CN118174959A - Intelligent diagnosis method, system and storage medium based on equipment online data - Google Patents

Abstract

The application provides an intelligent diagnosis method, a system and a storage medium based on equipment online data, wherein the method comprises the following steps: the method comprises the steps that an acquisition terminal acquires first data in a first period, compares the first data with preset normal data before the first period to determine whether the first data are consistent, writes a destination address of a first data packet header into an emergency destination address to obtain a first packet if the first data are inconsistent, and sends the first packet to data transfer equipment; after receiving the first packet, the data transfer device forwards the first packet to a data center corresponding to the emergency destination address with the highest priority if the destination address of the first packet is determined to be the emergency destination address; after the data center receives the first packet, analyzing the first packet to obtain first data of the first packet, performing intelligent diagnosis on the first data to determine a first abnormal condition corresponding to the first data, and executing an emergency flow corresponding to the first abnormal condition. The application has the advantage of high safety.

Description

Intelligent diagnosis method, system and storage medium based on equipment online data

Technical Field

The present invention relates to the Internet and data fields, and in particular to an intelligent diagnosis method, system and storage medium based on online data of equipment.

Background technique

The Industrial Internet is a new type of infrastructure, application model and industrial ecology that is a deep integration of the new generation of information and communication technology and the industrial economy. By fully connecting people, machines, objects, systems, etc., it builds a new manufacturing and service system covering the entire industrial chain and the entire value chain, providing a way to achieve the digitalization, networking and intelligent development of industry and even industries.

Online data based on industrial equipment needs to be diagnosed whether it is abnormal. The existing online data only transmits the online data, and does not diagnose whether the data is abnormal, which affects the safety of industrial equipment.

Summary of the invention

The embodiments of the present invention provide an intelligent diagnosis method, system and storage medium based on online data of equipment, which perform rapid abnormality diagnosis on industrial Internet data, improve the response speed to abnormal situations, and improve the safety of equipment in the same industry.

In a first aspect, an embodiment of the present invention provides an intelligent diagnosis method based on online data of a device, the method comprising the following steps:

The collection terminal collects first data within a first period, compares the first data with preset normal data before the first period to determine whether they are consistent, if they are consistent, writes the destination address of the first data packet header into the destination address of the communication transfer device to obtain a first packet, and sends the first packet to the data transfer device; if they are inconsistent, writes the destination address of the first data packet header into the emergency destination address to obtain a first packet, and sends the first packet to the data transfer device;

After receiving the first packet, if the data transfer device determines that the destination address of the first packet is an emergency destination address, the first packet is forwarded to the data center corresponding to the emergency destination address with the highest priority; if the destination address of the first packet is determined to be a local address, the normal data processing process is executed;

After receiving the first packet, the data center parses the first packet to obtain first data of the first packet, performs intelligent diagnosis on the first data to determine a first abnormal situation corresponding to the first data, and executes an emergency process corresponding to the first abnormal situation.

In a second aspect, an intelligent diagnosis method based on online data of a device is provided, wherein the system comprises: a collection terminal, a data transfer device and a data center.

A collection terminal is used to collect first data in a first period, compare the first data with preset normal data before the first period to determine whether they are consistent, if they are consistent, write the destination address of the first data packet header into the destination address of the communication transfer device to obtain a first packet, and send the first packet to the data transfer device; if they are inconsistent, write the destination address of the first data packet header into the emergency destination address to obtain the first packet, and send the first packet to the data transfer device;

The data transfer device is used for, after receiving the first packet, if it is determined that the destination address of the first packet is an emergency destination address, forwarding the first packet to the data center corresponding to the emergency destination address with the highest priority, and if it is determined that the destination address of the first packet is a local address, executing a normal data processing flow;

The data center is used for, after receiving the first packet, parsing the first packet to obtain first data of the first packet, performing intelligent diagnosis on the first data to determine a first abnormal situation corresponding to the first data, and executing an emergency process corresponding to the first abnormal situation.

In a third aspect, a computer-readable storage medium is provided, which stores a program for electronic data exchange, wherein the program enables an intelligent diagnosis system based on online data of equipment to execute the method provided in the first aspect.

Implementing the embodiments of the present invention has the following beneficial effects: the technical solution provided by the present application collects the first data in the first cycle by the acquisition terminal, compares the first data with the zeroth data of the zeroth cycle before the first cycle to determine whether they are consistent; if they are consistent, write the destination address of the first data packet header into the destination address of the communication transfer device to obtain the first packet, and send the first packet to the data transfer device; if they are inconsistent, write the destination address of the first data packet header into the emergency destination address to obtain the first packet, and send the first packet to the data transfer device; after the data transfer device receives the first packet, if it is determined that the destination address of the first packet is the emergency destination address, forward the first packet to the data center corresponding to the emergency destination address with the highest priority; if it is determined that the destination address of the first packet is the local address, execute the normal data processing process; after the data center receives the first packet, parses the first packet to obtain the first data of the first packet, performs intelligent diagnosis on the first data to determine the abnormal situation corresponding to the first data, and executes the emergency process corresponding to the abnormal situation. In this way, for the collection terminal, the abnormal data can be quickly sent to the data center through the emergency destination address. After the data center processes and determines the abnormal situation, it executes the corresponding emergency process, which avoids the delay of diagnosis of the data transfer equipment. For the collection terminal, the data it processes will not have forwarded data, and only local collection data will be processed. Therefore, the data processing speed can be improved, the abnormal response speed can be improved, and the abnormal situation diagnosis speed can be improved, thereby improving the security of data.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

FIG1 is a schematic diagram of the structure of an industrial Internet;

FIG2 is a schematic diagram of a process of an intelligent diagnosis method based on online data of equipment;

FIG. 3 is a schematic diagram of the structure of an intelligent diagnosis system based on online equipment data.

Detailed ways

The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

The terms "first", "second", "third" and "fourth" etc. in the specification and claims of the present invention and the drawings are used to distinguish different objects rather than to describe a specific order. 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 comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

Reference to "embodiments" herein means that a particular feature, result, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

Refer to Figure 1, which provides a structural diagram of an industrial Internet. Specifically, as shown in Figure 1, the industrial Internet may include: a data center 100, a communication transfer device 101, and a collection terminal 102, wherein the data center 100 is connected to the communication transfer device 101, and the collection terminal 102 is connected to the communication transfer device 101. The above connection methods may specifically be: limited method, wireless method, etc. communication methods, and the present application does not limit the above communication methods.

The acquisition terminal 102 may be various sensors, including but not limited to: a temperature sensor, a pressure sensor, a position sensor, an image sensor, a smoke sensor, and the like.

The communication transfer device 101 can be a computer device, and of course it can also be a communication device with data transfer, such as an access point (AP). The data center can be composed of multiple computer devices. The computer device can be a computer device with an operating system such as IOS, Android, Hongmeng, etc., and of course it can also be a computer device of other systems. This application does not limit the specific operating system. The computer device can be connected to other devices wirelessly, and of course it can also be connected to other devices by wire. The computer device can specifically be: a personal computer, a server, a tablet computer, etc.

For the data of the Industrial Internet, the data collected are generally specific data, such as the temperature data collected by the temperature sensor, the pressure data collected by the pressure sensor, etc. For such data, especially the data of the Industrial Internet, the data have a certain degree of repeatability. For example, due to the repeatability of industrial manufacturing, the sampling frequency of the temperature sensor is consistent, so the temperature data collected by the temperature sensor has periodic repeatability. In addition, the data collected by the same type of sensors at different locations may also be the same. The existing Industrial Internet transmits all data, which increases the amount of data transmitted and the subsequent storage capacity.

Referring to FIG. 2 , FIG. 2 is a flow chart of an intelligent diagnosis method based on online equipment data provided by the present application. The method is executed in the industrial Internet shown in FIG. 1 , and as shown in FIG. 2 , includes the following steps:

Step S201, the collection terminal collects the first data in the first cycle, compares the first data with the preset normal data before the first cycle to determine whether they are consistent, if they are consistent, write the destination address of the first data packet header into the destination address of the communication transfer device to obtain the first packet, and send the first packet to the data transfer device; if they are inconsistent, write the destination address of the first data packet header into the emergency destination address to obtain the first packet, and send the first packet to the data transfer device;

By way of example, comparing the first data with the preset normal data before the first cycle to determine whether they are consistent may specifically include:

The acquisition terminal adds the numerical value of each bit of the first data to obtain a first sum, and compares the first sum with the sum threshold (the numerical sum of the preset normal data) to see if they are consistent. If they are consistent (the difference between the first sum and the sum threshold may be zero or the difference may be within the first range), it is determined that the first data is consistent with the preset normal data before the first cycle; if they are inconsistent (the opposite of consistency, which will not be repeated here), it is determined that the first data is inconsistent with the preset normal data before the first cycle.

This method can reduce the overhead of comparison and can improve the speed compared with the normal one-by-one comparison. For one-by-one comparison, both data (preset normal data and first data) need to be extracted. Taking 32 kilobits of data as an example, it needs to occupy 64 kilobits of memory, which requires a lot of memory for the acquisition terminal because the data processing capacity of the acquisition terminal is limited. However, for only the comparison of and, only the first data needs to be extracted, that is, only 32 kilobits of memory is needed. For the and threshold, generally only 32 bits are occupied, which is almost negligible. Therefore, the memory occupied by this method will be reduced. In addition, the principle of and comparison is explained. Since the data collected by the acquisition terminal in the industrial Internet is very regular, taking the temperature sensor as an example, when there is no abnormal temperature, the temperature values collected in one cycle should be consistent, and since it is the same sensor, the acquisition frequency is also the same. Therefore, under normal circumstances, there is almost no difference in the data collected in one cycle, so it is possible to pass the and abnormality check.

For example, the emergency destination address may be a preset destination address, which may be a MAC address or an IP address, such as a special unused address such as 11111111. The emergency destination address may specifically be a virtual destination address allocated by an emergency processing device in a data center.

Step S202: After receiving the first packet, if the data transfer device determines that the destination address of the first packet is an emergency destination address, the first packet is forwarded to the data center corresponding to the emergency destination address with the highest priority; if the destination address of the first packet is determined to be a local address, the normal data processing process is executed;

For example, the above normal data processing flow may specifically include:

The first data of the first packet is saved or the collection period corresponding to the first packet is saved. Of course, in practical applications, since the first data is the same as the preset normal data, only the collection period corresponding to the first packet needs to be saved. This can reduce the amount of data storage.

Step S203: After receiving the first packet, the data center parses the first packet to obtain first data of the first packet, performs intelligent diagnosis on the first data to determine a first abnormal situation corresponding to the first data, and executes an emergency process corresponding to the first abnormal situation.

The emergency process for executing the abnormal situation can be obtained through the preset emergency process. For example, if the abnormal situation is temperature control abnormality, the production of the corresponding industrial equipment can be suspended. The emergency process can be set by the user or determined according to the historical emergency process.

The technical solution provided by the present application is that the acquisition terminal acquires the first data within the first cycle, compares the first data with the zeroth data of the zeroth cycle before the first cycle to determine whether they are consistent; if they are consistent, write the destination address of the first data packet header into the destination address of the communication transfer device to obtain the first packet, and send the first packet to the data transfer device; if they are inconsistent, write the destination address of the first data packet header into the emergency destination address to obtain the first packet, and send the first packet to the data transfer device; after the data transfer device receives the first packet, if it is determined that the destination address of the first packet is the emergency destination address, forward the first packet to the data center corresponding to the emergency destination address with the highest priority; if it is determined that the destination address of the first packet is the local address, execute the normal data processing process; after the data center receives the first packet, parses the first packet to obtain the first data of the first packet, performs intelligent diagnosis on the first data to determine the abnormal situation corresponding to the first data, and executes the emergency process corresponding to the abnormal situation. In this way, for the collection terminal, the abnormal data can be quickly sent to the data center through the emergency destination address. After the data center processes and determines the abnormal situation, it executes the corresponding emergency process, which avoids the delay of diagnosis of the data transfer equipment. For the collection terminal, the data it processes will not have forwarded data, and only local collection data will be processed. Therefore, the data processing speed can be improved, the abnormal response speed can be improved, and the abnormal situation diagnosis speed can be improved, thereby improving the security of data.

By way of example, the above-mentioned performing intelligent diagnosis on the first data to determine the abnormal situation corresponding to the first data specifically includes:

The first data is compared with preset normal data to determine an abnormal area of the first data, the abnormal area is analyzed to obtain an abnormal value corresponding to the abnormal area, the difference between the abnormal value and the normal value is calculated to obtain a first difference, and the abnormal situation of the first data is determined according to the interval in which the first difference is located.

The above-mentioned determining the abnormality of the first data according to the interval in which the first difference value is located may specifically include:

A first interval corresponding to the first difference is determined, and a first abnormal situation corresponding to the first interval is queried from a mapping relationship between intervals and abnormal situations.

Taking temperature as an example, the abnormal area is analyzed to obtain the abnormal value corresponding to the abnormal area, that is, the binary value of the abnormal area is converted into a decimal value. For example, the abnormal value is 50℃, the normal value is 30℃, and the difference is 20℃. In this way, the abnormal situation corresponding to 20℃ can be queried. The mapping relationship between the above interval and the abnormal situation can be obtained through the statistical data between the historical abnormal situation and the difference, which will not be repeated here.

For example, before executing the emergency process corresponding to the first abnormal situation, the above method may further include:

The data center obtains the association relationship of the first abnormal situation, extracts other data collected by other collection terminals under the association relationship in the first period, and the data center conducts intelligent diagnosis on the other data to determine the second situation corresponding to the other data. If the first abnormal situation is consistent with the second situation, the emergency process corresponding to the first abnormal situation is executed. If the second situation is normal, it is determined that the collection terminal is an equipment abnormality.

For example, the correlation between the above abnormal conditions can be obtained based on historical data. For example, if the first abnormal condition is a fire, the temperature value will be very high. At the same time, the smoke sensor will also detect the abnormality. Therefore, if the first abnormal condition is a fire, if the acquisition terminal is a temperature sensor, the data collected by the smoke sensor in the same area as the temperature sensor in the first cycle can be extracted as other data. Of course, there may be other correlations based on different abnormal conditions. The present application does not limit the specific form of expression of the above correlation.

Referring to FIG. 3 , FIG. 3 provides a schematic diagram of the structure of an intelligent diagnosis system based on online data of equipment, the system comprising: a collection terminal, a data transfer device and a data center,

A collection terminal is used to collect first data in a first period, compare the first data with preset normal data before the first period to determine whether they are consistent, if they are consistent, write the destination address of the first data packet header into the destination address of the communication transfer device to obtain a first packet, and send the first packet to the data transfer device; if they are inconsistent, write the destination address of the first data packet header into the emergency destination address to obtain a first packet, and send the first packet to the data transfer device;

The data transfer device is used for, after receiving the first packet, if it is determined that the destination address of the first packet is an emergency destination address, forwarding the first packet to the data center corresponding to the emergency destination address with the highest priority, and if it is determined that the destination address of the first packet is a local address, executing a normal data processing flow;

The data center is used for, after receiving the first packet, parsing the first packet to obtain first data of the first packet, performing intelligent diagnosis on the first data to determine a first abnormal situation corresponding to the first data, and executing an emergency process corresponding to the first abnormal situation.

For example,

The acquisition terminal is specifically used to add the numerical value of each bit of the first data to obtain a first sum, and compare the first sum with the sum threshold to see if they are consistent. If they are consistent, it is determined that the first data is consistent with the preset normal data before the first cycle; if they are inconsistent, it is determined that the first data is inconsistent with the preset normal data before the first cycle.

For example,

The collection terminal is specifically used to compare the first data with the preset normal data to determine the abnormal area of the first data, analyze the abnormal area to obtain the abnormal value corresponding to the abnormal area, calculate the difference between the abnormal value and the normal value to obtain the first difference, and determine the abnormal situation of the first data according to the interval where the first difference is located; determining the abnormal situation of the first data according to the interval where the first difference is located specifically includes: determining the first interval corresponding to the first difference, and querying the first abnormal situation corresponding to the first interval from the mapping relationship between the interval and the abnormal situation.

An embodiment of the present invention also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the intelligent diagnosis methods based on online data of equipment as recorded in the above method embodiments.

An embodiment of the present invention also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute part or all of the steps of any one of the intelligent diagnosis methods based on online data of the device as recorded in the above method embodiments.

It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be received in other sequences or performed simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present invention.

In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be electrical or other forms.

A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated: ROM), a random access memory (English: Random Access Memory, abbreviated: RAM), a magnetic disk or an optical disk, etc.

The embodiments of the present invention are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims (9)

1. An intelligent diagnosis method based on equipment online data is characterized by comprising the following steps:

The method comprises the steps that an acquisition terminal acquires first data in a first period, compares the first data with preset normal data before the first period to determine whether the first data are consistent, writes a destination address of a first data packet header into a destination address of communication transfer equipment to obtain a first packet, sends the first packet to the data transfer equipment, writes the destination address of the first data packet header into an emergency destination address to obtain the first packet if the first data are inconsistent, and sends the first packet to the data transfer equipment;

After the data transfer equipment receives the first packet, if the destination address of the first packet is determined to be an emergency destination address, forwarding the first packet to a data center corresponding to the emergency destination address with the highest priority, and if the destination address of the first packet is determined to be a local address, executing a normal data processing flow;

After the data center receives the first packet, analyzing the first packet to obtain first data of the first packet, performing intelligent diagnosis on the first data to determine a first abnormal condition corresponding to the first data, and executing an emergency flow corresponding to the first abnormal condition.

2. The intelligent diagnostic method based on the on-line data of the device according to claim 1, wherein comparing the first data with the preset normal data before the first period to determine whether the first data is consistent specifically comprises:

the acquisition terminal adds the numerical value of each bit of the first data to obtain a first sum, compares the first sum with a threshold value to judge whether the first sum is consistent or not, if so, determines that the first data is consistent with preset normal data before the first period, and if not, determines that the first data is inconsistent with the preset normal data before the first period.

3. The intelligent diagnosis method based on the on-line data of the device according to claim 1, wherein the normal data processing flow specifically comprises:

The data transfer device stores the first data of the first packet or the acquisition period corresponding to the first packet.

4. The intelligent diagnosis method based on the on-line data of the device according to claim 1, wherein the performing intelligent diagnosis on the first data to determine the abnormal condition corresponding to the first data specifically includes:

Comparing the first data with preset normal data to determine an abnormal region of the first data, analyzing the abnormal region to obtain an abnormal value corresponding to the abnormal region, calculating the difference between the abnormal value and the normal value to obtain a first difference value, and determining the abnormal condition of the first data according to the section where the first difference value is located;

the determining the abnormal condition of the first data according to the interval where the first difference value is located specifically includes:

And determining a first interval corresponding to the first difference value, and inquiring the first abnormal condition corresponding to the first interval from the mapping relation between the interval and the abnormal condition.

5. An intelligent diagnostic system based on device online data, the system comprising: the acquisition terminal, the data transfer equipment and the data center are characterized in that,

The acquisition terminal is used for acquiring first data in a first period, comparing the first data with preset normal data before the first period to determine whether the first data are consistent, if so, writing a destination address of a first data packet header into a destination address of the communication transfer equipment to obtain a first packet, sending the first packet to the data transfer equipment, and if not, writing the destination address of the first data packet header into an emergency destination address to obtain the first packet, and sending the first packet to the data transfer equipment;

The data transfer equipment is used for forwarding the first packet to a data center corresponding to the emergency destination address with the highest priority if the destination address of the first packet is determined to be the emergency destination address after the first packet is received, and executing a normal data processing flow if the destination address of the first packet is determined to be the local address;

And the data center is used for analyzing the first packet to obtain first data of the first packet after receiving the first packet, performing intelligent diagnosis on the first data to determine a first abnormal condition corresponding to the first data, and executing an emergency flow corresponding to the first abnormal condition.

6. The intelligent diagnostic system based on-line data of a device of claim 5,

The acquisition terminal is specifically configured to add the value of each bit of the first data to obtain a first sum, compare the first sum with a threshold value, and determine whether the first sum is consistent with preset normal data before the first period if the first sum is consistent with the threshold value, and determine that the first data is inconsistent with the preset normal data before the first period if the first sum is inconsistent with the threshold value.

7. The intelligent diagnostic system based on-line data of claim 5, wherein the normal data processing flow specifically comprises:

The data transfer device stores the first data of the first packet or the acquisition period corresponding to the first packet.

8. The intelligent diagnostic system based on-line data of a device of claim 5, wherein,

The acquisition terminal is specifically configured to compare the first data with preset normal data to determine an abnormal region of the first data, analyze the abnormal region to obtain an abnormal value corresponding to the abnormal region, calculate a difference between the abnormal value and the normal value to obtain a first difference value, and determine an abnormal condition of the first data according to a section where the first difference value is located; the determining the abnormal condition of the first data according to the interval where the first difference value is located specifically includes: and determining a first interval corresponding to the first difference value, and inquiring the first abnormal condition corresponding to the first interval from the mapping relation between the interval and the abnormal condition.

9. A computer-readable storage medium storing a program for electronic data exchange, characterized in that the program causes a device online data-based intelligent diagnostic system to perform the method according to any one of claims 1-4.