A data collection method, device and system for distributed computing equipment

Abstract

The present invention discloses a data collection method for distributed computing equipment, which collects data at a first frequency; determines whether the data collected at the first frequency meets a preset first numerical condition; if so, sends the data collected at the first frequency to a server at a second frequency lower than the first frequency; if not, directly sends the data collected at the first frequency to the server and issues an alarm. The application of the embodiments of the present invention can achieve timely monitoring and reporting of cracks or deformations that appear instantly in pipelines, greatly reducing maintenance costs.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a data acquisition method and a computing device for distributed computing equipment, and a system for data acquisition. Background Art

[0002] In modern life, natural resources such as natural gas, oil, and water resources play a very important role. It can be said that our daily life is inseparable from the above resources. However, the places where the above natural resources are stored are quite far away from human settlements. Certain pipelines are needed for transportation. In the process of transporting resources over time, a certain part of the pipeline may fail. These failures need to be monitored and handled in a timely manner to avoid causing greater losses to the company and causing great inconvenience to people's lives.

[0003] However, in the prior art, when monitoring the failures of these pipelines, most of them are monitored and field data is transmitted in seconds. However, in practice, there are some minor faults that occur instantaneously in the pipeline system, such as cracks or deformations that suddenly appear in the pipeline at a certain point in time. Although it does not directly cause leakage, long-term neglect will eventually lead to pipeline leakage, or even more serious consequences. Since these sudden failures occur instantaneously, the corresponding changes in pressure or stress that can be detected by sensors also exist instantaneously and may recover quickly; thus, when monitoring is performed in seconds, these sudden failures are often not detected in time, resulting in the failure not being discovered in time or even being completely ignored, which puts pipeline maintenance personnel in a passive position when performing pipeline maintenance. However, if the monitoring time is changed to milliseconds, a large amount of field data will be generated; for a large number of monitoring points on site, the amount of field data superimposed is extremely large, which will cause congestion in the data transmission line.

[0004] Therefore, how to timely monitor various sudden failures in pipelines is a technical problem that needs to be solved. Summary of the invention

[0005] The present invention provides a data collection method, device and system for distributed computing equipment to solve the problem in the prior art that instantaneous cracks or deformations in a pipeline cannot be monitored.

[0006] The present invention provides a data collection method for a distributed computing device, comprising:

[0007] collecting data at a first frequency;

[0008] Determining whether the data collected at the first frequency meets a preset first numerical condition;

[0009] If yes, sending the data collected at the first frequency to the server at a second frequency lower than the first frequency;

[0010] If not, the data collected at the first frequency is directly sent to the server and an alarm is issued.

[0011] Optionally, when the data collected at the first frequency is sent to the server, a corresponding time identifier is sent synchronously;

[0012] Receive first feedback information from a server; the first feedback information at least includes record information of the time mark;

[0013] Compare the time stamp in the record information with the time stamp corresponding to the data collected at the first frequency to obtain missing data corresponding to the time stamp missing in the record information;

[0014] The missing data is uploaded to the server.

[0015] Optionally, receiving second feedback information from the server; the feedback information is used to indicate whether the server receives the data collected at the first frequency;

[0016] Determining whether data transmission is normal based on the feedback information;

[0017] If not, a backup line is selected to send the data collected at the first frequency and a prompt is given locally.

[0018] Optionally, judging whether data sending is normal based on the feedback information includes:

[0019] receiving the second feedback information;

[0020] Determine whether the sending entity of the second feedback information is a server;

[0021] If so, it is judged that the data transmission is normal;

[0022] If not, it is determined that the data transmission is abnormal.

[0023] Optionally, the selecting a standby line to send the data collected at the first frequency includes:

[0024] Sending the data collected at the first frequency to an associated device via short-range wireless transmission;

[0025] Receive the uploaded feedback from the associated device and give a prompt locally.

[0026] Optionally, sending the data collected at the first frequency to the server at a second frequency lower than the first frequency includes:

[0027] compressing the data collected at the first frequency at a second frequency lower than the first frequency;

[0028] The compressed data is packaged and uploaded to the server.

[0029] Optionally determining whether the data collected at the first frequency meets a second numerical condition;

[0030] If not, the first frequency is adjusted.

[0031] Optionally, adjusting the first frequency includes:

[0032] The second numerical condition is used to measure the numerical range of the change of the data collected at the first frequency;

[0033] If the second numerical condition is met, data is collected at a third frequency greater than the first frequency.

[0034] Optionally, the first numerical condition is adjusted based on historical data collected at a first frequency.

[0035] Optionally, adjusting the first numerical condition based on historical data collected at a first frequency includes:

[0036] obtaining a third numerical condition based on historical data collected at a first frequency; the third numerical condition being subordinate to the first numerical condition;

[0037] The first numerical condition is replaced by the third numerical condition.

[0038] The present application also provides a data collection device for a distributed computing device, comprising:

[0039] An acquisition module, used for acquiring data at a first frequency;

[0040] A comparison module, used for judging whether the data collected by the acquisition module at the first frequency meets a preset first numerical condition;

[0041] The execution module is used to send the data collected at the first frequency to the server side according to the judgment of the comparison module on whether the data collected at the first frequency meets the preset first numerical condition; if the judgment is no, the data collected at the first frequency is sent to the server side at a second frequency lower than the first frequency; if the judgment is yes, the data collected at the first frequency is directly sent to the server side and an alarm is issued.

[0042] The present application also provides a data acquisition system for a distributed computing device, comprising: a sensor, a computing device, and a server;

[0043] Among them, the sensor serves as a terminal for collecting data and is controlled by a computing device;

[0044] The computing device controls the sensor to collect data to obtain data collected at the first frequency, and processes the collected data to implement the above method;

[0045] The server is used to receive data uploaded by the distributed computing device.

[0046] The data collection method for distributed computing devices provided in the present application is characterized by comprising:

[0047] The collection method for distributed computing equipment provided by the present invention first collects data at a first frequency, and then determines whether the data collected at the first frequency meets a preset first numerical condition; if not, the data collected at the first frequency is sent to the server at a second frequency lower than the first frequency; if so, the data collected at the first frequency is directly sent to the server. The entire process arranges targeted high-speed data collection and processing processes for the occurrence of sudden faults, which increases the frequency of information data collection. At the same time, under normal circumstances, the data transmission frequency will not be too high, so that the data transmission channel will not be congested, so that the collection and processing judgment of on-site detection information can be guaranteed to be immediate and efficient; using this technical solution, the occurrence of sudden faults can be timely known, the wear of the pipeline can be fully understood, and then the pipeline faults can be predicted and avoided. . BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a simple schematic diagram of fault detection and fault handling in the prior art.

[0049] Figure 2 It is a schematic diagram of a specific scenario application according to an embodiment of the present invention.

[0050] Figure 3 It is a flow chart of a data collection method for a distributed computing device according to an embodiment of the present invention.

[0051] Figure 4 It is a schematic diagram of complete upload of verification data according to an embodiment of the present invention.

[0052] Figure 5 2 is a schematic diagram of missing data transmission of a first computing device according to an embodiment of the present invention.

[0053] Figure 6 It is a schematic diagram of selecting an alternative route to upload collected data according to an embodiment of the present invention.

[0054] Figure 7 It is a structural diagram of a data acquisition device for distributed computing equipment according to an embodiment of the present invention.

[0055] Figure 8Schematic diagram of a data acquisition system for distributed computing devices according to an embodiment of the present invention. DETAILED DESCRIPTION

[0056] Many specific details are set forth in the following description to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of the present invention, so the present invention is not limited to the specific implementation disclosed below.

[0057] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0058] In the production activities using steam and water pipelines, in order to ensure the output ratio of output value, non-stop production activities are the basic requirement. In each link of this production activity, since the pipeline is its basic functional unit, ensuring the health of the pipeline is to ensure the normal operation of the entire production activity. Therefore, for the production activities using steam and water pipelines, timely elimination of pipeline faults becomes the key to ensuring the normal operation of the entire production activity.

[0059] When troubleshooting pipeline failures, the current common management model is: timely detection of failures and timely repairs; for specific scenarios, please refer to Figure 1 , which is a schematic diagram of the application scenarios of the above-mentioned existing technical means; Figure 1As shown, the prior art means are as follows: when a failure occurs in the pipeline 101, the sensor 102 deployed on the pipeline 101 sends the failure information (generally the location where the failure occurs) to the remote server 103 through wireless communication when the failure occurs. After receiving the failure message, the remote server 103 sends a failure prompt message. After seeing the failure prompt sent by the server 103, the maintenance personnel 104 carefully checks the received failure information and designates the maintenance personnel 104 to repair and eliminate the failure at the location where the failure occurs according to the failure information. The principle of monitoring the pipeline is that when a sudden failure occurs in the pipeline, the parameters related to the fluid medium in the pipeline will also change in a short period of time. By monitoring the relevant parameters with sensors, it can be known whether the pipeline is abnormal.

[0060] In actual applications, pipeline failures are often the result of the accumulation of multiple instantaneous or short-term mutations, such as cracks, deformations, water hammer, etc. If these mutations are detected in a targeted manner, a reasonable mathematical model is arranged, and reasonable numerical analysis and judgment are performed, the wear of the pipeline can be measured, and then the severely worn pipeline can be replaced in time before the pipeline fails. In this way, pipeline failures can be avoided, and the current production management mode of first discovering the failure and then repairing it can be transformed into a production management mode of predicting failures and avoiding them in advance. However, these forms of failure can often only be monitored at the moment of failure, and after the failure, the relevant detection data is restored.

[0061] Therefore, if you want to predict the wear of the pipeline, you need to increase the collection frequency in view of the instantaneous nature of the mutation. In addition, in order to ensure the timely handling and timely discovery of faults, you need real-time and efficient data collection, data processing and data transmission.

[0062] At present, the main method for collecting and processing information is to collect information data at a low frequency and send it to the server, which then processes the data. When using this method, due to the low frequency of information collection and data processing by the server, the collected data will inevitably not be sent in a timely manner. In addition, after the server obtains the data, it must store and process it, so that the data collection and processing cannot meet the requirements, and it is impossible to know the sudden change of the pipeline in the first time, and it is impossible to update the wear condition of the pipeline in time, and even completely unable to detect the occurrence of many sudden failures. Therefore, in order to ensure the completion of the above solution, whether the collection, processing and transmission of information data is timely and efficient has become a new requirement.

[0063] In order to solve the above problems, Figure 2As described, the present application provides a specific schematic diagram under an application scenario. Here is a brief explanation: sensors 102A and 102B are arranged around the pipeline 101, and the sensors 102A, 102B, the computing device 105 and the server 103 constitute a system 210. The sensors 102A and 102B collect data information near the pipeline 101 at a first frequency and upload it to the computing device 105. The computing device 105 is an edge distributed computing device, which can judge and process the data uploaded by the sensors 102A and 102B, and decide whether to upload the processed information directly to the server 103, or send the collected data to the server at a second frequency lower than the first frequency. After the server 103 successfully receives the processed information, it generates feedback information and returns it to the computing device 105. The server 103 also prompts the maintenance personnel 104 with the prediction results so that the maintenance personnel 104 can go to the pipeline site to handle the fault. It should be noted that the types of sensors in the present application can be, for example, temperature sensors, pressure sensors, flow sensors and other types of sensors, a single combination, or a combination of two or more. The specific combination type and the number of sensors are determined according to the needs of the actual application scenario. One sensor can also correspond to one computing device, and multiple sensors can also correspond to one computing device. The correspondence between the number of sensors and the number of computing devices can be specifically set in actual applications and is not specifically limited here. The sensor 102 and the computing device 105 are generally transmitted using a short-range wireless transmission method, for example, via Bluetooth. The system 210 of the present application provides a collection method for distributed computing devices to meet the above needs. This method can collect and process information data instantly and efficiently by judging and analyzing the data locally. The following is a specific embodiment.

[0064] This application implements the implementation method of the present invention based on a distributed computing device. Figure 3 Specific flow chart for the implementation of the present invention:

[0065] Step 301: Collect data at a first frequency.

[0066] In the prior art, when the pressure data (generally temperature and pressure) of the fluid medium in the pipeline is collected in seconds, the data collection time is too long, resulting in the data at the moment of deformation or failure of the pipeline being difficult to be collected in time, and it is difficult to reflect whether the pipeline has cracks or deformation. Therefore, it is necessary to adopt a new data collection method to ensure that the collected data can reflect the situation of cracks or deformation in the pipeline. The first frequency is a preset frequency for collecting data. For example, in this embodiment, the first frequency is preset to 50HZ, that is, the sensor of the distributed computing device uses 20ms as a collection cycle, and collects data in the pipeline every 20ms. If the data is collected at a high frequency and all the data is uploaded, it will cause communication line congestion, especially when the field sensor adopts 5G and other wireless transmission methods. Therefore, in order to achieve smooth data transmission, transmission route congestion should be avoided as much as possible. In view of the above problems, this embodiment proposes the following solution: when the collected data is within the normal range, there is no need to upload the collected data to the server immediately. Therefore, a local real-time database or data table is established on the distributed computing device side (such as computing device 105), and the data collected within a period of time is temporarily stored in the local real-time database, so as to facilitate sending it to the server for storage and display later; before sending, the edge computing device, such as computing device 105, can compress, package, delete and other processing on these data in the interval time to reduce the bandwidth occupied by data upload.

[0067] S302: Determine whether the data collected at the first frequency meets the preset first numerical condition; in this embodiment, after the data is collected at the first frequency, it is determined whether the data collected at the first frequency meets the preset first numerical condition. If there is no comparison standard for the data collected in the pipeline, it is impossible to directly determine whether the currently collected data is normal data, that is, there is no fault or leakage in the pipeline at this time. Therefore, in order to facilitate the judgment of whether the currently collected data is normal data, a first numerical condition is preset in the local real-time database of the distributed computing device. The first numerical condition is generally a numerical range, which is a mathematical condition that the change of the relevant data meets when the mutation occurs, and is used to determine whether the change of the data is sufficient to indicate that the relevant pipeline part has a mutation, and is used to indicate that under the set conditions, the data collected at the first frequency is in a predetermined interval range. The predetermined interval range generally indicates that within a period of time, when the water flow rate, water flow velocity and temperature do not change much, the value of the data collected in the pipeline at this time is in a relatively stable range.

[0068] Based on the first numerical condition, two different judgment results of step S303 and step S304 can be obtained; and according to different judgment results, different data sending methods are selected, so that when no mutation occurs, the data collected multiple times can be sent together, and when a mutation occurs, the data can be sent to the server instantly, thereby realizing efficient data transmission, and enabling the server to detect the occurrence of a fault in time and perform maintenance.

[0069] Step S303: If not, sending the data collected at the first frequency to the server at a second frequency lower than the first frequency.

[0070] In order to avoid uploading the collected data directly every time, the data upload will cause line congestion. The data collected in the pipeline is compared with the value in the current numerical range. If the collected data falls within the numerical range, it means that at the moment of collecting data in the pipeline, the pipeline at the current location of the distributed computing device has not been deformed or faulty. When the data collected at the first frequency is normal data, the collected data stored in the local real-time database is sent to the server for display using the second frequency. The second frequency is generally a preset fixed frequency, which is lower than the first frequency. In this embodiment, it is generally a frequency less than 50HZ. The range is about 40-49HZ, and the range of the second frequency value cannot be set to be too different from the range of the first frequency value. The purpose is to ensure that the uploaded data can be displayed in real time on the server, which is convenient for observation and prompts. Since the data collected at the first frequency is large, the transmission speed will be affected by uploading one by one. Therefore, in order to speed up the transmission speed, the data collected at the first frequency needs to be compressed in the local real-time database of the distributed computing device, and then the compressed data is packaged and sent to the server.

[0071] Step S304: If yes, the data collected at the first frequency is directly sent to the server and an alarm is issued.

[0072] If the data collected at this time does not fall within the current first numerical range, it means that the data currently collected is abnormal data, which means that the pipeline near the location of the distributed computing device that collects the data may be deformed or have other faults. At this time, it is necessary to send the abnormal data directly from the local database of the distributed computing device to the server side, and display it in a curve or other way that allows maintenance personnel to directly observe it. In order to enable the staff on the server side to discover abnormal data as soon as possible, an alarm is issued on the server side every time abnormal data is sent to the server. The above alarm method can be implemented by the following method: by setting a small light of a special color on the server side, which flashes when an alarm is issued. Or set an alarm sound of a certain volume to emit a certain sound when the data is abnormal. Other alarm methods that can remind staff to pay attention to data abnormalities in a timely manner belong to the embodiments of the present invention, and no more examples are given here.

[0073] However, with the change of seasons, the outside temperature will also change, which will in turn affect the temperature of the pipeline. Or according to other actual conditions, the water and steam in the pipeline, the flow rate and size will also cause the data in the pipeline to change, and failures or leaks in the pipeline may occur more frequently. At this time, if the data is collected at the first frequency, it is likely that the failure or leak in the current pipeline will not be collected, resulting in omission of collected data. Therefore, the first numerical condition needs to be dynamically adjusted according to the actual situation. This dynamic adjustment can be achieved through the following two methods.

[0074] Method 1: When the external temperature or other actual conditions change, and the gap with the first numerical condition is large, a second numerical condition is established in the local real-time database of the distributed computing device according to the actual situation. The second numerical condition is used to measure the numerical range of the data collected at the first frequency, and then the second numerical condition replaces the first numerical condition as the new standard for judging whether the collected data is normal. At the same time, in order to more accurately judge the abnormality of the data, when the numerical range changes, the frequency of data collection should also be adjusted accordingly. In other words, when the collected data meets the second numerical condition, the first frequency needs to be adjusted to the third frequency. The third frequency is generally greater than the first frequency. The third frequency is adjusted according to the actual situation, and the specific range is generally greater than 50HZ.

[0075] Method 2: When the temperature or other actual conditions of the outside world change, and the difference with the first numerical condition is small, at this time, it is possible to judge whether the current external environment has changed based on the historical data collected at the first frequency, and then adjust the first numerical condition based on the historical data collected at the first frequency, and adjust the first numerical condition to the third numerical condition. The third numerical condition is subordinate to the first numerical condition. Since the first numerical condition is adjusted when the external environment does not change much, within the range of the first numerical condition, a certain small range of values ​​is used as the third numerical condition, and then the third numerical condition replaces the first numerical condition as a new standard for judging whether the collected data is normal. Since the third numerical condition is part of the first numerical condition, the first frequency is still used to collect data.

[0076] When uploading the collected data from the local real-time database to the server through the wireless transmission unit, the transmitted data may be omitted due to some reasons. Therefore, the server needs to judge the received data and generate prompts, and then return the prompts to the local real-time database. The local real-time database determines whether the data transmitted to the server is complete based on the received prompts. The present invention implements the above prompts in the following way. When the data collected at the first frequency is sent to the server, the corresponding time identifier is sent synchronously. The time identifier is generally expressed as the time when the data is collected, that is, 0.02ms is used as a time node. As a time identifier, when collecting data, a corresponding time identifier is generated and stored in the local real-time database. When the local real-time database collected data is packaged and compressed, the corresponding time identifier is also packaged and compressed, and sent to the server together with the compressed and packaged collected data through the wireless unit. Figure 4 As shown, after receiving the packaged and compressed data, the server collects the collected time stamps together to form the first feedback information, and sends the first feedback information to the local real-time database. The first feedback information at least includes the record information of the corresponding time stamp. After receiving the first feedback information sent by the server, the local real-time database compares the time stamp in the record information in the first feedback information with the time stamp corresponding to the data previously collected at the first frequency to determine whether there is a missing time stamp. If not, it means that all the collected data has been successfully uploaded from the local real-time database to the server. If yes, confirm the missing time stamp in the record information, and then search for the missing data corresponding to the missing time stamp in the local real-time database, and send it to the server, such as Figure 5 As shown, an implementation method for supplementing missing data is provided. The figure is a flow chart of the implementation method for supplementing missing data. The specific steps are as follows:

[0077] S501: Identify a sequence fingerprint in the feedback information, where the sequence fingerprint is used to indicate uniqueness of the data collected at the first frequency.

[0078] In order to verify the integrity of data transmission, it is necessary to verify whether each data is completely received by the server. In this regard, in this embodiment, a sequence fingerprint that can indicate the uniqueness of the data is used for verification; wherein, the sequence fingerprint should be understood as being contained in the data collected at the first frequency; illustratively, data sequence number, collection time, identity identifier and other unique data information can be used as the sequence fingerprint, which is not limited here.

[0079] This step requires identification of the sequence fingerprint; specifically, after the data collected at the first frequency is sent to the server, the sequence fingerprint in the data will be extracted by the server and returned in the feedback information; illustratively, the sequence fingerprint can be made into a report or data text information and returned.

[0080] S502: Compare the sequence fingerprint in the feedback information with the sequence fingerprint corresponding to the data collected at the first frequency to obtain missing data corresponding to the sequence fingerprint missing in the feedback information.

[0081] After identifying the sequence information in the feedback information, the sequence fingerprint in the feedback information is compared with the sequence fingerprint corresponding to the data collected at the first frequency, so that the missing sequence fingerprint in the feedback information can be found; and since the sequence fingerprint points to the unique data collected at the first frequency, the missing data corresponding to the missing sequence fingerprint can be easily obtained.

[0082] S503: Upload the data corresponding to the missing sequence fingerprint to the server.

[0083] After the missing data is obtained in step S502, the missing data is uploaded to the server; after the missing data is uploaded to the server, the server only needs to insert the missing data into its corresponding position according to the sequence fingerprint, so that the problem of missing data can be solved.

[0084] For example, a group of data A1, B2, C3, D4, E5 is sent to the server at the same time, where 1, 2, 3, 4, and 5 are their respective serial numbers, namely, sequence fingerprints; after the data is sent to the server, after judging the feedback information received from the server, the sequence fingerprint is interpreted, and the text information 1, 3, and 4 is obtained; it is compared with the sequence fingerprint in the data to obtain the missing data B2 and E5 and send it to the server; when comparing the fingerprints, illustratively, the sequence fingerprint layer of the data is retrieved with 1, 3, and 4 respectively, so as to filter out the data B2 and E5 that have not been retrieved and identified.

[0085] In addition to the problem of missing data in the above-mentioned data transmission, there may be other reasons that prevent data from being uploaded. For example, due to damage to the wireless unit or other reasons, the local real-time database cannot upload the collected data to the server, which will cause problems in the pipeline near the current distributed computing device and cannot be displayed on the server. Therefore, the local real-time database of the distributed computing device also needs to determine whether the server can successfully receive the sent collected data. Then continue the subsequent operations based on the received feedback information. Figure 6 The subsequent specific operation processing steps are shown and briefly explained here.

[0086] Step S601: Collect data at a first frequency and send it to a server;

[0087] Step S602: Returning the first feedback information;

[0088] Step S603: Detect and determine whether the first feedback information returned by the server is obtained.

[0089] like Figure 6 As shown, the current distributed computing device (for the convenience of distinction, it is assumed to be the first computing device 105A, and it will be described as such in the following text) sends the collected data to the server 103 at the first frequency. After successfully receiving the collected data, the server 103 generates first feedback information based on the specific situation of receiving the collected data, and returns the first feedback information to the first computing device 105A. The first feedback information is used to indicate whether the server 103 has completely received the data collected at the first frequency, specifically whether the server 103 has received the data collected at the first frequency sent by the first computing device 105A. When the first computing device 105A receives the first feedback information, it can be judged by whether the sending subject of the first feedback information is the server 103, and then determine whether the data of the first computing device 105A is sent successfully. If the sending subject of the first feedback information is the server 103, it can be determined that the data transmission between the first computing device 105A and the server 103 is normal at this time. If the sender of the first feedback information is another distributed computing device, it can be determined that the data path for the first computing device 105A to transmit data to the server 103 cannot be transmitted normally, and the backup line has begun to be used to send the data collected at the first frequency, and a prompt is given locally on the computing device 105A or on the server 103. The above prompt is used to prompt the first computing device 105A that the collected data cannot be successfully uploaded to the server 103; accordingly, relevant processing measures can be taken.

[0090] The first computing device 105A needs to determine whether the first feedback information returned by the server 103 is obtained. A predetermined time can be set in advance, and the predetermined time can be set according to the transmission time of data between the server and the collection device in the actual scenario. If the predetermined time is exceeded by default, it means that the data transmission between the first computing device 105A and the server 103 fails. Therefore, it can be determined whether the first computing device 105A receives the first feedback information returned by the server 103 within the predetermined time range. If yes, step S604 is directly executed. If not, step S605 is directly executed.

[0091] Step S603: If yes, then end the process.

[0092] If yes, it means that within the predetermined time, the first computing device 105A receives the first feedback information returned by the server 103, which also means that the server 103 successfully receives the collected data uploaded by the first computing device 105A, and the data upload process ends. The maintenance staff can repair the fault point according to the uploaded collected data.

[0093] Step S604: If not, execute the first adjustment mechanism.

[0094] If not, it means that within the predetermined time, the first computing device 105A has not received the first feedback information returned by the server 103, which also means that the server 103 has not received the collected data uploaded by the first computing device 105A, and the first adjustment mechanism is executed at this time. At this time, since the data collected by the first computing device 105A at the first frequency has not been sent to the server 103, the first adjustment mechanism can be understood as sending the data collected by the first computing device 105A in other ways. Figure 6 Steps S605-S606 in provide one of the other methods, which are described in detail below.

[0095] Step S605-1: Send test information to the associated device;

[0096] The associated device (assumed to be the second computing device 105B, which will be used in the following description) means a device that is within a certain range from the first computing device 105A and can normally exchange information. In other words, the associated device only needs to be able to normally receive, process and send data. In this embodiment, the associated device can be a computing device related to production activities, or other devices that are not closely related to production activities. This embodiment does not limit the specific form of the associated device.

[0097] The first computing device 105A sends test information to the second computing device 105B. This is because when an abnormal situation occurs in which the first feedback information is not obtained, if the abnormal reason is that the function of the first computing device 105A receiving information is abnormal, then the feedback information of other devices cannot be received; and if the function of data transmission is abnormal, the feedback information of other devices can be received; based on this, different abnormal reasons can be judged by whether the information of other devices can be received, and then corresponding adjustments can be made to ensure the normal transmission of data and find out the abnormal reasons for resolution.

[0098] Step S605-2: Returning the second feedback information;

[0099] Step S605-3: Detect and determine whether second feedback information corresponding to the test information is obtained;

[0100] The first computing device 105A first sends a test message to the second computing device 105B; wherein the test message is used to test whether the function of the first computing device 105A to receive information is normal. Specifically, the second computing device 105B can respond to the test message, that is, return second feedback information corresponding to the test information. In other words, the specific reason why the first computing device 105A did not receive the first feedback information can be determined by whether the second computing device 105B receives the returned second feedback information.

[0101] Step S606-1: If so, the data collected at the first frequency is sent to the associated device via short-distance wireless transmission, and prompts that the data is sent abnormally;

[0102] Step S606-2: the associated device receives the message that the first frequency data collection and the data transmission are abnormal, and sends the message that the first frequency data collection and the data transmission are abnormal to the server;

[0103] Step S606-3: the server returns the third feedback information to the associated device;

[0104] Step S606-4: The associated device receives the third feedback information returned by the server and returns it to the first computing device.

[0105] When the first computing device 105A successfully receives the second feedback information, it means that the function of the first computing device 105a to receive information is normal, and the corresponding explanation is that the reason for failing to receive the first feedback information is that the function of the first computing device 105A to send data to the server 103 is abnormal. At this time, the data transmission path can be changed, that is, the data collected at the first frequency is sent to the second computing device 105B by short-distance wireless transmission, and the second computing device 105B then uploads the first frequency collected data to the server 103. After receiving the collected data uploaded by the second computing device 105B, the server 103 generates the third feedback information and returns the third feedback information to the second computing device 105B. After receiving the third feedback information, the second computing device 105B returns it to the first computing device 105A. That is, in this embodiment, the second computing device 105B is used as a transfer station for data transmission between the first computing device 105A and the server 103. In this way, it can be ensured that the collected data can be sent to the server 103 in time during the abnormal sending function of the first computing device 105A.

[0106] Of course, when the server 103 finds that the first computing device 105A cannot upload data smoothly, it is necessary to promptly dispatch maintenance personnel to repair the first computing device 105A. Otherwise, the long-term selection of the backup line to send the collected data will cause congestion problems for the upload lines of other computing devices, resulting in problems in the pipelines near other distributed computing devices. It cannot be reported to the server 103 in time, which causes great difficulties for subsequent maintenance.

[0107] Figure 7 4 is a structural diagram of a data acquisition device 700 for distributed computing equipment according to an embodiment of the present invention.

[0108] The device comprises the following units:

[0109] The acquisition module 710 is used to acquire data at a first frequency;

[0110] A comparison module 720, configured to determine whether the data collected by the collection module at the first frequency meets a preset first numerical condition;

[0111] The execution module 730 is used to send the data collected at the first frequency to the server side according to the judgment of the comparison module on whether the data collected at the first frequency meets the preset first numerical condition; if the judgment is no, the data collected at the first frequency is sent to the server side at a second frequency lower than the first frequency; if the judgment is yes, the data collected at the first frequency is directly sent to the server side and an alarm is issued.

[0112] Optionally, when the data collected at the first frequency is sent to the server, a corresponding time mark is sent synchronously;

[0113] Receive first feedback information from a server; the first feedback information at least includes record information of the time mark;

[0114] Compare the time stamp in the record information with the time stamp corresponding to the data collected at the first frequency to obtain missing data corresponding to the time stamp missing in the record information;

[0115] The missing data is uploaded to the server.

[0116] Optionally, second feedback information from the server is received; the feedback information is used to indicate whether the server receives the data collected at the first frequency;

[0117] Determining whether data transmission is normal based on the feedback information;

[0118] If not, a backup line is selected to send the data collected at the first frequency and a prompt is given locally.

[0119] Optionally, judging whether data transmission is normal based on the feedback information includes:

[0120] receiving the second feedback information;

[0121] Determine whether the sending entity of the second feedback information is a server;

[0122] If so, it is judged that the data transmission is normal;

[0123] If not, it is determined that the data transmission is abnormal.

[0124] Optionally, the selecting a standby line to send the data collected at the first frequency includes:

[0125] Sending the data collected at the first frequency to an associated device via short-range wireless transmission;

[0126] Receive the uploaded feedback from the associated device and give a prompt locally.

[0127] Optionally, sending the data collected at the first frequency to the server at a second frequency lower than the first frequency includes:

[0128] compressing the data collected at the first frequency at a second frequency lower than the first frequency;

[0129] The compressed data is packaged and uploaded to the server.

[0130] Optionally, determining whether the data collected at the first frequency meets a second numerical condition;

[0131] If not, the first frequency is adjusted.

[0132] Optionally, adjusting the first frequency includes:

[0133] The second numerical condition is used to measure the numerical range of the change of the data collected at the first frequency;

[0134] If the second numerical condition is met, data is collected at a third frequency greater than the first frequency.

[0135] Optionally, the first numerical condition is adjusted based on historical data collected at a first frequency.

[0136] Optionally, adjusting the first numerical condition based on historical data collected at a first frequency includes:

[0137] obtaining a third numerical condition based on historical data collected at a first frequency; the third numerical condition being subordinate to the first numerical condition;

[0138] The first numerical condition is replaced by the third numerical condition.

[0139] Figure 8 This is a schematic diagram of a data acquisition system for distributed computing devices according to an embodiment of the present invention, including: a sensor 810 , a computing device 820 , and a server 830 .

[0140] Among them, the sensor 810 is used as a terminal for collecting data and is controlled by the computing device 820;

[0141] 820, the computing device controls the sensor to collect data to obtain data collected at the first frequency, and processes the collected data to implement the above method;

[0142] 830 The server is used to receive data uploaded by the distributed computing device.

[0143] Although the present invention is disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be based on the scope defined by the claims of the present invention.

Claims

1. A data collection method for a distributed computing device, characterized in that: include: The sensors arranged around the pipeline collect data related to the fluid medium in the pipeline at a first frequency, and upload the data related to the fluid medium collected at the first frequency to the distributed computing device, and the sensors and the distributed computing device transmit data using a short-range wireless transmission method; The distributed computing device determines whether the fluid medium related data collected at the first frequency meets a preset first numerical condition, wherein the first numerical condition is a mathematical condition met by the change of the related data when a sudden change occurs in the pipeline, and is used to determine whether the change of the fluid medium related data indicates that a sudden change occurs in the relevant pipeline part; wherein a local real-time database is established in the distributed computing device, and the fluid medium related data collected within a period of time is temporarily stored in the local real-time database; If not, it is determined that no mutation phenomenon has occurred in the pipeline at the location of the distributed computing device, and the fluid medium related data collected multiple times at the first frequency are sent to the server end at a second frequency lower than the first frequency, and the fluid medium related data collected multiple times at the first frequency are stored in the local real-time database; If so, it is determined that the fluid medium related data collected at the first frequency is abnormal data, and it is determined that a sudden change may occur in the pipeline where the distributed computing device is located, and the abnormal data is instantly sent from the local real-time database to the server end, and an alarm is issued; If the distributed computing device does not receive the first feedback information returned by the server, a test message is sent to an associated device, wherein the first feedback information is used to indicate whether the server has completely received the fluid medium related data collected at the first frequency, and the associated device is a device that is within a certain range from the distributed computing device and can normally perform information exchange, and the test information is used to test whether the function of the distributed computing device to receive information is normal; If the distributed computing device obtains second feedback information corresponding to the test information, the fluid medium related data collected at the first frequency will be sent to the associated device via short-range wireless transmission, and a prompt will be given that the sending data is abnormal, so that the associated device will send the fluid medium related data collected at the first frequency and a message about the sending data abnormality to the server end. After the associated device receives the third feedback information returned by the server end, the third feedback information will be returned to the distributed computing device.

2. The method according to claim 1, characterized in that Also includes: When the fluid medium related data collected at the first frequency is sent to the server, a corresponding time mark is sent synchronously; Receiving first feedback information from the server; The first feedback information at least includes the record information of the time mark; Comparing the time mark in the recorded information with the time mark corresponding to the fluid medium related data collected at the first frequency, to obtain missing data corresponding to the time mark missing in the recorded information; The missing data is uploaded to the server.

3. The method according to claim 1, characterized in that The method of sending the fluid medium related data collected multiple times at the first frequency to the server end at a second frequency lower than the first frequency, and storing the fluid medium related data collected multiple times at the first frequency in the local real-time database, comprises: compressing the fluid medium related data collected multiple times at the first frequency at the second frequency, and storing the fluid medium related data collected multiple times at the first frequency in the local real-time database; Pack the compressed data and upload it to the server.

4. The method according to claim 1, characterized in that: include: Determining whether the fluid medium related data collected at the first frequency meets the second numerical condition; If not, the first frequency is adjusted.

5. The method according to claim 4, characterized in that Adjusting the first frequency includes: The second numerical condition is used to calculate the numerical range of the change of the fluid medium related data collected at the first frequency; If the second numerical condition is met, the fluid medium related data is collected at a third frequency greater than the first frequency.

6. The method according to claim 1, characterized in that include: The first numerical condition is adjusted based on historical data collected at a first frequency.

7. The method according to claim 6, characterized in that Adjusting the first numerical condition based on historical data collected at a first frequency includes: obtaining a third numerical condition based on historical data collected at a first frequency; the third numerical condition being subordinate to the first numerical condition; The first numerical condition is replaced by the third numerical condition.

8. A data collection device for distributed computing equipment, characterized in that: include: A collection module, used for collecting data related to the fluid medium in the pipeline at a first frequency; A comparison module, used for judging whether the fluid medium related data collected by the collection module at the first frequency meets a preset first numerical condition; The first numerical condition is a mathematical condition that the change of the relevant data meets when a sudden change occurs in the pipeline, and is used to determine whether the change of the fluid medium related data indicates that a sudden change occurs in the relevant pipeline part; wherein a local real-time database is established in the distributed computing device, and the fluid medium related data collected within a period of time is temporarily stored in the local real-time database; an execution module, configured to send the fluid medium related data collected at the first frequency to the server side according to the judgment of the comparison module on whether the fluid medium related data collected at the first frequency meets the preset first numerical condition; if the judgment is negative, determine that the pipeline at the location of the distributed computing device has not currently undergone a mutation phenomenon, send the fluid medium related data collected multiple times at the first frequency to the server side at a second frequency lower than the first frequency, and store the fluid medium related data collected multiple times at the first frequency in the local real-time database; if the judgment is positive, determine that the fluid medium related data collected at the first frequency is abnormal data, and determine that the pipeline at the location of the distributed computing device may undergo a mutation phenomenon, then send the abnormal data from the local real-time database to the server side instantaneously, and issue an alarm; If the distributed computing device does not receive the first feedback information returned by the server, a test message is sent to an associated device, wherein the first feedback information is used to indicate whether the server has completely received the fluid medium related data collected at the first frequency, and the associated device is a device that is within a certain range from the distributed computing device and can normally perform information exchange, and the test information is used to test whether the function of the distributed computing device to receive information is normal; If the distributed computing device obtains second feedback information corresponding to the test information, the fluid medium related data collected at the first frequency will be sent to the associated device via short-range wireless transmission, and a prompt will be given that the sending data is abnormal, so that the associated device will send the fluid medium related data collected at the first frequency and a message about the sending data abnormality to the server end. After the associated device receives the third feedback information returned by the server end, the third feedback information will be returned to the distributed computing device.

9. A data acquisition system for distributed computing devices, characterized in that: include: Sensors, computing devices, servers; Among them, the sensor serves as a terminal for collecting data and is controlled by a computing device; The computing device controls the sensor to collect data to obtain data collected at the first frequency, and processes the collected data to implement the method described in any one of claims 1 to 7; The server is used to receive data uploaded by the distributed computing device.

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