A data processing method and system for pressure measurement
The data processing system's acquisition, analysis, and adjustment units solved the problems of varying data formats from multiple sensors and environmental influences, achieving accurate, stable, and automated fusion of pressure data.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Shanxi Taihang Laboratory Co., Ltd.
- Filing Date
- 2026-03-10
- Publication Date
- 2026-07-21
AI Technical Summary
A single pressure sensor is susceptible to external factors under complex working conditions, leading to measurement errors. Multiple sensors have different data formats and lack an automated mechanism for dynamic adjustment, resulting in limitations in data fusion.
A data processing system is adopted, including acquisition, analysis, processing and adjustment units, to unify the data from multiple pressure sensors through preprocessing, median analysis, environmental labeling and environmental coefficient adjustment.
It improves the accuracy and stability of stress data, avoids data redundancy and conflicts, enhances the automation level and flexibility of the system, and ensures the authenticity and adaptability of stress fusion data.
Smart Images
Figure CN122432953A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data processing technology, and more specifically, to a data processing method and system for pressure measurement. Background Technology
[0002] With the continuous advancement of technology and the increasing complexity of application scenarios, single sensors are gradually becoming insufficient to meet practical needs for pressure measurement. In complex working conditions, such as those involving environmental interference, a single pressure sensor is easily affected by external factors, leading to measurement errors, data loss, or inaccuracies. Therefore, introducing multiple pressure sensors for pressure measurement has become an inevitable trend. However, the different data formats from multiple pressure sensors result in redundancy and conflicts. Furthermore, the fusion of data from different pressure sensors often relies on human experience, failing to dynamically adjust according to actual conditions. This limits the fusion process and lacks an automated mechanism to unify the data generated by multiple pressure sensors.
[0003] Therefore, it is necessary to design a data processing method and system for pressure measurement to solve the problems existing in the current technology. Summary of the Invention
[0004] In view of this, the present invention proposes a data processing method and system for pressure measurement, which aims to solve the problems of data from different data formats and units, resulting in redundancy and conflicts between data, making it impossible to dynamically adjust according to the actual situation, leading to certain limitations in data fusion, and lacking an automated mechanism to unify data generated by multiple pressure sensors.
[0005] In one aspect, the present invention provides a data processing system for pressure measurement, comprising: The acquisition unit is configured to acquire an environmental dataset and pressure data from several pressure sensors, and to preprocess the pressure data to determine the pressure dataset. The analysis unit is configured to determine the median based on the pressure dataset, determine a pressure calculation set based on the pressure dataset and the median, extract the maximum value of the calculated data in the pressure calculation set, determine the pressure deviation data value that deviates the most from the median based on the maximum value of the calculated data, reduce the pressure deviation data value in the pressure dataset, determine a pressure filter set based on the reduction result, and determine pressure fusion data based on the pressure filter set. The processing unit is configured to determine an environmental sequence based on the stress screening set and the environmental dataset, generate an environmental identifier based on the environmental sequence, the environmental identifier including an environmental conformity identifier, an environmental non-conformity identifier, and an environmental suspected conformity identifier, when the environmental non-conformity identifier is identified, perform set partitioning on the environmental sequence, determine the stress environmental coefficient based on the partitioning result, and when the environmental suspected conformity identifier is identified, determine the stress environmental coefficient based on the ratio of the environmental sequence. The adjustment unit is configured to adjust the pressure fusion data according to the pressure environment coefficient.
[0006] Furthermore, the preprocessing of the pressure data to determine the pressure dataset includes: The preprocessing includes data noise reduction, missing value handling, and outlier handling; The acquisition unit performs data noise reduction on the pressure data based on a preset algorithm; The pressure data after noise reduction is processed for missing values. The missing value processing is based on the K nearest neighbor algorithm to determine K samples in the feature space, and the missing values are determined according to the K samples to obtain the target pressure data. The outlier processing involves plotting a box plot based on the target pressure data, correcting the identified outliers, and determining the pressure dataset based on the correction results.
[0007] Furthermore, when determining the median based on the stress dataset, determining the stress calculation set based on the stress dataset and the median, and extracting the maximum value of the calculated data in the stress calculation set, the process includes: The analysis unit arranges each pressure data value in the pressure dataset in descending order, extracts the median, and calculates the absolute value of the difference between each pressure data value in the pressure dataset and the median to determine the pressure calculation set. Each calculated data value in the pressure calculation set is compared to determine the maximum value of the calculated data in the pressure calculation set.
[0008] Furthermore, when reducing the pressure deviation data values in the pressure dataset, determining the pressure filter set based on the reduction result, and determining the pressure fusion data based on the pressure filter set, the process includes: The analysis unit removes the pressure deviation data values from the pressure dataset and constructs a pressure reduction set from the remaining pressure data values in the pressure dataset. Obtain the average value of the data in the pressure reduction set, subtract the average value from each pressure data value in the pressure reduction set and take the absolute value to determine the pressure difference dataset, obtain the maximum difference value in the pressure difference dataset, compare the maximum difference value with a preset maximum difference threshold, and determine the pressure filter set based on the comparison result; If the maximum difference is less than or equal to the maximum difference threshold, then the pressure reduction set is determined as the pressure screening set; If the maximum difference is greater than the maximum difference threshold, then execute a loop instruction until the maximum difference is less than or equal to the maximum difference threshold, and determine the pressure filter set; The pressure fusion data is determined based on the mean of each data point in the pressure screening set.
[0009] Furthermore, when determining the environmental sequence based on the pressure filter set and the environmental dataset, and generating environmental identifiers based on the environmental sequence, the process includes: The processing unit extracts the environmental data of the pressure sensor corresponding to each data in the pressure screening set from the environmental dataset and constructs an environmental data series. Determine the standard environment sequence corresponding to the environment sequence, compare the environment sequence with the standard environment sequence, and generate the environment identifier based on the comparison result; When all environmental data in the environmental data series are equal to the standard environmental data in the standard environmental data series, the environmental conformity identifier is generated for the environmental data series, and the pressure fusion data is not adjusted. When none of the environmental data in the environmental sequence is equal to the standard environmental data in the standard environmental sequence, an environmental mismatch identifier is generated for the environmental sequence. When one or more environmental data points in the environmental data series are equal to the standard environmental data points in the standard environmental data series, and one or more environmental data points are not equal to the standard environmental data points in the standard environmental data series, then an environmental suspected compliance identifier is generated for the environmental data series.
[0010] Furthermore, when the environmental discrepancy marker is identified, the environmental data series is partitioned into sets, and the pressure environment coefficient is determined based on the partitioning results, including: When the environmental data in the environmental data series is less than the standard environmental data in the standard environmental data series, the corresponding environmental data will be used to construct a first environmental data set. When the environmental data in the environmental data series is greater than the standard environmental data in the standard environmental data series, the corresponding environmental data will be used to construct a second environmental data set. The processing unit determines the pressure environment coefficient based on the first environmental data set and the second environmental data set.
[0011] Furthermore, when the environment is identified as potentially matching the identifier, determining the pressure environment coefficient based on the ratio of the environmental data series includes: The processing unit counts the number of standard environmental data in the environmental data series that are equal to the standard environmental data in the standard environmental data series. The processing unit counts the number of discrepancies between the environmental data in the environmental data series and the standard environmental data in the standard environmental data series; Determine the ratio of the standard quantity to the non-standard quantity, and determine the pressure environment coefficient based on the ratio.
[0012] Furthermore, when determining the pressure environment coefficient based on the aforementioned quantity ratio, the following steps are included: The processing unit determines the quantity ratio; When the quantity ratio satisfies the first condition, the pressure environment coefficient of the pressure fusion data is determined according to the first condition. When the quantity ratio satisfies the second condition, the pressure environment coefficient of the pressure fusion data is determined according to the second condition. When the ratio of the quantities satisfies the third condition, the pressure environment coefficient of the pressure fusion data is determined according to the third condition.
[0013] Furthermore, when adjusting the pressure fusion data based on the pressure environment coefficient, the following steps are included: The pressure fusion data is directly proportional to the pressure environment coefficient.
[0014] Compared with existing technologies, the advantages of this invention are as follows: The pressure data is preprocessed by the acquisition unit, making the pressure dataset more accurate and complete, avoiding errors caused by data quality issues. The analysis unit uses the median to determine the pressure calculation set, identifies and removes pressure deviation data values, improving the quality of the pressure screening set and pressure fusion data, avoiding redundancy and conflicts between data, and ensuring that the pressure fusion data truly reflects the actual pressure situation. The processing unit generates environmental labels based on the pressure screening set and the environmental dataset. Different environmental labels correspond to different processing methods, ensuring the accuracy of pressure fusion data adjustment under different environments, avoiding intervention from human experience, and improving the system's automation level and flexibility. The adjustment unit adjusts the pressure fusion data according to the pressure environment coefficient, realizing compensation for the pressure fusion data, thereby effectively unifying the data generated by multiple pressure sensors and improving the reliability and stability of data processing.
[0015] On the other hand, this application also provides a data processing method for pressure measurement, applied to the aforementioned data processing system for pressure measurement, comprising: Acquire environmental datasets and pressure data from several pressure sensors, and preprocess the pressure data to determine the pressure dataset; The median is determined based on the stress dataset, and a stress calculation set is determined based on the stress dataset and the median. The maximum value of the calculated data in the stress calculation set is extracted. The stress deviation data value that deviates the most from the median is determined based on the maximum value of the calculated data. The stress deviation data values in the stress dataset are reduced. A stress filter set is determined based on the reduction result. Stress fusion data is determined based on the stress filter set. An environmental sequence is determined based on the stress screening set and the environmental dataset. An environmental identifier is generated based on the environmental sequence. The environmental identifier includes an environmental conformity identifier, an environmental non-conformity identifier, and an environmental suspected conformity identifier. When an environmental non-conformity identifier is identified, the environmental sequence is divided into sets. The stress environmental coefficient is determined based on the division result. When an environmental suspected conformity identifier is identified, the stress environmental coefficient is determined based on the ratio of the environmental sequence. The pressure fusion data is adjusted based on the pressure environment coefficient.
[0016] It is understandable that the above-mentioned data processing method and system for pressure measurement have the same beneficial effects, and will not be elaborated further here. Attached Figure Description
[0017] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A structural block diagram of a data processing system for pressure measurement provided in an embodiment of the present invention; Figure 2 A flowchart of a data processing method for pressure measurement provided in an embodiment of the present invention. Detailed Implementation
[0018] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.
[0019] In some embodiments of this application, see Figure 1 As shown, a data processing system for pressure measurement includes: The acquisition unit is configured to acquire environmental datasets and pressure data from several pressure sensors, and to preprocess the pressure data to determine the pressure dataset.
[0020] The analysis unit is configured to determine the median based on the pressure dataset, determine the pressure calculation set based on the pressure dataset and the median, extract the maximum value of the calculated data in the pressure calculation set, determine the pressure deviation data value that deviates the most from the median based on the maximum value of the calculated data, reduce the pressure deviation data values in the pressure dataset, determine the pressure filter set based on the reduction result, and determine the pressure fusion data based on the pressure filter set.
[0021] The processing unit is configured to determine the environmental sequence based on the stress screening set and the environmental dataset, generate environmental identifiers based on the environmental sequence, including environmental conformity identifiers, environmental non-conformity identifiers, and environmental suspected conformity identifiers, and when an environmental non-conformity identifier is identified, the environmental sequence is divided into sets, and the stress environmental coefficient is determined based on the division result. When an environmental suspected conformity identifier is identified, the stress environmental coefficient is determined based on the ratio of the environmental sequence.
[0022] The adjustment unit is configured to adjust the pressure fusion data according to the pressure environment coefficient.
[0023] Specifically, the acquisition unit is responsible for acquiring environmental datasets and pressure data from several pressure sensors. The environmental dataset represents a collection of multiple environmental data points, which are collected by acquisition devices such as temperature and humidity sensors. During the pressure measurement process, due to data noise and anomalies that may occur during the sensing process of pressure sensors, preprocessing is used to remove noise, outliers, and other interference factors from the data, thereby determining the pressure dataset. This provides a reliable foundation for subsequent analysis and processing, improving the stability and accuracy of the entire data processing system. The pressure dataset represents the collection of pressure data after preprocessing. The analysis unit determines the median based on the pressure dataset. The median, as the middle value in the pressure dataset, reflects the central tendency of the data. A pressure calculation set is determined based on the pressure dataset and the median, and the maximum value of the calculated data is extracted from this set. By identifying the maximum value, the pressure deviation data value that deviates most from the median can be found within the pressure calculation set. The purpose of this process is to identify biased data, as data that deviates excessively from the median is likely due to sensor malfunction or abnormal interference. If biased data is not removed, it will interfere with the overall data analysis and fusion results, leading to significant deviations in the final pressure fusion data. Therefore, by reducing the pressure deviation data values in the pressure dataset, a pressure filter set is determined based on the reduction results, and the pressure fusion data is determined based on this filter set. This more realistically reflects the actual pressure situation, improving the accuracy and reliability of the pressure fusion data. During pressure acquisition, each pressure sensor, due to differences in model, parameter standards, etc., perceives the environment differently. For example, when using piezoresistive and capacitive pressure sensors for pressure measurement, piezoresistive sensors are sensitive to temperature changes; the resistance of their internal semiconductor materials changes with temperature, thus affecting the accuracy of data fusion. Capacitive sensors, on the other hand, are significantly affected by ambient humidity; changes in humidity alter the sensor's capacitance, leading to deviations in data fusion. The processing unit determines the environmental data series based on the pressure filter set and the environmental dataset, and generates environmental labels accordingly. When an environmental label is detected that does not match the data series, the environmental data series is divided into sets, and a pressure environment coefficient is determined based on the division results. When an environmental label is detected that is suspected to match the data series, the pressure environment coefficient is determined based on the ratio of the environmental data series. By comprehensively considering the impact of environmental factors on the data generated by different pressure sensors, and by determining the pressure environment coefficient, the pressure fusion data can be adjusted accordingly to eliminate the influence of environmental factors, making the pressure data fusion results closer to the actual pressure conditions, thereby improving the accuracy and adaptability of the measurement.
[0024] Understandably, the performance of pressure sensors may change under different environmental conditions. By adjusting the pressure environment coefficient, the system can adjust the pressure fusion data under different environments, avoiding the judgment of human experience, which would affect the accuracy of pressure measurement results, and improving the automation level and flexibility of the entire data processing system.
[0025] In some embodiments of this application, when preprocessing the pressure data to determine the pressure dataset, the preprocessing includes: data denoising, missing value processing, and outlier processing. The acquisition unit performs data denoising on the pressure data based on a preset algorithm, performs missing value processing on the denoised pressure data, and determines the missing values based on the K nearest neighbor algorithm to obtain the target pressure data. The outlier processing plots a box plot based on the target pressure data and corrects the identified outliers. The pressure dataset is determined based on the correction results.
[0026] Specifically, in actual pressure measurement, the data acquired by pressure sensors is often subject to various noise interferences, which may originate from thermal noise of electronic components and electromagnetic interference in the environment. The presence of noise affects the accuracy and reliability of the data, reduces data quality, and may result in missing data due to sensor malfunctions, communication interruptions, or other reasons. Failure to process missing values will affect the integrity of the data and the accuracy of the analysis results. The acquisition unit performs data noise reduction on the pressure data based on preset algorithms. These preset algorithms include mean filtering, median filtering, and wavelet filtering algorithms. Data noise reduction using these preset algorithms can effectively filter out these noise signals, improving the data quality of the pressure dataset. The K-nearest neighbor algorithm determines the K nearest neighbors to the missing value sample in the feature space; these K samples and the missing value sample have high similarity in features. Missing values are identified by analyzing the feature values of the K samples (using the average or weighted average of the feature values). Once identified, these missing values are filled into the original pressure data to obtain the target pressure data. This avoids analytical bias caused by missing data, improves the reliability of the data analysis results, and provides a complete data foundation for subsequent outlier handling and the final determination of the pressure dataset. Outlier handling involves drawing box plots based on the target pressure data. Box plots can visually display the data distribution. Outliers may be caused by momentary sensor malfunctions, extreme environmental interference, etc. If not corrected, these outliers will affect subsequent data analysis and pressure fusion results, leading to significant deviations in the fusion results. The identification process is lengthy and mature, and will not be described in detail here. When correcting identified outliers, they are replaced with boundary values (such as the upper and lower limits in the box plot) or interpolated to calculate reasonable values based on adjacent normal data to replace the outliers. The pressure dataset is determined based on the corrected results, ensuring the integrity and accuracy of the data. In some embodiments of this application, when determining the median based on the pressure dataset, determining the pressure calculation set based on the pressure dataset and the median, and extracting the maximum value of the calculated data in the pressure calculation set, the method includes: the analysis unit arranging each pressure data value in the pressure dataset in descending order, extracting the median, subtracting each pressure data value in the pressure dataset from the median and taking the absolute value, determining the pressure calculation set, comparing each calculated data value in the pressure calculation set, and determining the maximum value of the calculated data in the pressure calculation set.
[0027] Specifically, the median is extracted by arranging each pressure data value in the pressure dataset in descending order. The median effectively reflects the central tendency of the data. Compared to the mean, the median is less affected by extreme values. In pressure measurement scenarios, some extreme and abnormal pressure data values may occur under complex working conditions. If the mean is used as a representative of the central tendency of the dataset, these extreme values will raise or lower the mean, failing to accurately reflect the pressure level under normal conditions. The median effectively avoids this situation, providing a stable and reliable benchmark for subsequent determination of the pressure calculation set and identification of abnormal data. For example, in a pressure dataset {10, 12, 15, 20, 100}, the mean is 27.4, while the median is 15. The median better represents the level of most pressure data values in this dataset, making subsequent data processing based on the median more realistic. The pressure calculation set is determined by subtracting each pressure data value from the median and taking the absolute value. This process highlights the degree of deviation between the pressure data values and the median. For example, in a relatively stable pressure measurement environment, most pressure data values fluctuate slightly around the median, such as within ±5. However, if a pressure data value deviates from the median by ±20 or even more, it will be reflected in the pressure calculation set. By comparing each calculated data value in the pressure calculation set to determine the maximum value, the pressure data value corresponding to this maximum value is the deviation data from the median. By identifying the maximum value, the accuracy and reliability of the entire pressure measurement data processing system are ensured.
[0028] In some embodiments of this application, when reducing pressure deviation data values in a pressure dataset, determining a pressure filter set based on the reduction result, and determining pressure fusion data based on the pressure filter set, the process includes: an analysis unit reducing pressure deviation data values in a pressure dataset and constructing a pressure reduction set from the remaining pressure data values in the pressure dataset; obtaining the average value of the data in the pressure reduction set; subtracting each pressure data value in the pressure reduction set from the average value and taking the absolute value to determine a pressure difference dataset; obtaining the maximum difference value in the pressure difference dataset; comparing the maximum difference value with a pre-set maximum difference threshold; determining a pressure filter set based on the comparison result; if the maximum difference value is less than or equal to the maximum difference threshold, then the pressure reduction set is determined as the pressure filter set; if the maximum difference value is greater than the maximum difference threshold, then a loop instruction is executed until the maximum difference value is less than or equal to the maximum difference threshold, thus determining the pressure filter set; and determining the pressure fusion data based on the average value of each data in the pressure filter set.
[0029] Specifically, after identifying and removing pressure deviation data values based on the median, a pressure reduction set is constructed and its average value is calculated. The difference between each pressure data value in the reduction set and the average value is taken as the absolute value to further uncover potential pressure deviation data. Pressure data values should exhibit a certain central tendency under normal operating conditions. By comparing the maximum difference with a pre-set maximum difference threshold, a secondary screening of the data is achieved, ensuring the reliability of the pressure reduction set. The median was initially chosen to effectively avoid interference from extreme values and accurately reflect the central tendency of the data, thus highlighting the deviation data with the largest deviation from the median. In the secondary screening process, the average value considers all data. Using the average value for further data analysis after constructing the pressure reduction set is because pressure deviation data values have already been removed, resulting in a relatively stable and concentrated pressure reduction set. By calculating the average value, the deviation of each pressure data value in the reduction set from the overall average level can be measured in detail, thus more accurately identifying some "deviation data values" that may still exist after the initial screening.
[0030] Understandably, when the maximum difference exceeds the maximum difference threshold, a loop instruction is executed. This loop instruction means repeating the secondary filtering process, reducing the pressure deviation data values, and continuing to build the pressure reduction set. The average data value is then redefined, and a new pressure difference dataset is determined, resulting in a completely new maximum difference. However, the pressure deviation data value identified in the repeat instruction is based on the data corresponding to the maximum difference. For example, after one filtering step, the pressure reduction set might be {5, 7, 8, 10, 20}, with an average value of 10. The corresponding pressure difference dataset would be {5, 3, 2, 0, 10}, with a maximum difference of 10. If the maximum difference threshold is 8, then a loop instruction needs to be executed. In this case, the identified pressure deviation data value is based on the difference... The data corresponding to the maximum value, which is 20 in the pressure reduction set, needs to be removed. The newly determined pressure reduction set is represented as {5, 7, 8, 10}, and the average value of the newly determined data is 7.5. The corresponding pressure difference dataset is {2.5, 0.5, 0.5, 2.5}. At this time, the maximum difference is 2.5, which is less than the set maximum difference threshold. Therefore, the newly determined pressure reduction set is used as the pressure filtering set. Through secondary filtering and loop instructions, the maximum difference is used until the condition is met. The dynamic loop mechanism adapts to the changes in pressure data under different complex working conditions. Even when there are multiple "deviation data values", data can be gradually removed to avoid data residue caused by incomplete filtering in one step, thus ensuring the reliability and stability of data processing.
[0031] In some embodiments of this application, when determining an environmental sequence based on a pressure screening set and an environmental dataset, and generating an environmental identifier based on the environmental sequence, the process includes: a processing unit extracting environmental data from the pressure sensors corresponding to each data point in the pressure screening set from the environmental dataset, constructing an environmental sequence, determining a standard environmental sequence corresponding to the environmental sequence, comparing the environmental sequence with the standard environmental sequence, generating an environmental identifier based on the comparison result, generating an environmental compliance identifier for the environmental sequence when all environmental data in the environmental sequence are equal to the standard environmental data in the standard environmental sequence, and not adjusting the pressure fusion data; generating an environmental non-compliance identifier for the environmental sequence when none of the environmental data in the environmental sequence are equal to the standard environmental data in the standard environmental sequence; and generating an environmental suspected compliance identifier for the environmental sequence when one or more environmental data in the environmental sequence are equal to the standard environmental data in the standard environmental sequence, and one or more environmental data are not equal to the standard environmental data in the standard environmental sequence.
[0032] Specifically, by defining a pressure filter set, pressure data from some pressure sensors can be excluded. Therefore, it's unnecessary to include the excluded pressure sensors as the evaluation benchmark for environmental measurements; only the environmental data of the pressure sensors corresponding to the data in the pressure filter set needs to be determined. Comparing the environmental data series with a standard environmental data series allows for accurate assessment of the degree of matching between the measurement environment of each pressure sensor and the standard environment. The standard environmental data series is obtained from the user manual of each pressure sensor, and the environmental data in the environmental data series corresponds one-to-one with the standard environmental data in the standard environmental data series. The environmental data includes data such as temperature and humidity. When an environmental compliance indicator is generated, it indicates that the current environment is consistent with the standard environment, and all pressure sensors are in ideal working condition, so no adjustment to the pressure fusion data is needed. When an environmental non-compliance indicator or a suspected compliance indicator is generated, it indicates that some pressure sensors have not reached ideal working condition, and interference factors in the environment need to be considered. For example, in variable outdoor pressure measurement scenarios, environmental factors are complex and constantly changing. By judging the environmental indicators, the system can dynamically adjust the pressure fusion data according to different environmental conditions, improving the stability of data fusion and thus ensuring the validity of the pressure measurement results.
[0033] In some embodiments of this application, when an environmental discrepancy marker is identified, the environmental data series is divided into sets, and the pressure environmental coefficient is determined based on the division results. This includes: when the environmental data in the environmental data series is less than the standard environmental data in the standard environmental data series, the corresponding environmental data is used to construct a first environmental data set; when the environmental data in the environmental data series is greater than the standard environmental data in the standard environmental data series, the corresponding environmental data is used to construct a second environmental data set; and the processing unit determines the pressure environmental coefficient based on the first environmental data set and the second environmental data set.
[0034] Specifically, based on the relationship between environmental data and standard environmental data, the data is divided into a first environmental data set and a second environmental data set, which enables refined analysis of environmental factors and improves the accuracy of determining the pressure environmental coefficient.
[0035] Specifically, the pressure environmental coefficient is obtained by counting the first number of environmental data in the first environmental dataset and the second number of environmental data in the second environmental dataset, using the following formula: ; Where K represents the pressure environment coefficient, e represents the natural constant (valued at 2.718 here), n represents the first quantity, Ri represents the i-th environmental data in the first environmental dataset, Qi represents the standard environmental data corresponding to the i-th environmental data in the first environmental dataset, m represents the second quantity, Lj represents the j-th environmental data in the second environmental dataset, and Hj represents the standard environmental data corresponding to the j-th environmental data in the second environmental dataset. By determining the pressure environment coefficient, adjustments based on human experience during data fusion are avoided, thus improving the overall automation and flexibility of the system.
[0036] In some embodiments of this application, when an environmental suspected compliance marker is identified, the pressure environment coefficient is determined based on the ratio of the environmental data series, including: the processing unit counts the number of standard environmental data in the environmental data series that are equal to the standard environmental data in the standard environmental data series; the processing unit counts the number of non-standard environmental data in the environmental data series that are not equal to the standard environmental data in the standard environmental data series; the processing unit determines the ratio of the number of standard data to the number of non-standard data; and the pressure environment coefficient is determined based on the ratio.
[0037] In some embodiments of this application, when determining the pressure environment coefficient based on the quantity ratio, the following steps are included: a processing unit determines the quantity ratio; when the quantity ratio meets a first condition, the pressure environment coefficient of the pressure fusion data is determined according to the first condition; when the quantity ratio meets a second condition, the pressure environment coefficient of the pressure fusion data is determined according to the second condition; and when the quantity ratio meets a third condition, the pressure environment coefficient of the pressure fusion data is determined according to the third condition.
[0038] Specifically, by statistically analyzing the number of standard and non-standard environmental data in the environmental data series and determining the ratio of these numbers, a quantitative basis is provided for determining the pressure environment coefficient. The processing unit pre-sets a first preset ratio and a second preset ratio, where the first preset ratio is greater than the second preset ratio. It also sets a first preset pressure environment coefficient, a second preset pressure environment coefficient, and a third preset pressure environment coefficient, where the first preset pressure environment coefficient is greater than the second preset pressure environment coefficient, and the second preset pressure environment coefficient is greater than the third preset pressure environment coefficient. When the ratio is greater than the first preset ratio, the first condition is met, and the first preset pressure environment coefficient is determined as the pressure environment coefficient. When the ratio is less than or equal to the first preset ratio but greater than the second preset ratio, the second condition is met, and the second preset pressure environment coefficient is determined as the pressure environment coefficient. When the ratio is less than or equal to the second preset ratio, the third condition is met, and the third preset pressure environment coefficient is determined as the pressure environment coefficient. By selecting the corresponding preset pressure environment coefficient based on the quantity ratio, dynamic adjustment of pressure fusion data can be achieved, ensuring adjustment accuracy and enhancing the system's adaptability in complex environments. This not only improves data processing efficiency but also reduces human intervention, avoiding subjectivity and bias, thereby enhancing the reliability of the entire system.
[0039] In some embodiments of this application, when adjusting the pressure fusion data according to the pressure environment coefficient, the pressure fusion data and the pressure environment coefficient are proportional.
[0040] Specifically, different environmental factors have varying degrees of influence on pressure measurement. By leveraging the direct proportionality between pressure fusion data and the pressure environment coefficient, the system can dynamically adjust the pressure fusion data based on real-time environmental conditions. Whether it's a single change in environmental factors such as temperature and humidity, or a combination of changes in multiple factors, the system can adjust the pressure fusion data according to the pressure environment coefficient to adapt to different environmental conditions. This enhances the system's environmental adaptability and stability, thereby improving the accuracy of data fusion from multiple pressure sensors.
[0041] In the above embodiments, the pressure data is preprocessed by the acquisition unit to make the pressure dataset more accurate and complete, avoiding errors caused by data quality issues. The analysis unit uses the median to determine the pressure calculation set, identifies and removes pressure deviation data values, improves the quality of the pressure screening set and pressure fusion data, avoids redundancy and conflicts between data, and ensures that the pressure fusion data truly reflects the actual pressure situation. The processing unit generates environmental labels based on the pressure screening set and the environmental dataset. Different environmental labels correspond to different processing methods, ensuring the accuracy of pressure fusion data adjustment under different environments, avoiding intervention from human experience, and improving the system's automation level and flexibility. The adjustment unit adjusts the pressure fusion data according to the pressure environment coefficient, realizing compensation for the pressure fusion data, thereby effectively unifying the data generated by multiple pressure sensors and improving the reliability and stability of data processing.
[0042] In another preferred embodiment based on the above embodiments, see [reference] Figure 2 As shown, this embodiment provides a data processing method for pressure measurement, applied to the aforementioned data processing system for pressure measurement, including: S100: Acquire environmental datasets and pressure data from several pressure sensors, preprocess the pressure data, and determine the pressure dataset.
[0043] S200: Determine the median based on the pressure dataset, and determine the pressure calculation set based on the pressure dataset and the median. Extract the maximum value of the calculated data in the pressure calculation set, determine the pressure deviation data value that deviates the most from the median based on the maximum value of the calculated data, reduce the pressure deviation data values in the pressure dataset, determine the pressure filter set based on the reduction results, and determine the pressure fusion data based on the pressure filter set.
[0044] S300: Determine the environmental sequence based on the stress screening set and the environmental dataset, generate environmental identifiers based on the environmental sequence, including environmental compliance identifiers, environmental non-compliance identifiers, and environmental suspected compliance identifiers. When an environmental non-compliance identifier is identified, the environmental sequence is divided into sets, and the stress environmental coefficient is determined based on the division results. When an environmental suspected compliance identifier is identified, the stress environmental coefficient is determined based on the ratio of the environmental sequence.
[0045] S400: Adjust pressure fusion data based on pressure environment coefficient.
[0046] Specifically, the acquisition unit preprocesses the pressure data to make the pressure dataset more accurate and complete, avoiding errors caused by data quality issues. The analysis unit uses the median to determine the pressure calculation set, identifies and removes pressure deviation data values, improves the quality of the pressure filter set and pressure fusion data, avoids redundancy and conflicts between data, and ensures that the pressure fusion data truly reflects the actual pressure situation. The processing unit generates environmental labels based on the pressure filter set and environmental dataset. Different environmental labels correspond to different processing methods, ensuring the accuracy of pressure fusion data adjustments under different environments, avoiding intervention from human experience, and improving the system's automation level and flexibility. The adjustment unit adjusts the pressure fusion data according to the pressure environment coefficient, realizing compensation for the pressure fusion data, thereby effectively unifying the data generated by multiple pressure sensors and improving the reliability and stability of data processing.
[0047] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0048] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0049] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0050] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.
Claims
1. A data processing system for pressure measurement, characterized in that, include: The acquisition unit is configured to acquire an environmental dataset and pressure data from several pressure sensors, and to preprocess the pressure data to determine the pressure dataset. The analysis unit is configured to determine the median based on the pressure dataset, determine a pressure calculation set based on the pressure dataset and the median, extract the maximum value of the calculated data in the pressure calculation set, determine the pressure deviation data value that deviates the most from the median based on the maximum value of the calculated data, reduce the pressure deviation data value in the pressure dataset, determine a pressure filter set based on the reduction result, and determine pressure fusion data based on the pressure filter set. The processing unit is configured to determine an environmental sequence based on the stress screening set and the environmental dataset, generate an environmental identifier based on the environmental sequence, the environmental identifier including an environmental conformity identifier, an environmental non-conformity identifier, and an environmental suspected conformity identifier, when the environmental non-conformity identifier is identified, perform set partitioning on the environmental sequence, determine the stress environmental coefficient based on the partitioning result, and when the environmental suspected conformity identifier is identified, determine the stress environmental coefficient based on the ratio of the environmental sequence. The adjustment unit is configured to adjust the pressure fusion data according to the pressure environment coefficient.
2. The data processing system for pressure measurement according to claim 1, characterized in that, Preprocessing the pressure data to determine the pressure dataset includes: The preprocessing includes data noise reduction, missing value handling, and outlier handling; The acquisition unit performs data noise reduction on the pressure data based on a preset algorithm; The pressure data after noise reduction is processed for missing values. The missing value processing is based on the K nearest neighbor algorithm to determine K samples in the feature space, and the missing values are determined according to the K samples to obtain the target pressure data. The outlier processing involves plotting a box plot based on the target pressure data, correcting the identified outliers, and determining the pressure dataset based on the correction results.
3. The data processing system for pressure measurement according to claim 2, characterized in that, When determining the median based on the stress dataset, determining the stress calculation set based on the stress dataset and the median, and extracting the maximum value of the calculated data in the stress calculation set, the process includes: The analysis unit arranges each pressure data value in the pressure dataset in descending order, extracts the median, and calculates the absolute value of the difference between each pressure data value in the pressure dataset and the median to determine the pressure calculation set. Each calculated data value in the pressure calculation set is compared to determine the maximum value of the calculated data in the pressure calculation set.
4. The data processing system for pressure measurement according to claim 3, characterized in that, The process of reducing the pressure deviation data values in the pressure dataset, determining a pressure filter set based on the reduction results, and determining pressure fusion data based on the pressure filter set includes: The analysis unit removes the pressure deviation data values from the pressure dataset and constructs a pressure reduction set from the remaining pressure data values in the pressure dataset. Obtain the average value of the data in the pressure reduction set, subtract the average value from each pressure data value in the pressure reduction set and take the absolute value to determine the pressure difference dataset, obtain the maximum difference value in the pressure difference dataset, compare the maximum difference value with a preset maximum difference threshold, and determine the pressure filter set based on the comparison result; If the maximum difference is less than or equal to the maximum difference threshold, then the pressure reduction set is determined as the pressure screening set; If the maximum difference is greater than the maximum difference threshold, then execute a loop instruction until the maximum difference is less than or equal to the maximum difference threshold, and determine the pressure filter set; The pressure fusion data is determined based on the mean of each data point in the pressure screening set.
5. The data processing system for pressure measurement according to claim 4, characterized in that, When determining the environmental data sequence based on the stress filter set and the environmental dataset, and generating environmental identifiers based on the environmental data sequence, the process includes: The processing unit extracts the environmental data of the pressure sensor corresponding to each data in the pressure screening set from the environmental dataset and constructs an environmental data series. Determine the standard environment sequence corresponding to the environment sequence, compare the environment sequence with the standard environment sequence, and generate the environment identifier based on the comparison result; When all environmental data in the environmental data series are equal to the standard environmental data in the standard environmental data series, the environmental conformity identifier is generated for the environmental data series, and the pressure fusion data is not adjusted. When none of the environmental data in the environmental sequence is equal to the standard environmental data in the standard environmental sequence, an environmental mismatch identifier is generated for the environmental sequence. When one or more environmental data points in the environmental data series are equal to the standard environmental data points in the standard environmental data series, and one or more environmental data points are not equal to the standard environmental data points in the standard environmental data series, then an environmental suspected compliance identifier is generated for the environmental data series.
6. The data processing system for pressure measurement according to claim 5, characterized in that, When the environmental non-compliance identifier is detected, the environmental data series is divided into sets, and the pressure environment coefficient is determined based on the division results, including: When the environmental data in the environmental data series is less than the standard environmental data in the standard environmental data series, the corresponding environmental data will be used to construct a first environmental data set. When the environmental data in the environmental data series is greater than the standard environmental data in the standard environmental data series, the corresponding environmental data will be used to construct a second environmental data set. The processing unit determines the pressure environment coefficient based on the first environmental data set and the second environmental data set.
7. The data processing system for pressure measurement according to claim 6, characterized in that, When an environment is identified as potentially matching the identifier, determining the pressure environment coefficient based on the ratio of the environmental data series includes: The processing unit counts the number of standard environmental data in the environmental data series that are equal to the standard environmental data in the standard environmental data series. The processing unit counts the number of discrepancies between the environmental data in the environmental data series and the standard environmental data in the standard environmental data series; Determine the ratio of the standard quantity to the non-standard quantity, and determine the pressure environment coefficient based on the ratio.
8. The data processing system for pressure measurement according to claim 7, characterized in that, When determining the pressure environment coefficient based on the aforementioned quantity ratio, the following is included: The processing unit determines the quantity ratio; When the quantity ratio satisfies the first condition, the pressure environment coefficient of the pressure fusion data is determined according to the first condition. When the quantity ratio satisfies the second condition, the pressure environment coefficient of the pressure fusion data is determined according to the second condition. When the ratio of the quantities satisfies the third condition, the pressure environment coefficient of the pressure fusion data is determined according to the third condition.
9. The data processing system for pressure measurement according to claim 8, characterized in that, When adjusting the pressure fusion data according to the pressure environment coefficient, the following are included: The pressure fusion data is directly proportional to the pressure environment coefficient.
10. A data processing method for pressure measurement, applied to the data processing system for pressure measurement as described in any one of claims 1-9, characterized in that, include: Acquire environmental datasets and pressure data from several pressure sensors, and preprocess the pressure data to determine the pressure dataset; The median is determined based on the stress dataset, and a stress calculation set is determined based on the stress dataset and the median. The maximum value of the calculated data in the stress calculation set is extracted. The stress deviation data value that deviates the most from the median is determined based on the maximum value of the calculated data. The stress deviation data values in the stress dataset are reduced. A stress filter set is determined based on the reduction result. Stress fusion data is determined based on the stress filter set. An environmental sequence is determined based on the stress screening set and the environmental dataset. An environmental identifier is generated based on the environmental sequence. The environmental identifier includes an environmental conformity identifier, an environmental non-conformity identifier, and an environmental suspected conformity identifier. When an environmental non-conformity identifier is identified, the environmental sequence is divided into sets. The stress environmental coefficient is determined based on the division result. When an environmental suspected conformity identifier is identified, the stress environmental coefficient is determined based on the ratio of the environmental sequence. The pressure fusion data is adjusted based on the pressure environment coefficient.