KR20240142058A - Device failure diagnosis detection system using AI chatbot - Google Patents

Abstract

The present invention relates to a device fault diagnosis detection system using an AI chatbot, and is characterized in that the system comprises an information management unit storing and managing basic data on at least one device; an alarm information collection unit collecting information on an alarm when an alarm for an abnormal symptom of the device occurs; an information detection unit obtaining basic data on the device where the alarm occurred from the information management unit and simultaneously obtaining information on the alarm from the alarm information collection unit when an alarm occurs in the device; a query generation unit generating at least one piece of query information based on the basic data and alarm information of the device obtained by the information detection unit; and a query provision unit providing the query information generated by the query generation unit to at least one AI chatbot through an Internet network and receiving response information from the AI chatbot for the query information and providing it to an administrator.
When an alarm for an abnormal symptom occurs in a device, the information detection unit obtains basic data about the device in which the alarm occurred from the information management unit, and at the same time, information about the alarm of the device is obtained from the alarm information collection unit and transmitted to the query generation unit, and the query generation unit automatically generates query information about the cause or solution of the abnormal symptom of the device in which the alarm occurred accurately and specifically, and the query information is inquired about to at least one AI chatbot through the query provision unit, and based on expert-level response information provided by the AI chatbot, the effect of inducing an effective resolution of the abnormal symptom of the device.
In addition, since it is a system in which query information is generated in the query generation unit based on the information acquired in the information detection unit, and the generated query information is provided to the AI chatbot through the query provision unit to receive response information, the series of processes are performed very quickly, so it is possible to quickly and accurately resolve abnormal symptoms occurring in the device, which has the effect of inducing stable operation management of the facility.
In addition, even if there is no expert on-site to diagnose abnormal symptoms of the device, it has the effect of inducing stable operation management of the device in the field as even beginners can flexibly respond when abnormal symptoms of the device occur.

Description

Device failure diagnosis detection system using AI chatbot

The present invention relates to a device fault diagnosis detection system using an AI chatbot, and more specifically, when an alarm for an abnormality occurs in a device, an information detection unit obtains basic data about the device in which the alarm occurred from an information management unit, and at the same time, information about the alarm of the device is obtained from an alarm information collection unit and transmitted to a query generation unit, and the query generation unit automatically generates query information about the cause or solution of the abnormality of the device in which the alarm occurred in an accurate and specific manner, and the query information is inquired about to at least one AI chatbot through a query provision unit so as to effectively resolve the abnormality of the device based on expert-level answer information provided by the AI chatbot.

In general, stable operation is very important for various devices used for automation processes of facilities.

For example, in the facilities of a large-scale production plant, tens or hundreds of devices are installed and operate in conjunction with each other to continuously produce products. If one of the many devices breaks down, a catastrophic situation can occur in which the entire operation of the facility comes to a halt.

At this time, downtime due to equipment failure inevitably results in enormous losses not only in equipment repair costs but also in operating costs and business effects wasted while the facility is down.

According to recent data from the Ministry of Employment and Labor and the Korea Occupational Safety & Health Agency, the total number of casualties from industrial accidents each year is estimated at around 100,000, and when converted to cost, it is estimated that an annual loss of 18 trillion won occurs.

To prevent these problems, devices or systems are being developed that detect abnormalities in the device and send an alarm to the surrounding area so that the device can be inspected and repaired.

However, even when abnormal symptoms of a device are detected through the above devices or systems, there are frequent cases where there is no expert on-site who can diagnose the cause of the abnormal symptom based on the abnormal symptom of the device and resolve the cause, so there is a problem in that it is difficult to respond smoothly to the abnormal symptoms of the device.

Moreover, even if there were experts, there was a problem that it took a lot of time for experts to diagnose the abnormal area, and the diagnosis results were often inaccurate, making it difficult to repair the device smoothly.

Meanwhile, AI CHATBOT is a technology that uses natural language processing to provide a service similar to a person-to-person conversation between a computer and a person. It is a technology that allows information to be obtained in a way similar to a person-to-person conversation without using an interface such as the web or an application.

In addition, AI chatbots have been providing services at the level of providing answers determined by pre-entered algorithms, but recently, AI chatbot services have made great strides with big data analysis, machine learning, and natural language processing technologies, and are evolving to provide accurate and correct answers to inquiries.

The present invention has been proposed to solve the above-mentioned problems, and its purpose is to provide a device fault diagnosis and detection system utilizing an AI chatbot, in which, when an alarm for an abnormal symptom occurs in a device, an information detection unit obtains basic data about the device in which the alarm occurred from an information management unit, and at the same time, information about the alarm of the device is obtained from an alarm information collection unit and transmitted to a query generation unit, and the query generation unit automatically generates query information about the cause or solution of the abnormal symptom of the device in which the alarm occurred accurately and specifically, and the query information is inquired about to at least one AI chatbot through a query provision unit, and the AI chatbot provides expert-level answer information so as to effectively resolve the abnormal symptom of the device.

In addition, since it is a system in which query information is generated in the query generation unit based on the information acquired in the information detection unit, and the generated query information is provided to the AI chatbot through the query provision unit to receive response information, a series of processes are performed very quickly, so it is possible to quickly and accurately resolve abnormal symptoms occurring in the device, thereby providing a device fault diagnosis and detection system utilizing an AI chatbot that can induce stable operation management of the equipment.

In addition, we are providing a device fault diagnosis and detection system utilizing AI chatbot that can induce stable operation and management of the device in the field by allowing even beginners to flexibly respond when abnormal symptoms of the device occur even if there is no expert diagnosing abnormal symptoms of the device on site where the device is used.

In order to achieve the above purpose, the system for diagnosing and detecting a device failure using an AI chatbot according to the present invention is characterized by including: an information management unit for storing and managing basic data on at least one device; an alarm information collection unit for collecting information on an alarm when an alarm regarding an abnormality in the device occurs; an information detection unit for obtaining basic data on the device in which the alarm occurred from the information management unit and simultaneously obtaining information on the alarm from the alarm information collection unit when an alarm occurs in the device; a query generation unit for generating at least one piece of query information based on the basic data and alarm information of the device obtained by the information detection unit; and a query provision unit for providing the query information generated by the query generation unit to at least one AI chatbot through an Internet network and receiving response information from the AI chatbot regarding the query information and providing it to an administrator.

In addition, the query generation unit is characterized by including an automatic module that automatically generates at least one query information including a sentence in language to resolve an abnormal symptom of the device based on the basic data and alarm information of the device acquired from the information detection unit.

In addition, the invention is characterized by further including a manual module that allows the query information generated through the automatic module of the query generation unit to be directly modified by the user, or allows the query information to be manually generated directly by the user.

In addition, the basic data of the device stored and managed in the above information management department includes the type of device, manufacturer, year of manufacture, specification information, service life, intended use, and operation information.

The above operating information is characterized by using waveform information that represents, in a graph form, information on changes in the size of item values over time for items that can be collected during the operation of the device, including energy consumed for the operation of the device, vibrations generated during the operation of the device, noise generated during the operation of the device, temperature, humidity, and pressure of the device or surroundings during the operation of the device.

In addition, the information management unit further comprises an image module that converts waveform information stored as operational information into an image, such as a photograph;

The above information detection unit is characterized in that, when an alarm occurs in a device, basic data about the device in which the alarm occurred is obtained from the information management unit, and the waveform information of the operation information is obtained as image information visualized through the image module so that the image information can be included as basic data in the query information generated by the query generation unit.

In addition, if the alarm information collected by the alarm information collection unit is an alarm corresponding to an item of the operation information, the waveform information of the device for the operation information item corresponding to the alarm is collected at the time the alarm occurs, and then the waveform information is imaged through the image module.

The above information detection unit is characterized by obtaining alarm information including image information from the alarm information collection unit.

In addition, it further includes a shooting module for taking pictures or videos of the device;

When an alarm occurs in the device, the photographing module is characterized in that it provides a photo or video information taken of the device in which the alarm occurred to the alarm information collection unit.

As described above, according to the device fault diagnosis detection system utilizing the AI chatbot according to the present invention, when an alarm for an abnormality occurs in the device, the information detection unit obtains basic data about the device in which the alarm occurred from the information management unit, and at the same time, information about the alarm of the device is obtained from the alarm information collection unit and transmitted to the query generation unit, and the query generation unit automatically generates query information about the cause or solution of the abnormality of the device in which the alarm occurred accurately and specifically, and the query information is inquired about to at least one AI chatbot through the query provision unit, and based on expert-level answer information provided by the AI chatbot, there is an effect of inducing effective resolution of the abnormality of the device.

In addition, since it is a system in which query information is generated in the query generation unit based on the information acquired in the information detection unit, and the generated query information is provided to the AI chatbot through the query provision unit to receive response information, the series of processes are performed very quickly, so it is possible to quickly and accurately resolve abnormal symptoms occurring in the device, which has the effect of inducing stable operation management of the facility.

In addition, even if there is no expert on-site to diagnose abnormal symptoms of the device, it has the effect of inducing stable operation management of the device in the field as even beginners can flexibly respond when abnormal symptoms of the device occur.

Figure 1 is a conceptual diagram of a device fault diagnosis detection system utilizing an AI chatbot according to an embodiment of the present invention.
Figure 2 is a drawing for explaining a device fault diagnosis detection system utilizing the AI chatbot illustrated in Figure 1.

A device fault diagnosis detection system utilizing an AI chatbot according to a preferred embodiment of the present invention is described in detail based on the attached drawings. Detailed descriptions of known functions and configurations that may unnecessarily obscure the gist of the present invention are omitted.

FIG. 1 and FIG. 2 illustrate a device fault diagnosis detection system utilizing an AI chatbot according to an embodiment of the present invention. FIG. 1 illustrates a conceptual diagram of a device fault diagnosis detection system utilizing an AI chatbot according to an embodiment of the present invention, and FIG. 2 illustrates a diagram for explaining a device fault diagnosis detection system utilizing the AI chatbot illustrated in FIG. 1.

As illustrated in FIG. 1, a device fault diagnosis detection system (100) utilizing an AI chatbot according to an embodiment of the present invention includes an information management unit (10), an alarm information collection unit (20), an information detection unit (30), a query generation unit (40), and a query provision unit (50).

The above information management unit (10) ensures that basic data for at least one device is stored and managed.

Here, as illustrated in Fig. 2a, the basic data of the device stored and managed in the information management unit (10) may include detailed information such as the type of the device, manufacturer, year of production, specification information, service life, intended use, and operation information, as information included in the query information to be generated in the query generation unit (40) described later. The reason for collecting detailed information about the device in this way is to include detailed information about the device in the query information generated in the query generation unit (40) to increase the accuracy of the answer output from the AI chatbot.

Normally, the more accurate and specific the content of the query to the AI chatbot is, the higher the accuracy and reliability of the answer output from the AI chatbot. Therefore, as described above, the information management unit (10) collects various pieces of information that can be collected from the device in detail and stores and manages them as basic data of the device.

Here, the information management unit (10) of course manages information on multiple devices in an integrated manner by dividing it by device.

In addition, as described above, in order to obtain an accurate answer from the AI chatbot for the query information generated by the query generation unit (40), it is desirable to provide various information that can serve as a judgment criterion. Accordingly, the operation information of the basic data may include waveform information that represents, as a graph, information on the change in the size of item values over time for items that can be collected when the device is operated, among items including energy consumed for the operation of the device, vibrations generated during the operation of the device, noise generated during the operation of the device, temperature, humidity, and pressure of the device or surroundings during the operation of the device.

For example, if the device is a motor, the basic data such as the type of device is motor, the manufacturing company is IT Space Co., Ltd., the manufacturing year is January 2020, the service life is 5 years, the specification information is rated current 30A and rated voltage 100V, and the usage is elevator operation, and detailed information can be stored and managed in the storage management unit (10), and such detailed basic data is included in the query information in the query generation unit (40) to obtain a more accurate and reliable answer from the AI chatbot.

Here, if the device is a motor, the waveform information on the current value, which is the energy consumed for the operation of the motor, and the waveform information on the vibration, noise, temperature, and surrounding temperature and humidity that occur during the operation of the motor can be collected and stored as basic data as the operation information of the basic data. However, for the convenience of explanation, if it is assumed that only the waveform information on the current value consumed for the operation of the motor is collected and managed as the operation information, the waveform information on this current value is a waveform in the form of a graph that shows the change in the size of the current value consumed by the motor over time as the motor operates, and the waveform information is information that can recognize the pattern (method) of the operation (movement) of the motor. If this information is provided to the AI chatbot as basic data, it will be possible to obtain more accurate and reliable answers to inquiries from the AI chatbot.

The above alarm information collection unit (20) collects information about an alarm when an alarm (alert) regarding an abnormal symptom of the device occurs.

Typically, equipment that constitutes a facility is equipped with a device (sensor, etc.) or system that detects abnormal signs occurring in the equipment before a failure occurs, and when an abnormal sign occurs in the equipment, an alarm is sent to the surrounding area so that the equipment can be inspected and repaired.

That is, as illustrated in Fig. 2b, when an alarm occurs to warn of an abnormality in the device, the alarm information collection unit (20) analyzes and collects information about the alarm. If an alarm occurs due to an abnormality such as an abnormal current occurring in the device or an abnormal vibration such as severe shaking, the information (type) for the alarm is an abnormal current or abnormal vibration.

In summary, the alarm information collection unit (20) collects specific information such as the type of alarm occurring in the device. For example, when an alarm occurs in a device such as a motor, specific information such as ‘an abnormal current of 50A is detected in the motor’ can be collected as information of the alarm.

The reason for collecting alarm information in this way is to make the query information generated by the query generation unit (40) more specific and to increase the accuracy of the response output from the AI chatbot.

When an alarm occurs in a device, the above information detection unit (30) obtains basic data about the device in which the alarm occurred from the information management unit (10) and, at the same time, obtains information about the alarm from the alarm information collection unit (20).

That is, as shown in Fig. 2c, the information detection unit (30) collects specific information about the alarm obtained from the alarm information collection unit (20) together with detailed basic data of the device obtained from the information management unit (10), and transmits the collected information to the query generation unit (40).

The above query generation unit (40) generates at least one query information including a sentence in language to resolve an abnormal symptom of the device based on the basic data and alarm information of the device obtained from the information detection unit (30) through the automatic module (41).

That is, as illustrated in FIG. 2d, the automatic module (41) of the query generation unit (40) basically automatically generates query information based on language for querying the AI chatbot to resolve abnormal symptoms of the device, and is programmed to generate a query (question) in the form of a sentence about the cause of the alarm or a solution that can resolve the cause while including the basic data of the device and the information on the alarm. However, the automatic module (41) can be programmed in various ways so that query information in various forms can be generated by considering the surrounding conditions in which the device or system is used.

In addition, it further comprises a manual module (42) that allows the query information generated through the automatic module (41) of the query generation unit (40) to be directly modified by the user, or allows the query information to be manually generated directly by the user.

That is, the user (administrator) can directly perform the task of modifying the query information generated by the automatic module (41) through the manual module (42), and also check the response from the AI chatbot to the query information generated through the automatic module (41), and manually regenerate the query information through the manual module (42) so that the user can additionally query the AI chatbot.

The above-mentioned question providing unit (50) provides the question information generated by the above-mentioned question generating unit (40) to at least one AI chatbot via the Internet network, and receives the AI chatbot's response information to the question information and provides it to the administrator.

That is, as illustrated in FIG. 2e, the question provision unit (50) provides the question information generated by the question generation unit (40) to the AI chatbot, receives the answer, and provides it to the administrator. Since the question information generated by the question generation unit (40) is generated as a question related to the cause of an abnormal symptom occurring in the device, a solution, etc., an answer presented by the AI chatbot regarding the cause or solution of an abnormal symptom of the device is received.

Typically, AI chatbots are models that have learned a huge amount of diverse information on the Internet, so expert-level answers can be expected from the AI chatbot to query information through the query provision unit (40).

Therefore, even if there is no expert on-site to diagnose and respond to the abnormality in the device when an abnormal symptom occurs, you can receive a solution that is better than that of an expert through the response of the AI chatbot.

Of course, as shown in FIG. 2f, if the cause or solution for the alarm that occurred in the device is not resolved through a single process of asking the AI chatbot about the query information generated by the query generation unit (40) and receiving the AI chatbot's response to the query information, the process of generating additional query information through the query generation unit (40) and receiving the AI chatbot's response to the additionally generated query information is repeated so that a clear cause or solution for the alarm that occurred in the device is presented.

In addition, the above-mentioned inquiry provision unit (50) can provide the administrator with clear information about the cause of the device alarm, solutions, etc. by inquiring about inquiry information to multiple AI chatbots through the Internet and providing the administrator with answers from each AI chatbot. As the AI chatbot to which inquiry information is inquired, ‘ChatGPT’ provided by Open AI in the United States and ‘Bing’ provided by Microsoft (MS) can be selectively used.

Meanwhile, it is configured to further include an image module (60) that converts waveform information stored and managed as operation information in the information management unit (10) into an image like a photograph;

When an alarm occurs in a device, the above information detection unit (30) obtains basic data about the device in which the alarm occurred from the information management unit (10), and obtains the waveform information of the operation information as image information through the image module (60) so that the image information can be included as basic data in the query information generated by the query generation unit (40).

That is, as illustrated in FIG. 2a, the image module (60) converts the graph-shaped waveform information stored as the device's operating information into an image like a photograph and provides it to the query generation unit (40) through the information detection unit (30), so that the query generation unit (40) clearly transmits and provides the graph-shaped waveform information among the basic data included in the query information to the AI chatbot through an image, thereby inducing a more accurate answer to the query from the AI chatbot.

Here, the AI chatbot that receives query information containing image information can of course be an AI chatbot that can recognize image information.

In addition, if the alarm information collected by the alarm information collection unit (20) is an alarm corresponding to an item of the operation information, the waveform information of the device for the operation information item corresponding to the alarm is collected at the time the alarm occurs, and then the waveform information is imaged through the image module (60).

The above information detection unit (30) obtains alarm information including image information from the above alarm information collection unit (20).

That is, as illustrated in FIG. 2b, the alarm information collection unit (20) provides the information detection unit (30) with image information of the graph waveform of the device for the operation information item corresponding to the alarm at the time of alarm occurrence along with information about the alarm that occurred in the device. Therefore, the query information of the query generation unit (40) that generates a question based on the information acquired by the information detection unit (30) can include very specific information about the alarm that occurred in the device, thereby enabling a more accurate and reliable answer to be acquired from the AI chatbot.

Meanwhile, the device further includes a shooting module (70) for taking pictures or videos;

When an alarm occurs in the device, the photographing module (70) provides a photo or video of the device in which the alarm occurred to the alarm information collection unit (20).

That is, as illustrated in FIG. 2g, the alarm information collection unit (20) can easily obtain photo or video information of the device from which the alarm occurred from the photographing module (70), and the photo or video information thus obtained is provided to the query generation unit (40) through the information detection unit (30), so that the query information of the query generation unit (40) that generates a question based on the information obtained from the information detection unit (30) can include photo or video information of the device from which the alarm occurred, thereby enabling a very accurate and highly reliable answer to be obtained from the AI chatbot.

The device fault diagnosis detection system (100) utilizing the AI chatbot according to the present invention, which is configured as described above, when an alarm for an abnormal symptom occurs in a device, the information detection unit (30) obtains basic data about the device in which the alarm occurred from the information management unit (10), and at the same time, information about the alarm of the device is obtained from the alarm information collection unit (20) and transmitted to the query generation unit (40), and the query generation unit (40) automatically and accurately generates query information about the cause or solution for the abnormal symptom of the device in which the alarm occurred, and the query information is inquired about to at least one AI chatbot through the query provision unit (50) so that the abnormal symptom of the device can be effectively resolved based on expert-level answer information provided by the AI chatbot.

In addition, since it is a system in which query information is generated in the query generation unit (40) based on the information acquired in the information detection unit (30), and the generated query information is provided to the AI chatbot through the query provision unit (50) to receive response information, the series of processes are performed very quickly, so it is possible to quickly and accurately resolve abnormal symptoms occurring in the device, thereby inducing stable operation management of the equipment.

In addition, even if there is no expert on-site to diagnose abnormal symptoms of the device, it has the effect of inducing stable operation management of the device in the field as even beginners can flexibly respond when abnormal symptoms of the device occur.

The device fault diagnosis detection system (100) utilizing an AI chatbot according to an embodiment of the present invention having the above configuration obtains answers about the cause and solution for a device in which an alarm has occurred from the AI chatbot as follows.

First, as shown in Fig. 2a, in order to ensure stable use of the device fault diagnosis detection system (100) utilizing the AI chatbot of the present invention, various basic data for multiple devices are stored and managed separately for each device in the information management unit (10).

Then, as shown in Fig. 2b, when an alarm occurs in the device, the alarm information collection unit (20) collects information about the alarm that occurred in the device. If the alarm information corresponds to an item of operation information of basic data, image information that visualizes the waveform information of the device for the operation information item corresponding to the alarm at the time the alarm occurred is collected together through the image module (60).

Then, as shown in Fig. 2c, the information detection unit (30) obtains the basic data of the device in which the alarm occurred from the information management unit (10) and, at the same time, obtains the alarm information collected from the alarm information collection unit (20), and transmits the basic data information and alarm information of the device thus obtained to the query generation unit (40).

Then, as shown in Fig. 2d, the automatic module (41) of the query generation unit (40) provides basic data and alarm information of the device where the alarm occurred, while generating query information about the cause of the alarm or a solution that can resolve the cause.

At this time, it goes without saying that the user can modify the query information generated through the manual module (42).

Then, as shown in Fig. 2e, the question providing unit (50) provides the question information generated by the question generating unit (40) to the AI chatbot, and receives the AI chatbot's response information for the question information and provides it to the administrator.

At this time, the answers provided by the AI chatbot can be expected to be expert-level answers, so it can very effectively resolve abnormal symptoms occurring in the device.

If the cause or solution for the alarm that occurred in the device is not resolved through the response from the AI chatbot side received through the query provision unit (50) as shown in FIG. 2f, the query information is regenerated through the manual module (42) and the AI chatbot side is repeatedly questioned and a response is received, thereby ensuring that the abnormality that occurred in the device is stably resolved.

The present invention has been described with reference to the embodiments illustrated in the attached drawings, but this is illustrative and not limited to the above-described embodiments, and those skilled in the art will understand that various modifications and equivalent embodiments are possible from this. In addition, it goes without saying that modifications are possible by those skilled in the art within a range that does not infringe the spirit of the present invention. Accordingly, the scope of rights claimed in the present invention is not limited within the scope of the detailed description, but is limited by the claims described below and the technical spirit thereof.

10. Information Management Department 20. Alarm Information Collection Department
30. Information detection unit 40. Query generation unit
41. Automatic module 42. Manual module
50. Query Provider 60. Image Module
70. Shooting module
100. Device fault diagnosis detection system using AI chatbot

Claims (7)

An information management unit (10) in which basic data for at least one device is stored and managed;
An alarm information collection unit (20) that collects information about an alarm when an alarm (alert) for an abnormal symptom of the device occurs;
When an alarm occurs in a device, an information detection unit (30) obtains basic data about the device in which the alarm occurred from the information management unit (10) and simultaneously obtains information about the alarm from the alarm information collection unit (20);
A query generation unit (40) that generates at least one query information based on the basic data and alarm information of the device obtained from the above information detection unit (30); and
A device fault diagnosis and detection system utilizing an AI chatbot, characterized in that it comprises a question provision unit (50) that provides question information generated in the question generation unit (40) to at least one AI chatbot through the Internet, and receives response information from the AI chatbot to the question information and provides it to an administrator.
In the first paragraph,
The above query generation unit (40) is
A device fault diagnosis detection system utilizing an AI chatbot, characterized in that it comprises an automatic module (41) that automatically generates at least one query information including a sentence in language to resolve an abnormal symptom of the device based on the basic data and alarm information of the device acquired from the above information detection unit (30).
In paragraph 2.
A device fault diagnosis detection system utilizing an AI chatbot, characterized in that it further includes a manual module (42) that allows the query information generated through the automatic module (41) of the query generation unit (40) to be directly modified by the user, or allows the query information to be manually generated by the user.
In any one of claims 1 to 3,
The basic data of the device stored and managed in the above information management unit (10) includes the type of device, manufacturer, year of manufacture, specification information, service life, intended use, and operation information.
With the above operating information,
A device fault diagnosis and detection system utilizing an AI chatbot, characterized in that the waveform information is used to represent, in a graph form, information on the change in the size of item values over time for items that can be collected during the operation of the device, including energy consumed for the operation of the device, vibrations generated during the operation of the device, noise generated during the operation of the device, temperature, humidity, and pressure of the device or surroundings during the operation of the device.
In paragraph 4,
It is configured to further include an image module (60) that converts waveform information stored as operation information in the above information management unit (10) into an image as a photograph;
The above information detection unit (30) obtains basic data about the device in which the alarm occurred from the information management unit (10) when an alarm occurs in the device, and obtains the waveform information of the operation information as image information through the image module (60) so that the image information can be included as basic data in the query information generated by the query generation unit (40). A device fault diagnosis detection system utilizing an AI chatbot.
In paragraph 5,
If the alarm information collected by the above alarm information collection unit (20) is an alarm corresponding to an item of the above operation information, the waveform information of the device for the above operation information item corresponding to the alarm is collected at the time the alarm occurs, and then the waveform information is imaged through the image module (60).
A device fault diagnosis detection system utilizing an AI chatbot, characterized in that the above information detection unit (30) obtains alarm information including image information from the above alarm information collection unit (20).
In clause 5 or 6,
Including a shooting module (70) for taking pictures or videos of the device;
A device fault diagnosis detection system utilizing an AI chatbot, characterized in that when an alarm occurs in the device, the photographing module (70) provides a photo or video information of the device in which the alarm occurred to the alarm information collection unit (20).