CN113887044A - Data quality monitoring method, device, equipment and readable storage medium - Google Patents
Data quality monitoring method, device, equipment and readable storage medium Download PDFInfo
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Abstract
The invention provides a data quality monitoring method, a device, equipment and a readable storage medium, wherein the data quality monitoring method comprises the following steps: determining source components affecting a measured measurement uncertainty in an engine emissions test and creating a mathematical model of the measured measurement uncertainty; obtaining a measured value of an engine emission test, and substituting the measured value into the mathematical model to obtain the magnitude of each source component of the measured measurement uncertainty; judging whether the numerical value of each source component is in a preset range or not; and if the numerical value of at least one source component is not in a preset range, outputting prompt information for controlling the at least one source component. The invention quantitatively analyzes the measured measurement uncertainty of each source component in the engine emission test to obtain an effective test data quality monitoring method, and can ensure the accuracy of the emission result of each pollutant ratio measured in a laboratory.
Description
Technical Field
The present invention relates to the field of inspection and detection technologies, and in particular, to a method, an apparatus, a device, and a readable storage medium for monitoring data quality.
Background
Measurement is an indispensable work in various fields of modern science and technology, industrial production and daily life, and the quality of a measurement result has a profound influence on social activities. For example, accuracy of cargo weighing in export trade; the amount of medical agent, etc. When reporting measurements, quantitative specifications must be given on the quality of the data to determine the trustworthiness of the measurement, and measurement uncertainty is a quantitative representation of the quality of the measurement, and the usefulness of a measurement depends largely on the magnitude of its uncertainty.
The engine emission detection is a measurement process integrating more variables, and the data quality evaluation of the emission detection result is relatively difficult. In the existing engine emission test, quality monitoring of a laboratory is usually restricted by industry standards or enterprise management regulations, the possibility of missing items and repeated work exists, even if the same test equipment and engine are adopted, emission tests are carried out on engine samples by different operators at different time, detection results have small difference, and the data quality cannot be effectively monitored.
Disclosure of Invention
The invention mainly aims to provide a data quality monitoring method, a device, equipment and a readable storage medium, and aims to solve the technical problem that the data quality of the engine pollutant specific emission detection cannot be effectively monitored in an engine emission test.
In a first aspect, the present invention provides a data quality monitoring method, including the following steps:
determining source components affecting a measured measurement uncertainty in an engine emissions test and creating a mathematical model of the measured measurement uncertainty;
obtaining a measured value of an engine emission test, and substituting the measured value into the mathematical model to obtain the magnitude of each source component of the measured measurement uncertainty;
judging whether the numerical value of each source component is in a preset range or not;
and if the numerical value of at least one source component is not in a preset range, outputting prompt information for controlling the at least one source component.
Optionally, the step of determining the source components that affect the measured uncertainty in the engine emissions test comprises:
when the measured measurement uncertainty in the engine emission test is determined to be caused by the repeatability of the test, determining that the source component of the measurement uncertainty is a first source component;
when it is determined that the measured measurement uncertainty in the engine emissions test is due to the accuracy of the test equipment, the source component of the measurement uncertainty is determined to be the second source component.
Optionally, the step of creating a mathematical model of the measured measurement uncertainty comprises:
creating a mathematical model of the first source component of the measured measurement uncertainty from the first source component;
creating a mathematical model of the second source component of the measured measurement uncertainty from the second source component;
and synthesizing the mathematical model of the first source component and the mathematical model of the second source component to obtain the mathematical model of the measured measurement uncertainty.
Optionally, the step of determining whether the magnitude of each source component is within a preset range includes:
and if the numerical values of all the source components are in the preset range, outputting prompt information for keeping the existing engine emission test scheme.
In a second aspect, the present invention further provides a data quality monitoring apparatus, including:
a determination module for determining source components that affect a measured measurement uncertainty in an engine emissions test and creating a mathematical model of the measured measurement uncertainty;
the acquisition module is used for acquiring a measured value of an engine emission test, and substituting the measured value into the mathematical model to obtain the magnitude of each source component of the measured measurement uncertainty;
the judging module is used for judging whether the numerical value of each source component is in a preset range or not;
and the output module is used for outputting prompt information for controlling the at least one source component if the numerical value of the at least one source component is not in a preset range.
Optionally, the determining module is configured to:
when the measured measurement uncertainty in the engine emission test is determined to be caused by the repeatability of the test, determining that the source component of the measurement uncertainty is a first source component;
when it is determined that the measured measurement uncertainty in the engine emissions test is due to the accuracy of the test equipment, the source component of the measurement uncertainty is determined to be the second source component.
Optionally, the determining module is configured to:
creating a mathematical model of the first source component of the measured measurement uncertainty from the first source component;
creating a mathematical model of the second source component of the measured measurement uncertainty from the second source component;
and synthesizing the mathematical model of the first source component and the mathematical model of the second source component to obtain the mathematical model of the measured measurement uncertainty.
Optionally, the output module is further configured to:
and if the numerical values of all the source components are in the preset range, outputting prompt information for keeping the existing engine emission test scheme.
In a third aspect, the present invention further provides a data quality monitoring device, which includes a processor, a memory, and a data quality monitoring program stored on the memory and executable by the processor, wherein when the data quality monitoring program is executed by the processor, the steps of the data quality monitoring method described above are implemented.
In a fourth aspect, the present invention further provides a readable storage medium, wherein the readable storage medium stores a data quality monitoring program, and when the data quality monitoring program is executed by a processor, the data quality monitoring program implements the steps of the data quality monitoring method as described above.
In the present invention, source components affecting the measured measurement uncertainty in an engine emissions test are determined and a mathematical model of the measured measurement uncertainty is created; obtaining a measured value of an engine emission test, and substituting the measured value into the mathematical model to obtain the magnitude of each source component of the measured measurement uncertainty; judging whether the numerical value of each source component is in a preset range or not; and if the numerical value of at least one source component is not in a preset range, outputting prompt information for controlling the at least one source component. The invention quantitatively analyzes the measured measurement uncertainty of each source component in the engine emission test to obtain an effective test data quality monitoring method, and can ensure the accuracy of the emission result of each pollutant ratio measured in a laboratory.
Drawings
Fig. 1 is a schematic hardware configuration diagram of a data quality monitoring device according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating an embodiment of a data quality monitoring method according to the present invention;
fig. 3 is a functional block diagram of an embodiment of a data quality monitoring apparatus according to the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In a first aspect, an embodiment of the present invention provides a data quality monitoring device.
Referring to fig. 1, fig. 1 is a schematic diagram of a hardware structure of a data quality monitoring device according to an embodiment of the present invention. In this embodiment of the present invention, the data quality monitoring device may include a processor 1001 (e.g., a Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used for realizing connection communication among the components; the user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard); the network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WI-FI interface, WI-FI interface); the memory 1005 may be a Random Access Memory (RAM) or a non-volatile memory (non-volatile memory), such as a magnetic disk memory, and the memory 1005 may optionally be a storage device independent of the processor 1001. Those skilled in the art will appreciate that the hardware configuration depicted in FIG. 1 is not intended to be limiting of the present invention, and may include more or less components than those shown, or some components in combination, or a different arrangement of components.
With continued reference to FIG. 1, the memory 1005 of FIG. 1, which is one type of computer storage medium, may include an operating system, a network communication module, a user interface module, and a data quality monitoring program. The processor 1001 may call a data quality monitoring program stored in the memory 1005, and execute the data quality monitoring method provided by the embodiment of the present invention.
In a second aspect, an embodiment of the present invention provides a data quality monitoring method.
Referring to fig. 2, fig. 2 is a schematic flow chart of an embodiment of the data quality monitoring method of the present invention.
In an embodiment of the data quality monitoring method of the present invention, the data quality monitoring method includes:
step S10, determining source components affecting the measured measurement uncertainty in the engine emissions test, and creating a mathematical model of the measured measurement uncertainty;
in this embodiment, in the engine emission test, the measured measurement result is affected by the equipment, the tester, and the test sample used in the test, so that the measured measurement result has a certain uncertainty, and therefore, it is necessary to analyze the source of the measured measurement uncertainty, determine each source component of the measured measurement uncertainty, create a mathematical model of the measured measurement uncertainty according to the types of different source components, and obtain the specific size of each source component of the quantitative measurement uncertainty.
Further, in one embodiment, the step of determining the source components that affect the measured uncertainty in the engine emissions test comprises:
when the measured measurement uncertainty in the engine emission test is determined to be caused by the repeatability of the test, determining that the source component of the measurement uncertainty is a first source component;
when it is determined that the measured measurement uncertainty in the engine emissions test is due to the accuracy of the test equipment, the source component of the measurement uncertainty is determined to be the second source component.
In the embodiment, the measured uncertain sources of measurement in the engine emission test are divided into two types, and if the measured uncertain sources of measurement in the engine emission test are caused by the repeatability of the test, the source component of the uncertainty of measurement is judged to be the first source component; if the measured measurement uncertainty in the engine emission test is due to the accuracy of the test equipment, the source component of the measurement uncertainty is determined to be the second source component. With NO in engine emission testsxSpecific emission as an example of a measurement, NOxThe specific emission results caused by random variations in test environmental conditions, operator, engine sample, readings on the instrument, etc. are the first source components; NOxThe result of the specific discharge being caused by fuel consumption meters and air flow meter devices in the exhaust gas flow measurement, or exhaust gas NOxError in the analyzer readings, accuracy and drift of calibration gas concentration, signal noise in concentration measurements, orNOxThe accuracy of the humidity and temperature sensors in the humidity correction or the accuracy of the torque flange and speed sensors in the power measurement, as described above by the accuracy of the test equipment, is the second source component.
Further, in one embodiment, the step of creating a mathematical model of the measured measurement uncertainty comprises:
creating a mathematical model of the first source component of the measured measurement uncertainty from the first source component;
creating a mathematical model of the second source component of the measured measurement uncertainty from the second source component;
and synthesizing the mathematical model of the first source component and the mathematical model of the second source component to obtain the mathematical model of the measured measurement uncertainty.
In this embodiment, if the first source component is determined, a mathematical model of the measured measurement uncertainty of the first source component is obtained according to statistical analysis, and since the first source component is the repeatability of the test, the arithmetic mean of the n independent observations is taken
And obtaining the standard deviation of the test of a single measurement by Bessel's formula
Obtaining a mathematical model of the first source component of the measured measurement uncertainty measured n times under repeated conditions as
If the second source component is determined, a mathematical model of the measured measurement uncertainty of the second source component is obtained according to the uncertain propagation law, and since the second source component is the accuracy of the test equipment, the measured estimated value y is determined from the n other quantities X1,X2,…,XnWhen determined by a linear measurement function f, the measured estimated value y ═ f (x)1,x2,...,xn) The mathematical model of the second source component of the measured measurement uncertainty is
Synthesizing the mathematical model of the first source component and the mathematical model of the second source component to obtain a mathematical model of the measured measurement uncertainty
Wherein, Y represents measured NOxSpecific discharge amount of (D), Y1Representing NO in each casexWeighted sum of emission mass flows, Y2Representing the weighted sum of engine power in each operating condition, Uc(f1) Is Y1Of the first source component of (a), Uc(f2) Is Y2A measurement uncertainty of the first source component of (a); u shapec(Y1) Is Y1The combined relative uncertainty, U, of the first and second source componentsc(Y2) Is Y2The combined measurement uncertainty of the first source component and the second source component.
Step S20, obtaining a measured value of an engine emission test, and substituting the measured value into the mathematical model to obtain the magnitude of each source component of the measured measurement uncertainty;
in this embodiment, the measured values in the engine emission test are obtained, and the measured values are substituted into the mathematical model to obtain the specific magnitude of each source component of the measured measurement uncertainty. With NO in engine emission testsxSpecific emissions were measured as an example, and NO in the test resultsxSubstituting specific discharge amount into
In (1) to obtain NOxThe value of the total measurement uncertainty of the specific emission is calculated, and then the source components are substituted into the corresponding mathematical model according to different source components in the test result,if the first source component is due to test repeatability, substituting the results of the n-times repeated tests into the mathematical model of the measured first source component of measurement uncertainty
The specific value of the corresponding first source component is calculated, and similarly, the result of said n quantities is substituted into the mathematical model of the measured measurement uncertainty of the second source component, e.g. due to the accuracy of the test equipment, as
And calculating to obtain the specific numerical value of the corresponding second source component.
Step S30, judging whether the value of each source component is in a preset range;
in this embodiment, it is determined whether the magnitude of each source component is within a preset range, so as to determine whether a measurement uncertainty caused by source components such as a tester, a test sample, and a test device related to an existing engine emission test scheme exceeds a threshold range, that is, whether the measurement uncertainty caused by the source components is within a range in which a deviation is controllable. Wherein, the threshold range of the measurement uncertainty of the national six-stage emission test result is recommended to be within +/-3%.
Step S40, if the value of the at least one source component is not within the preset range, outputting a prompt message for controlling the at least one source component.
In this embodiment, if the magnitude of the value of the at least one source component is not within the preset range, the prompt information for managing and controlling the at least one source component is output, and the magnitude of the influence of each source component not within the preset range on the measured measurement uncertainty in the existing engine emission test is prompted according to the magnitude of the value of the source component, and the causes of the corresponding source components are sorted and warned correspondingly according to different influences. The influence of each source component on the measurement result is positiveCorrelation, and the higher the accuracy grade of the corresponding test equipment, the less uncertainty is introduced, if at NOxIn the measuring process, the gas analyzer displays that the precision is the most influencing factor, and then prompt information for calibrating and checking the precision of the analyzer in the process of carrying out the engine test is output; if in NOxIn the correction process, the measurement accuracy of the atmospheric pressure sensor and the intake air temperature and humidity sensor is a main source of uncertainty, and prompt information for performing key inspection on the state of the equipment in the process of engine detection is output.
Further, in an embodiment, the step of determining whether the magnitude of the source component is within a preset range includes:
and if the numerical values of all the source components are in the preset range, outputting prompt information for keeping the existing engine emission test scheme.
In this embodiment, if the values of all the source components are within the preset range, it is indicated that the uncertainty of the measured measurement in the existing engine emission test is within the controllable error range, and it is not necessary to additionally inspect the corresponding test equipment in the engine emission test, so that only the prompt information for maintaining the existing engine emission test scheme needs to be output.
In this embodiment, source components that affect the measured measurement uncertainty in an engine emissions test are determined, and a mathematical model of the measured measurement uncertainty is created; obtaining a measured value of an engine emission test, and substituting the measured value into the mathematical model to obtain the magnitude of each source component of the measured measurement uncertainty; judging whether the numerical value of each source component is in a preset range or not; and if the numerical value of at least one source component is not in a preset range, outputting prompt information for controlling the at least one source component. The invention quantitatively analyzes the measured measurement uncertainty of each source component in the engine emission test to obtain an effective test data quality monitoring method, and can ensure the accuracy of the emission result of each pollutant ratio measured in a laboratory.
In a third aspect, an embodiment of the present invention further provides a data quality monitoring apparatus.
Referring to fig. 3, a functional block diagram of an embodiment of a data quality monitoring apparatus is shown.
In this embodiment, the data quality monitoring apparatus includes:
a determination module 10 for determining source components affecting a measured measurement uncertainty in an engine emissions test and creating a mathematical model of the measured measurement uncertainty;
an obtaining module 20, configured to obtain a measured value of an engine emission test, and substitute the measured value into the mathematical model to obtain a magnitude of each source component of a measured measurement uncertainty;
the judging module 30 is configured to judge whether the magnitude of the source component is within a preset range;
the output module 40 is configured to output a prompt message for controlling the at least one source component if the magnitude of the at least one source component is not within a preset range.
Further, in an embodiment, the determining module 10 is configured to:
when the measured measurement uncertainty in the engine emission test is determined to be caused by the repeatability of the test, determining that the source component of the measurement uncertainty is a first source component;
when it is determined that the measured measurement uncertainty in the engine emissions test is due to the accuracy of the test equipment, the source component of the measurement uncertainty is determined to be the second source component.
Further, in an embodiment, the determining module 10 is configured to:
creating a mathematical model of the first source component of the measured measurement uncertainty from the first source component;
creating a mathematical model of the second source component of the measured measurement uncertainty from the second source component;
and synthesizing the mathematical model of the first source component and the mathematical model of the second source component to obtain the mathematical model of the measured measurement uncertainty.
Further, in an embodiment, the output module 40 is further configured to:
and if the numerical values of all the source components are in the preset range, outputting prompt information for keeping the existing engine emission test scheme.
The function implementation of each module in the data quality monitoring apparatus corresponds to each step in the data quality monitoring method embodiment, and the function and implementation process thereof are not described in detail herein.
In a fourth aspect, the embodiment of the present invention further provides a readable storage medium.
The readable storage medium of the present invention stores a data quality monitoring program, wherein the data quality monitoring program, when executed by a processor, implements the steps of the data quality monitoring method as described above.
The method implemented when the data quality monitoring program is executed may refer to each embodiment of the data quality monitoring method of the present invention, and details thereof are not repeated herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for causing a terminal device to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A data quality monitoring method is characterized by comprising the following steps:
determining source components affecting a measured measurement uncertainty in an engine emissions test and creating a mathematical model of the measured measurement uncertainty;
obtaining a measured value of an engine emission test, and substituting the measured value into the mathematical model to obtain the magnitude of each source component of the measured measurement uncertainty;
judging whether the numerical value of each source component is in a preset range or not;
and if the numerical value of at least one source component is not in a preset range, outputting prompt information for controlling the at least one source component.
2. The data quality monitoring method of claim 1, wherein the step of determining source components that affect the measured measurement uncertainty in the engine emissions test comprises:
when the measured measurement uncertainty in the engine emission test is determined to be caused by the repeatability of the test, determining that the source component of the measurement uncertainty is a first source component;
when it is determined that the measured measurement uncertainty in the engine emissions test is due to the accuracy of the test equipment, the source component of the measurement uncertainty is determined to be the second source component.
3. The data quality monitoring method of claim 2, wherein the step of creating a mathematical model of the measured measurement uncertainty comprises:
creating a mathematical model of the first source component of the measured measurement uncertainty from the first source component;
creating a mathematical model of the second source component of the measured measurement uncertainty from the second source component;
and synthesizing the mathematical model of the first source component and the mathematical model of the second source component to obtain the mathematical model of the measured measurement uncertainty.
4. The method for monitoring data quality according to claim 1, wherein the step of determining whether the magnitude of the source component is within a predetermined range comprises:
and if the numerical values of all the source components are in the preset range, outputting prompt information for keeping the existing engine emission test scheme.
5. A data quality monitoring apparatus, characterized in that the data quality monitoring apparatus comprises:
a determination module for determining source components that affect a measured measurement uncertainty in an engine emissions test and creating a mathematical model of the measured measurement uncertainty;
the acquisition module is used for acquiring a measured value of an engine emission test, and substituting the measured value into the mathematical model to obtain the magnitude of each source component of the measured measurement uncertainty;
the judging module is used for judging whether the numerical value of each source component is in a preset range or not;
and the output module is used for outputting prompt information for controlling the at least one source component if the numerical value of the at least one source component is not in a preset range.
6. The data quality monitoring apparatus of claim 5, wherein the determination module is configured to:
when the measured measurement uncertainty in the engine emission test is determined to be caused by the repeatability of the test, determining that the source component of the measurement uncertainty is a first source component;
when it is determined that the measured measurement uncertainty in the engine emissions test is due to the accuracy of the test equipment, the source component of the measurement uncertainty is determined to be the second source component.
7. The data quality monitoring apparatus of claim 5, wherein the determination module is configured to:
creating a mathematical model of the first source component of the measured measurement uncertainty from the first source component;
creating a mathematical model of the second source component of the measured measurement uncertainty from the second source component;
and synthesizing the mathematical model of the first source component and the mathematical model of the second source component to obtain the mathematical model of the measured measurement uncertainty.
8. The data quality monitoring apparatus of claim 5, wherein the output module is further configured to:
and if the numerical values of all the source components are in the preset range, outputting prompt information for keeping the existing engine emission test scheme.
9. A data quality monitoring device, characterized in that the data quality monitoring device comprises a processor, a memory, and a data quality monitoring program stored on the memory and executable by the processor, wherein the data quality monitoring program, when executed by the processor, implements the steps of the data quality monitoring method according to any one of claims 1 to 4.
10. A readable storage medium having a data quality monitoring program stored thereon, wherein the data quality monitoring program, when executed by a processor, implements the steps of the data quality monitoring method of any one of claims 1 to 4.
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