A method and system for real-time monitoring of gas pressure in a diaphragm compressor

Abstract

This application relates to the field of monitoring and control technology, and discloses a method and system for real-time monitoring of gas pressure in a diaphragm compressor. The method includes: acquiring vibration signals from the diaphragm surface using a triaxial accelerometer to obtain vibration time-domain data; extracting the dominant frequency component, power spectral density value, and frequency band power spectral integral value using a fast Fourier transform to form vibration spectrum characteristics; calculating the real-time gas pressure feedback value by weighting the vibration characteristic parameters according to the correspondence between frequency and pressure; and automatically adjusting and controlling the pressure by setting upper and lower pressure limits, rate of change, and fluctuation adjustment thresholds, outputting a corresponding adjustment command when any threshold is exceeded. This application improves the accuracy and reliability of gas pressure monitoring in diaphragm compressors.

Description

Technical Field

[0001] This application relates to the field of monitoring and control technology, and in particular to a method and system for real-time monitoring of gas pressure in a diaphragm compressor. Background Technology

[0002] Diaphragm compressors, as important industrial compression equipment, are widely used in petrochemical, pharmaceutical, and food processing industries where high gas purity is required. In existing technologies, gas pressure monitoring for diaphragm compressors primarily employs direct measurement. This involves installing piezoresistive or capacitive pressure sensors on the compressor's inlet, outlet, or compression chamber. The sensors convert the pressure signal into an electrical signal, which is then conditioned and converted from analog to digital to obtain the final pressure value. This monitoring method uses a pressure threshold for simple alarm detection; when the detected pressure exceeds a preset range, an alarm signal is triggered. Traditional pressure monitoring systems also include data acquisition devices and monitoring software, capable of displaying pressure change curves in real time, recording historical data, and providing basic data analysis functions.

[0003] However, existing direct pressure measurement technologies have significant shortcomings. First, pressure sensors are prone to zero-point drift and sensitivity decay in the harsh operating environment of diaphragm compressors, especially under conditions of high temperature, strong vibration, and electromagnetic interference, making it difficult to guarantee the measurement accuracy and long-term stability of the sensors. Second, traditional monitoring systems have relatively slow response speeds and limited data acquisition frequencies, making it difficult to capture instantaneous pressure changes and abnormal fluctuations, potentially missing critical fault signs. Furthermore, existing technologies mainly rely on simple threshold judgments for fault identification, lacking in-depth analysis of pressure change trends and dynamic characteristics, thus failing to achieve accurate assessment of equipment operating status and fault prediction. Most importantly, pressure sensors directly installed in the gas circuit are susceptible to media corrosion and particulate contamination, resulting in high maintenance costs and limited service life. Summary of the Invention

[0004] This application provides a method and system for real-time monitoring of gas pressure in a diaphragm compressor, addressing the problems of poor sensor stability and low measurement accuracy in existing diaphragm compressor gas pressure monitoring methods under harsh operating environments. This improves the accuracy and reliability of gas pressure monitoring in diaphragm compressors.

[0005] In a first aspect, this application provides a method for real-time monitoring of gas pressure in a diaphragm compressor, the method comprising:

[0006] The vibration signal of the working diaphragm surface of the diaphragm compressor is acquired in real time by a triaxial accelerometer to obtain the time domain data of the diaphragm vibration.

[0007] Fast Fourier Transform is performed on the time-domain data of diaphragm vibration to extract the main frequency component of diaphragm vibration, the power spectral density value at the main frequency, and the power spectral integral value in a specific frequency band, forming the spectral characteristic parameters of diaphragm vibration.

[0008] Based on the correspondence between frequency and pressure in the diaphragm mechanical vibration theory, the main frequency component, power spectral density value and frequency band integral value in the diaphragm vibration spectrum characteristic parameters are weighted and calculated to obtain the real-time gas pressure feedback value currently acting on the diaphragm.

[0009] The system sets upper and lower pressure limit adjustment thresholds, pressure change rate adjustment thresholds, and pressure fluctuation adjustment thresholds to perform multi-level automatic adjustment and control on the real-time gas pressure feedback value. When any adjustment threshold is exceeded, the system outputs the corresponding pressure regulation and control command.

[0010] Optionally, the step of acquiring vibration signals from the working diaphragm surface of the diaphragm compressor in real time using a triaxial accelerometer to obtain diaphragm vibration time-domain data includes:

[0011] The triaxial accelerometer is installed by fixing it to the geometric center of the working diaphragm surface with adhesive, resulting in a rigid connection structure between the sensor and the working diaphragm.

[0012] Based on the rigid connection structure, the three-dimensional vibration acceleration of the working diaphragm surface is continuously detected and processed to obtain the original vibration signals in the X, Y, and Z directions;

[0013] The original vibration signal is input into a charge amplifier for signal amplification to obtain an amplified vibration signal.

[0014] The amplified vibration signal is processed by noise removal using a second-order Butterworth low-pass filter to obtain a purified vibration signal.

[0015] The purification vibration signal was processed by analog-to-digital conversion to obtain the diaphragm vibration time-domain data.

[0016] Optionally, the step of performing a Fast Fourier Transform on the diaphragm vibration time-domain data to extract the dominant frequency component of the diaphragm vibration, the power spectral density value at the dominant frequency, and the power spectral integral value within a specific frequency band, forming diaphragm vibration spectral characteristic parameters, including:

[0017] The time-domain data of diaphragm vibration was windowed using the Hanning window function to obtain windowed time-domain data with spectral leakage suppressed.

[0018] The windowed time-domain data is input into the Fast Fourier Transform algorithm for frequency domain transformation to obtain the power spectral density distribution;

[0019] Based on the peak detection algorithm, the power spectral density distribution is processed to identify the frequency components and obtain the main frequency components of diaphragm vibration.

[0020] The amplitude is extracted based on the corresponding position of the main frequency component in the power spectral density distribution to obtain the power spectral density value at the main frequency.

[0021] Numerical integration calculations are performed on the power spectral density distribution within a specific frequency band to obtain the frequency band integral value. The main frequency component, the power spectral density value at the main frequency, and the frequency band integral value are combined to form the diaphragm vibration spectrum characteristic parameters.

[0022] Optionally, the step of calculating the real-time gas pressure feedback value acting on the diaphragm by weighting the dominant frequency component, power spectral density value, and frequency band integral value in the diaphragm vibration spectrum characteristic parameters according to the correspondence between frequency and pressure in the diaphragm mechanical vibration theory includes:

[0023] The quadratic value of the main frequency component is obtained by squaring the main frequency component based on the diaphragm mechanical vibration theory.

[0024] The power spectral density value at the main frequency is input into a logarithmic transform function for quantization to obtain the logarithmic power spectral density value.

[0025] The frequency band integral value is numerically standardized using a normalization algorithm to obtain the standardized frequency band integral value;

[0026] Based on the weighting coefficients determined by the standard pressure source calibration experiment, the quadratic value of the main frequency component, the logarithmic value of the power spectral density, and the standardized frequency band integral value are linearly weighted to obtain the intermediate value of pressure calculation.

[0027] The intermediate pressure calculation value is corrected for temperature based on the temperature compensation coefficient to obtain the real-time gas pressure feedback value currently acting on the diaphragm.

[0028] Optionally, the setting of upper and lower pressure limit adjustment thresholds, pressure change rate adjustment thresholds, and pressure fluctuation adjustment thresholds allows for multi-level automatic adjustment and control of the real-time gas pressure feedback value. When any adjustment threshold is exceeded, a corresponding pressure regulation control command is output, including:

[0029] Threshold configuration is performed based on the working pressure range of the diaphragm compressor to obtain the absolute pressure control boundary.

[0030] The pressure change rate adjustment threshold is set according to the safe operation requirements of the diaphragm compressor, and the change rate is limited according to the pressure change rate adjustment threshold to obtain the pressure dynamic change control boundary.

[0031] The standard deviation is calculated based on multiple consecutive real-time gas pressure feedback values, and a pressure fluctuation adjustment threshold is set. The fluctuation amplitude is then limited according to the pressure fluctuation adjustment threshold to obtain the pressure stability control boundary.

[0032] The real-time gas pressure feedback value is input into a multi-level comparison and judgment algorithm to perform threshold over-limit detection processing, and the pressure state control judgment result is obtained.

[0033] Based on the pressure state control judgment result, control commands are generated and processed through a graded response strategy to obtain corresponding pressure regulation control commands. Specifically, when the pressure exceeds the absolute pressure control boundary, an emergency shutdown control command is output; when the pressure exceeds the dynamic pressure change control boundary, a pressure regulation device start control command is output; and when the pressure exceeds the pressure stability control boundary, a monitoring reminder control command is output.

[0034] Optionally, the step of inputting the real-time gas pressure feedback value into a multi-level comparison and judgment algorithm for threshold over-limit detection processing to obtain the pressure state control judgment result includes:

[0035] The real-time gas pressure feedback value is numerically compared with the pressure absolute value control boundary to obtain the pressure absolute value exceeding the limit judgment result.

[0036] The pressure change rate is calculated based on two consecutive real-time gas pressure feedback values ​​and compared with the pressure dynamic change control boundary to obtain the pressure change rate exceeding the limit judgment result.

[0037] The standard deviation is calculated based on multiple consecutive real-time gas pressure feedback values ​​and compared with the pressure stability control boundary to obtain the pressure fluctuation exceeding the limit judgment result.

[0038] The results of the pressure absolute value exceeding the limit judgment result, the pressure change rate exceeding the limit judgment result, and the pressure fluctuation exceeding the limit judgment result are logically combined to obtain a comprehensive anomaly judgment indicator.

[0039] Based on the type and degree of exceeding limits in the comprehensive anomaly judgment identifier, the pressure state control judgment result is obtained, which includes the anomaly type, anomaly degree, and response level.

[0040] Optionally, the step of logically combining the results of the pressure absolute value exceeding the limit judgment, the pressure change rate exceeding the limit judgment, and the pressure fluctuation exceeding the limit judgment to obtain a comprehensive anomaly judgment identifier includes:

[0041] The result of the pressure absolute value exceeding the limit is processed by logical state encoding to obtain the pressure absolute value abnormality flag bit, where the code is 01 when the upper limit threshold is exceeded, 10 when the lower limit threshold is exceeded, and 00 when the normal state is.

[0042] The results of the pressure change rate exceeding the limit are processed by logical state encoding to obtain the pressure change rate abnormality flag bit, where the code is 1 when the change rate exceeds the threshold and 0 when the normal state is.

[0043] The results of the pressure fluctuation exceeding the limit are processed by logical state encoding to obtain the pressure fluctuation abnormality flag bit, where the code is 1 when the fluctuation threshold is exceeded and 0 when the normal state is reached.

[0044] The absolute pressure value abnormality flag, the pressure change rate abnormality flag, and the pressure fluctuation abnormality flag are combined by bit operations to obtain a 4-bit binary abnormality status code.

[0045] Based on the 4-bit binary exception status code, the exception type is identified through the status mapping table to obtain a comprehensive exception judgment identifier that includes the exception type and severity.

[0046] Secondly, this application provides a real-time gas pressure monitoring system for a diaphragm compressor, the real-time gas pressure monitoring system for the diaphragm compressor comprising:

[0047] The scanning module is used to collect vibration signals from the working diaphragm surface of the diaphragm compressor in real time using a triaxial accelerometer to obtain time-domain data of diaphragm vibration.

[0048] The extraction module is used to perform fast Fourier transform processing on the diaphragm vibration time-domain data to extract the main frequency component of the diaphragm vibration, the power spectral density value at the main frequency, and the power spectral integral value in a specific frequency band, forming the diaphragm vibration spectral characteristic parameters.

[0049] The module is used to calculate the real-time gas pressure feedback value acting on the diaphragm by weighting the main frequency component, power spectral density value and frequency band integral value in the characteristic parameters of the diaphragm vibration spectrum according to the correspondence between frequency and pressure in the diaphragm mechanical vibration theory.

[0050] The control module is used to set the upper and lower pressure limit adjustment thresholds, the pressure change rate adjustment threshold, and the pressure fluctuation adjustment threshold. It performs multi-level automatic adjustment and control on the real-time gas pressure feedback value, and outputs the corresponding pressure regulation control command when any adjustment threshold is exceeded.

[0051] Thirdly, a real-time gas pressure monitoring device for a diaphragm compressor is provided, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor invokes the instructions in the memory to cause the real-time gas pressure monitoring device for the diaphragm compressor to execute the aforementioned real-time gas pressure monitoring method for the diaphragm compressor.

[0052] Fourthly, a computer-readable storage medium is provided, wherein instructions are stored therein, which, when executed on a computer, cause the computer to perform the above-described method for real-time monitoring of gas pressure of a diaphragm compressor.

[0053] The technical solution provided in this application innovatively transforms the pressure monitoring problem into a vibration signal analysis problem by acquiring the vibration signal of the working diaphragm surface of the diaphragm compressor in real time using a triaxial accelerometer, thus avoiding the stability issues of traditional pressure sensors in harsh environments. Fast Fourier Transform (FFT) processing is performed on the diaphragm vibration time-domain data to extract the dominant frequency component, power spectral density value at the dominant frequency, and power spectral integral value within a specific frequency band, forming diaphragm vibration spectral characteristic parameters. This fully utilizes the rich frequency domain information of the diaphragm vibration signal, resulting in higher information density and monitoring accuracy compared to traditional single-pressure numerical monitoring methods. Based on the correspondence between frequency and pressure in diaphragm mechanical vibration theory, the dominant frequency component, power spectral density value, and frequency band integral value in the diaphragm vibration spectral characteristic parameters are weighted and calculated to obtain the real-time gas pressure feedback value acting on the diaphragm. A pressure calculation method based on physical mechanisms is established, ensuring the accuracy and reliability of the monitoring results. By setting upper and lower pressure limit adjustment thresholds, pressure change rate adjustment thresholds, and pressure fluctuation adjustment thresholds, the real-time gas pressure feedback value is automatically adjusted and controlled at multiple levels. When any adjustment threshold is exceeded, a corresponding pressure adjustment control command is output, realizing the transformation from simple pressure monitoring to intelligent pressure control, which significantly improves the safety and stability of diaphragm compressor operation.

[0054] The Fast Fourier Transform (FFT) algorithm converts time-domain vibration signals into frequency-domain feature parameters. This not only extracts the dominant frequency component of diaphragm vibration, reflecting the main characteristics of pressure changes, but also obtains auxiliary feature parameters such as power spectral density and frequency band integral values, forming a multi-dimensional pressure characterization system. This algorithm effectively filters out random noise and interference components in the time-domain signal, highlighting useful signal features related to pressure changes. This makes the pressure calculation method based on the vibration spectrum highly resistant to interference and has high computational accuracy. Attached Figure Description

[0055] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 This is a schematic diagram of one embodiment of the real-time gas pressure monitoring method for a diaphragm compressor in this application.

[0057] Figure 2 This is a flowchart illustrating the anomaly detection process of the real-time gas pressure monitoring system for the diaphragm compressor in this embodiment of the application.

[0058] Figure 3This is a schematic diagram of one embodiment of the real-time gas pressure monitoring system for the diaphragm compressor in this application.

[0059] Figure 4 This is a schematic block diagram of the gas pressure real-time monitoring device for the diaphragm compressor in an embodiment of the present invention. Detailed Implementation

[0060] This application provides a method and system for real-time monitoring of gas pressure in a diaphragm compressor. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0061] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to [link / reference]. Figure 1 One embodiment of the real-time gas pressure monitoring method for diaphragm compressors in this application includes:

[0062] Step S101: The vibration signal of the working diaphragm surface of the diaphragm compressor is acquired in real time by a triaxial accelerometer to obtain the time domain data of diaphragm vibration;

[0063] Step S102: Perform fast Fourier transform processing on the diaphragm vibration time-domain data to extract the main frequency component of the diaphragm vibration, the power spectral density value at the main frequency, and the power spectral integral value in a specific frequency band, forming the diaphragm vibration spectral characteristic parameters.

[0064] Step S103: Based on the correspondence between frequency and pressure in the diaphragm mechanical vibration theory, the main frequency component, power spectral density value and frequency band integral value in the diaphragm vibration spectrum characteristic parameters are weighted and calculated to obtain the real-time gas pressure feedback value currently acting on the diaphragm.

[0065] Step S104: Set the upper and lower limit adjustment thresholds, the pressure change rate adjustment threshold, and the pressure fluctuation adjustment threshold to perform multi-level automatic adjustment and control on the real-time gas pressure feedback value. When any adjustment threshold is exceeded, the corresponding pressure adjustment control command is output.

[0066] It is understood that the executing entity of this application can be a real-time gas pressure monitoring system for a diaphragm compressor, or it can be a terminal or a server; no specific limitation is made here. This application's embodiment uses a server as an example for illustration.

[0067] Specifically, a triaxial accelerometer collects vibration signals from the working diaphragm surface of the diaphragm compressor, acquiring time-domain data of the diaphragm vibration. The time-domain data is processed using a Fast Fourier Transform (FFT) to obtain the frequency components and power spectral density values ​​of the diaphragm vibration. By integrating the power spectrum over a specific frequency band, diaphragm vibration spectral characteristic parameters are formed, providing a data foundation for subsequent analysis. These spectral characteristic parameters play a crucial role in gas pressure feedback calculations, enabling real-time monitoring of the diaphragm's operating status.

[0068] Based on the relationship between frequency and pressure in diaphragm mechanical vibration theory, the dominant frequency component, power spectral density value, and frequency band integral value in the spectral characteristic parameters are weighted and calculated to obtain the current gas pressure feedback value acting on the diaphragm. This pressure feedback value provides data support for real-time reflection of gas pressure during diaphragm operation, enabling real-time adjustment of the compressor's operating status. In practical applications, the real-time gas pressure feedback value can effectively avoid the impact of excessively large or small pressure fluctuations on the diaphragm, ensuring stable equipment operation.

[0069] The system sets upper and lower pressure limit adjustment thresholds, pressure change rate adjustment thresholds, and pressure fluctuation adjustment thresholds, and automatically adjusts and controls based on real-time gas pressure feedback values. When the pressure exceeds any adjustment threshold, the system automatically generates a pressure regulation control command to adjust the diaphragm's operating state. In practical applications, this control strategy ensures stable operation of the diaphragm compressor under different operating conditions, avoids equipment failure or performance degradation due to pressure fluctuations, and ensures that the pressure during operation remains within a safe and controllable range.

[0070] In this embodiment, a triaxial accelerometer is used to collect vibration signals from the working diaphragm surface of the diaphragm compressor in real time. The vibration signals are processed using a Fast Fourier Transform (FFT) to extract the dominant frequency component, power spectral density, and power spectral integral value of a specific frequency band, forming spectral characteristic parameters. By analyzing these spectral characteristic parameters and combining them with the relationship between frequency and pressure in diaphragm mechanical vibration theory, these parameters are weighted to obtain a real-time gas pressure feedback value. This feedback value reflects the changes in gas pressure during diaphragm operation, providing a basis for subsequent automatic adjustment and control. To ensure stable operation of the diaphragm compressor under various operating conditions, the system sets multiple pressure regulation thresholds, including upper and lower pressure limit adjustment thresholds, pressure change rate adjustment thresholds, and pressure fluctuation adjustment thresholds. When the real-time gas pressure feedback value exceeds any set threshold, the system automatically adjusts the operating state of the diaphragm compressor to ensure that the gas pressure remains within a safe and controllable range. This technical solution, through precise vibration signal acquisition and spectral analysis, as well as flexible automatic adjustment and control, not only improves the working efficiency of the diaphragm compressor but also extends the service life of the equipment and reduces equipment failures or efficiency declines caused by pressure fluctuations. Meanwhile, it adapts to various operating conditions, effectively improving the intelligence and automation of industrial equipment in practical applications. It is widely applicable to various equipment requiring precise pressure control, such as compressors and pumps. This technical solution provides an effective solution for the intelligent control of industrial equipment, promotes the development of automatic equipment adjustment technology, improves system safety and reliability, and meets the needs of modern industry for efficient and stable operating equipment.

[0071] In one specific embodiment, the process of performing step S101 may specifically include the following steps:

[0072] (1) The triaxial accelerometer is fixed to the geometric center of the working diaphragm surface with adhesive to obtain a rigid connection structure between the sensor and the working diaphragm.

[0073] (2) Based on the rigid connection structure, the three-dimensional vibration acceleration of the working diaphragm surface is continuously detected and processed to obtain the original vibration signals in the X, Y and Z directions;

[0074] (3) Input the original vibration signal into a charge amplifier for signal amplification to obtain an amplified vibration signal;

[0075] (4) The amplified vibration signal is filtered for noise by a second-order Butterworth low-pass filter to obtain a purified vibration signal;

[0076] (5) Perform analog-to-digital conversion on the purification vibration signal to obtain the diaphragm vibration time domain data.

[0077] Specifically, the triaxial accelerometer is fixed to the geometric center of the working diaphragm surface using an adhesive, ensuring a rigid connection between the sensor and the diaphragm. The adhesive can be one of epoxy resin, acrylic resin, or structural adhesive. This structural stability guarantees accurate transmission of the vibration signal, thus avoiding interference from external factors. Through this rigid connection, the sensor can continuously monitor the three-dimensional vibration acceleration of the diaphragm surface, acquiring the raw vibration signals in the X, Y, and Z directions, reflecting the vibration characteristics of the diaphragm in different directions.

[0078] The original vibration signal is amplified by a charge amplifier with a gain of 1000x. This gain ensures the signal is strong enough during processing, preventing data loss due to a weak signal. The amplified signal contains more vibration information, more accurately reflecting the diaphragm's operating state. The signal is then filtered for noise reduction using a second-order Butterworth low-pass filter with a cutoff frequency of 2500Hz. This effectively removes high-frequency noise while retaining crucial low-frequency signal components. The filtered signal has higher quality, ensuring the purity and accuracy of the vibration signal.

[0079] The purified vibration signal is converted using an analog-to-digital converter, with a sampling frequency set to 6000Hz to ensure sufficient data points are acquired per second to capture the details of diaphragm vibration. Within a 0.5-second time window, the system acquires 3000 sampling points, ensuring no vibration information is missed and improving data timeliness and accuracy. The diaphragm vibration time-domain data obtained through this processing accurately reflects the actual state of the diaphragm during operation, ensuring the control system can adjust and provide effective gas pressure values ​​in real time, thereby achieving precise control of the compressor system.

[0080] In one specific embodiment, the process of performing step S102 may specifically include the following steps:

[0081] (1) The diaphragm vibration time-domain data is windowed using the Hanning window function to obtain windowed time-domain data with spectral leakage suppressed;

[0082] (2) Input the windowed time-domain data into the fast Fourier transform algorithm for frequency domain transformation to obtain the power spectral density distribution;

[0083] (3) Based on the peak detection algorithm, the power spectral density distribution is processed to identify the frequency components and obtain the main frequency components of the diaphragm vibration.

[0084] (4) The amplitude is extracted based on the corresponding position of the main frequency component in the power spectral density distribution to obtain the power spectral density value at the main frequency.

[0085] (5) Perform numerical integration calculation on the power spectral density distribution within a specific frequency band to obtain the frequency band integral value, and combine the main frequency component, the power spectral density value at the main frequency and the frequency band integral value to form the diaphragm vibration spectrum characteristic parameters.

[0086] Specifically, the Hanning window function is applied to the time-domain data of diaphragm vibration to suppress spectral leakage. The Hanning window reduces signal edge effects and errors caused by spectral leakage, thereby improving frequency resolution. The windowed data is then further processed by a frequency domain transformation algorithm to perform a Fast Fourier Transform (FFT), converting the data from the time domain to the frequency domain. The resulting spectral density distribution has a frequency resolution of 2 Hz, covering a frequency range from 0 Hz to 3000 Hz, accurately reflecting the frequency characteristics of diaphragm vibration. Through the FFT, the frequency domain characteristics of the vibration signal are clearly presented, facilitating subsequent analysis and processing.

[0087] The power spectral density distribution is analyzed using a peak detection algorithm to identify its frequency components and extract the dominant frequency component of the diaphragm vibration. This dominant frequency component occupies a significant position in the spectrum and accurately reflects the main vibration characteristics of the diaphragm. The formula for calculating the power spectral density during dominant frequency component extraction is as follows:

[0088] ;

[0089] in, For the frequency domain complex components after windowed FFT, The number of sampling points. Sampling frequency, For frequency The power spectral density at that point. The criterion for determining its dominant frequency is:

[0090] , where the threshold function Defined as:

[0091] ;

[0092] in The average power density across the entire frequency band. For the local frequency band radius, The global significance coefficient is... This represents the local energy percentage threshold. By analyzing the spectral peaks in the spectrum, the system can identify the dominant frequency and further confirm its corresponding amplitude. The power spectral density value at the dominant frequency is obtained through the amplitude extraction process. This value effectively represents the energy intensity of this frequency component in the vibration signal, thus providing an important reference for subsequent gas pressure feedback and system adjustment. The extraction of the dominant frequency component and the power spectral density value signifies the effective identification of the frequency components of the vibration signal.

[0093] By analyzing the spectral peaks in the spectrum, the system can identify the dominant frequency and further confirm its corresponding amplitude. At this point, the power spectral density value at the dominant frequency is obtained through the amplitude extraction process. This value effectively represents the energy intensity of this frequency component in the vibration signal, thus providing an important reference for subsequent gas pressure feedback and system adjustment. The extraction of the dominant frequency component and the power spectral density value signifies the effective identification of the frequency components of the vibration signal.

[0094] Next, numerical integration of the power spectral density distribution within a specific frequency band (500Hz to 1500Hz) is performed to obtain the frequency band integral value. This calculation provides a basis for further analysis of the energy distribution of the vibration signal within this specific frequency band; integration yields the total energy information of the signal within that band. Finally, the dominant frequency component, the power spectral density value at the dominant frequency, and the frequency band integral value are combined to form the diaphragm vibration spectrum characteristic parameter. This parameter provides crucial data support for real-time monitoring and adjustment of the compressor's status.

[0095] Taking the vibration monitoring of a diaphragm pump as an example, the collected diaphragm vibration time-domain data is windowed using a Hanning window to reduce spectral leakage and improve the accuracy of frequency domain analysis. The windowed signal is then input into a Fast Fourier Transform algorithm to convert it into frequency domain data, obtaining a power spectral density distribution with a frequency resolution of 2Hz and a frequency range covering 0Hz to 3000Hz. A peak detection algorithm is applied to analyze the spectrum, extracting the dominant frequency component of the diaphragm vibration and identifying the main frequency characteristics from the spectrum. Based on the position of the dominant frequency component in the power spectrum, the power spectral density value at that frequency is extracted, reflecting the energy intensity of that frequency component in the vibration signal. Finally, a frequency band from 500Hz to 1500Hz is selected for numerical integration of the power spectral density distribution, obtaining the integral value for that frequency band. Combining the dominant frequency component, the power spectral density value at the dominant frequency, and the frequency band integral value yields the spectral characteristic parameters of the diaphragm vibration, which are used for subsequent gas pressure feedback and equipment performance adjustment. This processing can accurately extract key features of vibration signals, providing reliable data support for fault diagnosis and performance optimization of diaphragm pumps.

[0096] In one specific embodiment, the process of executing step S103 may specifically include the following steps:

[0097] (1) Based on the diaphragm mechanical vibration theory, the main frequency component is squared to obtain the quadratic value of the main frequency component;

[0098] (2) Input the power spectral density value at the main frequency into the logarithmic transformation function for quantization to obtain the logarithmic value of the power spectral density;

[0099] (3) The frequency band integral value is numerically standardized by a normalization algorithm to obtain the standardized frequency band integral value;

[0100] (4) Based on the weighting coefficients determined by the standard pressure source calibration experiment, the quadratic value of the main frequency component, the logarithmic value of the power spectral density and the integral value of the standardized frequency band are linearly weighted to obtain the intermediate value of pressure calculation;

[0101] (5) Based on the temperature compensation coefficient, the intermediate value of the pressure calculation is corrected by temperature to obtain the real-time gas pressure feedback value currently acting on the diaphragm.

[0102] Specifically, based on the diaphragm mechanical vibration theory, the square of the dominant frequency component is calculated to reflect its contribution to diaphragm vibration. This square value provides the foundational data for subsequent pressure calculations, more accurately reflecting the influence of the dominant frequency component on gas pressure changes. By squaring the square of the dominant frequency component, the system can transform important information in the spectrum into a more easily calculated form, ensuring that the data fully reflects the actual working state of the diaphragm. Furthermore, the power spectral density value at the dominant frequency is quantized using a logarithmic transform function to obtain its logarithmic value. This logarithmic transformation effectively reduces the impact of energy differences across different frequency bands on subsequent calculations, enhancing the stability and accuracy of the calculations and ensuring that various vibration signals during the calculation process are appropriately processed and quantized.

[0103] The frequency band integral values ​​are standardized using a normalization algorithm to match their data range with other parameters, providing a unified basis for weighted calculations. The standardized frequency band integral values ​​eliminate the influence of amplitude differences in vibration signals across different frequency bands, ensuring that the contribution of each frequency band is fairly reflected in the pressure calculation. Through this standardization process, the system can more accurately compare the impact of each frequency band on the overall vibration and lay the foundation for subsequent weighted calculations. During the weighting process, based on the weighting coefficients determined by the standard pressure source calibration experiment, the system linearly weights the quadratic value of the main frequency component, the logarithmic value of the power spectral density, and the standardized frequency band integral values ​​to obtain an intermediate value for the pressure calculation. The weighting coefficients are set based on experimental data to ensure that the weights of different parameters in the calculation are consistent with actual working conditions, thereby improving the reliability and accuracy of the calculation results.

[0104] After obtaining the intermediate pressure calculation value, the system performs temperature correction on this value based on a temperature compensation coefficient. The impact of temperature changes on diaphragm pressure is significant; the temperature compensation coefficient eliminates deviations caused by temperature fluctuations, ensuring the accuracy of the pressure feedback value. The temperature-compensated real-time gas pressure feedback value ultimately reflects the actual gas pressure acting on the diaphragm, providing a more precise basis for pressure monitoring and adjustment. This feedback value can be used for real-time adjustment of the compressor system, ensuring that the system always remains in optimal operating condition and avoiding pressure anomalies caused by temperature changes. Through this series of processing steps, the system can monitor the diaphragm's working pressure in real time and accurately, providing crucial protection for the safe and stable operation of the equipment and enhancing the intelligence and automation level of diaphragm compressors in industrial applications.

[0105] In one specific embodiment, the process of executing step S104 may specifically include the following steps:

[0106] (1) Threshold configuration processing is performed based on the working pressure range of the diaphragm compressor to obtain the absolute pressure control boundary;

[0107] (2) Set the pressure change rate adjustment threshold according to the safe operation requirements of the diaphragm compressor, and perform change rate limitation processing according to the pressure change rate adjustment threshold to obtain the pressure dynamic change control boundary;

[0108] (3) Calculate the standard deviation based on multiple consecutive real-time gas pressure feedback values ​​and set the pressure fluctuation adjustment threshold. Then, perform fluctuation amplitude limitation processing based on the pressure fluctuation adjustment threshold to obtain the pressure stability control boundary.

[0109] (4) Input the real-time gas pressure feedback value into the multi-level comparison and judgment algorithm to perform threshold over-limit detection processing, and obtain the pressure state control judgment result;

[0110] (5) Based on the pressure state control judgment result, control command generation and processing are performed through a graded response strategy to obtain the corresponding level of pressure regulation control command. When the pressure absolute value control boundary is exceeded, an emergency stop control command is output. When the pressure dynamic change control boundary is exceeded, a pressure regulation device start control command is output. When the pressure stability control boundary is exceeded, a monitoring reminder control command is output.

[0111] Specifically, based on the operating pressure range of the diaphragm compressor, an upper pressure adjustment threshold of 2.2 MPa and a lower pressure adjustment threshold of 0.05 MPa are set, thus establishing control boundaries for the absolute pressure values. This setting ensures that the operating pressure of the diaphragm compressor remains within the predetermined safe range, preventing equipment damage or efficiency reduction due to pressure exceeding this range. Through this threshold configuration, the system can monitor compressor pressure changes in real time, promptly detect and respond to abnormal pressure conditions, and ensure the compressor operates under safe conditions. Simultaneously, this control boundary also helps predict potential failure risks, allowing for proactive repair or adjustment measures to reduce downtime.

[0112] The system further sets the pressure change rate adjustment threshold to 0.2 MPa / s to limit the rate of pressure change. This threshold setting takes into account the compressor's safety, avoiding the burden on the equipment caused by excessively rapid pressure changes. By limiting the pressure change rate, the system ensures that the pressure changes gradually, without drastic fluctuations, thereby reducing mechanical wear or unnecessary energy consumption. The compressor's dynamic pressure changes are smoothly adjusted, improving the system's operational stability and equipment lifespan, while also reducing the occurrence of malfunctions caused by sudden pressure changes.

[0113] The system also incorporates a pressure fluctuation regulation threshold setting. By calculating the standard deviation of 10 consecutive real-time gas pressure feedback values, the fluctuation amplitude is limited to 0.02 MPa. This measure effectively controls the amplitude of pressure fluctuations, ensuring that the compressor's operating pressure remains within a stable range. When a pressure fluctuation exceeds the set threshold, the system promptly issues a warning, alerting operators to potential equipment instability. This pressure stability control method helps prevent performance degradation or damage due to frequent pressure fluctuations, ensuring the equipment remains efficient and stable during long-term operation.

[0114] After the real-time gas pressure feedback value is input into a multi-level comparison and judgment algorithm, the system will perform threshold over-limit detection. This detection process compares the pressure value with a set threshold in real time to determine whether the pressure exceeds the predetermined control boundary. If the pressure is found to exceed any control boundary, the system will immediately take appropriate control measures to ensure that the equipment is in a safe operating state. Through this process, the system can promptly identify pressure anomalies, prevent malfunctions or equipment damage caused by pressure runaway, and thus ensure the safety and stability of the equipment.

[0115] Specifically, based on the pressure status control judgment results, the system adopts a tiered response strategy to generate control commands. If the pressure exceeds the absolute pressure control boundary, the system will immediately output an emergency shutdown command to forcibly stop the equipment operation to prevent possible serious damage; if the pressure exceeds the dynamic pressure change control boundary, the pressure regulating device will be activated to adjust the pressure to the normal range; when the pressure fluctuation exceeds the pressure stability control boundary, the system will issue a monitoring alert to remind operators to pay attention to the equipment status. This tiered response mechanism ensures that the system can make reasonable and timely responses under different abnormal pressure conditions, which can both protect the safety of the equipment and avoid unnecessary downtime and production losses.

[0116] In one specific embodiment, the process of inputting real-time gas pressure feedback values ​​into a multi-level comparison and judgment algorithm for threshold over-limit detection to obtain a pressure state control judgment result can specifically include the following steps:

[0117] (1) Compare the real-time gas pressure feedback value with the pressure absolute value control boundary to obtain the pressure absolute value over-limit judgment result;

[0118] (2) Calculate the pressure change rate based on two consecutive real-time gas pressure feedback values ​​and compare it with the pressure dynamic change control boundary to obtain the pressure change rate exceeding the limit judgment result.

[0119] (3) Calculate the standard deviation based on multiple consecutive real-time gas pressure feedback values ​​and compare it with the pressure stability control boundary to obtain the pressure fluctuation exceeding the limit judgment result;

[0120] (4) Logically combine the results of the pressure absolute value exceeding the limit, the pressure change rate exceeding the limit, and the pressure fluctuation exceeding the limit to obtain a comprehensive abnormal judgment indicator;

[0121] (5) Based on the type and degree of exceeding the limit in the comprehensive anomaly judgment mark, perform level classification processing to obtain the pressure state control judgment result including anomaly type, anomaly degree and response level.

[0122] Specifically, the real-time gas pressure feedback value is compared with the absolute pressure control boundary to determine whether the pressure exceeds the set upper or lower limit. When the pressure exceeds these limits, the system promptly detects and marks it as an over-limit state. This process ensures that the equipment operates within a safe pressure range, preventing equipment damage caused by excessively high or low pressure. Through this comparison, the system can respond quickly and take measures such as stopping equipment operation or activating the regulation mechanism to prevent potential malfunctions.

[0123] Based on two consecutive real-time gas pressure feedback values, the system calculates the rate of pressure change and compares it with the pressure dynamic change control boundary. When the rate of pressure change exceeds a set threshold, the system issues a pressure change rate exceeding limit warning. This process helps monitor the rate of pressure change, avoiding additional burden on the equipment due to drastic pressure fluctuations and ensuring stable equipment operation. If the rate exceeds the limit, the system can take measures, such as activating the pressure regulating device, to make the pressure change more stable and reduce the impact on the equipment.

[0124] The system calculates the standard deviation based on 10 consecutive real-time gas pressure feedback values ​​and compares it with the set pressure stability control boundary to determine whether pressure fluctuations exceed limits. When pressure fluctuations exceed the set threshold, the system issues a fluctuation over-limit warning. This process can promptly detect abnormal pressure fluctuations and indicate unstable equipment operation. Through this detection, the system can accurately identify whether pressure fluctuations exceed the safe range, preventing equipment damage or efficiency reduction due to excessive fluctuations.

[0125] The system logically combines the three judgment results mentioned above to obtain a comprehensive anomaly judgment indicator. If the pressure exceeds the absolute value control boundary, the rate of change exceeds the limit, or the fluctuation is too large, the system will combine this information to determine the current pressure status of the equipment. Through logical combination, the system can more comprehensively evaluate the operating status of the equipment and promptly identify and respond to possible anomalies. At this time, the system will make a judgment on whether action is needed, providing a basis for subsequent control decisions.

[0126] By combining the type and severity of exceedances identified in the comprehensive anomaly assessment, the system categorizes anomalies and generates response control commands. If the pressure exceeds the limit, the system will immediately execute an emergency shutdown command; if the rate of pressure change or fluctuation exceeds the limit, the system will activate the regulating device to restore normal pressure changes. Through this tiered response strategy, the system can take the most appropriate control measures based on the actual situation, ensuring the safe operation of the equipment and improving overall operational efficiency.

[0127] In one specific embodiment, the process of logically combining the results of the pressure absolute value exceeding the limit judgment, the pressure change rate exceeding the limit judgment, and the pressure fluctuation exceeding the limit judgment to obtain a comprehensive anomaly judgment indicator may specifically include the following steps:

[0128] (1) Perform logical state encoding processing on the judgment result of the pressure absolute value exceeding the limit to obtain the pressure absolute value abnormality flag bit, where the code is 01 when the upper limit threshold is exceeded, 10 when the lower limit threshold is exceeded, and 00 when the normal state is normal.

[0129] (2) The result of the pressure change rate exceeding the limit is processed by logical state encoding to obtain the pressure change rate abnormality flag bit, which is encoded as 1 when the change rate exceeds the threshold and 0 when the normal state is.

[0130] (3) The pressure fluctuation exceeding the limit judgment result is processed by logical state encoding to obtain the pressure fluctuation abnormality flag bit, which is encoded as 1 when the fluctuation threshold is exceeded and 0 when the normal state is.

[0131] (4) Perform bitwise operations on the absolute pressure value abnormality flag bit, the pressure change rate abnormality flag bit, and the pressure fluctuation abnormality flag bit to obtain a 4-bit binary abnormality status code.

[0132] (5) Based on the 4-bit binary abnormal status code, the abnormal type is identified through the status mapping table to obtain a comprehensive abnormal judgment identifier that includes the abnormal type and severity.

[0133] Specifically, such as Figure 2 As shown in the figure, this is a flowchart of an anomaly judgment process for a real-time gas pressure monitoring system of a diaphragm compressor provided in an embodiment of this application. The specific process is as follows: First, the absolute pressure value exceeding the limit judgment result is processed by logical state encoding. When the upper limit threshold is exceeded, it is encoded as 01; when the lower limit threshold is exceeded, it is encoded as 10; and when the normal state is reached, it is encoded as 00. Through this encoding method, the system can represent different states of pressure exceeding the limit separately, which facilitates subsequent processing and analysis. If the pressure value exceeds the upper or lower limit boundary, the system can clearly identify which type of exceeding state it is through encoding, ensuring that the system can react in a timely manner. This encoding processing method provides a concise and intuitive data identifier for subsequent bit operations and anomaly judgment.

[0134] The system uses logical state encoding to process the results of pressure change rate exceeding limits. If the rate of change exceeds a predetermined threshold, it is encoded as 1, indicating an abnormal rate of change; if the rate of change is within the normal range, it is encoded as 0, indicating no abnormality. This encoding method allows the system to clearly identify whether pressure changes are too rapid, thereby determining whether the equipment's operating status is stable. Similarly, the system uses logical state encoding to process the results of pressure fluctuation exceeding limits. If the pressure fluctuation exceeds a set fluctuation threshold, it is encoded as 1, indicating an abnormal pressure fluctuation; if the fluctuation range is normal, it is encoded as 0, indicating no abnormality. This encoding method allows the system to identify fluctuations in the equipment during operation, providing a basis for subsequent control and monitoring.

[0135] The system performs bitwise operations on the absolute pressure value anomaly flag, the pressure change rate anomaly flag, and the pressure fluctuation anomaly flag to obtain a 4-bit binary anomaly status code. This binary status code integrates all the over-limit judgment results and clearly expresses the type and status of the current pressure anomaly. By inputting this status code into the status mapping table, the system can identify the anomaly type and its severity, generating a comprehensive anomaly judgment flag containing both the anomaly type and severity. This process provides a clear basis for subsequent response measures, enabling the system to take appropriate control measures for anomalies of different types and severity, such as issuing alarms, activating regulating devices, or emergency shutdown, thereby ensuring the safe operation of the equipment.

[0136] The above describes the real-time gas pressure monitoring method for the diaphragm compressor in the embodiments of this application. The following describes the real-time gas pressure monitoring system for the diaphragm compressor in the embodiments of this application. Please refer to [link / reference]. Figure 3 One embodiment of the real-time gas pressure monitoring system for the diaphragm compressor in this application includes:

[0137] The scanning module 201 is used to collect the vibration signal of the working diaphragm surface of the diaphragm compressor in real time through a triaxial accelerometer to obtain the time domain data of the diaphragm vibration.

[0138] Extraction module 202 is used to perform fast Fourier transform processing on the diaphragm vibration time domain data to extract the main frequency component of the diaphragm vibration, the power spectral density value at the main frequency, and the power spectral integral value in a specific frequency band, forming diaphragm vibration spectral characteristic parameters.

[0139] Module 203 is used to calculate the real-time gas pressure feedback value acting on the diaphragm by weighting the main frequency component, power spectral density value and frequency band integral value in the characteristic parameters of the diaphragm vibration spectrum according to the correspondence between frequency and pressure in the diaphragm mechanical vibration theory.

[0140] The control module 204 is used to set the upper and lower limit adjustment thresholds, the pressure change rate adjustment threshold, and the pressure fluctuation adjustment threshold, and to perform multi-level automatic adjustment and control on the real-time gas pressure feedback value. When any adjustment threshold is exceeded, the corresponding pressure regulation control command is output.

[0141] Through the coordinated operation of the aforementioned components, the system enables real-time monitoring and automatic control of the diaphragm compressor. The scanning module 201 acquires vibration signals from the diaphragm surface in real time using a triaxial accelerometer, converting these signals into time-domain data. This time-domain data contains the vibration characteristics of the diaphragm during operation. The extraction module 202 then performs a Fast Fourier Transform on this time-domain data, converting the time-domain signal into a frequency-domain signal, extracting the dominant frequency component of the diaphragm vibration and its corresponding power spectral density value. Simultaneously, it calculates the power spectral integral value within a specific frequency band to obtain the diaphragm vibration spectral characteristic parameters. These characteristic parameters are crucial for understanding the diaphragm's operating state and identifying possible failure modes.

[0142] Based on the correlation between frequency and pressure in the diaphragm mechanical vibration theory, the construction module 203 performs weighted calculations on the spectral characteristic parameters obtained from the extraction module 202 to obtain the real-time gas pressure feedback value. This feedback value accurately reflects the gas pressure acting on the diaphragm, helping the system monitor the diaphragm's working status in real time and providing data support for subsequent control decisions. The regulation module 204 then performs multi-level automatic adjustment and control on the real-time gas pressure feedback value according to the set upper and lower pressure limit adjustment thresholds, pressure change rate adjustment thresholds, and pressure fluctuation adjustment thresholds. When the pressure exceeds any adjustment threshold, the system will automatically output the corresponding pressure regulation control command. For example, if the pressure exceeds the preset upper and lower limits, the system will issue an emergency shutdown or pressure adjustment command; if the pressure change rate is too fast, the system will activate the adjustment device to stabilize the pressure fluctuation; if the pressure fluctuation amplitude is too large, a monitoring reminder command will be issued to prompt the operator to pay attention to the equipment's operating status.

[0143] above Figure 3 The real-time gas pressure monitoring system of the diaphragm compressor in this embodiment of the invention is described in detail from the perspective of modular functional entities. The real-time gas pressure monitoring device of the diaphragm compressor in this embodiment of the invention is described in detail from the perspective of hardware processing.

[0144] Reference Figure 4 This invention also provides a real-time gas pressure monitoring device for a diaphragm compressor. This device can be a server, and its internal structure can be as follows: Figure 4As shown, the real-time gas pressure monitoring device for the diaphragm compressor includes a processor, memory, display screen, input device, network interface, and database connected via a system bus. The processor, designed as a computer, provides computational and control capabilities. The memory of the real-time gas pressure monitoring device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the real-time gas pressure monitoring device for the diaphragm compressor stores the data corresponding to this embodiment. The network interface of the real-time gas pressure monitoring device for the diaphragm compressor is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the above-described method.

[0145] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the gas pressure real-time monitoring device of the diaphragm compressor to which the present invention is applied.

[0146] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when the instructions are executed on a computer, cause the computer to perform the steps of the real-time gas pressure monitoring method of the diaphragm compressor.

[0147] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0148] If the integrated unit 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, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a diaphragm compressor gas pressure real-time monitoring device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0149] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention 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 the present invention.

Claims

1. A method for real-time monitoring of gas pressure in a diaphragm compressor, characterized in that, The method includes: The vibration signal of the working diaphragm surface of the diaphragm compressor is acquired in real time by a triaxial accelerometer to obtain the time domain data of the diaphragm vibration. Fast Fourier Transform is performed on the time-domain data of diaphragm vibration to extract the main frequency component of diaphragm vibration, the power spectral density value at the main frequency, and the power spectral integral value in a specific frequency band, forming the diaphragm vibration spectral characteristic parameters. The specific frequency band is the range of 500Hz to 1500Hz. Based on the correspondence between frequency and pressure in the diaphragm mechanical vibration theory, the main frequency component, power spectral density value and frequency band integral value in the diaphragm vibration spectrum characteristic parameters are weighted and calculated to obtain the real-time gas pressure feedback value currently acting on the diaphragm. The system sets upper and lower pressure limit adjustment thresholds, pressure change rate adjustment thresholds, and pressure fluctuation adjustment thresholds to perform multi-level automatic adjustment and control on real-time gas pressure feedback values. When any adjustment threshold is exceeded, a corresponding pressure regulation control command is output. This includes: configuring thresholds based on the diaphragm compressor's operating pressure range to obtain the absolute pressure control boundary; setting the pressure change rate adjustment threshold according to the diaphragm compressor's safe operation requirements, and limiting the change rate based on the pressure change rate adjustment threshold to obtain the dynamic pressure change control boundary; calculating the standard deviation based on multiple consecutive real-time gas pressure feedback values ​​and setting a pressure fluctuation adjustment threshold, and limiting the fluctuation amplitude based on the pressure fluctuation adjustment threshold to obtain the pressure stability control boundary. The real-time gas pressure feedback value is input into a multi-level comparison and judgment algorithm for threshold over-limit detection to obtain the pressure state control judgment result. This includes: comparing the real-time gas pressure feedback value with the absolute pressure control boundary to obtain the absolute pressure over-limit judgment result; calculating the pressure change rate based on two consecutive real-time gas pressure feedback values ​​and comparing it with the pressure dynamic change control boundary to obtain the pressure change rate over-limit judgment result; calculating the standard deviation based on multiple consecutive real-time gas pressure feedback values ​​and comparing it with the pressure stability control boundary to obtain the pressure fluctuation over-limit judgment result; logically combining the absolute pressure over-limit judgment result, the pressure change rate over-limit judgment result, and the pressure fluctuation over-limit judgment result to obtain a comprehensive anomaly judgment identifier; and classifying the over-limit type and degree of over-limit in the comprehensive anomaly judgment identifier to obtain a pressure state control judgment result that includes anomaly type, anomaly degree, and response level. Based on the pressure state control judgment result, control commands are generated and processed through a graded response strategy to obtain corresponding pressure regulation control commands. Specifically, when the pressure exceeds the absolute pressure control boundary, an emergency shutdown control command is output; when the pressure exceeds the dynamic pressure change control boundary, a pressure regulation device start control command is output; and when the pressure exceeds the pressure stability control boundary, a monitoring reminder control command is output.

2. The method for real-time monitoring of gas pressure in a diaphragm compressor according to claim 1, characterized in that, The method involves real-time acquisition of vibration signals from the working diaphragm surface of the diaphragm compressor using a triaxial accelerometer to obtain time-domain data of diaphragm vibration, including: The triaxial accelerometer is installed by fixing it to the geometric center of the working diaphragm surface with adhesive, resulting in a rigid connection structure between the sensor and the working diaphragm. Based on the rigid connection structure, the three-dimensional vibration acceleration of the working diaphragm surface is continuously detected and processed to obtain the original vibration signals in the X, Y, and Z directions; The original vibration signal is input into a charge amplifier for signal amplification to obtain an amplified vibration signal; the amplified vibration signal is then filtered for noise by a second-order Butterworth low-pass filter to obtain a purified vibration signal. The purification vibration signal was processed by analog-to-digital conversion to obtain the diaphragm vibration time-domain data.

3. The method for real-time monitoring of gas pressure in a diaphragm compressor according to claim 1, characterized in that, The process of performing a Fast Fourier Transform on the time-domain data of diaphragm vibration extracts the dominant frequency component, the power spectral density value at the dominant frequency, and the power spectral integral value within a specific frequency band, forming diaphragm vibration spectral characteristic parameters, including: The time-domain data of diaphragm vibration was windowed using the Hanning window function to obtain windowed time-domain data with spectral leakage suppressed. The windowed time-domain data is input into the Fast Fourier Transform algorithm for frequency domain transformation to obtain the power spectral density distribution; Based on the peak detection algorithm, the power spectral density distribution is processed to identify the frequency components and obtain the main frequency components of diaphragm vibration. The amplitude is extracted based on the corresponding position of the main frequency component in the power spectral density distribution to obtain the power spectral density value at the main frequency. Numerical integration calculations are performed on the power spectral density distribution within a specific frequency band to obtain the frequency band integral value. The main frequency component, the power spectral density value at the main frequency, and the frequency band integral value are combined to form the diaphragm vibration spectrum characteristic parameters. The specific frequency band is the range of 500Hz to 1500Hz.

4. The method for real-time monitoring of gas pressure in a diaphragm compressor according to claim 1, characterized in that, Based on the correspondence between frequency and pressure in the diaphragm mechanical vibration theory, the dominant frequency component, power spectral density value, and frequency band integral value in the diaphragm vibration spectrum characteristic parameters are weighted and calculated to obtain the real-time gas pressure feedback value currently acting on the diaphragm, including: The quadratic value of the main frequency component is obtained by squaring the main frequency component based on the diaphragm mechanical vibration theory. The power spectral density value at the main frequency is input into a logarithmic transform function for quantization to obtain the logarithmic power spectral density value. The frequency band integral value is numerically standardized using a normalization algorithm to obtain the standardized frequency band integral value. Based on the weighting coefficients determined by the standard pressure source calibration experiment, the quadratic value of the main frequency component, the logarithmic value of the power spectral density, and the standardized frequency band integral value are linearly weighted to obtain the intermediate value for pressure calculation. The intermediate pressure calculation value is corrected for temperature based on the temperature compensation coefficient to obtain the real-time gas pressure feedback value currently acting on the diaphragm.

5. The method for real-time monitoring of gas pressure in a diaphragm compressor according to claim 1, characterized in that, The process of logically combining the results of the pressure absolute value exceeding the limit judgment, the pressure change rate exceeding the limit judgment, and the pressure fluctuation exceeding the limit judgment to obtain a comprehensive anomaly judgment indicator includes: The result of the pressure absolute value exceeding the limit is processed by logical state encoding to obtain the pressure absolute value abnormality flag bit, where the code is 01 when the upper limit threshold is exceeded, 10 when the lower limit threshold is exceeded, and 00 when the normal state is. The results of the pressure change rate exceeding the limit are processed by logical state encoding to obtain the pressure change rate abnormality flag bit, where the code is 1 when the change rate exceeds the threshold and 0 when the normal state is. The results of the pressure fluctuation exceeding the limit are processed by logical state encoding to obtain the pressure fluctuation abnormality flag bit, where the code is 1 when the fluctuation threshold is exceeded and 0 when the normal state is normal; the pressure absolute value abnormality flag bit, the pressure change rate abnormality flag bit, and the pressure fluctuation abnormality flag bit are combined by bit operation to obtain a 4-bit binary abnormality status code. Based on the 4-bit binary exception status code, the exception type is identified through the status mapping table to obtain a comprehensive exception judgment identifier that includes the exception type and severity.

6. A real-time gas pressure monitoring system for a diaphragm compressor, characterized in that, A method for real-time monitoring of gas pressure in a diaphragm compressor as described in any one of claims 1-5, wherein the real-time gas pressure monitoring system for the diaphragm compressor comprises: The scanning module is used to collect vibration signals from the working diaphragm surface of the diaphragm compressor in real time using a triaxial accelerometer to obtain time-domain data of diaphragm vibration. The extraction module is used to perform fast Fourier transform processing on the time-domain data of diaphragm vibration, extract the main frequency component of diaphragm vibration, the power spectral density value at the main frequency, and the power spectral integral value in a specific frequency band to form the spectral characteristic parameters of diaphragm vibration, wherein the specific frequency band is the range of 500Hz to 1500Hz. The module is used to calculate the real-time gas pressure feedback value acting on the diaphragm by weighting the main frequency component, power spectral density value and frequency band integral value in the characteristic parameters of the diaphragm vibration spectrum according to the correspondence between frequency and pressure in the diaphragm mechanical vibration theory. The control module is used to set the upper and lower pressure limit adjustment thresholds, the pressure change rate adjustment threshold, and the pressure fluctuation adjustment threshold. It performs multi-level automatic adjustment and control on the real-time gas pressure feedback value, and outputs the corresponding pressure regulation control command when any adjustment threshold is exceeded.

7. A real-time gas pressure monitoring device for a diaphragm compressor, characterized in that, The method includes a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the real-time gas pressure monitoring method for the diaphragm compressor according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is run by the processor, it causes the processor to execute the real-time gas pressure monitoring method for the diaphragm compressor as described in any one of claims 1 to 5.

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