Mechanical pressure gauge monitoring system and method

Abstract

The invention relates to the technical field of mechanical pressure gauge monitoring, and discloses a mechanical pressure gauge monitoring system and method, and the method comprises the steps: an interface end leakage monitoring mechanism of a monitoring unit carries out the protection and monitoring of an interface end; a mechanical pressure gauge interface end data acquisition module is used for collecting various data related to a pressure gauge interface end; a mechanical pressure gauge interface end data preprocessing module is used for preprocessing the data; a mechanical pressure gauge interface end data feature extraction module is used for extracting pressure features, vibration features and temperature features; the mechanical pressure gauge interface end leakage monitoring model training module is used for training the model, judging whether leakage exists or not, and classifying and identifying the leakage; and the real-time monitoring and early warning module inputs the data into a trained machine learning model, and the model outputs a prediction result. Various data related to the interface end of the pressure gauge are collected in real time, the leakage condition of the interface end can be monitored in real time and accurately recognized, and early warning is given out when leakage occurs.

Description

Technical Field

[0001] This application relates to the technical field of mechanical pressure gauge monitoring. More specifically, it relates to a mechanical pressure gauge monitoring system and method. Background Art

[0002] A mechanical pressure gauge is a sensor device used to measure the pressure of media such as liquids and gases. It converts the pressure of the measured medium into mechanical motion through a mechanical structure, and then uses mechanical principles or mechanical devices to convert this mechanical motion into pointer motion or digital display, thereby intuitively displaying the pressure value of the measured medium.

[0003] A mechanical pressure gauge usually consists of the following parts: a pressure measurement component, which is responsible for receiving the pressure of the measured medium and converting the pressure into mechanical motion. Common measurement components include bourdon tubes, pressure diaphragms, etc.; a mechanical transmission component, which transmits the mechanical motion of the pressure measurement component to the pointer or digital display device, usually realized through mechanical structures such as gears, connecting rods, and transmission shafts; a pointer or digital display device, which converts the mechanical motion into an intuitive pressure reading, usually a pointer type or digital type display; a housing and connectors, which protect the internal structure of the pressure gauge and at the same time provide an interface for connecting the measured medium. Common connection methods include threaded connection, flange connection, etc. The advantages of a mechanical pressure gauge include simple structure, high reliability, low usage cost, etc., and it is suitable for some occasions where the measurement accuracy requirement is not particularly high. However, it also has disadvantages such as low sensitivity and being easily affected by the external environment, and is not suitable for some measurement occasions with high precision requirements.

[0004] The prior art document with the publication number CN110779655A provides a mechanical pressure gauge monitoring system and method. By taking pictures of the displayed image on the mechanical water pressure gauge, the water pressure data on the water pressure gauge can be remotely obtained, improving the meter reading efficiency; the power supply module provides non-persistent electrical energy for the mechanical water pressure gauge, enabling the imaging device to take pictures of the mechanical water pressure gauge only during the preset monitoring period, which can improve the battery life of the water pressure monitoring system and reduce energy consumption.

[0005] Although the above prior art solutions can achieve relevant beneficial effects through the structures of the prior art, there are still the following defects; when this device is in use, since there will be a leakage problem at the interface end during the use of the mechanical pressure gauge, and since this device is not convenient for real-time monitoring of the leakage at the interface end, it is difficult to handle it in time when the interface end leaks, and the practicability is relatively low.

[0006] In view of this, we propose a mechanical pressure gauge monitoring system and method. Summary of the Invention

[0007] 1. Technical Problems to be Solved

[0008] The purpose of the present application is to provide a mechanical pressure gauge monitoring system and method, which solves the technical problems proposed in the above background art and realizes the technical effect of facilitating real-time monitoring of leakage at the interface end and timely handling when leakage occurs at the interface end.

[0009] 2. Technical solution

[0010] The embodiment of the present application provides a mechanical pressure gauge monitoring system and method, including: a protective shell, a pressure gauge main body, a protective cover, a connection end protection mechanism and a monitoring unit;

[0011] The pressure gauge main body is installed inside the protective shell, protective covers are rotatably connected and arranged on both sides of the protective shell, and a connection end protection mechanism is slidably matched and arranged at the bottom of the protective shell;

[0012] The monitoring unit includes an interface end leakage monitoring mechanism; an interface end leakage monitoring mechanism is slidably matched and arranged at the bottom of the protective shell.

[0013] The monitoring unit includes: a mechanical pressure gauge interface end data acquisition module, a real-time monitoring and early warning module, a mechanical pressure gauge interface end data preprocessing module, a mechanical pressure gauge interface end data feature extraction module, a mechanical pressure gauge interface end leakage monitoring model training module and an interface end leakage monitoring mechanism;

[0014] Mechanical pressure gauge interface end data acquisition module: Collect various data related to the pressure gauge interface end;

[0015] Mechanical pressure gauge interface end data preprocessing module: Perform preprocessing operations such as cleaning, denoising, and normalization on the collected data;

[0016] Mechanical pressure gauge interface end data feature extraction module: Extract key features of interface leakage from the preprocessed data;

[0017] Mechanical pressure gauge interface end leakage monitoring model training module: Use the extracted features to train a machine learning model, and the goal of the model is to predict whether leakage will occur at the interface end based on the input features;

[0018] Real-time monitoring and early warning module: Input the real-time collected data into the trained machine learning model, and the model will output a prediction result.

[0019] Interface end leakage monitoring mechanism: Monitor the mechanical pressure gauge interface end. Adopt advanced sensing technology and precision detection equipment to perceive the physical state of the interface end in real time. Transmit the collected real-time data to the data acquisition module to provide accurate and reliable data support for the entire monitoring system, ensuring that the system can timely and effectively detect and handle leakage problems at the interface end.

[0020] As an alternative solution to the technical solution of this application document, the mechanical pressure gauge interface end data acquisition module collects various data related to the pressure gauge interface end, including a pressure sensor, an on-line vibration monitor, and a temperature sensor; the collected data includes, but is not limited to, the pressure value, temperature, and vibration frequency of the interface end, etc.

[0021] Pressure sensor: It is used to measure the pressure received by the pressure gauge interface end, can detect the change of pressure, and convert the change into an electrical signal for output;

[0022] Temperature sensor: It is used to measure the temperature of the pressure gauge interface end, can monitor the change of temperature, and convert the change into an electrical signal for output.

[0023] On-line vibration monitor: Captures vibration information of the interface during operation through a vibration sensor, etc.

[0024] As an alternative solution to the technical solution of this application document, the mechanical pressure gauge interface end data preprocessing module performs preprocessing operations such as data cleaning, denoising, and normalization on the collected data. Data cleaning: Detects and corrects inaccurate, incomplete, or inapplicable parts in the data. For the data of the pressure gauge interface end, there may be incorrect measurement values, outliers, or missing values, which need to be processed by the data cleaning method of deleting outliers;

[0025] Denoising: During the data acquisition process, the data may be affected by environmental interference or the noise of the sensor itself, resulting in noise in the data. These interferences are removed from the data through the mean filtering method to retain the real signal;

[0026] Normalization: The data is scaled to a unified range through the Z-score standardization method to eliminate the dimensional and numerical range differences between different features. For the data of the pressure gauge interface end, such as pressure and temperature, they may have different numerical ranges and units and need to be normalized.

[0027] As an alternative solution to the technical solution of this application document, the mechanical pressure gauge interface end data feature extraction module extracts key features of interface leakage from the preprocessed data, including pressure features, vibration features, and temperature features;

[0028] Pressure feature: It includes the pressure change rate: calculates the change rate of pressure data, which can be used to capture sudden changes or fluctuations in pressure;

[0029] Temperature feature: It includes the temperature change rate: calculates the change rate of temperature data, which may be related to the temperature change caused by interface leakage.

[0030] As an alternative solution to the technical solution of this application document, the leakage monitoring model training module for the mechanical pressure gauge interface end uses the extracted temperature, pressure, vibration frequency, and vibration frequency fluctuation characteristics to train a machine learning model of a support vector machine. When training the model, data samples in normal and abnormal states are marked so that the model can distinguish between leakage and non-leakage states. The model determines whether there is leakage at the current pressure gauge interface end based on the input feature data and classifies and identifies it.

[0031] As an alternative solution to the technical solution of this application document, the real-time monitoring and warning module inputs the real-time collected data into the trained machine learning model. The model will output a prediction result. When the prediction result indicates that leakage may occur at the interface end, the system will issue a warning to remind the maintenance personnel to perform maintenance and handling in a timely manner, enabling real-time monitoring and accurate identification of the leakage situation at the interface end, reducing the workload and cost of manual inspections, and improving the reliability and safety of the equipment. When the prediction probability exceeds a pre-set threshold, the system determines that there is a high leakage risk at the interface end and immediately triggers a warning.

[0032] The present invention provides a method for monitoring a mechanical pressure gauge, including the following steps:

[0033] S1. The leakage monitoring mechanism 5 of the interface end of the monitoring unit protects and monitors the interface end of the mechanical pressure gauge;

[0034] S2. During the use of the mechanical pressure gauge, various data related to the interface end of the pressure gauge are collected through the data acquisition module of the mechanical pressure gauge interface end. Through the pressure sensor: used to measure the pressure received by the interface end of the pressure gauge, it can detect changes in pressure and convert the changes into electrical signals for output; through the temperature sensor: used to measure the temperature of the interface end of the pressure gauge, it can monitor changes in temperature and convert the changes into electrical signals for output;

[0035] S3. The data preprocessing module of the mechanical pressure gauge interface end performs preprocessing operations such as cleaning, denoising, and normalization on the collected data;

[0036] S4. Then the data feature extraction module of the mechanical pressure gauge interface end extracts the key features of interface leakage from the preprocessed data, including pressure features, vibration features, and temperature features;

[0037] S5. The leakage monitoring model training module for the mechanical pressure gauge interface end uses the extracted features to train a machine learning model of a support vector machine. When training the model, data samples in normal and abnormal states are marked so that the model can distinguish between leakage and non-leakage states. The model determines whether there is leakage at the current pressure gauge interface end based on the input feature data and classifies and identifies it;

[0038] S6. Then, the real-time monitoring and early warning module inputs the real-time collected data into the trained machine learning model, and the model outputs the prediction result. When the prediction result indicates that leakage may occur at the interface end, the system will issue an early warning to remind the maintenance personnel to perform maintenance and handling in a timely manner, enabling real-time monitoring and accurate identification of the leakage situation at the interface end, reducing the workload and cost of manual inspections, and improving the reliability and safety of the equipment.

[0039] 3. Beneficial Effects

[0040] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0041] 1. By collecting various data related to the interface end of the pressure gauge in real time in the present application, when the prediction result indicates that leakage may occur at the interface end, the system will issue an early warning to remind the maintenance personnel to perform maintenance and handling in a timely manner, enabling real-time monitoring and accurate identification of the leakage situation at the interface end, reducing the workload and cost of manual inspections, and improving the reliability and safety of the equipment.

[0042] 2. By setting up a leakage monitoring mechanism at the interface end, during the use of the mechanical pressure gauge, the monitoring cover is driven by a threaded rod at the interface end of the pressure gauge main body, and data is collected in real time by sensors. At the same time, by setting up a connection end protection mechanism, the protection sleeve is used to protect the interface end of the pressure gauge main body, avoiding damage to the thread teeth caused by external collisions during transportation and improving the protection effect.

[0043] 3. By setting up a protective shell, the protection of the pressure gauge main body is realized, avoiding pollution at the dial and affecting the real-time monitoring of the dial data. By setting up a protective cover, it is convenient to view the dial data, and at the same time, it is convenient to perform maintenance and adjustment on the pressure gauge main body, improving the practicability of the device. Brief Description of the Drawings

[0044] Figure 1 It is a schematic diagram of the monitoring unit structure of the mechanical pressure gauge monitoring system disclosed in a preferred embodiment of the present application;

[0045] Figure 2 It is a schematic diagram of the overall structure of the mechanical pressure gauge monitoring system disclosed in a preferred embodiment of the present application;

[0046] Figure 3 It is an unfolded schematic diagram of the protective cover structure of the mechanical pressure gauge monitoring system disclosed in a preferred embodiment of the present application;

[0047] Figure 4 It is an unfolded sectional view schematic diagram of the connection end protection mechanism and other structures of the mechanical pressure gauge monitoring system disclosed in a preferred embodiment of the present application;

[0048] Figure 5 Schematic diagram of the structural section expansion of the interface leakage monitoring mechanism of the mechanical pressure gauge monitoring system disclosed in a preferred embodiment of the present application;

[0049] Description of reference numerals in the figure: 1. Protective shell; 2. Pressure gauge main body; 3. Protective cover; 4. Connection end protection mechanism; 5. Interface end leakage monitoring mechanism; 301. Friction strip; 302. Spring; 401. Slide bar; 402. Slide block; 403. Connecting rod; 404. Tension spring; 405. Protective sleeve; 101. Chute; 501. Monitoring cover; 502. Rubber pad; 503. Slide sleeve; 504. Threaded rod; 505. Universal joint; 506. Knob. Specific embodiments

[0050] The present application will be further described in detail below with reference to the accompanying drawings of the specification.

[0051] Refer to Figure 1 and Figure 2 The present invention provides a mechanical pressure gauge monitoring system, including a protective shell 1, a pressure gauge main body 2, a protective cover 3, a connection end protection mechanism 4 and a monitoring unit;

[0052] The pressure gauge main body 2 is installed inside the protective shell 1, protective covers 3 are rotatably connected and arranged on both sides of the protective shell 1, and a connection end protection mechanism 4 is slidably matched and arranged at the bottom of the protective shell 1;

[0053] The monitoring unit includes an interface end leakage monitoring mechanism 5; an interface end leakage monitoring mechanism 5 is slidably matched and arranged at the bottom of the protective shell 1.

[0054] Refer to Figure 1 The monitoring unit includes: a mechanical pressure gauge interface end data acquisition module, a real-time monitoring and warning module, a mechanical pressure gauge interface end data preprocessing module, a mechanical pressure gauge interface end data feature extraction module, a mechanical pressure gauge interface end leakage monitoring model training module and an interface end leakage monitoring mechanism 5;

[0055] Mechanical pressure gauge interface end data acquisition module: Collect various data related to the pressure gauge interface end;

[0056] Mechanical pressure gauge interface end data preprocessing module: Perform preprocessing operations such as cleaning, denoising, and normalization on the collected data;

[0057] Mechanical pressure gauge interface end data feature extraction module: Extract key features of interface leakage from the preprocessed data;

[0058] Mechanical pressure gauge interface end leakage monitoring model training module: Use the extracted features to train a machine learning model, and the goal of the model is to predict whether there will be leakage at the interface end based on the input features;

[0059] Real-time monitoring and early warning module: Input the real-time collected data into the trained machine learning model, and the model will output the prediction result.

[0060] Leakage monitoring mechanism 5 for the interface end of the mechanical pressure gauge: Monitor the interface end of the mechanical pressure gauge. Adopt advanced sensing technology and precise detection equipment to perceive the physical state of the interface end in real time. Transmit the real-time data collected to the data acquisition module to provide accurate and reliable data support for the entire monitoring system, ensuring that the system can discover and handle the leakage problem at the interface end in a timely and effective manner.

[0061] Furthermore, the data acquisition module for the interface end of the mechanical pressure gauge collects various data related to the interface end of the pressure gauge, including pressure sensors, on-line vibration monitors, and temperature sensors; collect including but not limited to the pressure value, temperature, and vibration frequency of the interface end, etc. These data are the basis for subsequent analysis and judgment of whether there is a leakage risk at the interface end.

[0062] The pressure sensor is used to measure the pressure received by the interface end of the pressure gauge, can detect the change of pressure, and convert the change into an electrical signal for output;

[0063] The temperature sensor is used to measure the temperature of the interface end of the pressure gauge, can monitor the change of temperature, and convert the change into an electrical signal for output.

[0064] The on-line vibration monitor captures vibration information of the interface during operation through vibration sensors, etc.

[0065] The vibration sensor utilizes the characteristic that piezoelectric materials generate charges when subjected to vibration acceleration to convert vibration acceleration into an electrical signal. The on-line vibration monitor consists of multiple parts, including vibration sensors, signal conditioning circuits, data acquisition units, etc. The vibration sensor converts the vibration information of the interface end into weak electrical signals, and the signal conditioning circuit amplifies, filters, etc. these electrical signals to improve the quality and stability of the signals. The data acquisition unit samples the processed signals at a certain sampling frequency and transmits the collected data to the data acquisition module. By analyzing parameters such as vibration frequency and amplitude, it can be judged whether there are problems such as looseness and wear at the interface end, and these problems are often potential factors leading to leakage. For example, when the screws at the interface are loose, the vibration frequency and amplitude may change significantly, and the on-line vibration monitor can capture these abnormalities in time to provide a basis for early warning of leakage risk.

[0066] Furthermore, the data preprocessing module for the interface end of the mechanical pressure gauge performs preprocessing operations such as cleaning, denoising, and normalization on the collected data;

[0067] Data cleaning: Detect and correct inaccurate, incomplete, or inapplicable parts in the data. For the data at the pressure gauge interface end, there may be incorrect measurement values, outliers, or missing values, which need to be processed by the data cleaning method of removing outliers;

[0068] Denoising: During the data acquisition process, the data may be affected by environmental interference or noise from the sensor itself, resulting in noise in the data. Remove these interferences from the data through the mean filtering method to retain the true signal; By adopting advanced filtering algorithms such as Kalman filtering and wavelet denoising, reduce the impact of noise on the data to make the data clearer and more reliable.

[0069] Normalization: Scale the data to a unified range through the Z-score standardization method to eliminate the differences in dimension and numerical range between different features. For the data at the pressure gauge interface end, such as pressure and temperature, they may have different numerical ranges and units and need to be normalized.

[0070] Furthermore, the data feature extraction module at the mechanical pressure gauge interface end extracts the key features of interface leakage from the preprocessed data. The extracted features include pressure features, vibration features, and temperature features;

[0071] Pressure feature: It includes the pressure change rate. Calculate the change rate of pressure data, which can be used to capture sudden changes or fluctuations in pressure; The pressure change rate in the pressure feature is an important analysis index. During the actual operation process, the pressure borne by the mechanical pressure gauge interface end is not constant, but will fluctuate with the change of the system operation state. By calculating the change rate of pressure data, we can keenly capture any sudden changes or abnormal fluctuations in pressure. The calculation method of the pressure change rate is usually based on the ratio of the change amount of pressure value within a certain time interval to this time interval. When there is leakage at the interface end, the pressure will change significantly, and this change may be manifested as a sudden drop or rapid fluctuation of the pressure. Through the real-time monitoring and analysis of the pressure change rate, we can timely discover these abnormal situations. For example, in a steadily operating pipeline system, under normal circumstances, the pressure change rate should remain within a relatively small range. If it is suddenly detected that the pressure change rate rises significantly, this may mean that there is leakage at the interface, resulting in a rapid drop in pressure, thus triggering an abnormal fluctuation in the pressure change rate. This abnormal pressure change rate is an important signal of interface leakage, providing a key clue for subsequent risk assessment and fault diagnosis.

[0072] Calculate the pressure change rate according to the following formula:

[0073] R p =[ln(P i+1 ) - ln(P i )] / (△t压力 );where R p Represents the pressure change rate between two adjacent data points, which reflects the relative degree of pressure change within a specific time interval. This indicator can be used to observe the dynamic situation of pressure change in more detail and help determine whether the pressure at the interface is in a normal state. i Represents the value of the ith pressure data point, which is the pressure value of the mechanical pressure gauge interface measured at a certain moment. i+1 That is, the value of the i+1th pressure data point is the value immediately following P i The pressure value of the interface end measured at another moment later. By comparing P i+1 and P i The difference can be used to understand the change of pressure over time. ln is the natural logarithm function, and the natural logarithm of the pressure data is taken in the formula. 压力 Represents the time interval between two adjacent pressure data points. It is an important parameter to measure the speed of pressure change. By dividing the logarithmic change of pressure by the time interval, the relative rate of pressure change per unit time can be obtained.

[0074] Temperature characteristics: including the temperature change rate, the rate of change of the calculated temperature data, which may be related to the temperature change caused by the interface leakage. Under normal circumstances, the temperature of the interface end of the mechanical pressure gauge will remain in a relatively stable range. However, when the interface leaks, the heat exchange between the leaking medium and the surrounding environment will cause the interface end temperature to change. The temperature change rate is calculated in a similar way to the pressure change rate, which is based on the ratio of the change in temperature value within a certain time interval to the time interval. If there is a leak at the interface, the leakage of the leaking medium may take away heat, causing the interface end temperature to drop; or in some cases, the leaking medium reacts chemically with the surrounding material to generate heat, causing the interface end temperature to rise. Whether the temperature rises or falls, it will cause the temperature change rate to be abnormal. By monitoring and analyzing the temperature change rate, we can compare it with the temperature change rate during normal operation. If the temperature change rate is found to be beyond the normal range, it is necessary to further check whether there is a leakage problem at the interface. For example, in a high-temperature and high-pressure pipeline system, the normal temperature change rate at the interface is relatively stable. If the temperature change rate suddenly increases at a certain moment and other factors that may affect the temperature are eliminated, it is possible that leakage has occurred in the interface, causing the abnormal temperature change.

[0075] Calculate the temperature change rate according to the following formula:

[0076] R t ={sin[ln(T i+1 )]-sin[ln(T i )]} / (△t 温度 );where Rt represents the temperature change rate between two adjacent data points, which reflects the relative temperature change per unit time and is an important indicator for judging whether the temperature at the interface end is abnormal. T i represents the i-th temperature data point, which is the temperature value of the interface end of the mechanical pressure gauge measured at a specific moment. This value reflects the actual temperature state of the interface end at that moment. T i+1 is the (i + 1)-th temperature data point, which is the temperature value of the interface end measured at another moment immediately after T i After that, the temperature change trend over time can be calculated by comparison. sin is the sine function, which takes the sine value of the natural logarithm of the temperature data in the formula. ln is the natural logarithm function. △t 温度 represents the time interval between two adjacent temperature data points. It is an important parameter for measuring the speed of temperature change

[0077] Vibration characteristics: When the mechanical pressure gauge is working normally, its interface end will have a relatively stable vibration state. When the mechanical pressure gauge is in a normal working state, its interface end will maintain a relatively stable vibration state. This stable vibration is determined by the normal operation of the equipment and the working environment, and its vibration frequency, amplitude and other parameters fluctuate within a certain range. However, when potential problems such as loosening and wear occur at the interface, this stable vibration state will be broken and the vibration frequency will change significantly. For example, the loosening of the screw at the interface is a common problem. When the screw is loose, the connection at the interface becomes loose, and during the operation of the equipment, the connection will be subjected to greater impact force and vibration, resulting in increased vibration, and the vibration frequency may increase or show abnormal fluctuations. This change in vibration frequency is an important manifestation of potential problems at the interface. By collecting and analyzing vibration frequency information, we can use it as an important basis for judging whether the interface is working properly

[0078] Calculate the vibration frequency change rate between two adjacent data points according to the following formula:

[0079] R f =[arctan(f i+1 ) - arctan(f i )] / (△t 频率 ); R f represents the vibration frequency change rate between two adjacent data points. It is a key indicator for measuring the relative change degree of vibration frequency per unit time. Through this value, we can clearly understand the change trend of vibration frequency over time, and then judge whether the vibration state of the interface end is stable. f i represents the i-th vibration frequency data point. This is the vibration frequency value of the interface end of the mechanical pressure gauge measured at a specific moment, which reflects the actual vibration frequency situation of the interface end at that moment. f i+1is the i+1th vibration frequency data point. arctan is the inverse tangent function. △t 频率 Represents the time interval between two adjacent vibration frequency data points.

[0080] Calculate the vibration frequency fluctuation coefficient according to the following formula:

[0081] C f ={∑ n-1 j＝1 |Rf j / [(arctan(f i+1 )-arctan(f i ))]|} / (n-1); where C f It is the vibration frequency fluctuation coefficient, which is used to measure the overall fluctuation of the vibration frequency over a period of time. It comprehensively considers the vibration frequency change rate between multiple adjacent data points and can more comprehensively reflect the stability of the vibration frequency. f The larger the value of Rf, the more violent the fluctuation of the vibration frequency during this period, which means that the vibration state of the interface is more unstable. j It is the vibration frequency change rate between the jth adjacent data points calculated according to the vibration frequency change rate formula. It reflects the change of vibration frequency between each pair of adjacent moments and is an important basic data for calculating the vibration frequency fluctuation coefficient. n is the total number of vibration frequency data points obtained.

[0082] Furthermore, the mechanical pressure gauge interface leakage monitoring model training module uses the extracted temperature, pressure, vibration frequency and vibration frequency fluctuation features to train the support vector machine machine learning model. When training the model, the data samples of normal and abnormal states are marked so that the model can distinguish between leakage and non-leakage states. The model determines whether there is leakage at the current pressure gauge interface based on the input feature data, and classifies and identifies it. Leakage probability Y i The evaluation model is:

[0083] Y i =1 / [1+e (-Zi) ];Zi=w 0 +w 1 R p,i +w 2 R t,i +w 3 R f,i +w 4 C f,i ; In the formula, i represents the index of the sample, which is used to identify different samples. p,i Represents the pressure change rate of the i-th sample. t,i Represents the temperature change rate of the i-th sample. R f,i is the rate of change of the vibration frequency of the i-th sample.f,i represents the vibration frequency fluctuation coefficient of the i-th sample. w 0 is the bias term. Its role is to make a basic adjustment to the prediction result of the model, enabling the model to have reasonable outputs under different combinations of feature values, which helps the model better fit the data and improve prediction accuracy. W 1 is the weight corresponding to the pressure change rate. W 2 is the weight corresponding to the temperature change rate. W 3 is the weight corresponding to the vibration frequency change rate. W 4 is the weight corresponding to the vibration frequency fluctuation coefficient. Zi is an intermediate variable that synthesizes all the feature information of sample i. Through the action of weights, it linearly combines the impacts of different features on the prediction result.

[0084] Furthermore, the real-time monitoring and early warning module inputs the real-time collected data into the trained machine learning model. The model will output the prediction result. When the prediction result indicates that leakage may occur at the interface end, the system will issue an early warning to remind the maintenance personnel to conduct inspections and handling in a timely manner, enabling real-time monitoring and accurate identification of the leakage situation at the interface end, reducing the workload and cost of manual inspections, and improving the reliability and safety of the equipment. When the prediction probability exceeds a pre-set threshold (this threshold can be adjusted according to the actual situation and experience), the system determines that there is a high leakage risk at the interface end and immediately triggers an early warning. The forms of early warning signals are rich and diverse, aiming to ensure that the maintenance personnel can receive information in a timely and effective manner. Among them, the audible and visual alarm is the most intuitive way. By emitting a loud alarm sound and flashing lights, it attracts the attention of on-site personnel, enabling them to quickly detect potential problems. At the same time, the system will also send detailed early warning information to the relevant maintenance personnel through text messages, emails, etc. These messages not only include the prompt that leakage may occur at the interface end, but also attach specific location information, relevant feature data, and the predicted risk level and other detailed contents, so that the maintenance personnel can understand the situation in advance and make full preparations.

[0085] The present invention provides a mechanical pressure gauge monitoring method, including the following steps:

[0086] S1. The leakage monitoring mechanism 5 at the interface end of the monitoring unit protects and monitors the interface end of the mechanical pressure gauge;

[0087] S2. During the use of the mechanical pressure gauge, various data related to the interface end of the pressure gauge are collected through the data acquisition module at the interface end of the mechanical pressure gauge. The pressure received by the interface end of the pressure gauge is measured by the pressure sensor, and the change in pressure can be detected and converted into an electrical signal for output; the temperature of the interface end of the pressure gauge is measured by the temperature sensor, and the change in temperature can be monitored and converted into an electrical signal for output;

[0088] S3. Use the mechanical pressure gauge interface end data preprocessing module to perform preprocessing operations such as cleaning, denoising, and normalization on the collected data:

[0089] S4. Then, the mechanical pressure gauge interface end data feature extraction module extracts the key features of interface leakage from the preprocessed data, including pressure features and temperature features;

[0090] S5. Through the mechanical pressure gauge interface end leakage monitoring model training module, use the extracted features to train a machine learning model of support vector machine. When training the model, mark the data samples of normal and abnormal states so that the model can distinguish between leakage and non-leakage states. The model judges whether there is leakage at the current pressure gauge interface end according to the input feature data and classifies and identifies it;

[0091] S6. Then, the real-time monitoring and warning module inputs the real-time collected data into the trained machine learning model. The model will output the prediction result. When the prediction result indicates that leakage may occur at the interface end, the system will issue a warning to remind the maintenance personnel to perform maintenance and processing in time, which can realize the real-time monitoring and accurate identification of the leakage situation at the interface end, reduce the workload and cost of manual inspection, and improve the reliability and safety of the equipment.

[0092] Refer to Figure 3 , on the inner wall of one side of the protective cover 3 close to the protective shell 1, a friction strip 301 is slidably fitted. A plurality of springs 302 are connected between the friction strip 301 and the protective cover 3. The springs 302 generate frictional force on the friction strip 301, so that the protective cover 3 can maintain stability when it is closed and opened.

[0093] Refer to Figure 4 , the connection end protection mechanism 4 includes a sliding rod 401. The sliding rod 401 is slidably fitted with the inner wall of the chute 101 opened at the bottom end of the protective shell 1. The other end of the sliding rod 401 is fixedly connected with a slider 402. The outer wall of the slider 402 is slidably fitted with a connecting rod 403. A tension spring 404 is connected between the connecting rod 403 and the slider 402. A protective sleeve 405 is fixedly connected to the connecting rod 403. The protective sleeve 405 protects the interface end of the pressure gauge main body 2.

[0094] Refer to Figure 5 , the interface end leakage monitoring mechanism 5 includes a monitoring cover 501. A sensor is installed on the inner wall of the monitoring cover 501. A rubber pad 502 is connected to the bottom end of the monitoring cover 501. One end of the monitoring cover 501 is connected with a sliding sleeve 503. The sliding sleeve 503 is slidably and penetratingly fitted with the protective shell 1. A threaded rod 504 is threadedly connected to the inner wall of the sliding sleeve 503. The threaded rod 504 is connected with a universal joint 505. The other end of the universal joint 505 passes through the protective shell 1 and is connected with a knob 506. The rubber pad 502 realizes the sealing function.

[0095] The working principle of a mechanical pressure gauge monitoring system according to an embodiment of this application is as follows: When installing the pressure gauge main body 2, first pull down the protective sleeve 405 to remove the protective sleeve 405 from the interface end of the pressure gauge main body 2. Then push the sliding rod 401. Then, under the action of the tension spring 404, drive the protective sleeve 405 to move upward and retract. Then connect the interface end of the pressure gauge main body 2 to the position to be detected. Then rotate the knob 506, so that the knob 506 drives the threaded rod 504 connected to the universal joint 505 to rotate, which will drive the monitoring cover 501 connected to the sliding sleeve 503 to press around the interface end of the pressure gauge main body 2. When it is necessary to view the dial value of the pressure gauge main body 2, rotate the protective cover 3. Then the spring 302 will make the friction strip 301 contact the outer wall of the protective shell 1, so that the protective cover 3 remains in the open state;

[0096] Then, during the use of the mechanical pressure gauge, various data related to the pressure gauge interface end are collected through the mechanical pressure gauge interface end data acquisition module. The pressure received at the pressure gauge interface end is measured by the pressure sensor, and the change in pressure can be detected and converted into an electrical signal for output; the temperature at the pressure gauge interface end is measured by the temperature sensor, and the change in temperature can be monitored and converted into an electrical signal for output; the mechanical pressure gauge interface end data preprocessing module performs preprocessing operations such as cleaning, denoising, and normalization on the collected data; then the mechanical pressure gauge interface end data feature extraction module extracts the key features of interface leakage from the preprocessed data, including pressure features and temperature features; the mechanical pressure gauge interface end leakage monitoring model training module uses the extracted features to train a machine learning model of a support vector machine. When training the model, data samples in normal and abnormal states are marked so that the model can distinguish between leakage and non-leakage states. The model judges whether there is leakage at the current pressure gauge interface end according to the input feature data and classifies and identifies it; then the real-time monitoring and warning module inputs the real-time collected data into the trained machine learning model, and the model will output a prediction result. When the prediction result indicates that leakage may occur at the interface end, the system will issue a warning to remind the maintenance personnel to perform maintenance and processing in time, which can realize the real-time monitoring and accurate identification of the leakage situation at the interface end, reduce the workload and cost of manual inspection, and improve the reliability and safety of the equipment.

[0097] The present invention collects various data related to the interface end of the pressure gauge in real time. When the prediction result indicates that leakage may occur at the interface end, the system will issue a warning to remind the maintenance personnel to perform maintenance and handling in a timely manner, which can achieve real-time monitoring and accurate identification of the leakage situation at the interface end, reduce the workload and cost of manual inspection, and improve the reliability and safety of the equipment. By setting up a leakage monitoring mechanism at the interface end, during the use of the mechanical pressure gauge, the monitoring cover is driven by a threaded rod at the interface end of the pressure gauge main body, and data is collected in real time by sensors. At the same time, by setting up a protection mechanism for the connection end, the protection sleeve is used to protect the interface end of the pressure gauge main body, avoiding damage to the thread teeth caused by external collision during transportation and improving the protection effect. By setting up a protective shell, the protection of the pressure gauge main body is achieved, avoiding contamination of the dial and affecting the real-time monitoring of the dial data. By setting up a protective cover, it is convenient to view the dial data, and at the same time, it is convenient to perform maintenance and adjustment on the pressure gauge main body, improving the practicability of the device.

[0098] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A mechanical pressure gauge monitoring method, characterized in that: The following steps are involved: S1. When not in use, the interface end of the mechanical pressure gauge is protected by the connection end protection mechanism; when in use, the interface end leakage monitoring mechanism of the monitoring unit is used to protect and monitor the interface end of the mechanical pressure gauge; S2. During the use of the mechanical pressure gauge, various data related to the pressure gauge interface are collected through the mechanical pressure gauge interface data acquisition module; S3. Use the data preprocessing module at the interface of the mechanical pressure gauge to perform cleaning, denoising and normalization preprocessing operations on the collected data: S4, a data feature extraction module for the interface of a mechanical pressure gauge extracts key features of interface leakage from the preprocessed data, including pressure features, vibration features and temperature features; S5. The mechanical pressure gauge interface leakage monitoring model training module uses the extracted features to train the machine learning model of the support vector machine. When training the model, the data samples in normal and abnormal states are marked so that the model can distinguish between leakage and non-leakage states. The model determines whether there is leakage at the current pressure gauge interface based on the input feature data, and classifies and identifies it. S6. The real-time monitoring and early warning module inputs the real-time collected data into the trained machine learning model, and the model outputs the prediction results. When the prediction results indicate that leakage may occur at the interface, the system issues an early warning.

2. The mechanical pressure gauge monitoring method according to claim 1, characterized in that: The mechanical pressure gauge interface end data acquisition module includes a pressure sensor, an online vibration monitor and a temperature sensor; and collects various data related to the pressure gauge interface end, including the pressure value, temperature and vibration frequency data of the interface end.

3. The mechanical pressure gauge monitoring method according to claim 1, characterized in that: The mechanical pressure gauge interface data feature extraction module extracts key features of interface leakage from the preprocessed data, including pressure features, temperature features, vibration frequency change rate and vibration frequency fluctuation coefficient.

4. The mechanical pressure gauge monitoring method according to claim 3 is characterized in that: When extracting pressure features, the pressure change rate is calculated according to the following formula: R p =[ln(P i+1 )-ln(P i )] / (△t 压力 );where R p Represents the pressure change rate between two adjacent data points; P i Represents the value of the i-th pressure data point; P i+1 That is, the value of the i+1th pressure data point; ln is the natural logarithm function; △t 压力 Represents the time interval between two adjacent pressure data points.

5. The mechanical pressure gauge monitoring method according to claim 3, characterized in that: When extracting temperature features, the temperature change rate is calculated according to the following formula: R t ={sin[ln(T i+1 )]-sin[ln(T i )]} / (△t 温度 );where R t Indicates the temperature change rate between two adjacent data points; T i represents the i-th temperature data point; T i+1 That is, the i+1th temperature data point; sin is the sine function; ln is the natural logarithm function; △t 温度 Represents the time interval between two adjacent temperature data points.

6. The mechanical pressure gauge monitoring method according to claim 3, characterized in that: When extracting vibration features, the vibration frequency change rate between two adjacent data points is calculated according to the following formula: R f =[arctan(f i+1 )-arctan(f i )] / (△t 频率 );R f Represents the rate of change of vibration frequency between two adjacent data points; f i represents the i-th vibration frequency data point; f i+1 is the i+1th vibration frequency data point; arctan is the inverse tangent function; △t 频率 Represents the time interval between two adjacent vibration frequency data points; Calculate the vibration frequency fluctuation coefficient according to the following formula: C f ={∑ n-1 j＝1 |Rf j / [(arctan(f i+1 )-arctan(f i ))]|} / (n-1); where C f is the vibration frequency fluctuation coefficient; Rf j is the vibration frequency change rate between the jth adjacent data points calculated according to the vibration frequency change rate formula, and n is the total number of vibration frequency data points obtained.

7. The mechanical pressure gauge monitoring system and method according to claim 1, characterized in that: The mechanical pressure gauge interface leakage monitoring model training module uses the extracted features to train the support vector machine machine learning model. When training the model, the data samples in normal and abnormal states are marked so that the model can distinguish between leakage and non-leakage states. The model determines whether there is leakage at the current pressure gauge interface based on the input feature data, and classifies and identifies it: leakage probability Y i The evaluation model is: Y i =1 / [1+e (-Zi) ];Zi=w0+w1R p,i +w2R t,i +w3R f,i +w4C f,i ; In the formula, i represents the index of the sample; R p,i represents the pressure change rate of the i-th sample; R t,i represents the temperature change rate of the i-th sample; R f,i is the vibration frequency change rate of the i-th sample; C f,i represents the vibration frequency fluctuation coefficient of the i-th sample; w0 is the bias term; W1 is the weight corresponding to the pressure change rate; W2 is the weight corresponding to the temperature change rate; W3 is the weight corresponding to the vibration frequency change rate; W4 is the weight corresponding to the vibration frequency fluctuation coefficient; Zi is an intermediate variable.

8. The mechanical pressure gauge monitoring system and method according to claim 1, characterized in that: The connection end protection mechanism includes a sliding rod, which is slidably matched with the inner wall of a sliding groove opened at the bottom end of the protective shell. The other end of the sliding rod is connected and fixedly provided with a sliding block. The outer wall of the sliding block is slidably matched with a connecting rod. A tension spring is connected between the connecting rod and the sliding block, and a protective sleeve is fixedly connected to the connecting rod.

9. The mechanical pressure gauge monitoring system and method according to claim 1, characterized in that: The interface end leakage monitoring mechanism includes a monitoring cover, the inner wall of which is installed with a pressure sensor, an online vibration monitor and a temperature sensor, the bottom end of the monitoring cover is connected to a rubber pad, one end of the monitoring cover is connected to a sliding sleeve, the sliding sleeve and the protective shell are arranged to slide through, a threaded rod is threadedly connected to the inner wall of the sliding sleeve, the threaded rod is connected to a universal joint, and the other end of the universal joint passes through the protective shell and is connected to a knob.

10. A mechanical pressure gauge monitoring system, comprising: a protective shell, a pressure gauge body, a protective cover, a connection end protection mechanism and a monitoring unit; characterized in that: A pressure gauge body is installed in the protective shell, protective covers are rotatably connected on both sides of the protective shell, and a connection end protection mechanism is slidably provided at the bottom of the protective shell; The monitoring unit includes an interface leakage monitoring mechanism; the interface leakage monitoring mechanism is provided in a sliding manner at the bottom of the protective shell; The monitoring unit includes: a data acquisition module at the interface end of a mechanical pressure gauge, a real-time monitoring and early warning module, a data preprocessing module at the interface end of a mechanical pressure gauge, a data feature extraction module at the interface end of a mechanical pressure gauge, a leakage monitoring model training module at the interface end of a mechanical pressure gauge, and an interface end leakage monitoring mechanism; Mechanical pressure gauge interface data acquisition module: collects various data related to the pressure gauge interface; Mechanical pressure gauge interface data preprocessing module: performs cleaning, denoising and normalization preprocessing operations on the collected data; Mechanical pressure gauge interface data feature extraction module: extract key features of interface leakage from preprocessed data; Mechanical pressure gauge interface leakage monitoring model training module: Use the extracted features to train the machine learning model. The goal of the model is to predict whether the interface will leak based on the input features. Real-time monitoring and early warning module: inputs the real-time collected data into the trained machine learning model, and the model outputs the prediction results; Interface leakage monitoring mechanism: monitor the interface end of the mechanical pressure gauge.

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