Visual evaluation method for analyzing compressor performance based on actual operation data

Abstract

The invention discloses a visual evaluation method for analyzing compressor performance based on actual operation data. The method comprises the following steps that 1, data collection and monitoring are conducted on a compressor and the interior of a pipeline of the compressor; step 2, performing unified arrangement on the acquired monitoring data; 3, key indexes such as volume efficiency and adiabatic efficiency of the compressor are obtained; 4, establishing a model; and 5, evaluating the performance of the compressor according to the monitoring process or the monitoring average value of the regression analysis method on the data model. According to the method, the sensors are arranged in the compressors and the pipelines connected with the compressors, so that the method can be more convenient when data acquisition work of various parameters is carried out, and the conditions of data missing and the like can be avoided when the method evaluates the compressors by carrying out filtering and missing value filling work on the monitored data, so that the reliability of the compressor evaluation is improved. Therefore, the method is more accurate when the performance of the compressor is analyzed and evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field, and in particular to a visual evaluation method for analyzing compressor performance based on actual operation data. Background Art

[0002] A compressor is a device that compresses low-pressure gas into high-pressure gas. It is widely used in many fields, such as refrigeration systems, air-conditioning systems, automobiles, petrochemicals, etc. Compressors are divided into piston compressors, screw compressors, centrifugal compressors, linear compressors, etc. In the manufacturing process of compressors, it is often necessary to test their working efficiency, so as to better distinguish the efficiency performance of each compressor and evaluate it. However, the existing compressor evaluation method has some shortcomings, such as:

[0003] Application number: CN202311516873.3 A method and system for evaluating a natural gas pipeline compressor. The method determines the safety level of the natural gas pipeline compressor under the dimensions of each first-level evaluation indicator based on an evaluation model associated with each first-level evaluation indicator, thereby preventing potential safety hazards of the natural gas pipeline compressor during operation. However, in actual use, since the method does not perform data monitoring inside the compressor, it is difficult to collect and monitor various components and parameters in the compressor, which may cause the method to evaluate various parameters of the compressor inaccurately, thereby reducing the accuracy of the method in analyzing the performance of the compressor;

[0004] Therefore, we propose a visual evaluation method for analyzing compressor performance based on actual operation data in order to solve the problems raised above. Summary of the invention

[0005] The purpose of the present invention is to provide a visual evaluation method for analyzing compressor performance based on actual operating data, so as to solve the problem that the existing evaluation method for analyzing compressor performance on the market currently proposed in the above background technology does not perform data monitoring inside the compressor, making it difficult to collect and monitor various components and parameters in the compressor, which may cause the method to evaluate the various parameters of the compressor. Inaccurate evaluation, thereby reducing the accuracy of the method in analyzing the compressor performance.

[0006] To achieve the above object, the present invention provides the following technical solution: a visual evaluation method for analyzing compressor performance based on actual operation data, comprising the following steps:

[0007] Step 1: Install pressure sensors and flow rate sensors in the compressor and the pipes connected to the compressor to collect and monitor the internal data of the compressor and its pipes to ensure the accuracy of various parameter data during real-time monitoring;

[0008] Step 2: Filter the collected monitoring data and fill in missing values, then organize and preprocess them so that the preprocessed data of various parameters are comparable, and use the predicted parameters to compare with the actual collected data;

[0009] Step 3: Calculate various parameters after preprocessing, calculate key indicators of the compressor such as volumetric efficiency and adiabatic efficiency, so that the theoretical efficiency and actual efficiency of the specified compressor can be calculated;

[0010] Step 4: After preprocessing the real-time monitored parameter data, a model is established so that the administrator can better observe the parameter data. When establishing the model, the influence of different operating states of the compressor on the model can be monitored and recorded by making the compressor overload or other modes;

[0011] Step 5: Evaluate the performance of the compressor based on the monitoring process of the data model or the monitoring average value according to the regression analysis method, and obtain standards based on previous component parameter information or parameter information based on big data, so as to obtain the performance evaluation of each component in the compressor.

[0012] By setting sensors in the compressor and the pipes connected to the compressor, the method can be made more convenient when collecting data on various parameters, and by filtering the monitoring data and filling in missing values, the method can avoid data missing when evaluating the compressor, thereby making the method more accurate when analyzing and evaluating the performance of the compressor, thereby increasing the feasibility of the method.

[0013] As a preferred technical solution of the present invention, when pressure sensors and flow rate sensors are installed in various parts inside the compressor, a temperature sensing mechanism can be installed in the starting mechanism of the compressor to sense the temperature of the compressor in different operating states, so as to better understand the state of the compressor when operating in different states.

[0014] The adoption of the above technical solution can make it more convenient for administrators to collect data from running compressors, thereby increasing the accuracy of the method in collecting data.

[0015] As a preferred technical solution of the present invention, when filtering and filling missing values ​​of the collected monitoring data, the information of the monitoring data can be filtered by a filtering device, and when filling missing values, the mean value filling method or the median value filling method can be used to fill missing values ​​for the data with missing parameters, thereby avoiding the situation of incomplete data;

[0016] The mean value filling method is to calculate the mean value of the complete data records of the specified parameter and use the mean value to fill the missing values; while the median value filling method is to find the median of the complete data records of the parameter to fill the missing values; when there are outliers in the data that affect the mean, the median can better represent the central trend of the data.

[0017] The use of the above technical solution can make it more convenient to process some information with missing data, thereby ensuring the accuracy of the data.

[0018] As a preferred technical solution of the present invention, volumetric efficiency is one of the indicators for measuring the working performance of the compressor, and its calculation formula is as follows:

[0019]

[0020] Where: V actual Represents the actual volume flow rate of gas sucked by the compressor per unit time during the actual working process of the compressor, while V theoretical It is the theoretical volume flow rate of gas sucked by the compressor per unit time under ideal conditions, i.e. theoretical conditions;

[0021] And the compressibility formula of gas is as follows:

[0022]

[0023] Where ρ is the density of the gas after passing through the compressor. When the wind pressure exceeds 2500Pa, the compressibility of the transported gas needs to be considered, H is the compressor head, and Q is the flow rate of a similar compressor.

[0024] The use of the above technical solution can better calculate the actual gas flow quantity of the compressor when it is in use, so that the evaluation method can more accurately obtain the actual parameters of the compressor, thereby increasing the accuracy of the method when monitoring various data.

[0025] As a preferred technical solution of the present invention, adiabatic efficiency is the data used for the ratio of isentropic compression power to actual compression power, and its calculation formula is as follows:

[0026]

[0027] Where: W is represents the power required in the isentropic compression process, and W actual Represents the power consumed during the actual compression process;

[0028] In the ideal isentropic process, for ideal gas, the calculation formula of isentropic compression power is derived based on the first law of thermodynamics and the ideal gas state equation, that is, the actual usage data:

[0029]

[0030] Where: P 1 is the intake pressure, and V 1 is the volume of the intake air, P 2 is the exhaust pressure. The actual compression power is calculated by measuring the actual compression efficiency and the time taken for the compression process, which is W. actual =P*t, where P is the actual efficiency of the compressor and t is the compression time.

[0031] The use of the above technical solution can better calculate the temperature of various powers of the compressor when in use, so that the evaluation method can more accurately obtain the actual parameters of the compressor, thereby increasing the accuracy of the method when monitoring various data.

[0032] As a preferred technical solution of the present invention, after the volumetric efficiency formula and the adiabatic efficiency formula are determined, they can be transmitted to the model calculation device by preset or administrator input, so that the calculation device can automatically calculate according to each group of formulas.

[0033] The adoption of the above technical solution can make the evaluation method more convenient when applying various calculation formulas, thereby increasing the accuracy of the device in calculation.

[0034] As a preferred technical solution of the present invention, when the model is established, a line graph, a bar graph or a radar graph can be used to monitor the data of various parameters, so that the monitoring data of the various parameters can be observed more conveniently and accurately.

[0035] The use of the above technical solution can make it more convenient for administrators to observe the data of various parameters, thereby increasing the observability of the model after it is established.

[0036] As a preferred technical solution of the present invention, when a certain parameter data has a huge deviation, the time period of the specified group of data will be marked and saved, and the pattern will be explored, that is, the interval time and the number of occurrences will be observed to determine the possibility of data errors.

[0037] The use of the above technical solution enables the evaluation method to more effectively record some erroneous data and detect the frequency of occurrence of the specified data, thereby enabling the administrator to better evaluate the performance efficiency of the compressor.

[0038] As a preferred technical solution of the present invention, after confirming that the collected monitoring data is correct, a second or multiple monitoring is performed to determine that a component of the compressor has a problem, thereby making changes and appending the changed component data to the evaluation.

[0039] The above technical solution can more effectively judge the performance of the compressor by testing the compressor multiple times, so that the administrator can be more accurate in evaluating the performance of the compressor.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows: by arranging sensors in the compressor and the pipes connected to the compressor, the method can be more convenient when collecting data of various parameters, and by filtering the monitoring data and filling in missing values, the method can avoid data missing when evaluating the compressor, so that the method can be more accurate when analyzing and evaluating the performance of the compressor, thereby increasing the feasibility of the method;

[0041] Furthermore, by setting calculation formulas such as volumetric efficiency and adiabatic efficiency, the actual gas flow quantity and the temperature of each power of the compressor when in use can be better calculated, so that the evaluation method can more accurately obtain the actual parameters of the compressor, thereby increasing the accuracy of the method in monitoring various data;

[0042] Furthermore, by presenting the model diagram in different ways, it is more convenient for the administrator to observe the data of various parameters, thereby increasing the observability of the model after it is established. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic flow chart of the steps of the visual evaluation method for compressor performance of the present invention;

[0044] Figure 2 A detailed process diagram of the visual evaluation method for compressor performance of the present invention;

[0045] Figure 3 Detailed process diagram of the method for visually evaluating compressor performance according to Example 2 of the present invention. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0047] Example 1: Please refer to Figure 1-Figure 2 The present invention provides a technical solution: a visual evaluation method for analyzing compressor performance based on actual operation data, comprising the following steps:

[0048] Step 1: Install pressure sensors and flow rate sensors in the compressor and the pipes connected to the compressor to collect and monitor the internal data of the compressor and its pipes to ensure the accuracy of various parameter data during real-time monitoring;

[0049] Step 2: Filter the collected monitoring data and fill in missing values, then organize and preprocess them so that the preprocessed data of various parameters are comparable, and use the predicted parameters to compare with the actual collected data;

[0050] Step 3: Calculate various parameters after preprocessing, calculate key indicators of the compressor such as volumetric efficiency and adiabatic efficiency, so that the theoretical efficiency and actual efficiency of the specified compressor can be calculated;

[0051] Step 4: After preprocessing the real-time monitored parameter data, a model is established so that the administrator can better observe the parameter data. When establishing the model, the influence of different operating states of the compressor on the model can be monitored and recorded by making the compressor overload or other modes;

[0052] Step 5: Evaluate the performance of the compressor based on the monitoring process or the average value of the data model according to the regression analysis method, and obtain the standard based on the previous component parameter information or the parameter information based on big data, so as to obtain the performance evaluation of each component in the compressor;

[0053] The partial least squares method is used for regression analysis, and the regression equation of gas compression power H with respect to wind flow Q and fan power N is obtained as follows:

[0054]

[0055] When installing pressure sensors and flow rate sensors in various parts inside the compressor, a temperature sensing mechanism can be installed in the compressor's starting mechanism to sense the temperature of the compressor in different operating states, so as to better understand the state of the compressor when it is running in different states;

[0056] When filtering and filling missing values ​​of the collected monitoring data, the information of the monitoring data can be filtered through the filtering equipment, and when filling missing values, the mean value filling method or the median value filling method can be used to fill the missing values ​​of the data with missing parameters to avoid incomplete data;

[0057] The mean value filling method is to calculate the average value of the complete data records of the specified parameter and use the average value to fill the missing value; while the median value filling method is to find the median of the complete data records of the parameter to fill the missing value; when there are outliers in the data that affect the mean, the median can better represent the central trend of the data;

[0058] Volumetric efficiency is one of the indicators to measure the working performance of the compressor. Its calculation formula is as follows:

[0059]

[0060] Where: V actual Represents the actual volume flow rate of gas sucked by the compressor per unit time during the actual working process of the compressor, while V theoretical It is the theoretical volume flow rate of gas sucked by the compressor per unit time under ideal conditions, that is, theoretical conditions; for example, the compressor can theoretically absorb 10 cubic meters of gas per minute (V theoretical =10m 3 / min), but the actual volume is 9.5 cubic meters per minute (V actual =9.5m 3 / mi), then the volumetric efficiency of the compressor is That is 95% volumetric efficiency;

[0061] And the compressibility formula of gas is as follows:

[0062]

[0063] Where ρ is the density of the gas after passing through the compressor. When the wind pressure exceeds 2500Pa, the compressibility of the transported gas needs to be considered, and H is the compressor head, and Q is the flow rate of a similar compressor;

[0064] Adiabatic efficiency is the data used for the ratio of isentropic compression power to actual compression power, and its calculation formula is as follows:

[0065]

[0066] Where: W is represents the power required in the isentropic compression process, and W actual Represents the power consumed in the actual compression process; for example, the isentropic compression power W of the compressor is 99 kJ, actual compression power W actual is 110 kJ, then the adiabatic efficiency of the compressor is That is 90%;

[0067] In the ideal isentropic process, for ideal gas, the calculation formula of isentropic compression power is derived based on the first law of thermodynamics and the ideal gas state equation, that is, the actual usage data:

[0068]

[0069] Where: P 1 is the intake pressure, and V 1 is the volume of the intake air, P 2 is the exhaust pressure. The actual compression power is calculated by measuring the actual compression efficiency and the time taken for the compression process, which is W. actual =P*t, where P is the actual efficiency of the compressor and t is the compression time;

[0070] After the volumetric efficiency formula and the adiabatic efficiency formula are determined, they can be transmitted to the model calculation device by way of preset or administrator input, so that the calculation device can automatically calculate according to each set of formulas;

[0071] When the model is established, line graphs, bar graphs or radar charts can be used to monitor the data of various parameters, so that the monitoring data of various parameters can be observed more conveniently and accurately.

[0072] Example 2: Please refer to Figure 3 The difference between this embodiment and embodiment 1 is that: a visual evaluation method for analyzing compressor performance based on actual operation data comprises the following steps:

[0073] Step 1: Install pressure sensors and flow rate sensors in the compressor and the pipes connected to the compressor to collect and monitor the internal data of the compressor and its pipes to ensure the accuracy of various parameter data during real-time monitoring;

[0074] Step 2: Filter the collected monitoring data and fill in missing values, then organize and preprocess them so that the preprocessed data of various parameters are comparable, and use the predicted parameters to compare with the actual collected data;

[0075] Step 3: Calculate various parameters after preprocessing, calculate key indicators of the compressor such as volumetric efficiency and adiabatic efficiency, so that the theoretical efficiency and actual efficiency of the specified compressor can be calculated;

[0076] Step 4: After preprocessing the real-time monitored parameter data, a model is established so that the administrator can better observe the parameter data. When establishing the model, the influence of different operating states of the compressor on the model can be monitored and recorded by making the compressor overload or other modes;

[0077] Step 5: Evaluate the performance of the compressor based on the monitoring process or the average value of the data model according to the regression analysis method, and obtain the standard based on the previous component parameter information or the parameter information based on big data, so as to obtain the performance evaluation of each component in the compressor;

[0078] When a huge deviation occurs in the data of a certain parameter of the compressor through the model, the time period of the specified group of data will be marked and saved, and the pattern will be explored, that is, the interval time and the number of occurrences will be observed to determine the possibility of data errors; after confirming that the collected monitoring data is correct, a second or multiple monitoring will be carried out to determine that a certain component of the compressor has a problem, so that changes can be made and the data of the changed component will be attached to the evaluation;

[0079] By monitoring various parameters of the compressor multiple times, the sensing equipment can monitor the gas flow rate, pressure and temperature inside the compressor multiple times, thereby calculating the changes during each monitoring, making the evaluation method more accurate when evaluating the operating status of the compressor or a certain component.

[0080] Thereby completing a series of tasks, the contents not described in detail in this specification belong to the prior art known to professional and technical personnel in this field.

[0081] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A visual evaluation method for analyzing compressor performance based on actual operation data, characterized in that: The steps include: Step 1: Install pressure sensors and flow rate sensors in the compressor and the pipes connected to the compressor to collect and monitor the internal data of the compressor and its pipes to ensure the accuracy of various parameter data during real-time monitoring; Step 2: Filter the collected monitoring data and fill in missing values, then organize and preprocess them so that the preprocessed data of various parameters are comparable, and use the predicted parameters to compare with the actual collected data; Step 3: Calculate various parameters after preprocessing, calculate key indicators of the compressor such as volumetric efficiency and adiabatic efficiency, so that the theoretical efficiency and actual efficiency of the specified compressor can be calculated; Step 4: After preprocessing the real-time monitored parameter data, a model is established so that the administrator can better observe the parameter data. When establishing the model, the influence of different operating states of the compressor on the model can be monitored and recorded by making the compressor overload or other modes; Step 5: Evaluate the performance of the compressor based on the monitoring process of the data model or the monitoring average value according to the regression analysis method, and obtain standards based on previous component parameter information or parameter information based on big data, so as to obtain the performance evaluation of each component in the compressor.

2. The visual evaluation method for analyzing compressor performance based on actual operation data according to claim 1, characterized in that: When pressure sensors and flow rate sensors are installed in various parts inside the compressor, a temperature sensing mechanism may be installed in the starting mechanism of the compressor to sense the temperature of the compressor in different operating states, thereby being able to better understand the state of the compressor when it is running in different states.

3. The visual evaluation method for analyzing compressor performance based on actual operation data according to claim 1, characterized in that: When filtering and filling missing values ​​of the collected monitoring data, the information of the monitoring data can be filtered through the filtering equipment, and when filling missing values, the mean value filling method or the median value filling method can be used to fill the missing values ​​of the data with missing parameters to avoid incomplete data; The mean value filling method is to calculate the mean value of the complete data records of the specified parameter and use the mean value to fill the missing values; while the median value filling method is to find the median of the complete data records of the parameter to fill the missing values; when there are outliers in the data that affect the mean, the median can better represent the central trend of the data.

4. The visual evaluation method for analyzing compressor performance based on actual operation data according to claim 1, characterized in that: Volumetric efficiency is one of the indicators to measure the working performance of the compressor. Its calculation formula is as follows: Where: V actual Represents the actual volume flow rate of gas sucked by the compressor per unit time during the actual working process of the compressor, while V theoretical It is the theoretical volume flow rate of gas sucked by the compressor per unit time under ideal conditions, i.e. theoretical conditions; And the compressibility formula of gas is as follows: Where ρ is the density of the gas after passing through the compressor. When the wind pressure exceeds 2500Pa, the compressibility of the transported gas needs to be considered, H is the compressor head, and Q is the flow rate of a similar compressor.

5. The visual evaluation method for analyzing compressor performance based on actual operation data according to claim 1, characterized in that: Adiabatic efficiency is the data used for the ratio of isentropic compression power to actual compression power, and its calculation formula is as follows: Where: W is represents the power required in the isentropic compression process, and W actual Represents the power consumed during the actual compression process; In the ideal isentropic process, for ideal gas, the calculation formula of isentropic compression power is derived based on the first law of thermodynamics and the ideal gas state equation, that is, the actual usage data: Where: P1 is the intake pressure, V1 is the intake volume, P2 is the exhaust pressure, and the actual compression power is calculated by measuring the actual compression efficiency and the time taken for the compression process, which is W actual =P*t, where P is the actual efficiency of the compressor and t is the compression time.

6. The visual evaluation method for analyzing compressor performance based on actual operation data according to claim 1, characterized in that: After the volumetric efficiency formula and the adiabatic efficiency formula are determined, they can be transmitted to the model calculation device by way of preset or administrator input, so that the calculation device can automatically calculate according to each set of formulas.

7. The visual evaluation method for analyzing compressor performance based on actual operation data according to claim 1, characterized in that: When the model is established, line graphs, bar graphs or radar charts can be used to monitor the data of various parameters, so that the monitoring data of various parameters can be observed more conveniently and accurately.

8. The visual evaluation method for analyzing compressor performance based on actual operation data according to any one of claims 1 to 7, characterized in that: When a certain parameter data shows a huge deviation, the time period of the specified group of data will be marked and saved, and the pattern will be explored, that is, the interval time and the number of occurrences will be observed to determine the possibility of data errors.

9. The visual evaluation method for analyzing compressor performance based on actual operation data according to claim 8, characterized in that: After confirming that the collected monitoring data is correct, a second or multiple monitorings can be performed to determine that a component of the compressor has a problem, so that changes can be made and the changed component data can be attached to the evaluation.

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