Cell similarity-based gas flow standard device reliability evaluation method

Abstract

The application discloses a gas flow standard device reliability evaluation method based on cell similarity, which comprises the following steps: S1, collecting energy consumption data of the gas flow standard device during each calibration task; S2, standardizing the energy consumption data; S3, setting cell radius and cell interval; S4, calculating the area of the cell overlap region; S5, calculating the reliability index; wherein the cell radius is the standard deviation of the energy consumption at the same time of multiple calibration tasks. The application has the beneficial effect that the energy consumption data of the gas flow standard device is fully utilized to quantitatively evaluate the reliability of the device during each calibration task, and the practicability is stronger in complex situations; the cell is established through the energy consumption data, and the reliability evaluation accuracy is high; the reliability calculation amount of the gas flow standard device can be controlled through the cell interval, and the time of the reliability evaluation control can meet various requirements.

Description

Technical Field

[0001] This invention relates to the field of quality control technology, and in particular to a reliability evaluation method for a gas flow standard device based on cell similarity. Background Technology

[0002] Reliability evaluation of gas flow standard devices is a crucial task in industrial production and quality control. During production and testing, many devices require calibration to ensure the accuracy and reliability of their measurements. Reliability evaluation of gas flow standard devices assesses their normal operating conditions and performance stability, playing a key role in ensuring the accuracy of gas flow meter calibration results. Traditional reliability evaluation methods for gas flow standard devices primarily rely on failure mode analysis and statistical models, using indicators such as failure rate and time between failures to predict device reliability based on an assessment of environmental and equipment conditions. However, this method often fails to fully account for the actual operating conditions and complexity of the equipment.

[0003] Chinese patent document CN110991853B, published on October 25, 2022, discloses a method for dynamic evaluation of equipment reliability based on intelligent fault diagnosis. Users can dynamically update the health information of the equipment based on the results of real-time intelligent fault diagnosis, establish a dynamic record of equipment operation, and establish an equipment reliability evaluation model based on the dynamic record of equipment operation.

[0004] The drawback of the above-mentioned dynamic reliability assessment method is that using indicators such as failure rate and failure interval time to predict equipment reliability cannot fully take into account the actual working conditions and complexity of the equipment for gas flow standard devices, so it is not suitable for reliability assessment of gas flow standard devices. Summary of the Invention

[0005] The purpose of this invention is to address the problem that existing reliability assessment methods cannot be applied to gas flow rate standard devices, and to provide a reliability evaluation method for gas flow rate standard devices based on cell similarity. This method makes full use of the energy consumption data of the gas flow rate standard device and has the advantage of being able to efficiently evaluate the reliability of the gas flow rate standard device each time it performs a calibration task.

[0006] The technical solution adopted by the present invention to solve the above-mentioned technical problems is: a reliability evaluation method for a gas flow standard device based on cell similarity, comprising the following steps: S1: collecting energy consumption data of the gas flow standard device each time it performs a calibration task; S2: standardizing the energy consumption data; S3: setting the cell radius and cell spacing; S4: calculating the area of ​​the cell overlap region; S5: calculating the reliability index; wherein, the cell radius is the standard deviation of energy consumption at the same moment in multiple calibration tasks.

[0007] Using the above technical solution, after collecting energy consumption data, the energy consumption data is standardized and processed. Then, the cell radius and cell spacing are set, and the area of ​​the cell overlap region is calculated based on the set cell radius and cell spacing. Finally, the reliability index is calculated based on the obtained cell overlap region area.

[0008] Preferably, step S2 includes: for the i-th calibration task, the actual flow rate is Q. i ,exist The cumulative energy consumption at each moment is The energy consumption data is standardized according to the following formula: In the formula, After standardization The cumulative energy consumption at any given time; Q0 is the standard flow rate value. Specifically, standardizing the energy consumption data by comparing the standard flow rate value with the actual flow rate not only improves the accuracy of reliability evaluation but also allows the reliability evaluation method to meet the complexity of gas flow rate standard devices.

[0009] Preferably, the energy consumption data includes basic energy consumption data and energy consumption data to be verified. Specifically, the basic energy consumption data is the energy consumption data of the gas flow standard device when performing calibration tasks, while the energy consumption data to be verified is obtained based on the basic energy consumption data. In this way, the reliability of each calibration task can be evaluated by making full use of the energy consumption data of the gas flow standard device.

[0010] Preferably, step S1 includes: The basic energy consumption data are numbered sequentially as 1, 2, ..., n; The energy consumption data to be verified is numbered n+1; When the gas flow standard device performs its calibration task for the i-th time, The cumulative energy consumption at each moment is 1≤i≤n+1, where n+1 is the number of calibration tasks; 1≤j≤N i N i The total duration of the i-th calibration task is divided into segments based on the cell interval. Specifically, the collected cumulative energy consumption W... j This refers to energy consumption data. By limiting the range of calibration tasks and cell spacer segments, the reliability of the evaluation device is made more accurate each time it performs a calibration task.

[0011] Preferably, the cell interval is the time interval between adjacent cells in the same calibration task. Specifically, the cell interval is set manually, and can generally be 1s, 5s, 10s, etc. The smaller the cell interval, the more accurate the reliability index of the calibration device, but the greater the computational load.

[0012] Preferably, cell radius calculation includes: Calculate m j The calibration task is in t j Average energy consumption at time intervals : ,in, m j In n basic energy consumption data, at t j At any given time, there is a number of energy-consuming calibration tasks; Calculate cell radius r j： ; Specifically, due to t j At time t, some calibration tasks may have already completed and no longer generate energy consumption, so it is necessary to incorporate the basic energy consumption data from n iterations. j At any given time, the number of energy-consuming calibration tasks, m j This allows for a more accurate assessment of the reliability of gas devices.

[0013] As a preferred option Step S4 includes: Using coordinates respectively , With the origin as the reference point, r j Establish the cell based on its radius; Calculate t j The area S of the overlapping region of cells at time point j ; Calculate the total area of ​​all overlapping cell regions; In the formula, The total duration of the n+1th calibration task is divided into segments based on the cell interval. Specifically, The area of ​​the overlapping region of cells at any given time is calculated using the following formula: ; In this way, cells were established using energy consumption data, and the area of ​​overlapping regions of cells was calculated, quantitatively evaluating the reliability of the device each time it performs a calibration task, with high accuracy.

[0014] As a preferred option Step S5 includes: Calculate the reliability index of the calibration device for the (n+1)th calibration task: Specifically, the final accuracy index is calculated using the total area of ​​the overlapping cell regions and the cell radius. The cells are established using energy consumption data. By fully utilizing the energy consumption data of the gas flow standard device, the reliability of the device is quantitatively evaluated each time it performs a calibration task, making it more practical and capable of handling complex situations.

[0015] Preferably, depending on the stringency of the requirements, different values ​​of the reliability index can be set to control whether the result of the (n+1)th calibration task is accepted. Specifically, for example, a reliability index of 0.5 can be set... The result of the (n+1)th calibration task can be considered to meet the reliability index requirements. A higher reliability index results in more stringent requirements for the (n+1)th calibration task. Thus, by controlling the requirements of the calibration task through the reliability index, the reliability of the device can be quantitatively evaluated for each calibration task performed, making it more practical and capable of handling complex situations.

[0016] This invention provides a reliability evaluation method for a gas flow rate standard device based on cell similarity. First, the energy consumption data of the gas flow rate standard device is collected each time it performs a calibration task. Then, the energy consumption data is standardized to obtain processed energy consumption data. The cell radius is calculated using the energy consumption data. After setting the cell interval, the area of ​​the cell overlap region is calculated using the energy consumption data and the cell radius. Finally, the reliability index is obtained using the area of ​​the cell overlap region.

[0017] The beneficial effects of this invention are that it fully utilizes the energy consumption data of the gas flow standard device to quantitatively evaluate the reliability of the device each time it performs a calibration task, making it more practical in handling complex situations; it establishes cells based on energy consumption data, resulting in high accuracy in reliability evaluation; and it allows control over the reliability calculation amount of the gas flow standard device through cell intervals, meeting various needs and controlling the time of reliability evaluation.

[0018] Features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, combined with features in other embodiments, or substituted for features in other embodiments. It should be emphasized that the term "comprising / including" as used herein refers to the presence of a feature, integral, step, or component, but does not exclude the presence or addition of one or more other features, integrals, steps, or components. Attached Figure Description

[0019] Figure 1 This is a flowchart of a reliability evaluation method for a gas flow rate standard device based on cell similarity according to the present invention;

[0020] Figure 2 This is a schematic diagram of the cell radius of a gas flow rate standard device reliability evaluation method based on cell similarity according to the present invention;

[0021] Figure 3 This is a schematic diagram of the cell overlap region in the reliability evaluation method of a gas flow rate standard device based on cell similarity according to the present invention.

[0022] Figure 4This invention relates to the energy consumption data of a reliability evaluation method for a gas flow standard device based on cell similarity. Detailed Implementation

[0023] The specific implementation of the technical solution of the present invention will be further described below through examples and in conjunction with the accompanying drawings.

[0024] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0025] Example 1:

[0026] exist Figures 1 to 4 In the illustrated embodiment 1, the present invention provides a technical solution: a reliability evaluation method for a gas flow standard device based on cell similarity, comprising the following steps: S1: collecting energy consumption data of the gas flow standard device each time it performs a calibration task; S2: standardizing the energy consumption data; S3: setting the cell radius and cell spacing; S4: calculating the area of ​​the cell overlap region; S5: calculating the reliability index; wherein, the cell radius is the standard deviation of energy consumption at the same moment in multiple calibration tasks.

[0027] In this embodiment, the flowchart of the reliability evaluation method for a gas flow rate standard device based on cell similarity is as follows: Figure 1 The diagram shows a general overview of the reliability evaluation method's process, and also summarizes the overall technical solution. For example... Figure 1 The flowchart shown includes the following steps.

[0028] Step S100: Collect energy consumption data of the gas flow standard device each time it performs a calibration task. In this embodiment, the energy consumption data includes basic energy consumption data and energy consumption data to be verified. The basic energy consumption data is the energy consumption data of the gas flow standard device when performing a calibration task.

[0029] In this embodiment, the energy consumption data collected by the gas flow standard device each time it performs a calibration task includes: The basic energy consumption data are numbered sequentially as 1, 2, ..., n; The energy consumption data to be verified is numbered n+1; When the gas flow standard device performs its calibration task for the i-th time, The cumulative energy consumption at each moment is 1≤i≤n+1, where n+1 is the number of calibration tasks; 1≤j≤N iN i The total duration of the i-th calibration task is divided into segments based on the cell interval. The cell interval is the time interval between adjacent cells in the same calibration task. Specifically, the cell interval is manually set, typically 1s, 5s, 10s, etc. The smaller the cell interval, the more accurate the reliability index of the calibration device, but the greater the computational load. In this embodiment, the energy consumption data is as follows: Figure 4 As shown, the first to fifth times are basic energy consumption data, and the sixth time is energy consumption data to be verified.

[0030] Step S110: Energy consumption data standardization processing. In this embodiment, for the i-th calibration task, the actual flow rate is Q. i ,exist The cumulative energy consumption at each moment is The energy consumption data is standardized according to the following formula: In the formula, After standardization The cumulative energy consumption at any given time; Q0 is the standard flow rate value.

[0031] In this embodiment, the energy consumption data is as follows: Figure 4 As shown, the standardized data were calculated respectively. Standard flow rate. The first five times are the basic energy consumption data, and the actual flow rates are respectively , , , , The 6th data point is the energy consumption data to be verified; the actual flow rate is... .

[0032] Step S120: Set the cell radius and cell spacing. In this embodiment, the cell radius calculation includes: Calculate m j The calibration task is in t j Average energy consumption at time intervals : ,in, m j In n basic energy consumption data, at t j At any given time, the number of energy-consuming calibration tasks (due to the varying duration of each basic energy consumption data point, at time t) j At any given time, some calibration tasks may have already been completed and no longer consume energy. Calculate cell radius r j： ; The cell interval is set to 1 second, and the cell radius is as follows: Figure 2 As shown.

[0033] Step S130: Calculate the area of ​​the cell overlap region. In this embodiment, calculating the area of ​​the cell overlap region includes: Using coordinates respectively , Let r be the origin. j Establish the cell with the specified cell radius; Calculate t j The area S of the overlapping region of cells at time point j : ; Calculate the total area of ​​all overlapping regions of cells; In the formula, The total duration of the n+1th calibration task is divided into segments based on the cell interval. In this embodiment, the cell overlap region diagram is as follows: Figure 3 As shown, the total area of ​​all overlapping cell regions is .

[0034] Step S140: Calculate the reliability index. In this embodiment, calculating the reliability index includes: Calculate the reliability index of the calibration device for the (n+1)th calibration task: 。; In this embodiment, the reliability index of the calibration device for the 6th calibration task is calculated as follows: .

[0035] In this embodiment, the reliability index is set to 0.5. The result of the 6th calibration task meets the reliability index requirements, the device is reliable, and the result of the 6th calibration task can be added to the basic energy consumption data.

[0036] Based on the results of Example 1, the present invention provides a reliability evaluation method for a gas flow rate standard device based on cell similarity. First, energy consumption data is collected for each calibration task performed by the gas flow rate standard device. Then, the energy consumption data is standardized to obtain processed energy consumption data. Cell radius is calculated using the energy consumption data. After setting cell intervals, the area of ​​the cell overlap region is calculated using the energy consumption data and cell radius. Finally, the reliability index is obtained from the area of ​​the cell overlap region. Example 1 uses the reliability evaluation method of the present invention to evaluate the reliability of a gas flow rate standard device. The results show that the gas flow rate standard device meets the reliability index requirements. Therefore, the present invention provides a reliability evaluation method for a gas flow rate standard device based on cell similarity, which fully utilizes the energy consumption data of the gas flow rate standard device to quantitatively evaluate the reliability of the device each time it performs a calibration task.

[0037] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A reliability evaluation method for a gas flow rate standard device based on cell similarity, characterized in that, Includes the following steps: S1: Collect energy consumption data of the gas flow standard device each time it performs a calibration task; S2: Standardized processing of energy consumption data; S3: Set the cell radius and cell spacing, where the cell spacing is the time interval between adjacent cells in the same calibration task; S4: Calculate the area of ​​the overlapping cell region, expressed as coordinates. , With the origin as the reference point, r j Establish the cell with the specified cell radius; The Let mj be the average energy consumption of the calibration task at time point j; mj represents the number of energy-consuming calibration tasks at time tj in the nth set of basic energy consumption data. The W' jn+1 For the (n+1)th calibration task, after standardization, at t j Cumulative energy consumption at any given moment; n+1 represents the number of calibration tasks; S5: Calculate the reliability index; The cell radius is the standard deviation of energy consumption at the same moment in multiple calibration tasks.

2. The reliability evaluation method according to claim 1, characterized in that, Step S2 includes: For the i-th calibration task, the actual flow rate is Q. i ,exist The cumulative energy consumption at each moment is The energy consumption data is standardized according to the following formula: In the formula, After standardization The cumulative energy consumption at any given time; Q0 is the standard flow rate value.

3. The reliability evaluation method according to claim 1, characterized in that, The energy consumption data includes basic energy consumption data and energy consumption data to be verified.

4. The reliability evaluation method according to claim 1 or 3, characterized in that, Step S1 includes: The basic energy consumption data are numbered sequentially as 1, 2, ..., n; The energy consumption data to be verified is numbered n+1; When the gas flow standard device performs its calibration task for the i-th time, The cumulative energy consumption at each moment is , 1≤i≤n+1; 1≤j≤N i N i The total duration of the i-th calibration task is divided into segments based on the cell interval.

5. The reliability evaluation method according to claim 1, characterized in that, The cell radius calculation includes: Calculate m j The calibration task is in t j Average energy consumption at time intervals : ; Where, m j In n basic energy consumption data, at t j At any given time, there is a number of energy-consuming calibration tasks; Calculate cell radius r j： .

6. The reliability evaluation method according to claim 1, characterized in that, Step S4 includes: Calculate t j The area S of the overlapping region of cells at time point j : ； Calculate the total area of ​​all overlapping regions of cells; In the formula, The total duration of the (n+1)th calibration task is divided into segments based on the cell interval.

7. The reliability evaluation method according to claim 1, characterized in that, Step S5 includes: Calculate the reliability index of the calibration device for the (n+1)th calibration task: 。 8. The reliability evaluation method according to claim 1 or 7, characterized in that, Depending on the required stringency, different reliability indices can be set to control whether the results of the (n+1)th calibration task are accepted.

Images