TWM651596U - Rail vehicle monitoring management system - Google Patents

Abstract

A rail vehicle monitoring management system is provided. The rail vehicle monitoring management system includes an unmanned vehicles and a monitoring host. The monitoring host wirelessly receives the driving information output by the unmanned vehicle, and analyzes the driving information to learn the vibration conditions of the unmanned vehicle running on the track. When the vibration amount of the unmanned vehicle in the driving position of the rail does not match a corresponding reference value, the monitoring host further determines whether a vibration assistance condition is established. When the vibration auxiliary condition is judged to be established, the monitoring host determines that the vibration condition is abnormal and outputs an alarm signal. When the vibration assistance condition is not established, the monitoring host records the abnormality of the unmanned vehicle's driving position.

Description

Rail car monitoring and management system

This creation relates to a monitoring and management system, in particular to a rail car monitoring and management system.

The RGV (Rail Guided Vehicle) control system currently used by unmanned vehicles does not have a vibration detection function. Most of them install additional sensors during the trial operation of the unmanned vehicle to confirm whether there are any abnormalities. However, when the unmanned vehicle actually carries goods, there may not be excessive vibration in the initial use. However, as the use time increases, the unmanned vehicle or the track may be damaged or deformed, resulting in an increase in the amount of vibration, and ultimately affecting the quality of the goods being carried. Quality is affected.

The technical problem to be solved by this creation is to provide a rail car monitoring and management system in view of the shortcomings of the existing technology.

This creative embodiment provides a rail car monitoring and management system, including an unmanned vehicle and a monitoring host. When the unmanned vehicle is driving on a track, it wirelessly outputs a driving message. The driving message includes a driving position and a vibration amount of the unmanned vehicle driving on the track. And the monitoring host wirelessly receives the driving information and analyzes the driving information to learn a vibration condition of the unmanned vehicle driving on the track. Wherein, when the vibration amount of the unmanned vehicle at the driving position does not match a corresponding reference value, the monitoring host further determines whether a vibration assistance condition is established; When the vibration auxiliary condition is judged to be true, the monitoring host determines that the vibration condition is abnormal and outputs an alarm signal; and when the vibration auxiliary condition is not true, the monitoring host records that the unmanned vehicle is abnormal at the driving position.

To sum up, the rail car monitoring and management system provided by this creative embodiment can accurately detect the vibration conditions of the unmanned vehicle, and can further accurately identify the source of the vibration, thereby ensuring that the quality of the goods being carried is not affected by the amount of vibration. influence.

In order to further understand the characteristics and technical content of this creation, please refer to the following detailed description and diagrams about this creation. However, the diagrams provided are only for reference and illustration and are not used to limit this creation.

1:Unmanned vehicle

10:First controller

12: Driving module

14:Detection device

141:Identification circuit

143:Inertial sensor

16:First Radio Circuit

2: Monitor the host

20: Second controller

22:Second Radio Circuit

24:Database

26:Alarm circuit

GR: orbit

GR1: first track

GR2: Second track

OB: foreign body

IB: identification piece

BS: moving site

L1: First route

L2: Second route

S401: The unmanned vehicle starts traveling

S403: Collect detection data

S405: Return driving information to the monitoring host

S501: Receive data returned from each unmanned vehicle

S503: Data is normal

S505: There is a reference value

S507: Match match

S509: Record the reference value in the database

S511: Other unmanned vehicles are abnormal

S513: Issue an alarm for track anomalies in this section

S515: Tracks in other sections are also abnormal.

S517: Issue an alarm for abnormality of the unmanned vehicle

S519: The number of exceptions reaches the standard

S521: Issue an alarm for abnormality of tracks and unmanned vehicles in this section

S523: Record abnormality

Figure 1 is a circuit block diagram of a rail car monitoring and management system provided by this embodiment of the invention.

Figure 2 is a schematic diagram of an unmanned vehicle traveling on a track according to this embodiment of the invention.

Figure 3 is a vibration waveform obtained when an unmanned vehicle is driving under normal conditions.

Figure 4 is an operation flow chart for autonomous vehicle driving according to this embodiment of the present invention.

Figure 5 is a control flow chart for rail car monitoring and management provided by this creative embodiment.

Figure 6 is a schematic diagram of an unmanned vehicle traveling on a normal track according to this embodiment of the present invention.

Figure 7 is a schematic diagram of an unmanned vehicle traveling on a track with foreign objects according to this embodiment of the present invention.

Figure 8 is a schematic diagram of an unmanned vehicle traveling on a tilted track according to this embodiment of the present invention.

Figure 9 is another schematic diagram of an unmanned vehicle traveling on a skewed track according to this embodiment of the present invention.

Figure 10 is an example of an unmanned vehicle traveling at abnormal intervals on the track according to this creative embodiment. intention.

The following is a specific embodiment to illustrate the implementation of the present invention. Those skilled in the art can understand the advantages and effects of the present invention from the content provided in this specification. This invention can be implemented or applied through other different specific embodiments, and various details in this description can also be modified and changed based on different viewpoints and applications without departing from the concept of this invention. In addition, the accompanying drawings of this creation are only simple illustrations and are not depictions based on actual size, as stated in advance. The following embodiments will further describe the relevant technical content of this creation in detail, but the content provided is not intended to limit the scope of protection of this creation.

It should be understood that although terms such as “first”, “second” and “third” may be used herein to describe various components or signals, these components or signals should not be limited by these terms. These terms are mainly used to distinguish one component from another component, or one signal from another signal. In addition, the term "or" used in this article shall include any one or combination of more of the associated listed items, depending on the actual situation.

Embodiments of this invention provide a rail car monitoring and management system and a rail car monitoring and management method thereof. The rail car monitoring and management system described here is for unmanned autonomous vehicles (Raid Guided Vehicles; RGV) that are used to automatically transport goods. , this unmanned vehicle can transmit relevant data with the remote monitoring host using wireless communication technology. By monitoring the unmanned vehicle reporting data, it can determine whether there is an abnormality in the vibration amount of the driving situation, and can proactively report when an abnormality is determined; thereby Ensure that the cargo carried by unmanned vehicles is not affected by abnormal vibration.

[Hardware architecture of rail car monitoring and management system]

Please refer to Figures 1 and 2. Figure 1 is a circuit block diagram of a rail car monitoring and management system provided by this embodiment of the invention. Figure 2 is a schematic diagram of an unmanned vehicle traveling on a track provided by this embodiment of the invention. Figure. The rail vehicle monitoring and management system described in this embodiment includes, but is not limited to, an unmanned vehicle 1 and a monitoring host 2. The unmanned vehicle 1 can actively transmit driving information back to the monitoring host 2 when traveling on the track, so that the monitoring host 2 can receive the This driving information can analyze various possible vibration conditions of the unmanned vehicle 1 while driving on the track.

Furthermore, the monitoring host 2 can accurately determine whether there is abnormal vibration and the source of the abnormal vibration based on the analysis results. For example, the monitoring host 2 can know that the source of abnormal vibration is from at least one of the unmanned vehicle 1 and the track based on the comparison results of multiple judgment conditions. When the monitoring host 2 determines that an abnormal vibration has occurred, it can actively output an alarm to remind relevant personnel to improve the current abnormal situation, thereby effectively ensuring that the unmanned vehicle 1 and the track can still detect abnormal vibration conditions early even during long-term use.

Furthermore, the unmanned vehicle 1 includes, for example, but is not limited to, a first controller 10, a driving module 12, a detection device 14 and a first wireless circuit 16. The first controller 10 is electrically connected to the driving module 12, the detection device 14 and the first wireless circuit 16. device 14 and first wireless circuit 16. The driving module 12 includes, for example, a motor module and a motor drive circuit that can drive the unmanned vehicle 1 to move. The detection device 14 includes, for example, an identification circuit 141 and an inertial sensor 143. The unmanned vehicle 1 can obtain the identification information of the identification component on the track through the identification circuit 141 when traveling on the track. The identification information at least includes the driving position and driving direction of the unmanned vehicle 1. speed etc. The inertial sensor 143 is used to obtain the amount of vibration when the unmanned vehicle 1 is traveling. The inertial sensor 143 at least includes any one of an accelerometer and a gyroscope. The amount of vibration obtained by the inertial sensor 143 here includes, but is not limited to, detection. Detect the vibration of the unmanned vehicle while moving (such as Acc X, Acc Y, Acc Z), detect the steady level of the unmanned vehicle (such as Angle X, Angle Y, Angle X, Gyro Y, Gyro Z), detect the steady-state yaw of the unmanned vehicle (such as Roll (X-axis), Pitch (Y-axis), Yaw (Z-axis)), etc.

In one embodiment, the first controller 10 is configured to handle related control of the driving module 12 and the detection device 14. For example, the first controller 10 can obtain unmanned aerial vehicle information through the first wireless circuit 16. The driving task of the vehicle 1 on the track is controlled, and the operation of the driving module 12 is relatively controlled according to the driving task to drive the unmanned vehicle 1 to move. And the first controller 10 obtains the driving information of the unmanned vehicle 1 through the detection result of the detection device 14, and wirelessly outputs the driving information to the monitoring host 2 through the first wireless circuit 16. This driving information includes, for example, but is not limited to the driving position obtained through the identification circuit 141 and the vibration amount obtained through the inertial sensor 143 .

Figure 2 is an example of an unmanned vehicle driving on a track to obtain driving information. The track GR is provided with multiple identification parts IB and transfer stations BS. The unmanned vehicle 1 can drive on the track GR according to different driving tasks. Route L1 or the second route L2, and load or unload the cargo through the handling station BS. When the unmanned vehicle 1 is traveling, it can know which identification piece IB it passes through through the identification circuit 141, so that it can know which section of the track GR the unmanned vehicle 1 is currently on. That is to say, the first controller 10 can know according to the identification The identification result of the circuit 141 can obtain the driving position of the unmanned vehicle 1 on the track. At the same time, the first controller 10 can obtain the vibration amount of the unmanned vehicle 1 at the current driving position through the inertial sensor 143 . Accordingly, by operating in this way, the unmanned vehicle 1 can obtain the driving information of each section of the track GR, and this driving information includes, but is not limited to, the driving position in the track GR, the corresponding vibration amount, and the unmanned vehicle 1 itself. identity information.

It should be noted that when both the unmanned vehicle 1 and the track GR are under normal conditions, the vibration amount obtained by the unmanned vehicle 1 traveling on the track can be considered normal. Figure 3 shows an example of the direct vibration of the unmanned vehicle 1 on the track GR. Various normal vibration amounts obtained during walking sections or right-turn sections. These normal vibration amounts can be used as reference values for subsequent monitoring host 2 to determine whether the vibration situation is abnormal.

In one embodiment, the monitoring host 2 includes, but is not limited to, a second controller 20, a second wireless circuit 22, a database 24, and an alarm circuit 26. The second controller 20 is electrically connected to the second wireless circuit 22, the data circuit 22, and the alarm circuit 26 respectively. library 24 and alarm circuit 26. The second controller 20 is configured to process the vibration abnormality determination process. The vibration abnormality determination process here means that the second controller 20 receives the data returned by each unmanned vehicle 1 through the second wireless circuit 22 (for example, the track GR can Provide one or more units without People and vehicles 1 travel alone or at the same time, and the monitoring host 2 can identify different unmanned vehicles 1) based on obtaining different identity information. The data returned here is, for example, the driving information of the unmanned vehicle 1. Then, by analyzing the driving information, the vibration condition of the unmanned vehicle 1 while driving on the track is known. The database 24 is used to store reference values for judging vibration conditions. For example, the reference value refers to the normal vibration value of the unmanned vehicle 1 traveling on each section of the track under normal conditions (no abnormal vibration).

In one embodiment, the monitoring host 2 compares the vibration amount at the driving position of the unmanned vehicle 1 with a corresponding reference value based on the received driving information. When the comparison is determined to be consistent, the current situation can be determined. There was no abnormal vibration in the driving position of the unmanned vehicle 1 on the track. On the other hand, when the above comparison results are inconsistent, it can be initially determined that there may be an abnormal vibration situation, and other vibration auxiliary conditions will be further combined to further confirm the source of this abnormal vibration. If the vibration assistance condition is determined to be true, it can be determined that the abnormal vibration condition comes from one or both of the unmanned vehicle 1 itself and the track, and the monitoring host 2 can simultaneously output corresponding alarm content through the alarm circuit 26 . If the vibration assistance condition is ultimately judged not to be true, the monitoring host 2 can record an abnormality in the current driving position of the unmanned vehicle 1 for subsequent comparison data when the vibration assistance condition is executed.

It is worth noting that the vibration auxiliary condition here can be a combination of one or more judgment conditions. When the monitoring host 2 performs the judgment of the vibration auxiliary condition, it mainly judges the monitoring data other than the current driving information. The monitoring host 2 uses other The monitoring data is combined with the current driving information to accurately determine the source of abnormal vibration conditions.

For example, the vibration auxiliary condition is to determine whether there is another unmanned vehicle 1 at the same driving position whose vibration amount does not match the corresponding reference value. If the vibration auxiliary condition is determined to be yes, the monitoring host 2 determines that the current unmanned vehicle 1 is located There is an abnormality in the track at the driving position.

Or, for example, the vibration assistance condition is to determine whether the vibration amount of the unmanned vehicle 1 at other different driving positions on the track does not match the corresponding reference value. If the vibration assistance condition determines whether If the result is yes, the monitoring host 2 determines that the unmanned vehicle 1 is abnormal.

Or, for example, the vibration assistance condition is to determine whether the vibration amount of the unmanned vehicle 1 in the driving position does not match the corresponding reference value more than a preset number of times. If the vibration assistance condition is determined to be yes, the monitoring host 2 determines that the unmanned vehicle 1 1 and the track of unmanned vehicle 1 at the current driving position is abnormal.

[Example of unmanned vehicle reporting method]

Please refer to Figure 4. Figure 4 is an operation flow chart for autonomous vehicle driving according to this embodiment of the present invention. The flow chart shown in Figure 4 is based on the architecture of Figure 1 as an example, but is not limited thereto. The process shown in Figure 4 includes, for example, the following steps.

In step S401, the unmanned vehicle 1 starts traveling. When the first controller 10 of the unmanned vehicle 1 obtains the driving task wirelessly output by the monitoring host 2 through the first wireless circuit 16, the first controller 10 can control the driving module 12 to start, and the unmanned vehicle 1 can travel on the track.

In step S403, detection data is collected. When the unmanned vehicle 1 is traveling, the first controller 10 obtains the driving information of the unmanned vehicle 1 through the detection device 14. For example, the driving position of the unmanned vehicle 1 on the track can be obtained through the identification circuit 141 in the detection device 14 ( Such as which section of the track), and the vibration amount of the unmanned vehicle 1 at the current driving position can be obtained through the inertial sensor 143.

In step S405, the driving information is sent back to the monitoring host 2. After the first controller 10 obtains a driving message including at least the driving position of the unmanned vehicle 1 and the corresponding vibration amount of the driving position according to the detection result of the detection device 14 , the first controller 10 sends this information through the first wireless circuit 16 The driving information is wirelessly transmitted back to the monitoring host 2.

[Example of rail car monitoring and management method]

Please refer to Figure 5. Figure 5 is a control flow chart for rail car monitoring and management provided by this creative embodiment. The flow chart shown in Figure 5 is based on the architecture of Figure 1 as an example, but it is not intended to be used as an example. limit. The process shown in Figure 5 includes, for example, the following steps.

In step S501, data returned by each unmanned vehicle 1 is received. If there are multiple unmanned vehicles 1 traveling on the track, the second controller 20 in the monitoring host 2 can wirelessly receive the driving information returned by each unmanned vehicle 1 through the second wireless circuit 22 .

In step S503, it is determined whether the data received by the machine is normal. When the monitoring host 2 receives the driving message returned by any unmanned vehicle 1, the second controller 20 of the monitoring host 2 determines whether the received driving message includes the driving position and vibration amount data. If it does not include the driving position and vibration amount data, it can be determined that this The data is not normal, and the subsequent vibration judgment on the unmanned vehicle 1 cannot be continued. That is, if step S503 is judged to be negative, the process will return to step S501.

In step S505, it is determined whether there is a relative reference value. When the determination in step S503 is yes, the monitoring host 2 can then continue to determine whether the vibration amount in the driving information has a corresponding reference value in the database 24 for comparison. Here, the second controller 20 determines whether there is a reference value corresponding to the driving position in the current driving information in the database 24. If step S505 determines no, it may be the first time the unmanned vehicle 1 is used under normal circumstances. At this time, there is no relative reference value in the database 24 yet.

In step S507, compare whether they match. When the determination in step S505 is yes, the monitoring host 2 will compare the current vibration amount of the unmanned vehicle 1 with the reference value corresponding to the database 24. When the comparison results are consistent, it means that the current vibration condition of the unmanned vehicle 1 is not abnormal. , that is, the second controller 20 determines that the current vibration value of the unmanned vehicle 1 is within the normal range.

In step S509, the reference value is recorded in the database 24. When the determination in step S505 is negative, the second controller 20 will store the received driving information in the database 24, that is, set the corresponding vibration value of the driving position in the current driving information as the reference value in the database 24. used for subsequent comparison. Each reference value recorded in the database 24 has a corresponding driving position, that is, the database 24 can record the corresponding reference values of different sections in the track, so that the subsequent unmanned vehicle 1 can be used to travel in different sections. The vibration values obtained during orbit have corresponding benchmarks. Values are available for comparison.

In step S511, it is determined whether other unmanned vehicles 1 are abnormal at the same driving position. When the determination in step S507 is negative, it means that the vibration situation is abnormal. At this time, the second controller 20 of the monitoring host 2 will confirm whether other unmanned vehicles 1 also occur at the same driving position, as the comparison in step S507 does not match. As a result, it can be further confirmed whether multiple unmanned vehicles 1 have abnormal vibrations at the same driving position. Here, the monitoring host 2 can accurately determine whether the source of the abnormal vibration is the track itself through the judgment in step S511.

In step S513, an alarm is issued that the track of this section is abnormal. When the judgment in step S511 is yes, the monitoring host 2 can determine that a plurality of unmanned vehicles 1 have vibrated abnormally at the same driving position, so the second controller 20 of the monitoring host 2 can determine that in this section Track abnormality can be reported through the alarm circuit 26.

In step S515, it is determined whether the current unmanned vehicle 1 is also abnormal in other sections of the track. When the determination in step S511 is negative, the monitoring host 2 can determine whether the same unmanned vehicle 1 also has abnormal vibration conditions in other sections of the track. Through the determination in step S515, it can accurately determine whether the source of the abnormal vibration is the current one. The autonomous vehicle 1 itself.

In step S517, an alarm is issued that the unmanned vehicle 1 is abnormal. When the determination in step S515 is yes, the monitoring host 2 can determine that the same unmanned vehicle 1 has abnormal vibrations at its driving positions in different sections of the track. Therefore, the second controller 20 of the monitoring host 2 can determine that the unmanned vehicle 1 itself It is the source of abnormal vibration and can be reported through the alarm circuit 26.

In step S519, it is determined whether the number of exceptions reaches the standard. When the determination in step S515 is negative, the monitoring host 2 can further determine whether the current number of abnormal vibrations of the unmanned vehicle 1 at the same position reaches the standard. For example, when the accumulated number of abnormal vibrations reaches a preset value, the monitoring host determines that the standard is reached. Since the execution of step S519 already represents the elimination of a single source of abnormal vibration (such as unmanned vehicles or tracks), and through the execution judgment of step S519, it can be confirmed whether the sources of abnormal vibration come at the same time. It is caused by the interaction between the unmanned vehicle 1 and the track.

In step S521, an alarm is issued that there is an abnormality between the track and the unmanned vehicle 1 in this section. When step S519 is determined to be yes, the monitoring host 2 can base the abnormal vibration source on the interaction between the unmanned vehicle 1 and the track. Therefore, The second controller 20 of the monitoring host 2 can determine that the current unmanned vehicle 1 and the track itself in this section are sources of abnormal vibration, and can send a report through the alarm circuit 26 .

In step S523, the abnormality is recorded. When the determination in step S519 is no, the monitoring host can accumulate the number of abnormal times of the current unmanned vehicle 1 on the track in this section. For example, the initial value of the number of abnormal times is 0, and when each time When an exception occurs, the current number of exceptions will be accumulated by 1 until the accumulated number of exceptions reaches the standard. After that, the number of exceptions can be reset to 0 for next time re-judgment.

According to the above description, when the unmanned vehicle 1 is traveling on the track GR, the amount of vibration during the driving process of the unmanned vehicle 1 can be known through the built-in detection device 14 of the unmanned vehicle 1, and the monitoring host 2 can transmit the vibration amount to each unmanned vehicle 1 through the monitoring host 2. The amount of vibration is monitored, and the monitoring host 2 can know according to the monitoring results whether the unmanned vehicle 1 has abnormal vibrations while driving, and through analysis, it can know the source of the abnormal vibrations.

Next, examples will be given to illustrate several situations that cause the unmanned vehicle 1 to generate abnormal vibrations while driving on the track GR. Please refer to Figure 6. Figure 6 is a schematic diagram of an unmanned vehicle traveling on a normal track according to this embodiment of the invention. Here, the track GR and the unmanned vehicle 1 shown in Figure 6 are exemplified as being in a normal condition. At this time, the monitoring host 2 passes After receiving the real-time driving information returned by the unmanned vehicle 1 while traveling on the track GR, the monitoring host 2 can then determine the amount of vibration in the driving information to instantly know that the unmanned vehicle 1 does not have any abnormal vibrations while driving. In addition, the vibration amount in the driving information can be obtained through the detection device 14 installed at an appropriate position of the unmanned vehicle 1, and the installation position of the detection device 14 shown in Figure 6 is only an example, and the invention is not limited to this.

Please refer to Figure 7. Figure 7 is a schematic diagram of an unmanned vehicle traveling on a track with foreign objects according to this creative embodiment. Compared with Figure 6, the track GR shown in Figure 7 has more foreign objects OB, and this foreign object OB exists. The position of the track GR will produce abnormal vibrations for the unmanned vehicle 1 traveling at this position. Therefore, at this time, after the monitoring host 2 receives the driving message returned by the unmanned vehicle 1 after driving past the foreign object OB, the monitoring host 2 can then determine the amount of vibration in the driving message to instantly know that the unmanned vehicle 1 has been identified while driving. Abnormal vibration occurs. In addition, the monitoring host 2 can further determine that when different unmanned vehicles 1 are deemed to have abnormal vibrations when traveling to the position where the foreign object OB exists on the track GR, the monitoring host 2 can clearly confirm that the position where the foreign object OB exists on the track GR is abnormal. , and can further issue alarm notifications for track GR abnormalities in this section.

Please refer to FIGS. 8 and 9 . FIG. 8 is a schematic diagram of an unmanned vehicle driving on a skewed track according to an embodiment of the invention. FIG. 9 is another schematic diagram of an unmanned vehicle driving on a skewed track according to an embodiment of the invention. Compared with FIG. 6 , the track GR shown in FIGS. 8 and 9 is skewed. The skewed track GR here means that the adjacent first track GR1 and the second track GR2 in the track GR are not skewed. Align each other. That is, the unmanned vehicle 1 will generate abnormal vibrations when traveling at the misaligned intersection of the first track GR1 and the second track GR2. Therefore, at this time, after the monitoring host 2 receives the driving information returned from the misaligned intersection of the first track GR1 and the second track GR2 when the unmanned vehicle 1 drives, the monitoring host 2 can obtain the real-time information by judging the vibration amount in the driving information. It is known that the unmanned vehicle 1 has been found to have abnormal vibrations while driving. In the same way, the monitoring host 2 can further determine that when different unmanned vehicles 1 are deemed to have abnormal vibrations when traveling to the misaligned intersection of the first track GR1 and the second track GR2, then the monitoring host 2 can clearly confirm that the first track GR1 and the second track GR2 have abnormal vibrations. The position where the first track GR1 and the second track GR2 intersect and are misaligned has an abnormality, and a further alarm notification of abnormal track GR in this section can be issued.

Please refer to Figure 10. Figure 10 is a schematic diagram of an unmanned vehicle traveling at abnormal intervals on a track according to this embodiment of the present invention. Compared with Figure 6 , the track GR shown in Figure 10 has a gap situation. The track GR gap here refers to both the adjacent first track GR1 and the second track GR2 in the track. They are not closely dependent on each other. That is, the unmanned vehicle 1 will generate abnormal vibration at the intersection interval between the first track GR1 and the second track GR2. Therefore, after receiving the driving message returned by the unmanned vehicle 1 at the intersection of the first track and the second track, the monitoring host 2 can immediately know that no one is currently available by judging the amount of vibration in the driving message. Car 1 has been identified as having abnormal vibrations while driving. In the same way, the monitoring host 2 can further determine that when different unmanned vehicles 1 are deemed to have abnormal vibrations when traveling to the intersection of the first track and the second track, the monitoring host 2 can clearly confirm that the first track GR1 There is an abnormality in the position at the intersection interval with the second track GR2, and a further alarm notification of abnormal track GR in this section can be issued.

According to the contents disclosed in Figures 8 to 10 above, when the monitoring host 2 learns that the unmanned vehicle 1 has abnormal vibrations, it can further analyze whether the different unmanned vehicles 1 all have abnormal vibrations at the same place on the track GR. If it is judged to be so, it can be determined There is an abnormality in the track GR in this section. The abnormal situation of the track GR is, for example, the aforementioned abnormal phenomena such as foreign objects in the track GR, skewing of the track GR, or gaps in the track GR, but the invention is not limited to this.

In one embodiment, when the monitoring host 2 learns that the first unmanned vehicle has abnormal vibrations, it can further analyze whether the unmanned vehicles 1 other than the first unmanned vehicle all have abnormal vibrations at the same place on the track GR. When an unmanned vehicle in different sections of the track GR is determined to have abnormal vibrations by the monitoring host 2, it can be confirmed that the source of the vibration belongs to the first unmanned vehicle itself rather than the abnormality of the track GR.

In one embodiment, the first wireless circuit 16 and the second wireless circuit 22 are, for example, WI-FI communication circuits, Bluetooth communication circuits or radio frequency communication circuits. The alarm circuit 26 is, for example, various combinations of a display circuit, a light indicating circuit, or a speaker circuit. The first controller 10 and the second controller 20 may be, for example, one or any combination of an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or a system on a chip (SOC), and may cooperate with other Relevant circuit components and firmware are used to implement the above control process, but this creation is not limited to this.

To sum up, the monitoring host 2 can observe the driving information reported by the unmanned vehicle 1 for a long time. For example, when the unmanned vehicle 1 is used for a long time, the internal parts are aged (such as the elastic fatigue of the belt in the driving module), mechanical wear or long-term load bearing. , these factors will cause the amount of vibration to increase. This invention can provide early warning before the vibration expands to affect the quality of goods transported by the unmanned vehicle 1, so that relevant personnel can repair and maintain it in advance to avoid affecting the transportation due to excessive vibration amount exceeding expected dust. The production yield of goods.

[Beneficial effects of the embodiment]

The rail car monitoring and management system provided by our company can accurately detect the vibration conditions of unmanned vehicles and further accurately identify the source of the vibration. This can ensure that the quality of the goods being carried is not affected by the amount of vibration, and the alarm can be used to warn This allows unmanned vehicles or tracks to be handled immediately by personnel when abnormalities occur.

The contents provided above are only the preferred and feasible embodiments of this invention, and do not limit the scope of the patent application for this invention. Therefore, all equivalent technical changes made by using the description and drawings of this invention are included in the application for this invention. within the scope of the patent.

1:Unmanned vehicle

10:First controller

12: Driving module

14:Detection device

141:Identification circuit

143:Inertial sensor

16:First Radio Circuit

2: Monitor the host

20: Second controller

22:Second Radio Circuit

24:Database

26:Alarm circuit

Claims (10)

A rail car monitoring and management system includes: an unmanned vehicle, which wirelessly outputs a driving message when traveling on a track. The driving message includes a driving position and a vibration amount of the unmanned vehicle traveling on the track; and a monitoring host, Receive the driving information wirelessly and analyze the driving information to learn a vibration condition of the unmanned vehicle driving on the track; wherein the monitoring host determines that the vibration amount of the unmanned vehicle at the driving position is different from a corresponding reference value. When matched, the monitoring host further determines whether a vibration auxiliary condition is established; when the vibration auxiliary condition is determined to be established, the monitoring host determines that the vibration condition is abnormal and outputs an alarm signal; and when the vibration auxiliary condition is determined not to be established, The monitoring host records the abnormality of the unmanned vehicle at the driving position. The rail vehicle monitoring and management system as described in claim 1, wherein the vibration auxiliary condition is a combination of one or more judgment conditions, and one of the judgment conditions is to judge whether other unmanned vehicles have the vibration amount at the same driving position. If it is not consistent with the corresponding reference value, if the judgment is yes, the monitoring host determines that there is an abnormality in the track at the driving position. The rail vehicle monitoring and management system as described in claim 1, wherein the vibration auxiliary condition is a combination of one or more judgment conditions, and one of the judgment conditions is to judge the vibration amount of the unmanned vehicle at other different driving positions on the track. Whether it is inconsistent with the corresponding benchmark value, if it is determined to be yes, the monitoring host determines that the unmanned vehicle is abnormal. The rail vehicle monitoring and management system as described in claim 1, 2 or 3, wherein the vibration auxiliary condition is a combination of one or more judgment conditions, and one of the judgment conditions is to judge the vibration amount of the unmanned vehicle at the driving position. a reference value corresponding to Whether the number of discrepancies exceeds a preset number, if it is determined to be yes, the monitoring host determines that the unmanned vehicle and the track of the unmanned vehicle at the driving position are abnormal. The rail car monitoring and management system as claimed in claim 4, wherein the unmanned vehicle includes: a driving module; a first wireless circuit; a detection device; and a first controller electrically connected to the driving module, The detection device and the first wireless circuit, the first controller obtains a driving task of the unmanned vehicle on the track through the first wireless circuit, and relatively controls the operation of the driving module according to the driving task to drive the unmanned vehicle The vehicle is moving, and the first controller obtains the driving information of the unmanned vehicle through the detection result of the detection device, and wirelessly outputs the driving information to the monitoring host through the first wireless circuit. The rail vehicle monitoring and management system as described in claim 5, wherein the detection device includes an identification circuit that obtains the driving position and an inertial sensor that obtains the vibration amount. The identification circuit is used when the unmanned vehicle travels on the track. When the vehicle is running, an identification piece provided on the track is identified to obtain the driving position. The inertial sensor includes at least one of an accelerometer and a gyroscope. The rail car monitoring and management system as claimed in claim 5, wherein the monitoring host includes: a second wireless circuit; an alarm circuit; a database; and a second controller electrically connected to the second wireless circuit, the The database and the alarm circuit, the second controller is configured to process a vibration abnormality determination program. The vibration abnormality determination program is for the second controller to receive the driving data returned by each unmanned vehicle through the second wireless circuit. information, and analyze the driving information to learn the vibration conditions of the unmanned vehicle driving on the track. The rail vehicle monitoring and management system as described in claim 7, wherein the database stores a reference value used to judge vibration conditions, and the reference value is the normal vibration value of the unmanned vehicle traveling in each section of the track under normal circumstances. The rail vehicle monitoring and management system as described in request item 8, wherein the monitoring host compares the vibration amount at the driving position of the unmanned vehicle with the corresponding reference value after receiving the driving message. When When the comparison is determined to be consistent, it is determined that there is no abnormal vibration situation in the current driving position of the unmanned vehicle on the track. When the comparison results are inconsistent, it is determined that the unmanned vehicle has abnormal vibration conditions in the driving position on the track. The rail vehicle monitoring and management system as described in claim 9, wherein the monitoring host determines that the source of the abnormal vibration condition is foreign objects on the track, track deflection, abnormal track spacing, aging of the unmanned vehicle parts, mechanical wear of the unmanned vehicle, or the unmanned vehicle. The car has a long-term load bearing capacity.

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