determine if an emergency has occurred includes:

[0060] The preprocessed sensor information is compared with a safety threshold to determine if an emergency has occurred. If the sensor information exceeds the safety threshold, it is considered an emergency; if the sensor information does not exceed the safety threshold, it is considered a normal situation.

[0061] Specifically, after determining the safety threshold, the sensor information is compared with the safety threshold to determine whether an emergency has occurred.

[0062] Specifically, the support vector machine algorithm is used to analyze the preprocessed sensor data in real time. By comparing it with the vibration threshold and the impact threshold, it is determined whether the current vibration level and the impact level exceed the normal operating range of vibration and impact.

[0063] If the current sensor information indicates that the vibration level is within the normal operating range for vibration and the impact level is within the normal operating range for impact, the current transportation situation is considered normal.

[0064] If current sensor information indicates that the vibration level exceeds the normal operating range, or the impact level exceeds the normal operating range (i.e., the analysis results show that the maximum vibration acceleration exceeds the vibration threshold, or the maximum impact acceleration exceeds the impact threshold), the central control unit determines that an emergency has occurred. Specifically, when determining whether an emergency has occurred, if the peak vibration acceleration exceeds the vibration threshold, or the peak impact acceleration exceeds the impact threshold, it is determined that an emergency has occurred. Alternatively, if both the peak vibration acceleration and peak impact acceleration exceed the vibration threshold and the peak impact acceleration exceed the impact threshold, it is also determined that an emergency has occurred. This method compares sensor information with safety thresholds to determine if an emergency has occurred. If an emergency has occurred, the device is detached from the transport vehicle, improving the safety of the device during transportation.

[0065] By analyzing the relationship between preprocessed sensor information and safety thresholds, the current transportation status is determined to be normal. Furthermore, emergency judgment requirements can be designed as needed during the judgment process. By selecting appropriate algorithm types and adjusting algorithm parameters, such as the kernel function type of the Support Vector Machine (SVM), the number of layers and nodes in the neural network, algorithm performance is optimized, improving the accuracy and reliability of anomaly detection. Specifically, the SVM algorithm, by selecting appropriate kernel functions and adjusting parameters such as penalty factors, can find the optimal decision boundary in a high-dimensional feature space, accurately judging anomalies.

[0066] A high-dimensional feature space refers to mapping the original low-dimensional input data to a higher-dimensional space using specific mathematical transformations (usually kernel function tricks). The purpose of this transformation is to make data that was linearly inseparable in the low-dimensional space linearly separable in the high-dimensional space, thus simplifying the process of solving classification or regression problems. In short, a high-dimensional feature space is an abstract conceptual space that allows data to be more easily distinguished by a classifier in a new coordinate system. It is in this high-dimensional space that the Support Vector Machine (SVM) finds an optimal decision boundary, which can best separate data of different categories, even if these categories might overlap or be difficult to distinguish in the original data space.

[0067] At least based on sensor information to determine whether an emergency has occurred or is about to occur, it also includes:

[0068] S201: Based on sensor information, operating parameters, and environmental parameters, determine the characteristic factors used to characterize the emergency situation;

[0069] The massive historical data collected is preprocessed through data cleaning, denoising, and normalization to improve data quality and consistency. The data is then labeled according to the time points of the emergencies, forming a time-series sample set with emergency labels. Using signal processing techniques such as time-frequency analysis and wavelet transform, characteristic factors representing emergencies, such as vibration spectral entropy, impact response spectrum, and temperature rise rate, are extracted from the time-series sample data to construct an emergency feature vector.

[0070] S202: Determine the probability of an impending emergency based on characteristic factors;

[0071] The emergency feature vectors obtained in step S201 are used to train a support vector machine to construct an emergency prediction model, thereby determining the probability of an emergency.

[0072] In step S201, sensor information, operating parameters, environmental parameters, and feedback information from actual emergencies during device operation are continuously collected. The emergency prediction model is periodically retrained and optimized to continuously improve the accuracy and reliability of emergency prediction. The optimized model parameters are dynamically updated to the real-time monitoring system to achieve adaptive updating and continuous learning of the model.

[0073] S203: When the probability exceeds a preset probability threshold, an emergency situation is determined to occur.

[0074] By determining the probability of an emergency occurring, the system decides whether to trigger the escape mechanism and performs incremental training and parameter tuning on the emergency prediction model to continuously improve the accuracy and real-time performance of emergency prediction.

[0075] For example, the preset probability threshold is selected as 0.95. That is, when the predicted probability of an emergency exceeds 0.95, an alarm is triggered and an automatic detachment mechanism is started, while the detachment time and sensor information at the time of detachment are recorded.

[0076] There are two ways to trigger the release mechanism: one is when the sensor information reaches a safety threshold, and the other is to determine that an emergency is about to occur based on the sensor information. Executing the release mechanism in both ways helps to ensure the safe transportation performance of the reactor vibration reduction and isolation device.

[0077] Specifically, if an abnormal vibration or impact event is detected, i.e., an emergency situation determined by the central processing unit, the central processing unit triggers the rapid disengagement mechanism of the reactor vibration damping and isolation device. Since the reactor vibration damping and isolation device is connected to the vehicle via an electromagnet or a starting device, the rapid disengagement mechanism can quickly separate the reactor vibration damping and isolation device from the vehicle by controlling the electromagnet or pneumatic device on the reactor vibration damping and isolation device. After the reactor vibration damping and isolation device is disengaged, its built-in hydraulic buffer attenuates the impact force, ensuring the safe landing of the reactor vibration damping and isolation device.

[0078] After the reactor vibration damping and isolation device detaches from the transport vehicle, the buffer device will take effect, using springs or hydraulic buffers to reduce the impact force on the device and prevent secondary damage. For example, after the device detaches, the built-in hydraulic buffer will attenuate the impact force to below 500N within 10ms, ensuring the safe landing of the device.

[0079] When abnormal vibration or impact events are detected, the system sends alarm information through the wireless communication module. The alarm information includes the time of the event, the sensor location, the peak vibration acceleration or the peak impact acceleration, etc. The monitoring center personnel can quickly locate the problem and take countermeasures based on the alarm information.

[0080] While triggering an alarm, the system intelligently generates maintenance decision plans for the device based on the type and severity of the abnormal situation, combined with the damage level and the importance of the components. These plans include emergency shutdown, component replacement, and parameter adjustment, and are prioritized to guide maintenance personnel in quickly and efficiently eliminating potential device malfunctions and minimizing the impact of damage on device operation.

[0081] In S2, when an emergency is detected as having occurred or about to occur, the release mechanism is triggered, causing the reactor vibration damping and isolation device to detach from the vehicle. This also includes:

[0082] S204: Obtain sensor information after the reactor vibration damping and isolation device is disconnected, and compare the sensor information after disconnection with the sensor information before disconnection;

[0083] Specifically, after the reactor vibration damping and isolation device is detached from the transport vehicle, multiple sensors installed on the device immediately collect vibration and impact signals again. This newly collected sensor information is transmitted in real time to the central processing unit. The central processing unit preprocesses the received sensor information to obtain high-quality and reliable re-collected sensor information after noise reduction, filtering, and data synchronization. Based on the changes in vibration and impact signals before and after detachment, it determines whether the reactor vibration damping and isolation device has been damaged. If the mean, variance, or peak value of the vibration and impact signals changes abnormally after detachment (e.g., the peak vibration acceleration and peak impact acceleration exceed safety thresholds), it can be considered that the reactor vibration damping and isolation device was subjected to significant vibration and impact during the detachment process. By re-acquiring sensor information from the sensors installed on the device after detachment and comparing it with the sensor information before detachment, it is possible to determine whether the device has been damaged, providing a more convenient method for assessing the device's state after detachment.

[0084] S205: Based on the comparison results, determine whether the reactor vibration reduction and isolation device has been damaged and generate the corresponding maintenance method.

[0085] If the reactor vibration damping and isolation device is not damaged, reinstall the reactor vibration damping and isolation device onto the vehicle and continue the transportation process;

[0086] If the reactor vibration damping and isolation device is damaged, analyze the cause and record it in the cloud database.

[0087] Specifically, if the reactor vibration damping and isolation device is undamaged, the maintenance decision is to reinstall it. The central control unit generates a reinstallation command, and then uses automated equipment to dock and secure the device to the transport vehicle. Power and communication cables are reconnected, and the installation status of the device is monitored to ensure it can be put back into service. Furthermore, the data required for the reinstallation of the reactor vibration damping and isolation device, including docking position, fixing torque, and key connection parameters, is obtained and uploaded to a cloud database.

[0088] If the reactor's vibration damping and isolation device is damaged, the maintenance decision-making process marks it as a fault state, generates a maintenance task order, and generates a maintenance plan based on the re-collected sensor information, operating parameters, and environmental parameters, recording the maintenance data. Operating parameters refer to various data generated during the normal operation of the reactor's vibration damping and isolation device. These data reflect the device's working status, performance, and potential anomalies. Operating parameters may include, but are not limited to, voltage, current, temperature, pressure, speed, vibration frequency, load conditions, and output power. Environmental parameters refer to changes in the external environment in which the device is located. These changes may affect the device's operating status and performance. Environmental factors may include, but are not limited to, temperature, humidity, dust, oil, electromagnetic interference, vibration, load changes, and power grid fluctuations. Maintenance data includes, but is not limited to, fault phenomena and maintenance methods. Fault phenomena refer to the specific abnormal conditions exhibited by the equipment or device when a fault occurs. This includes, but is not limited to, abnormal sounds, vibrations, abnormal temperature increases, performance degradation, abnormal output, and system alarm prompts. Maintenance methods refer to the specific repair measures or processes taken for the identified fault phenomena. This includes, but is not limited to, the repair techniques used, the parts replaced, the parameter settings adjusted, and the test procedures implemented.

[0089] After the device is detached, it is determined whether it has been damaged and a corresponding maintenance method is generated, which improves the transportation efficiency and safety performance of the device during transportation.

[0090] For example, by collecting and analyzing vibration and impact data after the reactor vibration damping and isolation device is detached, machine learning algorithms and statistical models such as support vector machines and random forests are used to determine whether the reactor vibration damping and isolation device has been damaged, and different maintenance decision schemes are generated based on whether damage has occurred. If the device is undamaged, the central control unit generates a reinstallation command, and the device is precisely docked and fixed to the transport vehicle using automated equipment such as robotic arms or hydraulic devices. Power and communication cables are reconnected, and installation status is checked to ensure that the device can be reliably put back into use. After the device is reinstalled and passes the inspection, it can be put into normal transportation use, while its operating parameters and status data are continuously recorded and analyzed to assess the health status of the device. For example, the electromagnet's attraction force can reach 500N, and the pneumatic device's action time can be controlled within 0.5s, ensuring the speed and reliability of the detachment process.

[0091] If the device is confirmed to be damaged, the central control unit immediately marks the status as faulty and automatically generates a maintenance task order. The device is then quickly transported to a professional maintenance center via the logistics management system. Before the device is sent for maintenance, historical operating data is analyzed using techniques such as association rule mining and time-series pattern recognition to preliminarily determine the cause of the fault, providing direction for subsequent detailed diagnosis. During maintenance, the fault diagnosis system comprehensively analyzes multi-source heterogeneous data, including vibration and shock data, operating parameters, and environmental factors. Knowledge reasoning and deep learning algorithms, such as convolutional neural networks for feature extraction and fault mode recognition of vibration signals, and LSTM networks for modeling and prediction of time-series data, are used to accurately locate the cause of the fault and provide targeted maintenance solutions to guide maintenance personnel in carrying out their work efficiently. Simultaneously, key maintenance data, such as fault phenomena and maintenance methods, are recorded and collected, and fed back to the design and manufacturing departments to optimize the device's structural design and manufacturing processes, improving its reliability and stability. After the equipment maintenance is completed, augmented reality technology is used to overlay virtual information such as vibration spectrum diagrams and temperature distribution diagrams onto the physical equipment to achieve visualized display and real-time monitoring of performance parameters. Through human-computer interaction, it guides the testing personnel to conduct comprehensive testing and evaluation to ensure that all indicators of the equipment meet the factory standards, and generates test reports, which are then uploaded to the full life cycle management system.

[0092] Finally, based on the big data analysis platform, the operating parameters, environmental parameters, maintenance data, and performance testing data of the equipment are comprehensively mined and modeled to establish a health status assessment model and a remaining service life prediction model. Based on the assessment and prediction results of the models, maintenance strategies and management plans are dynamically optimized. For example, when the health status index of the equipment is lower than the preset threshold, maintenance alarms and work orders are automatically generated, and the priority and execution time of maintenance tasks are optimized according to the fault risk level and maintenance cost. Based on the prediction results of the remaining service life of the equipment, spare parts replacement plans and resource scheduling schemes are formulated in advance to maximize the availability and safety of the equipment and reduce transportation and maintenance costs.

[0093] S3: Based on the sensor information, operating parameters, and environmental parameters after the reactor vibration reduction and isolation device is disengaged, adjust the trigger threshold and response time of the disengagement mechanism.

[0094] Specifically, this includes S301: Based on sensor information, operating parameters, and environmental parameters after the reactor vibration reduction and isolation device has disengaged, determine the key parameters for the disengagement event.

[0095] Specifically, during the transportation of the reactor vibration reduction and isolation device, steps S1 and S2 are repeatedly repeated to continuously record sensor data, operating parameters, and environmental parameters related to device detachment events. This data is then uploaded to a cloud database for storage and management. Based on the sensor data, operating parameters, and environmental parameters of the detachment events, the detachment frequency, vibration acceleration at detachment, and impact acceleration are obtained through data cleaning, integration, and transformation, constructing a multidimensional dataset of detachment events. A multi-factor analysis of variance is used to obtain the relationship between the detachment frequency and operating and environmental parameters (such as vibration level, impact intensity, transportation conditions, and ambient temperature), identifying the factors with the greatest impact on detachment events, such as vibration level and impact intensity.

[0096] S302: Determine the correlation between the trigger threshold and response time of the detachment mechanism and the detachment frequency based on key parameters;

[0097] Specifically, based on the results of multi-factor analysis of variance, a model of device pull-out events is established to quantitatively describe the functional relationship between various influencing factors and the pull-out frequency. Using local sensitivity analysis, through techniques such as partial derivatives or finite differences, the sensitivity coefficients of the model output to each input parameter are calculated. The magnitude of these sensitivity coefficients reflects the importance of key sensitivity parameters such as the trigger threshold and response time of the pull-out mechanism; a higher sensitivity coefficient indicates a stronger correlation between the trigger threshold and response time of the pull-out mechanism and the pull-out frequency.

[0098] S303: Adjust the trigger threshold based on correlation to reduce the probability of false triggering events.

[0099] After completing step S302, a parameter optimization model is constructed, using the weighted sum of minimizing the expulsion frequency and false trigger rate as the objective function for multi-objective optimization. Constraints include an upper limit and a lower limit of the safety threshold, and a maximum allowable response time. Heuristic algorithms such as genetic algorithms and particle swarm optimization are used to solve the optimization model, obtaining the optimal combination of sensitivity parameters that satisfies the multi-objective requirements. This ensures safe and reliable expulsion while minimizing the probability of false trigger events. The optimized expulsion mechanism's sensitivity parameters are then sent to the device's control unit for adjustment.

[0100] The disconnection frequency refers to the number or frequency of times the reactor vibration damping and isolation device accidentally disconnects during transportation. This indicator directly reflects the stability and reliability of the device during transportation. An excessively high disconnection frequency not only affects transportation efficiency but may also damage the device itself. The false trigger rate refers to the probability that the device accidentally disconnects due to misjudgment or misoperation when it should not. False triggers may lead to unnecessary downtime, increased maintenance costs, and even affect the continuity and safety of transportation. Response time refers to the time required from when sensor information reaches the safety threshold to trigger the disconnection mechanism and complete the protective action (activating the buffer device). Shortening the response time can improve the protection efficiency of the device.

[0101] By setting quantitative evaluation indicators such as disconnection success rate, false trigger rate, and disconnection response time, the changes in these indicators before and after optimization are compared to assess the effectiveness and benefits of the optimization measures. A cost-benefit analysis is also conducted to balance the optimization inputs and returns. Simultaneously, through long-term operational monitoring and data analysis, the implementation status and long-term stability of the optimization measures are continuously tracked, and dynamic adjustments and improvements are made as needed. Based on a big data analysis platform for unit disconnection events, statistical reports on unit disconnection behavior are generated regularly, including disconnection frequency trends, changes in key influencing factors, and the effectiveness of optimization measures. This provides decision support for transportation management departments and continuously optimizes the unit disconnection mechanism to improve transportation efficiency and unit performance.

[0102] For example, during the transportation of the reactor vibration reduction and isolation device, data on the pull-out event is collected every 5 minutes, including pull-out time, GPS location, triaxial acceleration, impact force, etc. A four-factor analysis of variance was used to find that vibration level and impact intensity are the main effects affecting the pull-out frequency. The P-value of the interaction effect vibration × impact is 0.012, and the goodness of fit R² = 0.95.

[0103] A nonlinear regression model for the exit frequency was established, considering quadratic and cross terms. Ten model parameters were estimated using the gradient descent method, with a mean squared error (MSE) of 0.1. Sensitivity analysis was performed on the model, and the first-order partial derivatives were calculated. The sensitivity coefficients for vibration threshold, impact threshold, and response time were 0.6, 0.3, and 0.2, respectively.

[0104] A multi-objective genetic algorithm optimization model was constructed, with the objective function being 0.8 × elimination frequency + 0.2 × false trigger rate. The variable values ​​ranged from the trigger threshold ± 20%, the maximum response time was 2 seconds, the iterations were 500, the crossover probability was 0.6, and the mutation probability was 0.1, yielding the Pareto optimal solution set. A parameter combination that reduced the elimination frequency by 40% and the false trigger rate by 60% was selected and sent to the device controller.

[0105] After three months of operational testing, the average disconnection response time was reduced to 1.5 seconds, the reliable disconnection rate increased to 99.5%, the false trigger rate decreased to less than once per month, transportation efficiency improved by 20%, and the overall cost-effectiveness ratio reached 1:8. Quarterly disconnection event analysis reports are generated regularly to provide timely warnings of abnormal trends, continuously optimize the disconnection mechanism, and achieve full lifecycle health management of the equipment.

[0106] Based on the same inventive concept as the first embodiment described above, the second embodiment of this disclosure provides a safe transportation device for a reactor vibration damping and isolation device, comprising:

[0107] The acquisition module is used to acquire sensor information, operating parameters, and environmental parameters of the reactor vibration reduction and isolation device in real time during transportation.

[0108] The detachment module is used to determine, at least based on the sensor information, whether an emergency has occurred or is about to occur. When it is determined that an emergency has occurred or is about to occur, the detachment mechanism is triggered to detach the reactor vibration damping and isolation device from the vehicle.

[0109] The adjustment module is used to adjust the trigger threshold and response time of the disconnection mechanism based on the sensor information, operating parameters and environmental parameters after the reactor vibration reduction and isolation device is disconnected.

[0110] Furthermore, the escape module includes a safety threshold comparison module, which compares sensor information with a safety threshold to determine whether an emergency has occurred.

[0111] The release module includes a safety threshold determination module, which is used to determine the safety threshold based on the structural characteristics and material properties of the reactor vibration reduction and isolation device.

[0112] Furthermore, the escape module includes an emergency prediction module, used to determine whether an emergency has occurred or is about to occur based on the sensor information.

[0113] Furthermore, the emergency prediction module includes:

[0114] The feature factor determination module is used to determine the feature factors used to characterize an emergency situation based on sensor information, operating parameters, and environmental parameters.

[0115] The probability determination module is used to determine the probability of an impending emergency based on characteristic factors.

[0116] The emergency situation determination module compares the probability with a preset probability threshold. When the probability exceeds the preset probability threshold, it determines that an emergency situation is about to occur.

[0117] Furthermore, the decoupling module includes:

[0118] The comparison module is used to compare the sensor information after detachment with the sensor information before detachment;

[0119] The judgment module is used to determine whether the reactor vibration reduction and isolation device has been damaged based on the comparison results and generate the corresponding maintenance method.

[0120] Furthermore, the adjustment module includes:

[0121] The key parameter determination module is used to determine the key parameters for the occurrence of the disconnection event based on the sensor information, operating parameters and environmental parameters after the reactor vibration reduction and isolation device disconnects.

[0122] The correlation determination module is used to determine the correlation between the trigger threshold and response time of the escape mechanism and the escape frequency based on key parameters.

[0123] The trigger threshold adjustment module is used to adjust the trigger threshold of the exit mechanism based on correlation to reduce the probability of false triggering events.

[0124] This disclosure includes vibration and shock signal monitoring, automatic emergency judgment and rapid exit mechanism, damage assessment, optimization of the trigger threshold for the exit mechanism, and the establishment and application of an emergency prediction model. It improves the safety of reactor vibration damping and isolation devices during transportation, reduces the risk of damage caused by accidental impacts or vibrations, and reduces unnecessary maintenance costs and time. Simultaneously, through intelligent data analysis and emergency prediction models, it enhances the early warning capability and response speed to potential risks, thereby optimizing overall transportation efficiency and device performance.

[0125] Based on the same inventive concept as the first embodiment described above, the third embodiment of this disclosure provides a storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of the above-described control method, specifically including:

[0126] S11: Real-time acquisition of sensor information, operating parameters, and environmental parameters of the reactor vibration reduction and isolation device during transportation;

[0127] S12: At least based on sensor information, determine whether an emergency has occurred or is about to occur. When it is determined that an emergency has occurred or is about to occur, trigger the release mechanism to release the reactor vibration damping and isolation device from the vehicle.

[0128] S13: Based on the sensor information, operating parameters, and environmental parameters after the reactor vibration reduction and isolation device is disengaged, adjust the trigger threshold and response time of the disengagement mechanism.

[0129] Of course, it can also be used for other steps in the control method to implement the above implementation scheme.

[0130] This disclosure includes vibration and shock signal monitoring, automatic emergency judgment and rapid exit mechanism, damage assessment, optimization of the trigger threshold for the exit mechanism, and the establishment and application of an emergency prediction model. It improves the safety of reactor vibration damping and isolation devices during transportation, reduces the risk of damage caused by accidental impacts or vibrations, and reduces unnecessary maintenance costs and time. Simultaneously, through intelligent data analysis and emergency prediction models, it enhances the early warning capability and response speed to potential risks, thereby optimizing overall transportation efficiency and device performance.

[0131] Based on the same inventive concept as the first embodiment described above, the fourth embodiment of this disclosure proposes an electronic device, including at least a memory and a processor. The memory stores a computer program, and the processor, when executing the computer program in the memory, implements the steps of the aforementioned control method, specifically including:

[0132] S21: Real-time acquisition of sensor information, operating parameters, and environmental parameters of the reactor vibration reduction and isolation device during transportation;

[0133] S22: At least based on sensor information, determine whether an emergency has occurred or is about to occur. When it is determined that an emergency has occurred or is about to occur, trigger the release mechanism to release the reactor vibration damping and isolation device from the vehicle.

[0134] S23: Based on the sensor information, operating parameters, and environmental parameters after the reactor vibration reduction and isolation device is disengaged, adjust the trigger threshold and response time of the disengagement mechanism.

[0135] Of course, it can also be used for other steps in the control method to implement the above implementation scheme.

[0136] This disclosure includes vibration and shock signal monitoring, automatic emergency judgment and rapid exit mechanism, damage assessment, optimization of the trigger threshold for the exit mechanism, and the establishment and application of an emergency prediction model. It improves the safety of reactor vibration damping and isolation devices during transportation, reduces the risk of damage caused by accidental impacts or vibrations, and reduces unnecessary maintenance costs and time. Simultaneously, through intelligent data analysis and emergency prediction models, it enhances the early warning capability and response speed to potential risks, thereby optimizing overall transportation efficiency and device performance.

[0137] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0138] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0139] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0140] In the embodiments provided in this application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0141] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0142] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0143] If the integrated module is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various motor torque control method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0144] Furthermore, the features of the embodiments shown in the accompanying drawings or the various embodiments mentioned in this specification should not be construed as independent embodiments. Rather, each feature described in one example of an embodiment can be combined with one or more other desired features from other embodiments to produce other embodiments not described in words or with reference to the drawings.

[0145] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A control method for safe transport of a reactor vibration isolation device, characterized by, The application relates to a method for adjusting a trigger threshold and a response time of a disengagement mechanism of a reactor vibration isolation device, comprising the following steps: real-time acquisition of sensor information, operation parameters and environmental parameters of the reactor vibration isolation device during transportation; determination of whether an emergency situation has occurred or is about to occur based on at least the sensor information, and triggering of the disengagement mechanism to make the reactor vibration isolation device disengage from a carrier when it is determined that an emergency situation has occurred or is about to occur; adjustment of the trigger threshold and the response time of the disengagement mechanism based on sensor information, operation parameters and environmental parameters of the reactor vibration isolation device after disengagement, comprising the following steps: determination of key parameters of a disengagement event based on sensor information, operation parameters and environmental parameters of the reactor vibration isolation device after disengagement; determination of the correlation between the trigger threshold and the response time of the disengagement mechanism and a disengagement frequency based on the key parameters; wherein the disengagement frequency is the number or frequency of accidental disengagement of the reactor vibration isolation device during transportation; and the response time is the time required for triggering the disengagement mechanism and completing a protection action after the sensor information reaches a safety threshold; adjustment of the trigger threshold of the disengagement mechanism based on the correlation to reduce the probability of a false triggering event.

2. The control method of the safety transportation of the reactor isolation device according to claim 1, characterized in that, The determination of whether an emergency situation has occurred or is about to occur based on at least the sensor information comprises comparison of the sensor information with a safety threshold to determine whether an emergency situation has occurred.

3. The control method of the safety transportation of the reactor-decoupling device according to claim 2, characterized in that, The safety threshold is determined by the following method: determination of the safety threshold based on structural features and material properties of the reactor vibration isolation device.

4. The control method of the safety transportation of the reactor-decoupling device according to claim 1, characterized in that, The determination of whether an emergency situation has occurred or is about to occur based on at least the sensor information further comprises the following steps: determination of characteristic factors for representing an emergency situation based on the sensor information, the operation parameters and the environmental parameters; determination of the probability of an emergency situation based on the characteristic factors; determination of an emergency situation about to occur when the probability exceeds a preset probability threshold.

5. The control method of the safety transportation of the reactor-decoupling device according to claim 1, characterized in that, After the triggering of the disengagement mechanism to make the reactor vibration isolation device disengage from a carrier when it is determined that an emergency situation has occurred or is about to occur, the following steps are further included: acquisition of sensor information after disengagement of the reactor vibration isolation device, comparison of the sensor information after disengagement with sensor information before disengagement; determination of whether the reactor vibration isolation device is damaged based on the comparison result and generation of a corresponding maintenance mode.

6. The control method of the safety transportation of the reactor-decoupling device according to claim 1, characterized in that, The sensor information comprises at least one of vibration acceleration and impact acceleration.

7. A control device for safe transport of a reactor vibration isolation device, characterized in that The application relates to a method for adjusting a trigger threshold and a response time of a reactor vibration isolation device, comprising the following steps: a sensor information acquisition module for real-time acquisition of sensor information, operation parameters and environmental parameters of the reactor vibration isolation device during transportation; a disengagement module for determination of whether an emergency situation has occurred or is about to occur based on at least the sensor information, and triggering of the disengagement mechanism to make the reactor vibration isolation device disengage from a carrier when it is determined that an emergency situation has occurred or is about to occur; an adjustment module for adjustment of the trigger threshold and the response time of the disengagement mechanism based on sensor information, operation parameters and environmental parameters of the reactor vibration isolation device after disengagement; the adjustment module comprises a key parameter determination module configured to determine a key parameter of the escape event based on sensor information, operating parameters and environmental parameters after the reactor vibration isolation device is escaped; a correlation determination module configured to determine a correlation between a trigger threshold and a response time of the escape mechanism and an escape frequency, wherein the escape frequency is a number or frequency of the reactor vibration isolation device being accidentally escaped during transportation, and the response time is a time required for triggering the escape mechanism and completing a protection action after the sensor information reaches a safety threshold; a trigger threshold adjustment module configured to adjust the trigger threshold of the escape mechanism based on the correlation to reduce a probability of a false trigger event.

8. A storage medium storing a computer program, characterized by The computer program, when executed by a processor, implements the steps of the method of any one of claims 1 to 6.

9. An electronic device comprising at least a memory, a processor, said memory having stored thereon a computer program, characterized in that, The processor, when executing the computer program on the memory, implements the steps of the method of any one of claims 1 to 6.

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