Four-in-one intelligent multi-parameter early warning sensor for industrial monitoring

Abstract

This invention belongs to the field of industrial monitoring electrical technology and discloses a four-in-one intelligent multi-parameter early warning sensor for industrial monitoring. It includes a four-in-one parameter acquisition unit, a raw feature preprocessing module, a progressive coupling calculation module, an early warning decision module, a non-dedicated data transmission conversion module, and an embedded main control core. All modules are electrically connected and work collaboratively. The progressive coupling calculation module performs temperature drift correction calculation, progressive interference weight calculation, and early warning confidence calculation. The embedded main control core schedules the timing of all modules. This invention solves the problems of existing multi-parameter monitoring technologies lacking progressive coupling processing and interference affecting monitoring accuracy, achieving multi-parameter collaborative early warning and ensuring the stability and reliability of industrial monitoring.

Description

Technical Field

[0001] This invention belongs to the field of industrial monitoring electrical technology, specifically relating to a four-in-one intelligent multi-parameter advanced early warning sensor for industrial monitoring. Background Technology

[0002] In industrial field monitoring, it is necessary to simultaneously monitor four key parameters: thermodynamic temperature, vibration acceleration, gas concentration, and electromagnetic interference field strength. Existing multi-parameter sensors mostly employ a single-parameter independent processing mode, failing to address the coupling effects between these parameters. Specifically, gas concentration detection is susceptible to drift due to temperature changes, leading to inaccurate results. Vibration acceleration and electromagnetic interference field strength can superimpose interference on the corrected gas concentration signal; current technologies cannot progressively quantify and correct for this type of interference, thus affecting the accuracy of early warning systems and hindering the timely detection of early signs of equipment failure.

[0003] Based on the above problems, there is an urgent need for a multi-parameter advanced early warning sensor that can progressively process multi-parameter coupled interference and improve the accuracy of early warning. Summary of the Invention

[0004] To address the problems existing in current technologies, this invention proposes a four-in-one intelligent multi-parameter early warning sensor for industrial monitoring. It includes a four-in-one parameter acquisition unit, a raw feature preprocessing module, a progressive coupling calculation module, an early warning decision module, a non-dedicated data transmission conversion module, and an embedded main control core. The four-in-one parameter acquisition unit is electrically connected to the raw feature preprocessing module and is used to acquire thermodynamic temperature signals, vibration acceleration signals, gas concentration signals, and electromagnetic interference field strength signals. The raw feature preprocessing module is electrically connected to both the four-in-one parameter acquisition unit and the progressive coupling calculation module, and is used to remove random Gaussian noise from the four types of signals and perform standardized dimensionless processing. The progressive coupling calculation module is connected to the raw feature preprocessing module... The feature preprocessing module, the advanced early warning decision module, and the embedded main control core are electrically connected to sequentially perform temperature drift correction calculation, progressive interference weight calculation, and advanced early warning confidence calculation. The advanced early warning decision module is electrically connected to the progressive coupling calculation module and the non-dedicated data transmission conversion module to output advanced early warning commands based on the advanced early warning confidence. The non-dedicated data transmission conversion module is electrically connected to the advanced early warning decision module to perform data format conversion and wireless transmission. The embedded main control core is electrically connected to the four-in-one parameter acquisition unit, the original feature preprocessing module, the progressive coupling calculation module, the advanced early warning decision module, and the non-dedicated data transmission conversion module to schedule the working sequence of all modules.

[0005] Preferably, the four-in-one parameter acquisition unit includes a temperature acquisition subunit, a vibration acquisition subunit, a gas concentration acquisition subunit, and an electromagnetic acquisition subunit. The temperature acquisition subunit is electrically connected to the original feature preprocessing module and is used to acquire thermodynamic temperature signals. The vibration acquisition subunit is electrically connected to the original feature preprocessing module and is used to acquire vibration acceleration signals and output vibration acceleration amplitude. The gas concentration acquisition subunit is electrically connected to the original feature preprocessing module and is used to acquire gas concentration signals and output original gas concentration detection values. The electromagnetic acquisition subunit is electrically connected to the original feature preprocessing module and is used to acquire electromagnetic interference field strength signals and output electromagnetic interference field strength.

[0006] In a further preferred embodiment, the original feature preprocessing module includes a noise removal subunit and a standardization processing subunit. The noise removal subunit is electrically connected to the four-in-one parameter acquisition unit and the standardization processing subunit, and is used to remove random Gaussian noise from the thermodynamic temperature signal, vibration acceleration amplitude, original gas concentration detection value, and electromagnetic interference field strength. The standardization processing subunit is electrically connected to the noise removal subunit and the progressively coupled calculation module, and is used to perform standardized dimensionless processing on the noise-removed parameters, and output standardized thermodynamic temperature, standardized vibration acceleration amplitude, standardized original gas concentration detection value, and standardized electromagnetic interference field strength.

[0007] In a further preferred embodiment, the progressive coupling calculation module includes a drift correction subunit, a weight calculation subunit, and a confidence calculation subunit. The drift correction subunit is electrically connected to the standardization processing subunit and the weight calculation subunit, and is used to perform temperature drift correction calculation based on the standardized thermodynamic temperature and the standardized original gas concentration detection value, and output the temperature-corrected gas concentration value. The weight calculation subunit is electrically connected to the drift correction subunit and the confidence calculation subunit, and is used to perform progressive interference weight calculation based on the standardized vibration acceleration amplitude, the standardized electromagnetic interference field strength, and the temperature-corrected gas concentration value, and output the progressive coupling comprehensive weight. The confidence calculation subunit is electrically connected to the weight calculation subunit and the advanced warning decision module, and is used to perform advanced warning confidence calculation based on the temperature-corrected gas concentration value, the progressive coupling comprehensive weight, the standardized thermodynamic temperature, and the standardized vibration acceleration amplitude, and output the advanced warning confidence value.

[0008] In a further preferred embodiment, the drift correction subunit employs a coupled drift correction logic that combines linear correction and nonlinear compensation. Based on the standardized thermodynamic temperature and the standardized original gas concentration detection value, it performs temperature drift correction calculations by combining the preset temperature drift sensitivity coefficient, the standard thermodynamic temperature, and the first standardized proportional coefficient, and outputs the temperature-corrected gas concentration value.

[0009] In a further preferred embodiment, the weight calculation subunit performs progressive coupling weight calculation. The calculation process combines the standardized vibration acceleration amplitude, the standardized electromagnetic interference field strength, and the temperature-corrected gas concentration value. Through a preset dimensionless processing logic, the progressive coupling comprehensive weight is output. The progressive coupling comprehensive weight is used for the subsequent calculation of the advanced warning confidence level.

[0010] In a further preferred embodiment, the confidence calculation subunit performs advance warning confidence calculation. The calculation process combines the temperature-corrected gas concentration value, progressively coupled comprehensive weight, standardized thermodynamic temperature, and standardized vibration acceleration amplitude. Through preset nonlinear calculation logic, the advance warning confidence is output, and the advance warning confidence is used to generate advance warning commands.

[0011] In a further preferred embodiment, the advanced early warning decision module includes an instruction generation subunit and an instruction output subunit. The instruction generation subunit is electrically connected to the confidence calculation subunit and the instruction output subunit, and is used to receive the advanced early warning confidence and generate an advanced early warning instruction. The instruction output subunit is electrically connected to the instruction generation subunit and the non-dedicated data transmission conversion module, and is used to transmit the advanced early warning instruction to the non-dedicated data transmission conversion module.

[0012] In a further preferred embodiment, the non-dedicated data transmission conversion module includes a format conversion subunit and a wireless transmission subunit. The format conversion subunit is electrically connected to the instruction output subunit and the wireless transmission subunit, and is used to perform general format conversion on the standardized thermodynamic temperature, temperature-corrected gas concentration value, progressive coupling comprehensive weight, advance warning confidence level, and advance warning instruction. The wireless transmission subunit is electrically connected to the format conversion subunit and is used to perform wireless transmission of the format-converted parameters and instructions.

[0013] In a further preferred embodiment, the embedded main control core includes a timing scheduling subunit and an algorithm control subunit. The timing scheduling subunit is electrically connected to the algorithm control subunit, the four-in-one parameter acquisition unit, the original feature preprocessing module, the progressive coupling calculation module, the early warning decision module, and the non-dedicated data transmission conversion module, and is used to uniformly schedule the working timing of all modules. The algorithm control subunit is electrically connected to the timing scheduling subunit and the progressive coupling calculation module, and is used to control the operation flow of temperature drift correction calculation, progressive coupling weight calculation, and early warning confidence calculation.

[0014] Technical effects: The core inventive technology of this invention is that the progressive coupling calculation module sequentially performs temperature drift correction calculation, progressive interference weight calculation, and advanced warning confidence calculation. This solves the problem in the background technology that existing multi-parameter sensors do not perform progressive processing of multi-parameter coupling interference and have insufficient early warning accuracy. It realizes multi-parameter collaborative monitoring and advanced early warning, eliminates the influence of temperature drift, vibration, and electromagnetic interference, and ensures the accuracy of industrial monitoring data and the timeliness of early warning. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A schematic diagram of the overall architecture and data flow of a four-in-one intelligent multi-parameter early warning sensor system for industrial monitoring; Figure 2 A schematic diagram of the interaction timing of a four-in-one intelligent multi-parameter early warning sensor module for industrial monitoring. Figure 3 A schematic diagram illustrating the working state transition of a four-in-one intelligent multi-parameter early warning sensor for industrial monitoring. Detailed Implementation

[0017] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0018] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0019] Existing multi-parameter sensors employ a single-parameter independent processing mode, which cannot address the drift in gas concentration detection caused by thermodynamic temperature changes, nor can it perform progressive quantification of the superimposed interference formed by vibration acceleration and electromagnetic interference field strength. The coupling effects between various parameters are not incorporated into the calculation system, ultimately resulting in consistently low accuracy of early warning and failing to meet the needs of stable monitoring in industrial settings.

[0020] Based on this, please refer to Figures 1-3This embodiment provides a four-in-one intelligent multi-parameter early warning sensor for industrial monitoring, including a four-in-one parameter acquisition unit, a raw feature preprocessing module, a progressive coupling calculation module, an early warning decision module, a non-dedicated data transmission conversion module, and an embedded main control core. The four-in-one parameter acquisition unit is electrically connected to the raw feature preprocessing module. The four-in-one parameter acquisition unit is used to acquire thermodynamic temperature signals, vibration acceleration signals, gas concentration signals, and electromagnetic interference field strength signals from the industrial site. The raw feature preprocessing module is electrically connected to both the four-in-one parameter acquisition unit and the progressive coupling calculation module. The raw feature preprocessing module is used to remove random Gaussian noise from the four types of signals output by the four-in-one parameter acquisition unit and performs standardized dimensionless processing on the noise-removed signals. The progressive coupling calculation module is electrically connected to the raw feature preprocessing module, the early warning decision module, and the embedded main control core. The progressive coupling calculation module is used to sequentially perform temperature drift correction calculation, progressive interference weight calculation, and early warning confidence calculation. The advanced early warning decision module establishes electrical connections with both the progressive coupling calculation module and the non-dedicated data transmission conversion module. The advanced early warning decision module generates and outputs an advanced early warning command based on the advanced early warning confidence level output by the progressive coupling calculation module. The non-dedicated data transmission conversion module establishes electrical connections with the advanced early warning decision module. The non-dedicated data transmission conversion module performs data format conversion operations on the acquired signals, calculated parameters, and advanced early warning commands, and then wirelessly transmits the converted content. The embedded main control core establishes electrical connections with the four-in-one parameter acquisition unit, the original feature preprocessing module, the progressive coupling calculation module, the advanced early warning decision module, and the non-dedicated data transmission conversion module. The embedded main control core schedules the working sequence of all modules, ensuring that all modules operate collaboratively according to preset logic. This implementation method constructs a complete industrial multi-parameter monitoring and early warning system through the coordinated operation of multiple modules. Its core relies on the progressive calculation logic of the progressively coupled calculation module, which sequentially incorporates the effects of temperature on gas concentration and the superimposed interference from vibration and electromagnetic fields into the calculation process. This fundamentally solves the monitoring distortion problem caused by multi-parameter coupling, enabling the sensor to stably output accurate monitoring data and early warning commands. This implementation method can eliminate the coupling interference between various parameters, ensuring the accuracy of monitoring data and the timeliness of early warnings.

[0021] The existing four-in-one parameter acquisition unit only has a general signal acquisition function. It does not separate the acquisition of different types of physical quantities. The acquisition processes of various signals interfere with each other, and the accuracy of the acquired parameters cannot meet the basic requirements of subsequent calculations. The specificity and stability of the signal output are obviously defective.

[0022] Based on this, the four-in-one parameter acquisition unit includes a temperature acquisition subunit, a vibration acquisition subunit, a gas concentration acquisition subunit, and an electromagnetic acquisition subunit. The temperature acquisition subunit is electrically connected to the original feature preprocessing module and is used to acquire thermodynamic temperature signals from the industrial site. The vibration acquisition subunit is electrically connected to the original feature preprocessing module and is used to acquire vibration acceleration signals from the industrial site, converting the acquired vibration acceleration signals into vibration acceleration amplitude values. The gas concentration acquisition subunit is electrically connected to the original feature preprocessing module and is used to acquire gas concentration signals from the industrial site, converting the acquired gas concentration signals into raw gas concentration detection values. The electromagnetic acquisition subunit is electrically connected to the original feature preprocessing module and is used to acquire electromagnetic interference field strength signals from the industrial site, converting the acquired electromagnetic interference field strength signals into electromagnetic interference field strength values. This implementation divides the four-in-one parameter acquisition unit into four independent sub-units. Each sub-unit corresponds to the acquisition and conversion of a specific type of physical quantity. The acquisition object and output parameter type of each sub-unit are clearly defined, avoiding signal crosstalk issues during the acquisition of different physical quantities. Each type of acquired parameter has its own dedicated acquisition channel, ensuring the relevance and accuracy of the acquired data. This provides a stable and high-quality raw data foundation for subsequent signal preprocessing and coupling calculations. This implementation improves the accuracy of the acquired parameters, providing reliable data support for subsequent calculation processes.

[0023] The existing original feature preprocessing module does not functionally decompose the signal processing flow. Noise removal and standardization operations are performed together. Noise signals will interfere with the results of standardization. The inconsistency of the dimensions of different parameters will also directly affect the rationality of subsequent coupled calculations. The overall effect of signal preprocessing cannot meet the expected standard.

[0024] Based on this, the original feature preprocessing module includes a noise removal subunit and a normalization subunit. The noise removal subunit is electrically connected to both the four-in-one parameter acquisition unit and the normalization subunit. This noise removal subunit removes random Gaussian noise from the thermodynamic temperature signal, vibration acceleration amplitude, original gas concentration detection value, and electromagnetic interference field strength. The normalization subunit is electrically connected to both the noise removal subunit and the progressively coupled calculation module. This normalization subunit performs normalization dimensionless processing on the various parameters after noise removal, and outputs normalized thermodynamic temperature, normalized vibration acceleration amplitude, normalized original gas concentration detection value, and normalized electromagnetic interference field strength after processing. This implementation divides the original feature preprocessing module into two independent sub-units. First, the noise removal sub-unit removes random Gaussian noise. Then, the standardization sub-unit performs dimensionless processing, strictly adhering to the logic of denoising before standardization to avoid negatively impacting the standardization results. Simultaneously, dimensionless processing eliminates dimensional differences between thermodynamic temperature, vibration acceleration amplitude, gas concentration detection values, and electromagnetic interference field strength, ensuring all parameters are on a unified computational dimension and guaranteeing the rationality and accuracy of subsequent coupled calculations. This implementation improves the quality of signal preprocessing, eliminates dimensional differences between different parameters, and ensures the stable operation of subsequent calculation processes.

[0025] The existing progressive coupled calculation module does not functionally decompose the coupled calculation process. Temperature drift correction, interference weight calculation and confidence calculation are executed in a mixed manner. The calculation logic is chaotic and parameter calling errors occur frequently. It cannot achieve progressive coupled calculation. The influence relationship between multiple parameters cannot be accurately quantified, and the reliability of the calculation results remains low.

[0026] Based on this, the progressive coupling calculation module includes a drift correction subunit, a weight calculation subunit, and a confidence calculation subunit. The drift correction subunit is electrically connected to both the standardization processing subunit and the weight calculation subunit. The drift correction subunit performs temperature drift correction calculations based on the standardized thermodynamic temperature and standardized original gas concentration detection values ​​output by the standardization processing subunit, and outputs the temperature-corrected gas concentration value after the calculation. The weight calculation subunit is also electrically connected to both the drift correction subunit and the confidence calculation subunit. The weight calculation subunit performs progressive interference weight calculations based on the standardized vibration acceleration amplitude, the standardized electromagnetic interference field strength, and the temperature-corrected gas concentration value, and outputs the progressive coupling comprehensive weight after the calculation. The confidence calculation subunit establishes an electrical connection with both the weight calculation subunit and the advanced warning decision module. The confidence calculation subunit performs advanced warning confidence calculation based on the temperature-corrected gas concentration value, the progressively coupled comprehensive weight, the standardized thermodynamic temperature, and the standardized vibration acceleration amplitude. After calculation, it outputs the advanced warning confidence level. This embodiment divides the progressively coupled calculation module into three independent subunits. These three subunits execute calculations sequentially according to a progressive calculation logic. The drift correction subunit first completes the temperature drift correction of the gas concentration. The weight calculation subunit then performs the quantitative calculation of the interference weight based on the corrected gas concentration value. Finally, the confidence calculation subunit combines the calculation results from the first two steps to calculate the warning confidence level. This clarifies the input parameters, output parameters, and core calculation functions of each subunit, making the progressively coupled calculation process clear and orderly. Each calculation step relies on the calculation results of the previous step, ensuring the accuracy and consistency of the coupled calculation. This implementation method can standardize the logical flow of progressively coupled calculations, improve the accuracy of calculation results, and provide reliable data for the generation of early warning instructions.

[0027] The existing drift correction subunit does not use standardized calculation logic and only completes temperature drift correction through simple numerical adjustments. This cannot match the actual characteristics of gas concentration changes with thermodynamic temperature in industrial settings. The effects of linear drift and nonlinear coupling are not included in the correction system, and the accuracy of temperature drift correction cannot meet the needs of gas concentration monitoring.

[0028] Based on this, the drift correction subunit incorporates a basic coupling drift correction formula, which is as follows: ; The parameters in the formula corresponding to the standardized thermodynamic temperature ,parameter The dimensions are , It is the international standard unit of thermodynamic temperature, used to visually characterize the degree of hotness or coldness in industrial environments. It is a parameter that has undergone standardization. This eliminates numerical discrepancies caused by varying temperature acquisition ranges, providing a unified calculation benchmark for temperature data across different acquisition scenarios. The standardized raw gas concentration detection value corresponds to the parameters in the formula. ,parameter The dimensions are , It is a common dimension for gas concentration detection in the industrial field, representing the content of the target gas per million parts per volume, and is a standardized parameter. This ensures the comparability of detection data across different concentration ranges, avoiding deviations in correction results due to differences in baseline concentration. The temperature drift sensitivity coefficient corresponds to the parameter in the formula. ,parameter The dimensions are This dimension represents the drift of the original gas concentration reading for every unit change in thermodynamic temperature (Kelvin). It is used to accurately quantify the linear effect of thermodynamic temperature on the gas concentration reading. (Parameter) The values ​​are obtained based on the electrochemical characteristics calibration of commonly used gas sensors in industrial settings. The standard thermodynamic temperature corresponds to the parameters in the formula. ,parameter The dimensions are As a fixed reference value for temperature drift correction, all temperature drift correction calculations are based on the parameter. For reference purposes, to ensure the consistency and stability of the correction logic, the first standardized scaling factor corresponds to the parameter in the formula. ,parameter This is a dimensionless constant used to balance the numerical magnitudes of different terms in the formula, preventing any single term from being too large or too small and excessively affecting the overall correction result, allowing all terms in the formula to work synergistically to correct the problem. The temperature-corrected gas concentration value corresponds to the parameter in the formula. ,parameter The dimensions are , and parameters The dimensions are kept completely consistent to ensure that the corrected gas concentration value can be directly used for subsequent interference weight calculations without further dimension conversion. The theoretical design of the basic coupling drift correction formula is based on the actual working characteristics of gas sensors in industrial settings. The electrochemical characteristics of gas sensors exhibit linear drift with changes in thermodynamic temperature, while a nonlinear coupling relationship exists between thermodynamic temperature and gas concentration. A single linear correction cannot completely eliminate drift errors. Therefore, the formula combines the dual logic of linear correction and nonlinear compensation to achieve accurate temperature drift correction. The logical derivation of the basic coupling drift correction formula relies on the physical characteristics of gas concentration temperature drift. First, the linear influence of thermodynamic temperature on gas concentration is determined, and then... As a linear correction term, it directly offsets the gas concentration drift error caused by the deviation of thermodynamic temperature from the standard value. Then, the nonlinear coupling relationship between thermodynamic temperature and gas concentration is analyzed, and the following is introduced... As a nonlinear compensation component, it makes up for the nonlinear drift error that the linear correction cannot cover, and finally uses the original gas concentration detection value. Subtracting the value of the linear correction term and adding the value of the nonlinear compensation term, we finally obtain the accurate temperature-corrected gas concentration value. The drift correction subunit substitutes the collected standardized parameters into the basic coupled drift correction formula and performs real-time calculations through the embedded computing unit. The calculation process requires no manual intervention, and the results are transmitted to the weight calculation subunit in real time. This implementation can achieve precise correction of gas concentration temperature drift, completely eliminating the linear and nonlinear effects of thermodynamic temperature on gas concentration detection and improving the accuracy of gas concentration monitoring.

[0029] The existing weight calculation subunit does not establish a progressive quantification logic for vibration and electromagnetic interference. It only performs simple calculations for a single interference factor, which cannot reflect the amplification effect of vibration acceleration on electromagnetic interference, nor can it quantify the comprehensive impact of the two types of interference on the corrected gas concentration value. The calculation results of interference weight cannot truly reflect the interference status of the industrial site.

[0030] Based on this, the weight calculation subunit performs progressive coupling weight calculation, which is completed based on the progressive coupling weight calculation formula, which is: ; The parameters in the formula corresponding to the standardized vibration acceleration amplitude ,parameter The dimensions are , It is the international standard unit of acceleration, used to accurately characterize the intensity of mechanical vibrations in industrial settings. It is a standardized parameter. This eliminates the numerical differences caused by different vibration acquisition ranges, ensuring a unified calculation standard for acquired data of varying vibration intensities. The parameters in the standardized electromagnetic interference field strength formula are... ,parameter The dimensions are , It is the international standard unit of electric field strength, used to intuitively characterize the strength of electromagnetic interference in industrial environments. It is a standardized parameter. This ensures the consistency of computational logic under different electromagnetic interference scenarios. The vibration coupling influence coefficient corresponds to the parameters in the formula. ,parameter The dimensions are This is used to accurately quantify the influence of vibration acceleration amplitude on the progressive coupling integrated weight. (Parameters) The values ​​are calibrated based on the vibration characteristics of different types of machinery in industrial settings, adapting to the interference calculation needs of various industrial vibration scenarios. The electromagnetic progressive weighting coefficient corresponds to the parameters in the formula. ,parameter The dimensions are This is used to accurately quantify the influence of electromagnetic interference field strength on the progressive coupling integrated weight, while also reflecting the progressive amplification effect of vibration acceleration on electromagnetic interference. (Parameters) The numerical values ​​are obtained by combining the complexity of the electromagnetic environment at the industrial site. The second standardized proportional coefficient corresponds to the parameters in the formula. ,parameter This is a dimensionless constant used to balance the numerical magnitudes of the numerator and denominator in the formula, ensuring that the calculation result of the progressive coupling comprehensive weight is stable within a reasonable numerical range, avoiding calculation failures caused by numerical overflow or excessively small values. The progressive coupling comprehensive weight corresponds to the parameters in the formula. ,parameter This is a dimensionless parameter used to comprehensively quantify the progressive superposition of vibration acceleration and electromagnetic interference field strength on the temperature-corrected gas concentration value. The magnitude of the value directly reflects the severity of interference in the industrial field, providing a precise quantitative basis for subsequent early warning confidence calculation. The theoretical design of the progressive coupling weight calculation formula relies on the actual laws governing multi-physics field coupling interference in industrial environments. Vibration acceleration induces micro-deformation in sensor hardware, which further amplifies the degradation effect of electromagnetic interference on the sensor signal. The two types of interference exhibit a progressive influence relationship. Simultaneously, the degree of interference is directly related to the temperature-corrected gas concentration. Therefore, the formula adopts a structure combining the numerator and denominator to fully reconstruct the coupling influence relationship between vibration, electromagnetic interference, and the corrected gas concentration. The logical derivation of the progressive coupling weight calculation formula is based on the characteristics of progressive multi-physics field interference. First, the synergistic interference relationship between the vibration acceleration amplitude and the electromagnetic interference field strength is determined. The product of the two can intuitively reflect the superposition effect of the two types of interference. Nonlinear quantification of the synergistic interference effect is performed to match the actual characteristics of increasing interference in industrial settings, and then the temperature-corrected gas concentration value is... Incorporating molecular calculations to reflect the direct impact of interference on the corrected gas concentration signal, the molecular part... The denominator fully characterizes the synergistic interference contributions of vibration, electromagnetic forces, and the corrected gas concentration. By combining the fundamental effects of electromagnetic interference with the nonlinear compensation of coordinated interference, and through the ratio calculation of the numerator and denominator, a progressively coupled comprehensive weight that can truly reflect the degree of interference is finally obtained. The weight calculation subunit receives the temperature-corrected gas concentration value output by the drift correction subunit, and simultaneously calls the standardized vibration acceleration amplitude and standardized electromagnetic interference field strength output by the standardization processing subunit. These three parameters are substituted into the progressively coupled weight calculation formula to complete real-time calculation, and the calculation result is transmitted to the confidence calculation subunit in real time. This implementation can accurately quantify the progressively superimposed effects of vibration and electromagnetic interference, providing reliable interference quantification data for calculating the confidence level of early warning.

[0031] The existing confidence calculation subunit does not combine the synergistic effect of multiple parameters and interference weights in the calculation. It only relies on the value of a single parameter to judge the warning level, which cannot comprehensively reflect the pre-fault state of the industrial site. The calculation results of the warning confidence lack scientificity and accuracy, which can easily lead to false alarms or missed alarms.

[0032] Based on this, the confidence calculation subunit performs advance warning confidence calculation. The advance warning confidence calculation is completed based on the advance warning confidence calculation formula, which is as follows: ; The third standardized scaling factor corresponds to the parameter in the formula. ,parameter This is a dimensionless constant used to standardize the overall calculation results to a range of zero to one, providing a unified standard for judging the confidence level of the early warning, thus facilitating the generation and judgment of subsequent warning commands. The temperature-corrected gas concentration value corresponds to the parameter in the formula. ,parameter This is a precise gas concentration value after temperature drift correction, directly reflecting gas-related early warning information in industrial settings, and is a core parameter for calculating early warning confidence. The parameters in the formula corresponding to the progressively coupled comprehensive weight are... ,parameter This is a quantified value of the interference level, used to correct deviations in the judgment of fault precursors, eliminate the negative impact of interference on the calculation of early warning confidence, and ensure the authenticity of the calculation results. The parameters in the formula corresponding to the early warning confidence level are... ,parameter It is a dimensionless parameter, with a stable value range between zero and one. The higher the value, the higher the probability of an impending equipment failure in the industrial field, and the higher the priority for the sensor to trigger an early warning. The formula... The term is used to characterize the synergistic effect of standardized thermodynamic temperature and standardized vibrational acceleration amplitude, reflecting the amplifying effect of thermodynamic temperature on vibrational disturbances. In the formula... The term is used to characterize the synergistic effect between the standardized electromagnetic interference field strength and the temperature-corrected gas concentration value, reflecting the influence of electromagnetic interference on the corrected gas concentration signal. The sum of the two values ​​comprehensively reflects the intensity of the fault precursor under the synergistic effect of multiple parameters. In the formula... The exponential components constituting the S-shaped function, due to its characteristics, nonlinearly constrain the growth rate of the early warning confidence level, preventing abrupt changes in the confidence level value. This perfectly aligns with the gradual development of fault precursors in industrial settings, ensuring that the trend of the early warning confidence level matches the actual state of the industrial site. The theoretical design of the early warning confidence level calculation formula relies on the nonlinear development law of industrial fault precursors. Equipment fault precursors do not change nonlinearly but are a nonlinear process influenced by multi-parameter coupling and interference. Furthermore, the early warning confidence level needs to remain stable within a controllable range. Therefore, the formula uses the S-shaped function to constrain the calculation results, combining the temperature-corrected gas concentration value and the progressively coupled comprehensive weight as dual core parameters, while also incorporating the synergistic effect of multiple parameters to achieve accurate quantification of the early warning confidence level. The logical derivation of the early warning confidence level calculation formula is based on the quantitative judgment logic of fault precursors. First, the core influencing factors of the early warning confidence level are determined, such as the temperature-corrected gas concentration value. Directly reflects the precursors of gas-related faults, with progressively coupled comprehensive weights. To correct the judgment error caused by interference, the product of the two constitutes the basic strength of the fault precursor after interference correction, and then a multi-parameter synergistic effect term is introduced. The baseline strength of fault precursors is nonlinearly corrected using an S-shaped function, constraining the numerical range and growth rate of the confidence level. Finally, a third standardized scaling factor is used. After completing the numerical standardization process, the advanced warning confidence level that can be directly used for early warning judgment is finally obtained. The confidence calculation subunit calls upon the temperature-corrected gas concentration value, the progressive coupling comprehensive weight, the standardized thermodynamic temperature, the standardized vibration acceleration amplitude, and the standardized electromagnetic interference field strength, substituting all parameters into the advanced warning confidence calculation formula to complete real-time calculation. The calculated advanced warning confidence score is then transmitted to the advanced warning decision module in real time. This implementation method can accurately quantify the confidence score of fault precursors in industrial sites, comprehensively considering the synergistic effect of multiple parameters and the influence of interference correction, providing a scientific and reliable basis for the generation of advanced warning commands.

[0033] The existing advanced early warning decision module does not separate the functions of command generation and transmission. The receiving of early warning confidence, command generation and command output operations are performed in a mixed manner. The response speed of command generation is slow and the stability of command transmission is poor. It is impossible to achieve rapid output of advanced early warning commands and the timeliness of early warning cannot be guaranteed.

[0034] Based on this, the advanced early warning decision module includes an instruction generation subunit and an instruction output subunit. The instruction generation subunit establishes an electrical connection with both the confidence calculation subunit and the instruction output subunit. The instruction generation subunit receives the advanced early warning confidence level output by the confidence calculation subunit and generates a corresponding advanced early warning instruction based on the confidence level value. The instruction output subunit establishes an electrical connection with both the instruction generation subunit and the non-dedicated data transmission conversion module. The instruction output subunit stably transmits the advanced early warning instruction generated by the instruction generation subunit to the non-dedicated data transmission conversion module. This embodiment divides the advanced early warning decision module into two independent subunits. The instruction generation subunit focuses on receiving the advanced early warning confidence level and generating the warning instruction, quickly generating the instruction based on a preset numerical correspondence logic. The instruction output subunit focuses on the stable transmission of the warning instruction. The two subunits have clear division of labor and cooperate effectively, avoiding confusion in the instruction generation and transmission process and ensuring that the advanced early warning instruction can be quickly and stably transmitted to the data transmission module. This implementation method can standardize the generation and transmission process of early warning commands, improve the response speed and transmission stability of early warning commands, and ensure the timeliness of early warnings.

[0035] Existing non-dedicated data transmission conversion modules do not separate format conversion and wireless transmission functions. Inconsistent data formats lead to poor transmission compatibility, low efficiency of wireless transmission, and monitoring data and early warning instructions cannot be uploaded to the back-end terminal in a timely manner. The integrity and real-time performance of data transmission are significantly deficient.

[0036] Based on this, the non-dedicated data transmission conversion module includes a format conversion subunit and a wireless transmission subunit. The format conversion subunit establishes an electrical connection with both the instruction output subunit and the wireless transmission subunit. This subunit performs a general format conversion operation on standardized thermodynamic temperature, temperature-corrected gas concentration values, progressive coupling comprehensive weight, early warning confidence level, and early warning instructions, converting all data and instructions into an industrially common transmission format. The wireless transmission subunit establishes an electrical connection with the format conversion subunit and performs a wireless transmission operation on the converted parameter data and early warning instructions, stably transmitting all content to the backend monitoring terminal. This embodiment splits the non-dedicated data transmission conversion module into two independent subunits. First, the format conversion subunit unifies the data and instruction formats, improving transmission compatibility between different devices. Then, the wireless transmission subunit performs the wireless transmission operation, ensuring data transmission efficiency and stability, allowing monitoring data and early warning instructions from the industrial site to be uploaded to the backend in a timely and complete manner. This embodiment improves data transmission compatibility and efficiency, ensuring the complete transmission and real-time uploading of monitoring data and early warning instructions.

[0037] The existing embedded main control core does not functionally decompose timing scheduling and algorithm control, resulting in chaotic module timing scheduling, ineffective control of coupled computational algorithm processes, disordered collaborative operation rhythm of all modules, and persistently low overall stability and reliability of sensor operation.

[0038] Based on this, the embedded main control core includes a timing scheduling subunit and an algorithm control subunit. The timing scheduling subunit establishes electrical connections with the algorithm control subunit, the four-in-one parameter acquisition unit, the original feature preprocessing module, the progressive coupling calculation module, the advanced early warning decision module, and the non-dedicated data transmission conversion module. The timing scheduling subunit is used to uniformly schedule the working sequence of all modules, setting the start time, runtime, and data transmission sequence of each module to ensure that all modules operate in an orderly manner according to preset logic. The algorithm control subunit establishes electrical connections with both the timing scheduling subunit and the progressive coupling calculation module. The algorithm control subunit is used to control the computational flow of the basic coupling drift correction formula, the progressive coupling weight calculation, and the advanced early warning confidence calculation, managing the start timing of formula calculations, the parameter calling order, and the output rhythm of computation results. This implementation divides the embedded main control core into two independent sub-units. The timing scheduling sub-unit is responsible for the timing control of the overall system, ensuring that the working rhythm of all modules is coordinated and unified. The algorithm control sub-unit is responsible for the algorithm flow control of coupled calculations, ensuring that the three progressive calculation processes are connected in an orderly manner. The two sub-units work together to make the operating logic of the entire sensor system clear and the process standardized. This implementation can standardize the working timing of all modules and the algorithm flow of coupled calculations, ensuring the stable and reliable operation of the entire sensor system.

[0039] Unless otherwise specified, the equipment components involved in the above embodiments are all conventional equipment components, and the connection methods and control methods involved are all conventional connection methods and control methods unless otherwise specified.

[0040] The present invention has been described in detail above with reference to the embodiments. However, those skilled in the art will understand that, without departing from the spirit of the present invention, various specific parameters in the above embodiments can be changed to form multiple specific embodiments, all of which are common variations of the present invention, and will not be described in detail here.

Claims

1. A four-in-one intelligent multi-parameter early warning sensor for industrial monitoring, comprising a four-in-one parameter acquisition unit, a raw feature preprocessing module, a progressive coupling calculation module, an early warning decision module, a non-dedicated data transmission conversion module, and an embedded main control core. The four-in-one parameter acquisition unit is electrically connected to the raw feature preprocessing module and is used to acquire thermodynamic temperature signals, vibration acceleration signals, gas concentration signals, and electromagnetic interference field strength signals. The raw feature preprocessing module is electrically connected to the four-in-one parameter acquisition unit and the progressive coupling calculation module and is used to remove random Gaussian noise from the four types of signals and perform standardized dimensionless processing. The progressive coupling calculation module is connected to the raw feature preprocessing module, ... The advanced early warning decision module is electrically connected to the embedded main control core, and is used to sequentially perform temperature drift correction calculation, progressive interference weight calculation, and advanced early warning confidence calculation. The advanced early warning decision module is electrically connected to the progressive coupling calculation module and the non-dedicated data transmission conversion module, and is used to output advanced early warning commands based on the advanced early warning confidence. The non-dedicated data transmission conversion module is electrically connected to the advanced early warning decision module, and is used to perform data format conversion and wireless transmission. The embedded main control core is electrically connected to the four-in-one parameter acquisition unit, the original feature preprocessing module, the progressive coupling calculation module, the advanced early warning decision module, and the non-dedicated data transmission conversion module, and is used to schedule the working sequence of all modules.

2. The four-in-one intelligent multi-parameter early warning sensor for industrial monitoring according to claim 1, characterized in that, The four-in-one parameter acquisition unit includes a temperature acquisition subunit, a vibration acquisition subunit, a gas concentration acquisition subunit, and an electromagnetic acquisition subunit. The temperature acquisition subunit is electrically connected to the original feature preprocessing module and is used to acquire thermodynamic temperature signals. The vibration acquisition subunit is electrically connected to the original feature preprocessing module and is used to acquire vibration acceleration signals and output vibration acceleration amplitude. The gas concentration acquisition subunit is electrically connected to the original feature preprocessing module and is used to acquire gas concentration signals and output original gas concentration detection values. The electromagnetic acquisition subunit is electrically connected to the original feature preprocessing module and is used to acquire electromagnetic interference field strength signals and output electromagnetic interference field strength.

3. The four-in-one intelligent multi-parameter advanced early warning sensor for industrial monitoring according to claim 2, characterized in that, The original feature preprocessing module includes a noise removal subunit and a normalization processing subunit. The noise removal subunit is electrically connected to the four-in-one parameter acquisition unit and the normalization processing subunit, and is used to remove random Gaussian noise from the thermodynamic temperature signal, vibration acceleration amplitude, original gas concentration detection value, and electromagnetic interference field strength. The normalization processing subunit is electrically connected to the noise removal subunit and the progressively coupled calculation module, and is used to perform normalization dimensionless processing on the noise-removed parameters, and output normalized thermodynamic temperature, normalized vibration acceleration amplitude, normalized original gas concentration detection value, and normalized electromagnetic interference field strength.

4. The four-in-one intelligent multi-parameter advanced early warning sensor for industrial monitoring according to claim 3, characterized in that, The progressive coupling calculation module includes a drift correction subunit, a weight calculation subunit, and a confidence calculation subunit. The drift correction subunit is electrically connected to the standardization processing subunit and the weight calculation subunit. It is used to perform temperature drift correction calculation based on the standardized thermodynamic temperature and the standardized original gas concentration detection value, and output the temperature-corrected gas concentration value. The weight calculation subunit is electrically connected to the drift correction subunit and the confidence calculation subunit. It is used to perform progressive interference weight calculation based on the standardized vibration acceleration amplitude, the standardized electromagnetic interference field strength, and the temperature-corrected gas concentration value, and output the progressive coupling comprehensive weight. The confidence calculation subunit is electrically connected to the weight calculation subunit and the advanced warning decision module. It is used to perform advanced warning confidence calculation based on the temperature-corrected gas concentration value, the progressive coupling comprehensive weight, the standardized thermodynamic temperature, and the standardized vibration acceleration amplitude, and output the advanced warning confidence value.

5. The four-in-one intelligent multi-parameter advanced early warning sensor for industrial monitoring according to claim 4, characterized in that, The drift correction subunit adopts a coupled drift correction logic that combines linear correction and nonlinear compensation. Based on the standardized thermodynamic temperature and the standardized original gas concentration detection value, it performs temperature drift correction calculation by combining the preset temperature drift sensitivity coefficient, the standard thermodynamic temperature and the first standardized proportional coefficient, and outputs the temperature-corrected gas concentration value.

6. The four-in-one intelligent multi-parameter advanced early warning sensor for industrial monitoring according to claim 5, characterized in that, The weight calculation subunit performs progressive coupling weight calculation. The calculation process combines the standardized vibration acceleration amplitude, the standardized electromagnetic interference field strength, and the temperature-corrected gas concentration value. Through preset dimensionless processing logic, it outputs the progressive coupling comprehensive weight, which is used for the subsequent calculation of the advanced warning confidence level.

7. The four-in-one intelligent multi-parameter advanced early warning sensor for industrial monitoring according to claim 6, characterized in that, The confidence calculation subunit performs the advance warning confidence calculation. The calculation process combines the temperature-corrected gas concentration value, progressive coupling comprehensive weight, standardized thermodynamic temperature and standardized vibration acceleration amplitude. Through preset nonlinear calculation logic, the advance warning confidence is output. The advance warning confidence is used to generate the advance warning command.

8. The four-in-one intelligent multi-parameter advanced early warning sensor for industrial monitoring according to claim 7, characterized in that, The advanced early warning decision module includes an instruction generation subunit and an instruction output subunit. The instruction generation subunit is electrically connected to the confidence calculation subunit and the instruction output subunit, and is used to receive the advanced early warning confidence and generate advanced early warning instructions. The instruction output subunit is electrically connected to the instruction generation subunit and the non-dedicated data transmission conversion module, and is used to transmit the advanced early warning instructions to the non-dedicated data transmission conversion module.

9. The four-in-one intelligent multi-parameter advanced early warning sensor for industrial monitoring according to claim 8, characterized in that, The non-dedicated data transmission conversion module includes a format conversion subunit and a wireless transmission subunit. The format conversion subunit is electrically connected to the instruction output subunit and the wireless transmission subunit, and is used to perform general format conversion on standardized thermodynamic temperature, temperature-corrected gas concentration value, progressive coupling comprehensive weight, early warning confidence level and early warning instruction. The wireless transmission subunit is electrically connected to the format conversion subunit and is used to perform wireless transmission of the format-converted parameters and instructions.

10. The four-in-one intelligent multi-parameter advanced early warning sensor for industrial monitoring according to claim 9, characterized in that, The embedded main control core includes a timing scheduling subunit and an algorithm control subunit. The timing scheduling subunit is electrically connected to the algorithm control subunit, the four-in-one parameter acquisition unit, the raw feature preprocessing module, the progressive coupling calculation module, the early warning decision module, and the non-dedicated data transmission conversion module. It is used to uniformly schedule the working timing of all modules. The algorithm control subunit is electrically connected to the timing scheduling subunit and the progressive coupling calculation module. It is used to control the operation flow of temperature drift correction calculation, progressive coupling weight calculation, and early warning confidence calculation.

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