Abnormity early warning system of intelligent transport trolley

Abstract

The invention discloses an abnormity early warning system of an intelligent transport trolley, which belongs to the technical field of trolley transport monitoring and comprises a path planning module used for planning and determining a transport path of the transport trolley and controlling the trolley to transport along the central line of the planned path; the data acquisition module is used for acquiring relevant parameter information of the transportation trolley in the transportation process; the analysis module is used for analyzing the abnormal condition of the trolley according to the obtained relevant parameter information so as to generate a corresponding strategy; and the execution module is used for executing the generated corresponding strategy. The vehicle condition analysis module can perform analysis according to data such as the temperature and the vibration frequency of the trolley to judge whether the overall condition of the conveying trolley is abnormal or not, so that potential faults of the trolley are repaired and maintained in time under the condition that large faults do not occur, follow-up faults are avoided, and the service life of the trolley is prolonged. And the conveying quality of the conveying trolley is ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of trolley transport monitoring, and in particular relates to an abnormal warning system for an intelligent transport trolley. Background Art

[0002] Smart transport vehicles are vehicles that can automatically navigate and perform transport tasks without direct human operation. They move along pre-programmed paths to deliver goods and are widely used in manufacturing, warehousing and logistics, healthcare, airports and other scenarios to improve efficiency, reduce labor costs, and enhance safety.

[0003] In order to ensure the transportation safety of the intelligent transport vehicle, a corresponding alarm device is generally installed on the transport vehicle. Once the relevant parameters of the transport vehicle exceed the alarm threshold, an alarm will be issued to remind the vehicle of abnormalities. Although this method can ensure the transportation safety of the intelligent transport vehicle in a timely manner, since the alarm threshold is generally set manually, it only alarms the parameters with problems and cannot warn of potential abnormal problems of the intelligent transport vehicle. Summary of the invention

[0004] The purpose of the present invention is to provide an abnormal warning system for an intelligent transport vehicle to solve the problems faced in the above-mentioned background technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions: An abnormal warning system for an intelligent transport vehicle, the warning system comprising: A path planning module, which is used to plan and determine the transport path of the transport vehicle and control the vehicle to be transported along the center line of the planned path; A data acquisition module, which is used to obtain relevant parameter information of the transport vehicle during the transportation process; An analysis module, wherein the analysis module includes a path analysis module and a vehicle condition analysis module. The path analysis module is used to judge whether the vehicle transport path is abnormal based on the acquired relevant parameter information, thereby generating a corresponding strategy. The vehicle condition analysis module is used to judge whether the overall condition of the transport vehicle is abnormal based on the acquired relevant parameter information, thereby generating a corresponding strategy. An execution module is used to execute the generated corresponding strategy.

[0006] Furthermore, the relevant parameter information includes position information, conveying information, vibration frequency information of the conveying vehicle, and temperature information.

[0007] Furthermore, the working method flow of the path analysis module is as follows: Step 1: Determine the reasonable conveying area of ​​the trolley according to the generated conveying path, obtain the position of the transport trolley on the conveying path in real time, and judge whether it is within the reasonable conveying area: if the position of the transport trolley is not within the reasonable conveying area, generate a position abnormality alarm strategy, otherwise, go to step 2; Step 2: When the transport vehicle does not generate a position abnormality alarm strategy, , obtain the position of the trolley n times, so as to determine the position difference between the trolley position and the center line of the transportation path , and propose a curve of position difference changing with the number of acquisitions ; By formula Path anomaly coefficient ; when When , the position of the transport trolley is judged to be abnormal, and an adjustment strategy is generated; in, is the coefficient of volatility, and , is the position difference obtained for the jth time, , For fixed period The first collection within For fixed period The last collection within is the maximum slope, as well as Preset coefficients for each, is the preset path anomaly coefficient threshold.

[0008] Furthermore, the adjustment strategy includes a left adjustment instruction and a right adjustment instruction: Get the position of the trolley when generating the adjustment strategy, and determine whether the trolley is on the left or right side of the center line of the transport path. If it is on the left side, generate a right adjustment instruction; if it is on the right side, generate a left adjustment instruction.

[0009] Furthermore, the execution module works as follows: when a right call instruction is generated, the formula Move the transport cart closer to the center of the transport path distance; When the left-hand instruction is generated, the formula Move the transport cart closer to the center of the transport path distance; in, is the distance conversion coefficient, as well as is the moving length.

[0010] Furthermore, the vehicle condition analysis module works as follows: When the transport vehicle is working normally, collect the time it takes to reach the destination during each transport process for m times , The number of times the position abnormality alarm strategy is generated during each transport and the number of times the strategy was adjusted ; By formula Obtain the comprehensive status value of the transport trolley ; The comprehensive status value obtained Comprehensive status judgment threshold set by the system Row comparison: when When , a maintenance strategy is generated; in, is the standard time for the transport vehicle to reach the destination, is the condition coefficient, It is the preset comprehensive condition threshold.

[0011] Furthermore, the condition coefficient The acquisition method is: Vibration sensors and temperature sensors are installed at key locations of the transport trolley to obtain the average vibration frequency of the transport trolley during each transport. and average temperature ; So through the formula Obtain the vibration frequency value for each delivery ; By formula Get the temperature value at each delivery ; And formulate the curve function of vibration frequency value changing with the number of conveying times And the temperature value changes with the number of conveying times ; By formula Condition coefficient ; in, as well as is the preset coefficient, u is the number of key parts, is the maximum vibration frequency detected in all key parts, is the maximum temperature detected in all key parts, It is the standard curve function of the preset vibration frequency value changing with the number of conveying times. It is the standard curve function of the preset temperature value changing with the number of conveying times. is the first delivery in the m-times delivery process, It is the last delivery in the m delivery process.

[0012] Furthermore, the execution module working method also includes: When the position abnormality alarm strategy is generated, the position abnormality alarm is performed; When a maintenance strategy is generated, a maintenance alarm is generated and the next transport of the transport trolley is prevented.

[0013] Beneficial effects of the present invention: The present invention uses a path analysis module to analyze in real time whether the transport trolley has abnormal position deviation during the transportation process, so as to timely perform alarm processing. At the same time, when there is no abnormal position deviation, the path abnormality coefficient of the transport trolley within a fixed period can be analyzed, and according to the path abnormality coefficient, it is judged whether the transport trolley has a tendency to deviate from the path abnormality, so as to make timely adjustments and corrections to ensure the normal transportation of the trolley; The vehicle condition analysis module provided in the present invention can perform analysis based on the temperature, vibration frequency and other data of the trolley to determine whether there is any abnormality in the overall condition of the conveying trolley, so as to promptly repair and maintain the potential faults of the trolley before a major fault occurs, thereby avoiding the occurrence of subsequent faults and ensuring the conveying quality of the conveying trolley.

[0014] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0016] Figure 1 It is a system module block diagram of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] In one embodiment, an abnormal warning system for an intelligent transport vehicle is disclosed, such as Figure 1 As shown, the early warning system includes: Path planning module, which is used to plan and determine the transport path of the transport vehicle and control the vehicle to transport along the center line of the planned path; The data acquisition module is used to obtain relevant parameter information of the transport vehicle during the transportation process, and the relevant parameter information includes position information, transportation information, vibration frequency information of the transport vehicle, and temperature information; An analysis module, which includes a path analysis module and a vehicle condition analysis module. The path analysis module is used to judge whether the vehicle transport path is abnormal based on the relevant parameter information obtained, thereby generating a corresponding strategy. The vehicle condition analysis module is used to judge whether the overall condition of the transport vehicle is abnormal based on the relevant parameter information obtained, thereby generating a corresponding strategy. The execution module is used to execute the generated corresponding strategy.

[0019] Through the above technical scheme, the present application uses a path analysis module to analyze in real time whether the transport trolley has any abnormal position deviation during the transportation process, so as to perform alarm processing in time; at the same time, when there is no abnormal position deviation, the path abnormality coefficient of the transport trolley within a fixed period can be analyzed, and the path abnormality coefficient can be used to determine whether there is a trend of abnormal path deviation of the transport trolley, so as to make timely adjustments and corrections to ensure the normal transportation of the trolley; the vehicle condition analysis module set up in addition can also analyze the temperature, vibration frequency and other data of the trolley to determine whether there is any abnormality in the overall condition of the transport trolley, so as to timely repair the vehicle condition in the absence of a major fault, avoid the occurrence of subsequent faults, and ensure the transportation quality of the transport trolley.

[0020] As an implementation of the present invention, the working method flow of the path analysis module is as follows: Step 1: Determine the reasonable conveying area of ​​the trolley according to the generated conveying path, obtain the position of the transport trolley on the conveying path in real time, and judge whether it is within the reasonable conveying area: if the position of the transport trolley is not within the reasonable conveying area, generate a position abnormality alarm strategy, otherwise, go to step 2; Step 2: When the transport vehicle does not generate a position abnormality alarm strategy, , obtain the position of the trolley n times, so as to determine the position difference between the trolley position and the center line of the transportation path , and propose a curve of position difference changing with the number of acquisitions ; By formula Path anomaly coefficient ; when When , the position of the transport trolley is judged to be abnormal, and an adjustment strategy is generated; in, is the coefficient of volatility, and , is the position difference obtained for the jth time, , For fixed period The first collection within For fixed period The last collection within is the maximum slope, as well as Preset coefficients for each, is the preset path anomaly coefficient threshold.

[0021] Through the above technical scheme, this embodiment provides a specific process of the path analysis module. First, the reasonable conveying area of ​​the trolley is determined according to the generated conveying path. The trolley moves along the center line of the conveying path, and the position of the trolley on the conveying path is obtained in real time to determine whether it is within the reasonable conveying area: when the position of the trolley is not within the reasonable conveying area, it means that the position of the trolley is abnormally deviated at this time, and a position abnormality alarm strategy is generated to remind the operating personnel to deal with it. Otherwise, further analysis is performed, so that it can be analyzed in real time whether the position deviation of the trolley is abnormal during the conveying process; and when the transport trolley does not generate a position abnormality alarm strategy, at this time, a fixed period is set. , and obtain the position of the trolley n times in a fixed period, so as to determine the position difference between the trolley position and the center line of the transportation path at each acquisition , and propose a curve of position difference changing with the number of acquisitions , and then through the formula Path anomaly coefficient ,formula It is expressed as a cumulative situation of position difference within a fixed interval period. The larger its value is, the greater the position deviation is, which means that the deviation trend of the car is greater. The formula It is expressed as the maximum slope of the deviation value change within a fixed period. The larger its value is, the greater the deviation trend of the car is. is the coefficient of volatility, and , which can represent the fluctuation of the deviation value within a fixed period. The larger its value is, the greater the change between each position difference is. Therefore, when the path anomaly coefficient is The larger the value, the greater the tendency of the car to deviate from its position. Therefore, when obtaining the path anomaly coefficient Then, compare it with the preset path anomaly coefficient threshold For comparison, when When the position deviation of the trolley is large, it indicates that the position deviation of the trolley is large. In this way, the position of the transport trolley is judged to be abnormal, and an adjustment strategy is generated to adjust the position in time so that the trolley returns to the center line of the transport path to ensure the normal transportation of the transport trolley. In this way, when there is no abnormal position deviation, the path abnormality coefficient can be obtained by analyzing the deviation of the transport trolley within a fixed period. According to the path abnormality coefficient, it can be judged whether the transport trolley has a tendency to deviate from the path abnormality, so as to make timely adjustments and corrections to ensure the normal transportation of the trolley.

[0022] It should be noted that the preset coefficient as well as , preset path anomaly coefficient threshold All can be formulated based on historical data and experience data, and fixed according to the cycle The duration can be determined artificially based on experience, so I will not go into details here.

[0023] As an implementation mode of the present invention, the adjustment strategy includes a left adjustment instruction and a right adjustment instruction: Get the position of the trolley when generating the adjustment strategy, and determine whether the trolley is on the left or right side of the center line of the transport path. If it is on the left side, generate a right adjustment command, and if it is on the right side, generate a left adjustment command; When the right call instruction is generated, the formula Move the transport cart closer to the center of the transport path distance; When the left-hand instruction is generated, the formula Move the transport cart closer to the center of the transport path distance; in, is the distance conversion coefficient, which is determined based on historical data. as well as is the moving length.

[0024] Through the above technical solution, this embodiment provides a specific method for the execution module to adjust the position of the trolley according to the adjustment strategy. First, the position of the trolley when the adjustment strategy is generated is obtained, and it is determined whether the trolley is on the left or right side of the center line of the transportation path. When it is on the left side, it means that the trolley has a tendency to deviate to the left, and a right adjustment instruction is generated to correct the trolley. When it is on the right side, it means that the trolley has a tendency to deviate to the right, and a left adjustment instruction is generated to correct the trolley. When the right adjustment instruction is generated, the formula is used at this time. Move the transport cart closer to the center of the transport path distance, it can be seen that when the path abnormality coefficient exceeds more, it means that it deviates more to the left, and the corresponding length that needs to be corrected to the right is more; similarly, when the left adjustment instruction is generated, at this time, through the formula Move the transport cart closer to the center of the transport path In this way, the position of the trolley can be accurately adjusted in time according to the path abnormality coefficient to ensure that the trolley returns to the center line of the transportation path, thereby ensuring normal transportation.

[0025] As an implementation mode of the present invention, the vehicle condition analysis module works as follows: When the transport vehicle is working normally, collect the time it takes to reach the destination during each transport process for m times , The number of times the position abnormality alarm strategy is generated during each transport and the number of times the strategy was adjusted ; By formula Obtain the comprehensive status value of the transport trolley ; The comprehensive status value obtained Comprehensive status judgment threshold set by the system For comparison: when When , a maintenance strategy is generated; in, is the standard time for the transport vehicle to reach the destination, is the preset comprehensive condition threshold, is the condition coefficient, The acquisition method is: Vibration sensors and temperature sensors are installed at key locations of the transport trolley to obtain the average vibration frequency of the transport trolley during each transport. and average temperature ; So through the formula Obtain the vibration frequency value for each delivery ; By formula Get the temperature value at each delivery ; And formulate the curve function of vibration frequency value changing with the number of conveying times And the temperature value changes with the number of conveying times ; By formula Condition coefficient ; in, as well as is the preset coefficient, u is the number of key parts, is the maximum vibration frequency detected in all key parts, is the maximum temperature detected in all key parts, It is the standard curve function of the preset vibration frequency value changing with the number of conveying times. It is the standard curve function of the preset temperature value changing with the number of conveying times. is the first delivery in the m-times delivery process, It is the last delivery in the m delivery process.

[0026] Through the above technical solution, this embodiment provides a specific method for the vehicle condition analysis module to work. Since the vibration frequency and temperature conditions of key parts during the transportation of the trolley can more accurately reflect the overall condition of the trolley, vibration sensors and temperature sensors are first installed at key parts of the transport trolley to obtain the average vibration frequency of the transport trolley during each transportation. and average temperature , and then through the formula Obtain the vibration frequency value for each delivery , through the formula The temperature value at each conveying is obtained. It can be seen that the larger the vibration frequency value and the temperature value, the worse the condition of the trolley. At the same time, a curve function of the vibration frequency value changing with the number of conveying times is proposed. And the temperature value changes with the number of conveying times , through the formula Condition coefficient ; The obtained vibration frequency change and temperature change are compared with their respective standard changes. The larger the value, the greater the difference between the temperature and vibration frequency of the trolley during the m-time transportation process and the historical transportation, indicating that the possibility of potential failure of the trolley is greater; at the same time, when the transport trolley is working normally, the time to reach the destination during each transportation process is collected during the m-time transportation process , The number of times the position abnormality alarm strategy is generated during each transport and the number of times the strategy was adjusted , through the formula Obtain the comprehensive status value of the transport trolley ; It can be seen that the more times the adjustment strategy is generated, the more times the position abnormality alarm strategy is generated, or the greater the difference between the arrival time and the standard arrival time during transportation, the greater the possibility of abnormal conditions in the car. Therefore, combined with the condition coefficient Conduct a comprehensive analysis and use the formula Obtain the comprehensive status value of the transport trolley , and then the comprehensive status value obtained Comprehensive status judgment threshold set by the system For comparison: when When the transport trolley is detected, it indicates that there is a potential fault in the transport trolley. A maintenance strategy is generated to repair the transport trolley in time to eliminate some hidden faults. In this way, a comprehensive analysis can be performed based on the temperature, vibration frequency, alarm status, delivery time and other data of the trolley to determine whether there is any abnormality in the overall condition of the transport trolley. In this way, the potential fault of the trolley can be repaired in time without a major fault, avoiding the occurrence of subsequent faults to ensure the transportation quality of the transport trolley.

[0027] It should be noted that the preset coefficient as well as , Comprehensive status judgment threshold set by the system All can be formulated based on historical data and experience data, and the preset vibration frequency value changes with the number of conveying times. , the preset temperature value changes with the number of conveying times standard curve function It is determined based on the normal historical operating data of the running car, and no further explanation is given here.

[0028] The working method of the execution module also includes: when generating a position abnormality alarm strategy, performing a position abnormality alarm to remind the management personnel to manage the trolley; When a maintenance strategy is generated, a maintenance alarm is generated and the next transport of the transport trolley is prevented, so that the trolley can be repaired and maintained in time.

[0029] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. An abnormal warning system for an intelligent transport vehicle, characterized in that: The early warning system includes: A path planning module, which is used to plan and determine the transport path of the transport vehicle and control the vehicle to be transported along the center line of the planned path; A data acquisition module, which is used to obtain relevant parameter information of the transport vehicle during the transportation process; An analysis module, wherein the analysis module includes a path analysis module and a vehicle condition analysis module. The path analysis module is used to judge whether the vehicle transport path is abnormal based on the acquired relevant parameter information, thereby generating a corresponding strategy. The vehicle condition analysis module is used to judge whether the overall condition of the transport vehicle is abnormal based on the acquired relevant parameter information, thereby generating a corresponding strategy. An execution module is used to execute the generated corresponding strategy.

2. According to claim 1, the abnormal warning system of the intelligent transport vehicle is characterized in that: The relevant parameter information includes position information, conveying information, vibration frequency information of the conveying vehicle and temperature information.

3. The abnormal warning system of the intelligent transport vehicle according to claim 2 is characterized in that: The working method flow of the path analysis module is as follows: Step 1: Determine the reasonable conveying area of ​​the trolley according to the generated conveying path, obtain the position of the transport trolley on the conveying path in real time, and judge whether it is within the reasonable conveying area: if the position of the transport trolley is not within the reasonable conveying area, generate a position abnormality alarm strategy, otherwise, go to step 2; Step 2: When the transport vehicle does not generate a position abnormality alarm strategy, , obtain the position of the trolley n times, so as to determine the position difference between the trolley position and the center line of the transportation path , and propose a curve of position difference changing with the number of acquisitions ; By formula Path anomaly coefficient ; when When , the position of the transport trolley is judged to be abnormal, and an adjustment strategy is generated; in, is the coefficient of volatility, and , is the position difference obtained for the jth time, , For fixed period The first collection within For fixed period The last collection within is the maximum slope, as well as Preset coefficients for each, is the preset path anomaly coefficient threshold.

4. The abnormal warning system for an intelligent transport vehicle according to claim 3 is characterized in that: The adjustment strategy includes left adjustment instructions and right adjustment instructions: Get the position of the trolley when generating the adjustment strategy, and determine whether the trolley is on the left or right side of the center line of the transport path. If it is on the left side, generate a right adjustment instruction; if it is on the right side, generate a left adjustment instruction.

5. The abnormal warning system for an intelligent transport vehicle according to claim 4 is characterized in that: The working method of the execution module is: when a right call instruction is generated, the formula Move the transport cart closer to the center of the transport path distance; When the left-hand instruction is generated, the formula Move the transport cart closer to the center of the transport path distance; in, is the distance conversion coefficient, as well as is the moving length.

6. The abnormal warning system for an intelligent transport vehicle according to claim 3 is characterized in that: The vehicle condition analysis module works as follows: When the transport vehicle is working normally, collect the time it takes to reach the destination during each transport process for m times , The number of times the position abnormality alarm strategy is generated during each transport and the number of times the strategy was adjusted ; By formula Obtain the comprehensive status value of the transport trolley ; The comprehensive status value obtained Comprehensive status judgment threshold set by the system For comparison: when When , a maintenance strategy is generated; in, is the standard time for the transport vehicle to reach the destination, is the condition coefficient, It is the preset comprehensive condition threshold.

7. The abnormal warning system for an intelligent transport vehicle according to claim 6 is characterized in that: The condition coefficient The acquisition method is: Vibration sensors and temperature sensors are installed at key locations of the transport trolley to obtain the average vibration frequency of the transport trolley during each transport. and average temperature ; So through the formula Obtain the vibration frequency value for each delivery ; By formula Get the temperature value at each delivery ; And formulate the curve function of vibration frequency value changing with the number of conveying times And the temperature value changes with the number of conveying times ; By formula Condition coefficient ; in, as well as is the preset coefficient, u is the number of key parts, is the maximum vibration frequency detected in all key parts, is the maximum temperature detected in all key parts, It is the standard curve function of the preset vibration frequency value changing with the number of conveying times. It is the standard curve function of the preset temperature value changing with the number of conveying times. is the first delivery in the m-times delivery process, It is the last delivery in the m delivery process.

8. The abnormal warning system for an intelligent transport vehicle according to claim 7 is characterized in that: The execution module working method also includes: When the position abnormality alarm strategy is generated, the position abnormality alarm is performed; When a maintenance strategy is generated, a maintenance alarm is generated and the next transport of the transport trolley is prevented.

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