Data processing method and device, electronic equipment and storage medium

Abstract

The invention provides a data processing method and device, electronic equipment and a storage medium. The method comprises the following steps: step 1, acquiring data variables and reference group data; 2, acquiring a first group of operation data; step 3, comparing each first operation data included in the first group of operation data with corresponding first data and second data to obtain each first comparison result and each second comparison result, the first data = the reference data + the data variable corresponding to the reference data, and the second data = the reference data + the data variable corresponding to the reference data; the second data = the reference data minus the data variable corresponding to the reference data; step 4, according to each first comparison result or each second comparison result, determining whether to retain the first group of operation data; 5, if the reference group data is reserved, updating the reference group data as the first group of operation data; and step 6, repeating the step 3, the step 4 and the step 5 for the subsequently acquired second group of operation data,..., and the Mth group of operation data. According to the invention, the storage amount and the transmission amount of operation data are greatly reduced.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of industrial control technology, and more particularly to a data processing method, device, electronic device, and storage medium. Background Art

[0002] Operational data collection refers to the real-time or periodic collection and recording of various performance indicators and operational data during system operation. This operational data is crucial for monitoring system status, analyzing system performance, optimizing resource allocation, and preventing and resolving potential problems. It is the most fundamental part of industrial control and a key step in ensuring the performance and stability of production systems.

[0003] Typically, a computer uses its own clock to sample data at a set frequency and save all collected operational data at that time. If more accurate operational data is required, the sampling frequency and detection accuracy can be increased. However, this increases the amount of operational data to be stored and transmitted, significantly consuming software and hardware resources. Summary of the Invention

[0004] To solve the above problems, embodiments of the present invention provide a data processing method, device, electronic device, and storage medium.

[0005] In a first aspect, an embodiment of the present invention provides a data processing method, including:

[0006] Step 1: obtaining a benchmark group data of data variables and production process equipment, wherein the benchmark group data includes a plurality of benchmark data;

[0007] Step 2: obtaining a first set of operating data of the production process equipment, wherein the first set of operating data includes a plurality of first operating data, and the plurality of reference data respectively correspond to the plurality of first operating data;

[0008] Step 3: Compare each first operating data with the corresponding first data and second data to obtain each first comparison result and each second comparison result, where the first data = reference data + a data variable corresponding to the reference data, and the second data = reference data - a data variable corresponding to the reference data;

[0009] Step 4: determining whether to retain the first set of operating data based on the first comparison results or the second comparison results;

[0010] Step 5: If retained, update the benchmark group data to the first group of operating data;

[0011] Step 6: Repeat the aforementioned steps 3, 4, and 5 for the second set of operating data, the third set of operating data, ..., the Mth set of operating data of the production process equipment obtained subsequently, where M is an integer greater than or equal to 1.

[0012] In a possible implementation, determining whether to retain the first set of operating data according to the respective first comparison results or the respective second comparison results includes:

[0013] If one of the first comparison results is that the first operating data is greater than the corresponding first data, or one of the second comparison results is that the first operating data is less than the corresponding second data, it is determined that the first set of operating data is retained, otherwise it is not retained.

[0014] In one possible implementation, the method further includes:

[0015] Determine to retain the baseline group data;

[0016] Determining to retain N sets of operating data from the first set of operating data, the second set of operating data, ..., the Mth set of operating data, where N is an integer greater than or equal to 1 and less than or equal to M;

[0017] N charts are generated according to the benchmark group data, the N groups of operating data, and timestamps corresponding to the benchmark group data and the N groups of operating data.

[0018] In a possible implementation, each piece of operating data in each group of operating data in the N groups of operating data is power and voltage of production process equipment.

[0019] In a possible implementation, the powers in the N groups of operating data are P1, P2, ..., P N , the currents are I1, I2, ..., I N The timestamps corresponding to the N powers and currents are t'1, ..., t' N , the timestamp corresponding to the power and current in the benchmark group data is t'0;

[0020] Generating N charts according to the benchmark group data and the N groups of operating data and the timestamps corresponding to the benchmark group data and the N groups of operating data, respectively, includes:

[0021] With time as the horizontal axis and power as the vertical axis, according to P1, P2, ..., P N and P1, P2, ..., P N The corresponding timestamps are t'1, ..., t' Nand the power included in the reference group data and the timestamp t'0 corresponding to the power included in the reference group data, determining the first N+1 points;

[0022] Connecting every two adjacent points in the first N+1 points with a straight line to obtain a first graph;

[0023] With time as the horizontal axis and current as the vertical axis, according to I1, I2, ..., I N and I1, I2, ..., I N The corresponding timestamps are t'1, ..., t' N and the current included in the reference group data and the timestamp t'0 corresponding to the current included in the reference group data, determining the second N+1 points;

[0024] Connect every two adjacent points in the second N+1 points with a straight line to obtain a second graph.

[0025] In one possible implementation, the method further includes:

[0026] The first graph and the second graph are displayed.

[0027] In one possible implementation, the production process equipment includes a pump, a fan, and an air compressor.

[0028] In a second aspect, an embodiment of the present invention provides a data processing device, including:

[0029] A first acquisition module is used to acquire a data variable and a benchmark group data of a production process equipment, wherein the benchmark group data includes a plurality of benchmark data;

[0030] A second acquisition module is configured to acquire a first set of operating data of the production process equipment, wherein the first set of operating data includes a plurality of first operating data, and the plurality of reference data are respectively in correspondence with the plurality of first operating data;

[0031] a comparison module, configured to compare each first operating data with the corresponding first data and second data, respectively, to obtain each first comparison result and each second comparison result, wherein the first data = reference data + a data variable corresponding to the reference data, and the second data = reference data - a data variable corresponding to the reference data;

[0032] a determination module, configured to determine whether to retain the first set of operating data based on the respective first comparison results or the respective second comparison results;

[0033] an updating module, configured to update the benchmark group data to the first group of operating data if the benchmark group data is retained;

[0034] The processing module is used to repeat the functions of the aforementioned comparison module, determination module and update module for the second set of operation data, the third set of operation data, ..., the Mth set of operation data of the production process equipment obtained subsequently, where M is an integer greater than or equal to 1.

[0035] In a third aspect, an embodiment of the present invention provides an electronic device, including:

[0036] A memory and a processor, wherein the processor and the memory communicate with each other via a bus; the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the method described in the first aspect and each step in various possible implementations.

[0037] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect and each step in various possible implementations.

[0038] In a fifth aspect, an embodiment of the present invention provides a computer program product comprising instructions, which, when run on a computer, enables the computer to execute the various steps in the method and various possible implementations described in the first aspect.

[0039] The embodiments of the present invention provide the following technical effects:

[0040] 1) For production process equipment such as pumps, fans, and air compressors whose operating data does not change much, the embodiment of the present invention compares each first operating data with the corresponding first data and second data to obtain each first comparison result and each second comparison result, where the first data = the reference data + the data variable corresponding to the reference data, and the second data = the reference data - the data variable corresponding to the reference data. Based on each first comparison result or each second comparison result, it is determined whether to retain the first set of operating data; if retained, the reference set of data is updated to the first set of operating data. The aforementioned steps are repeated for the second set of operating data, the third set of operating data, ..., and the Mth set of operating data of the production process equipment obtained subsequently, where M is an integer greater than or equal to 1. This can significantly reduce the storage and transmission volume of the operating data.

[0041] 2) Due to the reduction in the amount of data transmission, the transmission cost can be reduced when using existing civilian wireless networks for transmission;

[0042] 3) Compared with storing all the operating data, the operating data with reduced storage volume according to the embodiment of the present invention can be used for operating efficiency evaluation and fault diagnosis, achieving 95% consistency, which fully meets production needs.

[0043] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 A diagram of a system architecture applicable to an embodiment of the present invention;

[0046] Figure 2 A flowchart of a data processing method provided by an embodiment of the present invention;

[0047] Figure 3a A schematic diagram of a time and power curve diagram of a baseline group of data and ten groups of operating data provided by an embodiment of the present invention;

[0048] Figure 3b A schematic diagram of time and current curves of a baseline set of data and ten sets of operating data provided by an embodiment of the present invention;

[0049] Figure 4a A schematic diagram of a time and power curve diagram of the baseline group data and the retained operating data provided in an embodiment of the present invention;

[0050] Figure 4b A schematic diagram of a time and current graph of baseline group data and retained operating data provided by an embodiment of the present invention;

[0051] Figure 5 A schematic block diagram of a data processing device provided in an embodiment of the present invention;

[0052] Figure 6 A schematic block diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0054] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The singular forms "a", "an", "the" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise.

[0055] It should be understood that the term "and / or" as used herein is merely a description of the relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0056] The word "if," as used herein, may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if monitoring (stated condition or event)" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)," depending on the context.

[0057] Operational data collection refers to the real-time or periodic collection and recording of various performance indicators and operational data during system operation. This operational data is crucial for monitoring system status, analyzing system performance, optimizing resource allocation, and preventing and resolving potential problems. It is the most fundamental link in industrial control and a key step in ensuring the performance and stability of production systems. It involves multiple aspects such as data collection, processing, storage, and analysis. The main purposes of operational data collection include: monitoring system performance to ensure stable system operation; analyzing system bottlenecks and optimizing system configuration; predicting system failures and performing maintenance in advance; supporting decision-making and improving management efficiency. Application scenarios for operational data collection include: monitoring equipment operating status and evaluating equipment operating efficiency; collecting data such as application response time, state changes, and trends; process monitoring: tracking the execution of operational processes and analyzing process efficiency; and security monitoring: collecting data on security incidents and abnormal behavior for security analysis and response.

[0058] Typically, a computer samples data at a set sampling frequency and according to its built-in clock at specified times, saving all collected operational data at that time. If more accurate operational data is required, the sampling frequency and detection accuracy can be increased. However, this increases the amount of data stored and transmitted, significantly consuming software and hardware resources.

[0059] Since the collected operation data is of float type, each operation data occupies 4 bytes. Assuming 1 data sampling point and a sampling frequency of 1 time / second, the number of bytes occupied in different time periods is shown in Table 1:

[0060] Table 1

[0061]

[0062] Sometimes a frequency of 1 time / second is not enough. For example, vibration data used for fault analysis must reach 100 times / second to be analyzable. The number of bytes occupied by one such data sampling point in different time periods is shown in Table 2:

[0063] Table 2

[0064]

[0065] Generally, the collected operation data also needs to be timestamped. Operation data without timestamps is meaningless for parameter storage, query, and diagnosis. In different programming languages, the timestamp occupies different bytes, which may be 4, 8, 64, or 256 bytes respectively. You can consider 8 bytes in general, or save the machine's time data once per second. The number of bytes occupied by timestamps in different time periods is shown in Table 2:

[0066] Table 3

[0067]

[0068] The operating data above only represents the operating data for a single sampling point. As can be seen, the actual sampling process generates a large amount of operating data. Saving and transmitting all this operating data consumes significant hardware and software resources, which in turn increases system operating costs. Therefore, a data processing method is urgently needed to reduce the amount of data stored and transmitted.

[0069] In view of this, the embodiment of the present invention provides a new idea. In order to facilitate the understanding of the present application, the system architecture applicable to the embodiment of the present invention is first described. Figure 1 An exemplary system architecture to which embodiments of the present invention may be applied is shown. Figure 1 As shown in , the system architecture may include a terminal device and a data processing device located at the server end.

[0070] The data processing device may process data using the data processing method provided in the embodiment of the present invention.

[0071] As one possible implementation method, the data processing device can be set on the server side. The user uploads data variables, the baseline group data of the production process equipment, and the first group of operating data to the server side through the terminal device. Then the data processing device uses the data processing method provided by the embodiment of the present invention to compare each first operating data with the corresponding first data and second data, and obtains each first comparison result and each second comparison result, the first data = baseline data + data variable corresponding to the baseline data, the second data = baseline data - data variable corresponding to the baseline data; according to each first comparison result or each second comparison result, determine whether to retain the first group of operating data; if retained, update the baseline group data to the first group of operating data; the user uploads the second group of operating data, the third group of operating data, ..., the Mth group of operating data of the production process equipment through the terminal device, M is an integer greater than or equal to 1; the data processing device repeats the above steps for the second group of operating data, the third group of operating data, ..., the Mth group of operating data of the production process equipment obtained subsequently. Wherein, the data processing device and the terminal device can interact through the network, Figure 1 The illustrated system illustrates this implementation.

[0072] The above-mentioned data processing device can be set up in a single server, or in a server group consisting of multiple servers, or in a cloud server. A cloud server, also known as a cloud computing server or cloud host, is a host product in the cloud computing service system to solve the defects of difficult management and weak service scalability in traditional physical hosts and virtual private servers (VPS). Figure 1 In addition to the shown architecture, the data processing device can also be set in a computer terminal with strong computing capabilities.

[0073] Terminal devices may include, but are not limited to, smart mobile terminals, smart home devices, wearable devices, and personal computers (PCs). Smart mobile terminals may include mobile phones, tablets, laptops, PDAs (Personal Digital Assistants), and internet-connected cars. Smart home devices may include smart TVs and smart refrigerators. Wearable devices may include smart watches, smart glasses, virtual reality devices, augmented reality devices, and mixed reality devices (i.e., devices that support both virtual reality and augmented reality).

[0074] Figure 2 A flow chart of a data processing method provided by an embodiment of the present invention, which can be Figure 1 The data processing device in the system shown in FIG. Figure 2 As shown in , the method may include the following steps:

[0075] Step 201: Obtaining benchmark group data of data variables and production process equipment, where the benchmark group data includes a plurality of benchmark data.

[0076] Step 202: Acquire a first set of operating data of the production process equipment, where the first set of operating data includes a plurality of first operating data, and the plurality of reference data respectively correspond to the plurality of first operating data.

[0077] Step 203: Compare each first operating data with the corresponding first data and second data to obtain each first comparison result and each second comparison result, where the first data = benchmark data + data variable corresponding to the benchmark data, and the second data = benchmark data - data variable corresponding to the benchmark data.

[0078] Step 204: Determine whether to retain the first set of operating data according to each first comparison result or each second comparison result.

[0079] Step 205: If retained, update the baseline group data to the first group of operating data.

[0080] Step 206: Repeat the aforementioned steps 203, 204 and 205 for the second set of operating data, the third set of operating data, ..., the Mth set of operating data of the production process equipment obtained subsequently, where M is an integer greater than or equal to 1.

[0081] The following describes in detail each step of the above process and the effects that can be further produced in conjunction with the embodiments of the present invention. It should be noted that the "first" and "second" and other limitations involved in the embodiments of the present invention do not have restrictions on size, order, or quantity, but are only used to distinguish them in name. For example, "first comparison result" and "second comparison result" are used to distinguish two different comparison results.

[0082] First, the above step 201, namely, "obtaining data variables and benchmark group data of production process equipment, wherein the benchmark group data includes a plurality of benchmark data", is described in detail in conjunction with an embodiment of the present invention.

[0083] In an embodiment of the present invention, a data processing device obtains data variables and benchmark group data of production process equipment, and the benchmark group data includes a plurality of benchmark data.

[0084] As one possible implementation manner, the data processing device may collect the operating data of the production process equipment at preset time intervals.

[0085] As one possible implementation method, a group of operation data of the production process equipment collected at any time is used as the benchmark group data, and the benchmark group data is given a timestamp t0.

[0086] As one possible implementation method, the production process equipment includes pumps, fans, and air compressors.

[0087] The above step 202, i.e., "obtaining a first set of operating data of the production process equipment, the first set of operating data including a plurality of first operating data, and the plurality of reference data respectively corresponding to the plurality of first operating data" is described in detail below in conjunction with an embodiment of the present invention.

[0088] In the embodiment of the present invention, after step 201, the data processing device obtains a first set of operating data of the production process equipment, the first set of operating data including a plurality of first operating data, the plurality of reference data corresponding to the plurality of first operating data, and the first set of operating data carries a timestamp t1.

[0089] As one possible implementation manner, the first set of operating data includes: at least one of the inlet pressure, outlet pressure, power, flow, current, and voltage of the production process equipment.

[0090] As one possible implementation, the subsequent step 206 further acquires the second set of operation data, ..., and the Mth set of operation data. The second set of operation data, ..., and the Mth set of operation data are respectively provided with time stamps t2, ..., t M . The time interval between each two adjacent timestamps is the preset time interval. That is, the time interval between t1 and t0 is the preset time interval, the time interval between t2 and t1 is the preset time interval, ..., t M With t M-1 The time interval between them is a preset time interval. For example, M is 10. The first set of operating data, the second set of operating data, ..., the ninth set of operating data, and the tenth set of operating data respectively include the power and current of the production process equipment, as shown in Table 4. The timestamps of the first set of operating data, the second set of operating data, ..., the ninth set of operating data, and the tenth set of operating data are t1, t2, ..., t9, t 10 .

[0091] Table 4

[0092]

[0093] It should be noted that in the embodiments of the present invention, illustratively, the first set of operating data, the second set of operating data, ..., the ninth set of operating data, and the tenth set of operating data each include only power and current. The baseline set of data also includes only power and current. The power included in the baseline set of data is referred to as the first baseline data, and the data variable in this case is referred to as the first data variable. Exemplarily, the first baseline data is 7, and the first data variable is 0.2. The current included in the baseline set of data is referred to as the second baseline data, and the data variable in this case is referred to as the second data variable. Exemplarily, the second baseline data is 25, and the second data variable is 1.

[0094] For example, the timestamp t0 corresponding to the reference group data is 0, and the timestamps t1, t2, ..., t9, t10 corresponding to the first group of operation data, the second group of operation data, ..., the ninth group of operation data, and the tenth group of operation data are respectively 10 They are 1, 2, ..., 9, and 10 respectively. The time and power curve is as follows Figure 3a As shown, the time and current curve is as follows Figure 3b shown.

[0095] The above-mentioned step 203, namely, "comparing each first operating data with the corresponding first data and second data, respectively, to obtain each first comparison result and each second comparison result, first data = benchmark data + data variable corresponding to the benchmark data, second data = benchmark data - data variable corresponding to the benchmark data" is described in detail below in conjunction with an embodiment of the present invention.

[0096] In an embodiment of the present invention, each first operating data is compared with the corresponding first data and second data to obtain each first comparison result and each second comparison result, where the first data = reference data + data variable corresponding to the reference data, and the second data = reference data - data variable corresponding to the reference data.

[0097] As one possible implementation, when the power included in the baseline group data is referred to as the first baseline data and the data variable is referred to as the first data variable, the first data = the first baseline data + the first data variable corresponding to the first baseline data, and the second data = the first baseline data - the first data variable corresponding to the first baseline data. When the current included in the baseline group data is referred to as the second baseline data and the data variable is referred to as the second data variable, the first data = the second baseline data + the second data variable corresponding to the second baseline data, and the second data = the second baseline data - the second data variable corresponding to the second baseline data.

[0098] The above step 204, ie, "determining whether to retain the first set of operating data according to each first comparison result or each second comparison result," is described in detail below in conjunction with an embodiment of the present invention.

[0099] In the embodiment of the present invention, whether to retain the first set of operating data is determined according to each first comparison result or each second comparison result.

[0100] As one possible implementation method, if one or more first comparison results among the first comparison results are that the first operating data corresponding to the first comparison result is greater than the first data, or if one or more second comparison results among the second comparison results are that the first operating data corresponding to the second comparison result is less than the second data, then it is determined that the first set of operating data is retained, otherwise it is not retained.

[0101] For example, the first baseline data is 7, and the first data variable is 0.2. In this case, the first data = 7 + 0.2 = 7.2, and the second data = 7 - 0.2 = 6.8. As shown in Table 4, the first set of operating data includes a power of 7.5, which is greater than 7.2, so the first set of operating data is retained. The second baseline data is 25, and the second data variable is 1. In this case, the first data = 25 + 1 = 26, and the second data = 25 - 1 = 24. As shown in Table 4, the first set of operating data includes a current of 25, which is not greater than 26 and not less than 24, so the first set of operating data is not retained.

[0102] It should be noted that, as can be seen from the above, the first set of operating data is determined to be retained based on the power included in the first set of operating data being greater than the first data value of 7.2, while the first set of operating data is determined not to be retained based on the current included in the first set of operating data being neither greater than the first data value of 26 nor less than the first data value of 24. In this case, the first set of operating data is determined to be retained based on whether one or more of the first comparison results indicates that the first operating data corresponding to the first comparison result is greater than the first data, or whether one or more of the second comparison results indicates that the first operating data corresponding to the second comparison result is less than the second data. In other words, as long as the first set of operating data is determined to be retained based on one parameter (power or current) included in the first set of operating data, the first set of operating data is retained.

[0103] The above step 205, ie, "if retained, updating the reference group data to the first group of operating data" is described in detail below in conjunction with an embodiment of the present invention.

[0104] In the embodiment of the present invention, if the first set of operating data is retained in step 204 , the reference set of data is updated to the first set of operating data.

[0105] Exemplarily, the baseline group data, namely 7 and 25, is updated to the first group of operating data, namely 7.5 and 25.

[0106] The above-mentioned step 206, i.e., "repeating the above-mentioned steps 203, 204 and 205 for the second set of operating data, the third set of operating data, ..., the Mth set of operating data of the production process equipment obtained subsequently, where M is an integer greater than or equal to 1" is described in detail below in conjunction with an embodiment of the present invention.

[0107] In an embodiment of the present invention, the aforementioned steps 203, 204 and 205 are repeated for the second set of operating data, the third set of operating data, ..., the Mth set of operating data of the production process equipment obtained subsequently, where M is an integer greater than or equal to 1.

[0108] In an embodiment of the present invention, it is determined to retain the baseline group data; it is determined to retain N groups of operating data from the first group of operating data, the second group of operating data, ..., the Mth group of operating data, where N is an integer greater than or equal to 1 and less than or equal to M; and N charts are generated based on the baseline group data and the N groups of operating data and the timestamps corresponding to the baseline group data and the N groups of operating data, respectively.

[0109] As one possible implementation method, the powers in the N groups of operating data are P1, P2, ..., P N , the currents are I1, I2, ..., I N The timestamps corresponding to the N powers and currents are t'1, ..., t' N ,The timestamp corresponding to the power and current in the benchmark group data is t'0.

[0110] As one possible implementation method, N charts are generated based on the benchmark group data and N groups of operating data and the timestamps corresponding to the benchmark group data and the N groups of operating data, including: using time as the horizontal axis and power as the vertical axis, according to P1, P2, ..., P N and P1, P2, ..., P N The corresponding timestamps are t'1, ..., t' N and the power included in the benchmark group data and the timestamp t'0 corresponding to the power included in the benchmark group data, determine the first N+1 points; connect every two adjacent points in the first N+1 points with a straight line to obtain a first graph; use time as the horizontal axis and current as the vertical axis, according to I1, I2, ..., I N and I1, I2, ..., I N The corresponding timestamps are t'1, ..., t' N and the current included in the reference group data and the timestamp t'0 corresponding to the current included in the reference group data, determining the second N+1 points; and connecting every two adjacent points in the second N+1 points with a straight line to obtain a second graph.

[0111] As one possible implementation manner, a first chart and a second chart are displayed.

[0112] As one possible implementation, the second, ..., and Mth groups of operating data each include at least one of the inlet pressure, outlet pressure, power, flow rate, current, and voltage of the production process equipment. In this embodiment of the present invention, it is assumed that the second, ..., and Mth groups of operating data only include power and current.

[0113] For example, the baseline data set at this time is the first set of operating data. At this time, 7.5 + 0.2 = 7.7, and 7.5 - 0.2 = 7.3. The power 7.4 in the second set of operating data is neither greater than 7.7 nor less than 7.3, so the second set of operating data is not retained. At this time, 25 + 1 = 26, and 25 - 1 = 24. The current 25 in the second set of operating data is neither greater than 26 nor less than 24, so the second set of operating data is not retained. In summary, the second set of operating data is not retained. The baseline data set at this time remains the first set of operating data.

[0114] For example, if the baseline data set is still the first set of operating data, then 7.5 + 0.2 = 7.7, and 7.5 - 0.2 = 7.3. The power 7.2 in the third set of operating data is not greater than 7.7, but less than 7.3. Therefore, the third set of operating data is retained. It is no longer necessary to determine whether to retain the third set of operating data based on the current in the third set of operating data. The baseline data set is now updated to the third set of operating data.

[0115] For example, the baseline data set at this point is the third set of operating data. At this point, 7.2 + 0.2 = 7.4, and 7.2 - 0.2 = 7. The power 7.1 in the fourth set of operating data is neither greater than 7.4 nor less than 7, so the fourth set of operating data is not retained. At this point, 23 + 1 = 24, and 23 - 1 = 22. 23 is neither greater than 24 nor less than 22, so the fourth set of operating data is not retained. In summary, the fourth set of operating data is not retained. The baseline data set at this point remains the third set of operating data.

[0116] For example, the baseline data set at this time is the third set of operating data. At this time, 7.2 + 0.2 = 7.4, and 7.2 - 0.2 = 7. The power 7 in the fifth set of operating data is neither greater than 7.4 nor less than 7. Therefore, the fifth set of operating data is not retained. At this time, 23 + 1 = 24, and 23 - 1 = 22. Although 21 is not greater than 24, it is less than 22. Therefore, the fifth set of operating data is retained. In summary, the fifth set of operating data is retained. The baseline data set is updated to the fifth set of operating data.

[0117] For example, the baseline data set at this point is the fifth set of operating data. At this point, 7 + 0.2 = 7.2, and 7 - 0.2 = 6.8. The power 7.1 in the sixth set of operating data is neither greater than 7.2 nor less than 6.8, so the sixth set of operating data is not retained. At this point, 21 + 1 = 22, and 21 - 1 = 20. 22 is neither greater than 22 nor less than 20, so the sixth set of operating data is not retained. In summary, the sixth set of operating data is not retained. The baseline data set at this point remains the fifth set of operating data.

[0118] For example, the baseline data set at this time is the fifth set of operating data. At this time, 7 + 0.2 = 7.2, and 7 - 0.2 = 6.8. The power 7.2 in the seventh set of operating data is neither greater than 7.2 nor less than 6.8, so the seventh set of operating data is not retained. At this time, 21 + 1 = 22, and 21 - 1 = 20. Since 25 is greater than 22, the seventh set of operating data is retained. In summary, the seventh set of operating data is retained. At this point, the baseline data set is updated to the seventh set of operating data.

[0119] For example, the baseline data set at this time is the seventh set of operating data. At this time, 7.2 + 0.2 = 7.4, 7.2 - 0.2 = 7. The power of 6.8 in the eighth set of operating data is less than 7, so the eighth set of operating data is retained. It is no longer necessary to determine whether to retain the eighth set of operating data based on the current in the eighth set of operating data. The baseline data set is now updated to the eighth set of operating data.

[0120] For example, the baseline data set at this time is the eighth set of operating data. At this time, 6.8 + 0.2 = 7, and 6.8 - 0.2 = 6.6. The power 6.7 in the ninth set of operating data is neither greater than 7 nor less than 6.6, so the ninth set of operating data is not retained. At this time, 24 + 1 = 25, and 24 - 1 = 23. The current 25 in the ninth set of operating data is neither greater than 25 nor less than 23, so the ninth set of operating data is not retained. In summary, the ninth set of operating data is not retained. The baseline data set at this time remains the eighth set of operating data.

[0121] For example, the baseline data set at this time is the eighth set of operating data. At this time, 6.8 + 0.2 = 7, and 6.8 - 0.2 = 6.6. The power 7 in the tenth set of operating data is neither greater than 7 nor less than 6.6, so the tenth set of operating data is not retained. At this time, 24 + 1 = 25, and 24 - 1 = 23. The current 25 in the tenth set of operating data is neither greater than 25 nor less than 23, so the tenth set of operating data is not retained. In summary, the tenth set of operating data is not retained.

[0122] In summary, the remaining operating data are the first, third, fifth, seventh and eighth groups of operating data, and the corresponding timestamps are t1, t3, t5, t7 and t8, which are 1, 3, 5, 7 and 8. The time and power curve is as follows: Figure 4a As shown, the time and current curve is as follows Figure 4b That is to say, the N groups of operating data retained above are the first group of operating data, the third group of operating data, the fifth group of operating data, the seventh group of operating data and the eighth group of operating data, and the N charts are Figure 4a and Figure 4b The first chart is Figure 4a , the second chart is Figure 4b .

[0123] As can be seen from the above content, the embodiment of the present invention is aimed at production process equipment such as pumps, fans, and air compressors whose operating data does not change much. The embodiment of the present invention obtains each first comparison result and each second comparison result by comparing each first operating data with the corresponding first data and second data, where the first data = reference data + data variable corresponding to the reference data, and the second data = reference data - data variable corresponding to the reference data; based on each first comparison result or each second comparison result, it is determined whether to retain the first set of operating data; if retained, the reference set data is updated to the first set of operating data; the above steps are repeated for the second set of operating data, the third set of operating data, ..., and the Mth set of operating data of the production process equipment obtained subsequently, where M is an integer greater than or equal to 1, which can significantly reduce the storage and transmission volume of the operating data; due to the reduction in the amount of operating data transmitted, the transmission cost can be reduced when transmitting using existing civilian wireless networks; compared with storing all the operating data, the operating efficiency evaluation and fault diagnosis using the operating data with reduced storage volume according to the embodiment of the present invention can achieve 95% consistency, fully meeting production needs.

[0124] According to an embodiment of another aspect, a data processing apparatus is provided. Figure 5 A schematic block diagram of a data processing device according to an embodiment is shown. The device may be arranged in Figure 1 The server side of the architecture shown in Figure 1. Figure 5 As shown, the apparatus may include: a first acquisition module 501, a second acquisition module 502, a comparison module 503, a determination module 504, an update module 505, and a processing module 506. The main functions of each component module are as follows:

[0125] The first acquisition module 501 is used to acquire data variables and benchmark group data of production process equipment, wherein the benchmark group data includes multiple benchmark data;

[0126] The second acquisition module 502 is used to acquire a first set of operating data of the production process equipment, where the first set of operating data includes a plurality of first operating data, and the plurality of reference data are respectively in correspondence with the plurality of first operating data;

[0127] The comparison module 503 is configured to compare each first operating data with the corresponding first data and second data, respectively, to obtain each first comparison result and each second comparison result, where the first data = the reference data + the data variable corresponding to the reference data, and the second data = the reference data - the data variable corresponding to the reference data;

[0128] The determination module 504 is configured to determine whether to retain the first set of operating data based on the respective first comparison results or the respective second comparison results;

[0129] The updating module 505 is configured to update the reference group data to the first group of operating data if the reference group data is retained;

[0130] The processing module 506 is used to repeat the functions of the aforementioned comparison module, determination module and update module for the second set of operation data, the third set of operation data, ..., the Mth set of operation data of the production process equipment obtained subsequently, where M is an integer greater than or equal to 1.

[0131] In one possible implementation, the determination module 504 is specifically used to determine whether to retain the first set of operating data if one of the first comparison results among the first comparison results is that the first operating data is greater than the corresponding first data or one of the second comparison results among the second comparison results is that the first operating data is less than the corresponding second data, otherwise not to retain it.

[0132] In one possible implementation, the device also includes a target processing module for determining to retain baseline group data; determining to retain N groups of operating data from the first group of operating data, the second group of operating data,..., the Mth group of operating data, where N is an integer greater than or equal to 1 and less than or equal to M; and generating N charts based on the baseline group data and the N groups of operating data and the timestamps corresponding to the baseline group data and the N groups of operating data respectively.

[0133] In a possible implementation, each piece of operating data in each group of operating data in the N groups of operating data is power and voltage of production process equipment.

[0134] In a possible implementation, the powers in the N groups of operating data are P1, P2, ..., P N , the currents are I1, I2, ..., I N The timestamps corresponding to the N powers and currents are t'1, ..., t'N , the timestamp corresponding to the power and current in the benchmark group data is t'0;

[0135] The target processing module is specifically used to use time as the horizontal coordinate and power as the vertical coordinate according to P1, P2, ..., P N and P1, P2, ..., P N The corresponding timestamps are t'1, ..., t' N and the power included in the reference group data and the timestamp t'0 corresponding to the power included in the reference group data, determining the first N+1 points;

[0136] Connecting every two adjacent points in the first N+1 points with a straight line to obtain a first graph;

[0137] With time as the horizontal axis and current as the vertical axis, according to I1, I2, ..., I N and I1, I2, ..., I N The corresponding timestamps are t'1, ..., t' N and the current included in the reference group data and the timestamp t'0 corresponding to the current included in the reference group data, determining the second N+1 points;

[0138] Connect every two adjacent points in the second N+1 points with a straight line to obtain a second graph.

[0139] In a possible implementation, the device further includes a display module, configured to display the first chart and the second chart.

[0140] In one possible implementation, the production process equipment includes a pump, a fan, and an air compressor.

[0141] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple. For the relevant parts, refer to the partial description of the method embodiment. The device embodiment described above is only exemplary, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without making any creative efforts.

[0142] In addition, an embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of any one of the methods in the aforementioned method embodiments are implemented.

[0143] And an electronic device comprising:

[0144] one or more processors; and

[0145] A memory associated with the one or more processors, the memory being used to store program instructions, wherein the program instructions, when read and executed by the one or more processors, execute the steps of any one of the method embodiments described above.

[0146] An embodiment of the present invention further provides a computer program product, comprising a computer program, which implements the steps of any one of the methods described in the aforementioned method embodiments when executed by a processor.

[0147] in, Figure 6 The electronic device architecture is shown as an example, and may include a processor 610, a video display adapter 611, a disk drive 612, an input / output interface 613, a network interface 614, and a memory 620. The processor 610, the video display adapter 611, the disk drive 612, the input / output interface 613, the network interface 614, and the memory 620 may be communicatively connected via a communication bus 630.

[0148] The processor 610 may be implemented as a general-purpose CPU, a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and may be used to execute relevant programs to implement the technical solutions provided by the embodiments of the present invention.

[0149] The memory 620 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 620 can store an operating system 621 for controlling the operation of the electronic device 600 and a basic input and output system (BIOS) 622 for controlling the low-level operations of the electronic device 600. In addition, a web browser 623, a data storage management system 624, and a data processing device 625 can also be stored. The above-mentioned data processing device 625 can be an application program that specifically implements the operations of the aforementioned steps in the embodiment of the present invention. In short, when the technical solution provided by the embodiment of the present invention is implemented by software or firmware, the relevant program code is stored in the memory 620 and is called and executed by the processor 610.

[0150] The input / output interface 613 is used to connect to an input / output module to implement information input and output. The input / output module can be configured as a component in the device (not shown in the figure) or can be externally connected to the device to provide corresponding functions. Among them, input devices may include a keyboard, mouse, touch screen, microphone, various sensors, etc., and output devices may include a display, speaker, vibrator, indicator light, etc.

[0151] The network interface 614 is used to connect to a communication module (not shown) to enable communication between the device and other devices. The communication module can communicate via a wired method (such as USB, network cable, etc.) or a wireless method (such as mobile network, WiFi, Bluetooth, etc.).

[0152] The bus 630 comprises a pathway for transmitting information between the various components of the device (eg, the processor 610 , the video display adapter 611 , the disk drive 612 , the input / output interface 613 , the network interface 614 , and the memory 620 ).

[0153] It should be noted that although the above device only shows a processor 610, a video display adapter 611, a disk drive 612, an input / output interface 613, a network interface 614, a memory 620, a bus 630, etc., in a specific implementation, the device may also include other components necessary for normal operation. In addition, it will be understood by those skilled in the art that the above device may also include only the components necessary to implement the solution of the present application, and does not necessarily include all the components shown in the figure.

[0154] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0155] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, rather than to limit them. Although the embodiments of the present invention have been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A data processing method, characterized in that: include: Step 1: obtaining a benchmark group data of data variables and production process equipment, wherein the benchmark group data includes a plurality of benchmark data; Step 2: obtaining a first set of operating data of the production process equipment, wherein the first set of operating data includes a plurality of first operating data, and the plurality of reference data respectively correspond to the plurality of first operating data; Step 3: Compare each first operating data with the corresponding first data and second data to obtain each first comparison result and each second comparison result, where the first data = reference data + a data variable corresponding to the reference data, and the second data = reference data - a data variable corresponding to the reference data; Step 4: determining whether to retain the first set of operating data based on the first comparison results or the second comparison results; Step 5: If retained, update the benchmark group data to the first group of operating data; Step 6: Repeat the aforementioned steps 3, 4, and 5 for the second set of operating data, the third set of operating data, ..., the Mth set of operating data of the production process equipment obtained subsequently, where M is an integer greater than or equal to 1.

2. The method according to claim 1, characterized in that The determining whether to retain the first set of operating data according to each of the first comparison results or each of the second comparison results includes: If one of the first comparison results is that the first operating data is greater than the corresponding first data, or one of the second comparison results is that the first operating data is less than the corresponding second data, it is determined that the first set of operating data is retained, otherwise it is not retained.

3. The method according to claim 1, characterized in that The method further comprises: Determine to retain the baseline group data; Determining to retain N sets of operating data from the first set of operating data, the second set of operating data, ..., the Mth set of operating data, where N is an integer greater than or equal to 1 and less than or equal to M; N charts are generated according to the benchmark group data, the N groups of operating data, and timestamps corresponding to the benchmark group data and the N groups of operating data.

4. The method according to claim 3, characterized in that Each piece of operating data in each of the N groups of operating data is the power and voltage of the production process equipment.

5. The method according to claim 4, characterized in that The powers in the N groups of operating data are P1, P2, ..., P N , the currents are I1, I2, ..., I N The timestamps corresponding to the N powers and currents are t'1, ..., t' N , the timestamp corresponding to the power and current in the benchmark group data is t'0; Generating N charts according to the benchmark group data and the N groups of operating data and the timestamps corresponding to the benchmark group data and the N groups of operating data, respectively, includes: With time as the horizontal axis and power as the vertical axis, according to P1, P2, ..., P N and P1, P2, ..., P N The corresponding timestamps are t'1, ..., t' N and the power included in the reference group data and the timestamp t'0 corresponding to the power included in the reference group data, determining the first N+1 points; Connecting every two adjacent points in the first N+1 points with a straight line to obtain a first graph; With time as the horizontal axis and current as the vertical axis, according to I1, I2, ..., I N and I1, I2, ..., I N The corresponding timestamps are t'1, ..., t' N and the current included in the reference group data and the timestamp t'0 corresponding to the current included in the reference group data, determining the second N+1 points; Connect every two adjacent points in the second N+1 points with a straight line to obtain a second graph.

6. The method according to claim 5, characterized in that The method further comprises: The first graph and the second graph are displayed.

7. The method according to any one of claims 1 to 6, characterized in that The production process equipment includes pumps, fans and air compressors.

8. A data processing device, characterized in that: include: A first acquisition module is used to acquire a data variable and a benchmark group data of a production process equipment, wherein the benchmark group data includes a plurality of benchmark data; A second acquisition module is configured to acquire a first set of operating data of the production process equipment, wherein the first set of operating data includes a plurality of first operating data, and the plurality of reference data are respectively in correspondence with the plurality of first operating data; a comparison module, configured to compare each first operating data with the corresponding first data and second data, respectively, to obtain each first comparison result and each second comparison result, wherein the first data = reference data + a data variable corresponding to the reference data, and the second data = reference data - a data variable corresponding to the reference data; a determination module, configured to determine whether to retain the first set of operating data based on the respective first comparison results or the respective second comparison results; an updating module, configured to update the benchmark group data to the first group of operating data if the benchmark group data is retained; The processing module is used to repeat the functions of the aforementioned comparison module, determination module and update module for the second set of operation data, the third set of operation data, ..., the Mth set of operation data of the production process equipment obtained subsequently, where M is an integer greater than or equal to 1.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the processor and the memory communicate with each other via a bus; The memory stores program instructions that can be executed by the processor, and the processor can execute the method according to any one of claims 1 to 7 by calling the program instructions.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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