CN112631370B - Machine lesion analysis system and wearable device with machine lesion analysis function - Google Patents

Abstract

The present invention mainly proposes a machine lesion analysis system, which mainly includes a machine condition collection unit, at least one wearable device and a processing and control device. Among them, the machine condition collection unit is used to collect machine condition data of at least one machine, the wearable device is used for users to wear on their bodies, and the processing and control device has a historical database and a lesion analysis unit. When an abnormality or failure occurs in a machine, the processing and control device receives the machine condition data through the machine condition collection unit, and the lesion analysis unit finds the corresponding machine abnormality cause and the corresponding machine maintenance record from the historical database based on the machine condition data, and then generates at least one machine troubleshooting plan. With such a design, the on-site engineer wearing the wearable device can quickly and accurately complete the troubleshooting of the machine under the instructions of the machine troubleshooting plan, without spending time looking for the cause of the machine failure.

Description

Machine lesion analysis system and wearable device with machine lesion analysis function

Technical field: The present invention relates to the technical field of machine maintenance based on artificial intelligence, and in particular to a machine lesion analysis system and a wearable electronic device with a machine lesion analysis function.

Background technology: Traditionally, process machines or automated machines usually only have a few simple operating buttons. However, as technology becomes more and more advanced, technological machines are all equipped with electronic control panels, which makes their operation complicated. Therefore, online operators must read the relevant machine manuals in detail and pass the assessment (qualify) before they can become operators of the machine. For these technological machines equipped with electronic control panels, troubleshooting and/or machine maintenance are also very difficult. When the machine issues a fault notification, the operator will notify the engineer and let the operator perform troubleshooting. However, since the technological machine usually has both a mechanical structure and an electronic control circuit, the engineer must refer to the corresponding machine maintenance guide to complete the troubleshooting in a targeted manner. Practical experience shows that the machine maintenance guide has a lot of pages, which causes engineers to spend a lot of time reading the machine maintenance guide, so they cannot find troubleshooting solutions when they are urgently needed, causing delays in machine maintenance. Even more serious is that engineers arbitrarily change machine settings or replace machine parts before finding the correct solution, causing irreversible serious consequences.

Therefore, if a junior engineer still cannot find the best troubleshooting solution after spending a lot of time reading the machine maintenance manual, he or she will usually use a real-time communication device to report the on-site situation to the senior engineer at the head office. In this way, the senior engineer can determine the cause of the machine failure based on the real-time situation on site, and then provide the best troubleshooting solution to the junior engineer on site. On the other hand, some equipment manufacturers adopt the method of producing a troubleshooting SOP manual, so that the on-site engineers can analyze and eliminate the cause of the machine that issues a fault warning based on the contents of the troubleshooting SOP manual.

Both of the above methods can help on-site engineers to complete the cause analysis and troubleshooting of the machine in a short time. However, these two methods still have their own practical application defects. As for the former method, once the senior engineer of the head office takes leave or resigns, even if the on-site engineer reports the on-site situation to the head office through the real-time communication equipment, it still does not help the on-site engineer to find the best troubleshooting solution in a short time. As for the latter method, following the troubleshooting SOP manual to check and confirm the cause of the machine failure one by one, the machine that has failed can be repaired in the end. However, it must be noted that the entire inspection and confirmation process still takes a lot of time. Furthermore, some unknown causes of failure are usually caused by assembly defects or parts defects of the machine. These unknown causes of failure are not recorded in the general troubleshooting SOP manual, which makes it impossible for on-site engineers to complete the cause analysis and troubleshooting of the machine.

From the above description, it can be seen that it is necessary to redesign and develop a device or system that can help maintenance engineers complete the cause analysis and troubleshooting of machine failures in a short period of time.

In view of this, the inventor of the present invention has made great efforts to research and invent, and finally developed a machine lesion analysis system and a wearable electronic device with a machine lesion analysis function of the present invention.

Invention content: The main purpose of the present invention is to provide a machine lesion analysis system and a wearable electronic device with a machine lesion analysis function, wherein the machine lesion analysis system mainly includes a machine condition collection unit, at least one wearable device and a processing and control device. In particular, the machine condition collection unit is used to collect machine condition data of at least one machine, the wearable device is used for users to wear on their bodies, and the processing and control device has a historical database and a lesion analysis unit. When an abnormality or failure occurs in a machine, the processing and control device receives the machine condition data through the machine condition collection unit. Further, the lesion analysis unit can find the corresponding machine abnormality cause and the corresponding machine maintenance record from the historical database based on the machine condition data, and then generate at least one machine troubleshooting solution. With such a design, the on-site engineer wearing the wearable device can quickly and accurately complete the troubleshooting of the machine under the instructions of the machine troubleshooting solution, without spending time looking for the cause of the machine failure.

To achieve the above-mentioned object, the present invention proposes an embodiment of the machine lesion analysis system, which comprises:

a machine status collection unit, used to collect machine status data of at least one machine;

At least one wearable device, for at least one user to wear on the user, and each of the wearable devices has a first communication unit and a machine status collection unit for collecting machine status data of at least one machine; and

A processing and control device receives the machine status data through the machine status collection unit, and includes:

a second communication unit, configured to communicate with the first communication unit;

a processing unit, linked to the second communication unit;

a lesion analysis unit, linked to the processing unit; and

a history database, linking the lesion analysis unit and the processing unit, and storing a plurality of machine abnormal conditions, a plurality of machine abnormal causes corresponding to the plurality of machine abnormal conditions, and a plurality of machine maintenance records corresponding to the plurality of machine abnormal causes;

The processing unit receives the machine status data transmitted from the wearable device through the second communication unit and the first communication unit, so that the lesion analysis unit finds the corresponding machine abnormality cause and the corresponding machine maintenance record from the historical database based on the machine status data, and then generates at least one machine fault troubleshooting solution; the processing unit transmits the at least one machine fault troubleshooting solution back to the wearable device through the second communication unit and the first communication unit.

Furthermore, the present invention also provides an embodiment of the wearable electronic device with the machine lesion analysis function, which is used for a user to wear on his body and includes:

a processor unit;

a machine status collection unit, linked to the processor unit, for collecting machine status data of at least one machine;

a history database, linked to the processor unit, and storing a plurality of machine abnormal conditions, a plurality of machine abnormal causes corresponding to the plurality of machine abnormal conditions, and a plurality of machine maintenance records corresponding to the plurality of machine abnormal causes;

a lesion analysis unit, linking the historical database and the processor unit; and

a display unit, linked to the processor unit;

Among them, the processor unit receives the machine status data through the machine status collection unit, so that the lesion analysis unit finds the corresponding machine abnormality cause and the corresponding machine maintenance record from the historical database based on the machine status data, and then generates at least one machine troubleshooting solution and displays it on the display unit through mixed reality.

In the aforementioned embodiments of the machine lesion analysis system of the present invention and the embodiments of the wearable electronic device having a machine lesion analysis function, the machine has a plurality of sensors for transmitting the machine status data to the machine status collection unit via wired or wireless transmission.

Description of the drawings:

FIG1 shows a schematic diagram of a machine lesion analysis system of the present invention;

FIG2 shows a functional block diagram of the machine lesion analysis system of the present invention;

FIG. 3A is a three-dimensional diagram showing a feasible embodiment of a wearable device of the machine lesion analysis system of the present invention;

FIG3B is a perspective view showing another possible embodiment of a wearable device;

FIG4 shows a structural diagram of a wearable device with a machine lesion analysis function according to the present invention; and

FIG. 5 shows a functional block diagram of a wearable device with a machine lesion analysis function according to the present invention.

Reference numerals:

Machine lesion analysis system 1

User 2

Machine 3

Sensor 31

Wearable devices 10

Machine status collection unit 101

Display unit 102

First communication unit 103

Feedback unit 104

Processing and control equipment 11

Second communication unit 111

Processing unit 112

Lesion Analysis Unit 113

Historical database 114

Self-study unit 115

Wearable device with machine lesion analysis function 5

Processor unit 50

Machine status collection unit 51

Historical database 52

Lesion Analysis Unit 53

Display unit 54

Feedback unit 55

Self-study unit 56

Communication unit 57

Specific implementation method:

In order to more clearly describe the machine lesion analysis system and the wearable electronic device with machine lesion analysis function proposed by the present invention, the preferred embodiments of the present invention will be described in detail below with reference to the drawings.

Machine lesion analysis system

FIG. 1 shows an architecture diagram of a machine lesion analysis system of the present invention, and FIG. 2 shows a functional block diagram of the machine lesion analysis system of the present invention. As shown in FIG. 1 and FIG. 2, the machine lesion analysis system 1 of the present invention mainly includes: a machine condition collection unit 101, at least one wearable device 10 and a processing and control device 11, wherein the machine condition collection unit 101 is used to collect a machine condition data of at least one machine 3. On the other hand, the at least one wearable device 10 is used for at least one user 2 to wear on the user, and each of the wearable devices 10 has a first communication unit 103. In addition, the wearable device 10 also has a display unit 102. FIG. 1 shows that the wearable device 10 is a mixed reality (MR) helmet, but it is not intended to limit the feasible embodiment of the wearable device 10. FIG. 3A shows a stereoscopic view of a feasible embodiment of the wearable device 10, and FIG. 3B shows a stereoscopic view of another feasible embodiment of the wearable device 10. As shown in FIG. 3A, in a feasible embodiment, the wearable device 10 can also be a set of smart glasses. Furthermore, in another feasible embodiment, the wearable device 10 may also be a Scouter detector as shown in FIG. 3B .

On the other hand, FIG. 1 represents the processing and control device 11 with a laptop computer. However, it must be known that the relevant equipment data of the machine 3 of the process purpose or the automated production line are usually stored in a central control system, and the central control system can also control the activation/shutdown of a specific machine 3 when necessary. It can be seen that the present invention does not limit the implementation of the processing and control device 11. In a feasible embodiment, the processing and control device 11 can be any of the following: a central control system, an industrial computer, a server computer, a desktop computer, a laptop computer, a tablet computer, or a smart phone. In more detail, as shown in FIG. 2, the processing and control device 11 includes: a second communication unit 111 for communicating with the first communication unit 103, a processing unit 112 linked to the second communication unit 111, a lesion analysis unit 113 linked to the processing unit 112, and a historical database 114. The history database 114 links the lesion analysis unit 114 and the processing unit 112 , and stores a plurality of machine abnormal conditions, a plurality of machine abnormal causes corresponding to the plurality of machine abnormal conditions, and a plurality of machine maintenance records corresponding to the plurality of machine abnormal causes.

Generally speaking, each of the machines 3 for process purposes or automated production lines has a plurality of sensors 31 and an alarm unit. According to the design of the present invention, when the sensor 31 detects that a specific machine 3 has a fault, the alarm unit will be notified to emit an alarm light or information. At the same time, the machine condition collection unit 101 will receive a machine condition data transmitted from the sensor 31 by wired transmission or wireless transmission. The machine condition data referred to herein include: normal abnormal conditions and/or emergency abnormal conditions related to the machine 3. Then, the processing unit 112 receives the machine condition data through the machine condition collection unit 101, so that its lesion analysis unit 114 finds the corresponding machine abnormality cause and the corresponding machine maintenance record from the historical database 113 based on the machine condition data, and then generates at least one machine fault troubleshooting solution. Afterwards, the processing unit 112 transmits the at least one machine fault troubleshooting solution back to the wearable device 10 through the second communication unit 111 and the first communication unit 103.

It is easy to understand that both the first communication unit 103 and the second communication unit 111 can be a wired communication unit or a wireless communication unit. On the other hand, the machine troubleshooting solution can be displayed on the display unit 102 in a mixed reality manner. According to the design of the present invention, the machine troubleshooting solution includes: a plurality of machine abnormality causes arranged in order according to the probability of occurrence and a plurality of machine maintenance records corresponding to the plurality of machine abnormality causes. With such a design, the user 2 (i.e., the field engineer) wearing the wearable device 10 can quickly and accurately complete the troubleshooting of the specific machine 3 under the instruction of the machine troubleshooting solution displayed on the display unit 102, without spending time on finding the cause of the failure of the machine 3. For example, in the case of a failure of the machine 3 numbered A, the machine maintenance steps indicated by the machine troubleshooting solution seen by the field engineer through the wearable device 10 are A B C. In contrast, when the machine 3 numbered B fails, the machine troubleshooting solution obtained by the field engineer through the wearable device 10 indicates the machine maintenance steps B, C, and D. In short, according to different machines 3, the machine troubleshooting solution generated by the lesion analysis unit 113 based on historical data will not have the same maintenance steps. In this way, not only can the entire machine maintenance schedule be greatly shortened, but it can also prevent the field engineer from changing the machine settings or replacing machine parts at will before finding the correct solution.

It is to be supplemented that the above description describes that the machine 3 has a sensor 31, and the sensor 31 transmits the machine status data to the machine status collection unit 101 of the wearable device 10 by wired transmission or wireless transmission, which means that the machine status collection unit 101 is a sensing data receiving module. Of course, in a feasible embodiment, the machine status collection unit 101 can also be a sensor control device to control each of the sensors 31 and manage the sensing signals transmitted by each of the sensors 31.

However, in some cases, the on-site engineer (i.e., user 2) may still not be able to successfully troubleshoot the machine 3 even if he/she follows the machine troubleshooting solution. In this case, user 2 can also use the image capture unit, sound capture unit, or camera of the wearable device 10 to directly report the on-site conditions to the central control system (i.e., processing and control device 11) at the head office, so that the experienced engineers at the head office can determine the cause of the machine failure based on the real-time conditions at the site, and then provide the best troubleshooting solution to the on-site engineers.

As shown in FIG2 , the wearable device 10 further includes a feedback unit 104, and the processing and control device 11 further includes a self-learning unit 115 linking the processing unit 112 and the historical database 114. After the field engineer completes the troubleshooting of the machine 3 according to the best troubleshooting solution provided by the senior engineer at the head office, the field engineer (i.e., the user 2) can also send back the correct machine fault cause and its corresponding troubleshooting method to the processing and control device 11 through the feedback unit 104 and the first communication unit 103. After the processing unit 112 receives the correct machine fault cause and its corresponding troubleshooting method, the self-learning unit 11 reorganizes the various machine abnormal conditions, the various machine abnormal causes, and the multiple machine maintenance records stored in the historical database 114, so that the lesion analysis unit 113 can quickly and accurately generate the best machine troubleshooting solution based on historical data.

Typically, the lesion analysis unit 113 and the self-learning unit 115 can be edited into at least one application program in the form of a library, a variable or an operand, and then created in the processing and control device 11. In this way, the processing and control device 11 is not limited to a central control system located in a headquarters, and it can be a laptop, a tablet computer, or a smart phone that the user 2 can carry with him. Even if the wearable device 10 is equipped with a processor with high-speed computing capabilities, the lesion analysis unit 113 and the self-learning unit 115 can also be edited into at least one application program in the form of a library, a variable or an operand, and then created in the wearable device 10. In the following, a wearable device with a machine lesion analysis function will be introduced.

Wearable device with machine lesion analysis function

FIG4 shows an architecture diagram of a wearable device with a machine lesion analysis function of the present invention, and FIG5 shows a functional block diagram of the wearable device with a machine lesion analysis function of the present invention. As shown in FIG4 and FIG5, the wearable device 5 with a machine lesion analysis function of the present invention is used for a user 2 (i.e., a field engineer) to wear on him, and includes: a processor unit 50, a machine condition collection unit 51, a history database 52, a lesion analysis unit 53, a display unit 54, a feedback unit 55, a self-learning unit 56, and a communication unit 57. Among them, the machine condition collection unit 51 is linked to the processor unit 50 to collect a machine condition data of at least one machine 3. In a feasible embodiment, the machine condition collection unit 51 can be any of the following: a sensor data receiving module, an image capture unit, a sound capture unit, or a photographic device.

To explain in more detail, the historical database 52 is linked to the processor unit 50, and stores a variety of machine abnormalities, a variety of machine abnormality causes corresponding to the various machine abnormalities, and a plurality of machine maintenance records corresponding to the various machine abnormalities. In addition, the lesion analysis unit 53 is linked to the historical database 52 and the processor unit 50, and the display unit 54 is linked to the processor unit 50. On the other hand, the feedback unit 55 is linked to the processor unit 50, and the self-learning unit 56 is linked to the processor unit 50 and the historical database 52. When the wearable device 5 with a machine lesion analysis function of the present invention is actually used, the sensor 31 will transmit a machine status data to the machine status collection unit 51 by wired transmission or wireless transmission when an abnormality or failure occurs in a specific machine 3. After the processing unit 112 receives the machine status data through the machine status collection unit 51, the lesion analysis unit 114 finds the corresponding machine abnormality cause and the corresponding machine maintenance record from the historical database 113 according to the machine status data, and then generates at least one machine fault elimination plan and displays it on the display unit 54 in a mixed reality manner. At this time, the user 2 (i.e., the field engineer) wearing the wearable device 5 with the machine lesion analysis function of the present invention can quickly and accurately complete the troubleshooting of the specific machine 3 under the instruction of the machine fault elimination plan displayed on the display unit 54, without spending time looking for the cause of the failure of the machine 3.

It should be supplemented that the above description describes that the sensor 31 of the machine 3 transmits the machine condition data to the machine condition collection unit 51 of the wearable device 5 by wired transmission or wireless transmission, which means that the machine condition collection unit 51 is a sensing data receiving module. It is worth noting that in a feasible embodiment, the machine condition collection unit 51 can be an independent sensor control device for controlling each of the sensors 31 and managing the sensing signals transmitted by each of the sensors 31. Simply put, the machine condition collection unit 51 does not need to be integrated into the wearable device 5 with the machine lesion analysis function of the present invention, but can receive the sensing signal from each of the sensors 31 by bridging, and then forward the sensing signal to the wearable device 5 with the machine lesion analysis function of the present invention.

However, in some cases, the on-site engineer (i.e., user 2) may still not be able to successfully troubleshoot the machine 3 even if he/she follows the machine troubleshooting solution. In this case, user 2 can also use the image capture unit, sound capture unit, or camera of the wearable device 5 in conjunction with the communication unit 57 to directly report the on-site conditions to the central control system at the head office, so that the experienced engineers at the head office can determine the cause of the machine failure based on the real-time conditions at the site, and then provide the best troubleshooting solution to the on-site engineers.

After the on-site engineer has completed troubleshooting the fault (or abnormality) of the machine 3 according to the best troubleshooting solution provided by the senior engineer at the head office, the on-site engineer (i.e., user 2) can also send back the correct machine fault cause and its corresponding troubleshooting method to the processor unit 50 through the feedback unit 55. After the processor unit 50 receives the correct machine fault cause and its corresponding troubleshooting method, the self-learning unit 56 reorganizes the various machine abnormal conditions, the various machine abnormality causes, and the multiple machine maintenance records stored in the historical database 52, thereby enabling the lesion analysis unit 53 to quickly and accurately generate the best machine troubleshooting solution based on historical data.

Thus, the above is a complete and clear description of a machine lesion analysis system and a wearable electronic device with a machine lesion analysis function of the present invention. It must be emphasized that the above disclosure of this case is a preferred embodiment, and any partial changes or modifications derived from the technical ideas of this case and easily inferred by a person familiar with the said art are within the scope of the patent right of this case.

Claims (9)

1. A machine focus analysis system, comprising:

A machine condition collecting unit for collecting machine condition data of at least one machine;

At least one wearable device for at least one user to wear on, and each wearable device is provided with a first communication unit and a display unit; and

A processing and control device, which receives the machine condition data through the machine condition collecting unit, and comprises:

a second communication unit for communicating with the first communication unit;

a processing unit linking the second communication unit;

A lesion analysis unit, linking the processing units; and

A history database linking the focus analysis unit and the processing unit, and storing a plurality of machine maintenance records for a plurality of machine anomalies, a plurality of machine anomalies corresponding to the plurality of machine anomalies, and a plurality of machine maintenance records corresponding to the plurality of machine anomalies;

The processing unit receives the machine condition data transmitted from the wearable device through the second communication unit and the first communication unit, so that the focus analysis unit finds out the corresponding machine abnormality reason and the corresponding machine maintenance record from the historical database according to the machine condition data, and further generates at least one machine troubleshooting scheme, wherein the machine troubleshooting scheme comprises: a plurality of machine abnormality reasons sequentially arranged according to the occurrence probability of faults and a plurality of machine maintenance records corresponding to the machine abnormality reasons;

The processing unit transmits the at least one machine fault elimination scheme back to the wearable device through the second communication unit and the first communication unit, and enables the machine fault elimination scheme to be displayed on the display unit in a Mixed reality (Mixed reality) mode.

2. The machine tool focus analysis system according to claim 1, wherein the machine tool has a plurality of sensors for transmitting the machine tool condition data to the machine tool condition collection unit by wired transmission or wireless transmission.

3. The machine tool focus analysis system according to claim 1, wherein the wearable device further comprises a feedback unit, so that after a user completes a troubleshooting process of each machine tool, a correct machine tool fault cause can be returned to the processing and control device through the feedback unit and the first communication unit.

4. The machine tool lesion analysis system according to claim 3, wherein said processing and control device further comprises a self-learning unit linking said processing unit with said history database; the processing unit is characterized in that after receiving the correct machine fault reasons, the self-learning unit rearranges the abnormal conditions of the multiple machines, the abnormal reasons of the multiple machines and the maintenance records of the multiple machines stored in the history database.

5. The machine tool focus analysis system according to claim 4, wherein the focus analysis unit and the self-learning unit are edited into at least one application program in the form of a library, variables or operands, and further created in the processing and control device.

6. A wearable device with a machine focus analysis function, configured to be worn by a user, comprising:

A processor unit;

A machine condition collection unit linked to the processor unit for collecting machine condition data of at least one machine;

A history database linking the processor unit and storing a plurality of machine abnormal conditions, a plurality of machine abnormal reasons corresponding to the plurality of machine abnormal conditions, and a plurality of machine maintenance records corresponding to the plurality of machine abnormal reasons;

a lesion analysis unit linking said history database with said processor unit; and

A display unit linked to the processor unit;

The processor unit receives the machine condition data through the machine condition collecting unit, so that the focus analyzing unit finds out the corresponding machine abnormality reason and the corresponding machine maintenance record from the historical database according to the machine condition data, and generates at least one machine fault removal scheme and displays the at least one machine fault removal scheme on the display unit in a Mixed reality (Mixed reality) mode, wherein the machine fault removal scheme comprises: a plurality of machine abnormality reasons sequentially arranged according to the occurrence probability of faults, and a plurality of machine maintenance records corresponding to the plurality of machine abnormality reasons.

7. The wearable device with machine focus analysis function according to claim 6, further comprising: a feedback unit linked to the processor unit, so that the user can return a correct machine fault cause to the processor unit through the feedback unit after completing a fault removal process of each machine.

8. The wearable device with machine focus analysis function according to claim 7, further comprising: a self-learning unit linking the processor unit and the history database; after the processor unit receives the correct machine fault cause, the self-learning unit rearranges the abnormal conditions of the multiple machines, the abnormal causes of the multiple machines and the maintenance records of the multiple machines stored in the history database.

9. The wearable device with machine focus analysis function according to claim 7, further comprising: a communication unit, linked to the processor unit, for communicating with a central control system.