Spraying Robot Abnormality Detection Method, Device and Terminal Equipment

Abstract

The present invention is applicable to the technical field of vehicle painting, and discloses a method, a device and a terminal device for detecting abnormalities of a spraying robot. The method includes: for each production line, collecting the body information of each vehicle on the production line and the operation data of each spraying robot on the production line during the operation state in real time, and determining whether each spraying robot is working normally according to the operation data of each spraying robot during the operation state; if it is determined that a certain spraying robot on the production line is not working normally, an alarm is given; the vehicle identification numbers of the vehicles affected by the spraying robot that is not working normally are determined according to the body information of each vehicle on the production line, and the vehicle identification numbers of the vehicles affected by the spraying robot that is not working normally are sent to a specified terminal. The present invention can automatically detect whether the spraying robot is working normally, without consuming manpower and saving time. At the same time, it can improve the accuracy of abnormality detection and can automatically give an alarm when an abnormality is detected.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle painting, and particularly relates to a method, device and terminal device for detecting anomalies of a spraying robot. Background Art

[0002] At present, automatic robots are becoming increasingly popular in various fields, and the automotive manufacturing industry is no exception. In order to improve production efficiency, spraying robots are used for automatic painting during the car paint coating process.

[0003] If an anomaly occurs during the operation of the spraying robot, it will affect the spraying effect and the quality of the vehicle body. However, the spraying robot only has a display function. If a quality problem occurs during the operation, manual inspection is still required. However, it is difficult to detect anomalies manually, which is time-consuming and error-prone. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method, device and terminal device for detecting anomalies of a spraying robot, so as to solve the problem that in the prior art, if a quality problem occurs during the operation, manual inspection is still required, but it is difficult to detect anomalies manually, which is time-consuming and error-prone.

[0005] The first aspect of the embodiments of the present invention provides a method for detecting anomalies of a spraying robot, including:

[0006] For each line body, the body information of each vehicle on the line body and the operation data of each spraying robot on the line body in the operating state are collected in real time, and it is determined whether each spraying robot is working normally according to the operation data of each spraying robot in the operating state;

[0007] If it is determined that a certain spraying robot on the line body is not working normally, an alarm is issued;

[0008] The vehicle identification number of the vehicle affected by the spraying robot that is not working normally is determined according to the body information of each vehicle on the line body, and the vehicle identification number of the vehicle affected by the spraying robot that is not working normally is sent to a specified terminal.

[0009] The second aspect of the embodiments of the present invention provides a device for detecting anomalies of a spraying robot, including:

[0010] An anomaly detection module, configured to collect in real time the body information of each vehicle on the line body and the operation data of each spraying robot on the line body in the operating state for each line body, and determine whether each spraying robot is working normally according to the operation data of each spraying robot in the operating state;

[0011] An alarm module, configured to issue an alarm if it is determined that a certain spraying robot on the line body is not working normally;

[0012] An information sending module, configured to determine the vehicle identification numbers of the vehicles affected by the spraying robot that is not working properly according to the body information of each vehicle on the production line, and send the vehicle identification numbers of the vehicles affected by the spraying robot that is not working properly to a specified terminal.

[0013] A third aspect of the embodiments of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the spraying robot anomaly detection method described in any item of the first aspect are implemented.

[0014] A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by one or more processors, the steps of the spraying robot anomaly detection method described in any item of the first aspect are implemented.

[0015] The beneficial effects of the embodiments of the present invention compared with the prior art are as follows: For each production line, the embodiments of the present invention collect the body information of each vehicle on the production line and the operation data of each spraying robot in the running state in real time, and determine whether each spraying robot is working properly according to the operation data of each spraying robot in the running state; if it is determined that a certain spraying robot on the production line is not working properly, an alarm is given; the vehicle identification numbers of the vehicles affected by the spraying robot that is not working properly are determined according to the body information of each vehicle on the production line, and the vehicle identification numbers of the vehicles affected by the spraying robot that is not working properly are sent to a specified terminal. The embodiments of the present invention can automatically detect whether the spraying robot is working properly, without consuming manpower, saving time, improving the accuracy of anomaly detection, and automatically giving an alarm when an anomaly is detected, and automatically determining the vehicle identification numbers of the affected vehicles and sending them to a specified terminal, which is convenient for the staff to check or repair. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 It is a schematic flowchart of the implementation of the spraying robot anomaly detection method provided by an embodiment of the present invention;

[0018] Figure 2 It is a schematic diagram of a specific application scenario of the spraying robot anomaly detection method provided by an embodiment of the present invention;

[0019] Figure 3 It is a schematic diagram of the fault type provided by an embodiment of the present invention;

[0020] Figure 4 It is a schematic diagram of the data structure of the equipment operation data table provided by an embodiment of the present invention;

[0021] Figure 5 It is an effect diagram of the relationship among the AVI data table, the equipment operation data table, and the abnormal data table provided by an embodiment of the present invention;

[0022] Figure 6 It is a schematic diagram of the information received by the specified terminal provided by an embodiment of the present invention;

[0023] Figure 7 It is a schematic diagram of the operation data monitoring of the spraying robot provided by an embodiment of the present invention;

[0024] Figure 8 It is a schematic block diagram of the abnormal detection device of the spraying robot provided by an embodiment of the present invention;

[0025] Figure 9 It is a schematic block diagram of the terminal device provided by an embodiment of the present invention. Detailed implementation manners

[0026] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. However, those skilled in the art should understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0027] To illustrate the technical solutions described in the present invention, the following will be described through specific embodiments.

[0028] Figure 1 It is a schematic diagram of the implementation process of the abnormal detection method of the spraying robot provided by an embodiment of the present invention. For the convenience of illustration, only the parts related to the embodiments of the present invention are shown. The execution subject of the embodiments of the present invention can be a terminal device. This terminal device can be a host computer.

[0029] As Figure 1 shown, the method may include the following steps:

[0030] S101: For each line body, collect the body information of each vehicle on the line body and the operation data of each spraying robot in the running state in real time, and determine whether each spraying robot is working properly according to the operation data of each spraying robot in the running state.

[0031] Among them, the above-mentioned production line refers to the production line for vehicle body painting, which can be an undercoat production line, a primer surfacer production line or a topcoat production line. Painting the vehicle body is a production line operation, and multiple spraying robots are required for each production line. When the spraying robot detects that the vehicle is in its working position, it enters the running state, starts spraying, and records the number of runs and the start running time each time. The number of runs starts from 1 and increases incrementally; if the vehicle is not detected in its working position, it is in the non-running state and does not spray. Whether it is in the running state can be determined according to the value of the running state parameter of the spraying robot. Specifically, if the value of the running state parameter is 0, it is in the non-running state; if the value of the running state parameter is 1, it is in the running state.

[0032] In the embodiment of the present invention, the body information of each vehicle on the production line can be collected by a scanning device. Among them, the body information includes the vehicle number, and the vehicle number starts from 1 and increases incrementally.

[0033] Exemplarily, when the scanning device scans the first vehicle, the vehicle number of the first vehicle is 1. When the first vehicle is conveyed to the working position corresponding to the spraying robot L1 on the production line, the spraying robot L1 starts working for the first time and records the start running time, that is, the number of runs is 1 and its corresponding start running time. When the first vehicle is conveyed to the working position corresponding to the spraying robot L2 on the production line, the spraying robot L2 starts working for the first time and records the start running time, that is, the number of runs is 1 and its corresponding start running time, and so on.

[0034] When the scanning device scans the second vehicle, the vehicle number of the second vehicle is 2. When the second vehicle is conveyed to the working position corresponding to the spraying robot L1 on the production line, the spraying robot L1 starts working for the second time and records the start running time, that is, the number of runs is 2 and the corresponding start running time. When the second vehicle is conveyed to the working position corresponding to the spraying robot L2 on the production line, the spraying robot L2 starts working for the second time and records the start running time, that is, the number of runs is 2 and the corresponding start running time, and so on.

[0035] Among them, the scanning device can be an AVI (Automated Visual Inspection) detector.

[0036] The body information of each vehicle can be stored in the AVI data table. The body information can include one or more of the vehicle number, vehicle identification number (VIN), vehicle color, vehicle configuration and other information. Among them, the vehicle identification number can also be called the vehicle identification number.

[0037] In an embodiment of the present invention, by constructing a device local area network, communication connection between the terminal device and the spraying robot is achieved. The terminal device can collect the operation data of the spraying robot in the operating state in real time, and determine whether each spraying robot is working properly according to the operation data of each spraying robot in the operating state.

[0038] S102: If it is determined that a certain spraying robot on the line is not working properly, an alarm is given.

[0039] Among them, giving an alarm can be that the terminal device gives an audible and visual alarm; it can also be sending an alarm signal to the spraying robot that is not working properly, for instructing the spraying robot that is not working properly to give an audible and visual alarm.

[0040] S103: Determine the vehicle frame numbers of the vehicles affected by the spraying robot that is not working properly according to the body information of each vehicle on the line, and send the vehicle frame numbers of the vehicles affected by the spraying robot that is not working properly to the designated terminal.

[0041] Among them, the designated terminal can be the mobile terminal of the designated staff. Exemplarily, it can be sent to the designated terminal through the DingTalk robot, or can be sent to the designated terminal through text messages, WeChat, etc.

[0042] In a specific application scenario, taking a spraying robot as an example, as Figure 2 shown, the vehicle is conveyed on the line. When the vehicle is conveyed to the position where the scanning device 10 is located, the scanning device 10 scans the body information of the vehicle and sends the body information to the terminal device 40, that is, the upper computer. When the vehicle is conveyed to the position where the spraying robot 20 is located, the spraying robot 20 enters the operating state and starts spraying. The terminal device 40 can collect the operation data of the spraying robot 20 in the operating state, and determine whether the spraying robot 20 is working properly according to the operation data. If it is determined that the spraying robot 20 is not working properly, an alarm is given. The terminal device can also determine the vehicle frame number of the affected vehicle according to the body information, and send the vehicle frame number to the designated terminal 50 through DingTalk, WeChat, etc.

[0043] Among them, the terminal device 40 can establish a data analysis model internally to analyze the body information and operation data, and determine whether the spraying robot 20 is working properly and the vehicle frame numbers of the affected vehicles, etc. Of course, it can also be established externally, for example, in a server, and no specific limitation is made here.

[0044] As can be seen from the above description, the embodiments of the present invention can automatically detect whether the spraying robots are working properly, without consuming manpower, saving time, improving the accuracy of anomaly detection, automatically alarming when an anomaly is detected, and automatically determining the vehicle identification number (VIN) of the affected vehicle and sending it to a designated terminal, which is convenient for the staff to check or repair. There is no need to manually check the quality problems after the spraying line is completed, saving a lot of time and avoiding missed inspections.

[0045] In one embodiment of the present invention, the above operation data includes the actual values of various operation parameters and the set values of various operation parameters.

[0046] "Determining whether each spraying robot is working properly according to the operation data of each spraying robot in the operating state" in S101 above may include:

[0047] For each operation parameter of each spraying robot, in consecutive preset numbers of operation data collections, if the actual value of this operation parameter is greater than the set value of this operation parameter each time, or the operation difference of this operation parameter is greater than the operation difference of this operation parameter last time each time, or the number of times that the actual value of this operation parameter and the set value of this operation parameter meet the preset conditions is greater than the preset number of times, or the difference obtained by subtracting the operation difference of this operation parameter last time from the operation difference of this operation parameter each time is less than the preset difference, or the actual value of this operation parameter is less than the set value of this operation parameter each time, then it is determined that this spraying robot is not working properly.

[0048] Wherein, the operation difference of this operation parameter is the actual value of this operation parameter minus the set value of this operation parameter; the preset condition is that the actual value of this operation parameter and the set value of this operation parameter are not equal this time and the operation difference of this operation parameter and the operation difference of this operation parameter last time are not equal.

[0049] In one embodiment of the present invention, the above operation parameters may include at least one of high-voltage parameters, speed parameters, and forming parameters. Among them, the speed parameter may be a rotational speed parameter.

[0050] The acquisition frequency of the operation data may be 1 second / time, the preset number of times may be 20 times, and the preset difference may be 3. Of course, in actual applications, it can be set according to actual needs and is not limited here.

[0051] Specifically, for each spraying robot, if any one of its operation parameters meets at least one of the above 5 situations, it is determined that this spraying robot is not working properly; otherwise, it is determined that this spraying robot is working properly.

[0052] Exemplarily, taking the high-pressure parameters of a spraying robot as an example, in the continuous collection of 20 runs of operation data, it is determined whether the actual value of the high-pressure parameter collected each time is greater than the set value of the high-pressure parameter collected each time. If the actual values of the high-pressure parameters collected 20 times are all greater than the corresponding set values of the high-pressure parameters, it is determined that the spraying robot is not working properly; it is determined whether the difference obtained by subtracting the set value of the high-pressure parameter collected each time from the actual value of the high-pressure parameter collected each time is greater than the difference obtained by subtracting the set value of the high-pressure parameter collected last time from the actual value of the high-pressure parameter collected last time. If so, it is determined that the spraying robot is not working properly; it is determined whether the number of times that the actual value of the high-pressure parameter collected 20 times and the set value of the high-pressure parameter meet the preset conditions is greater than the preset number of times. If so, it is determined that the spraying robot is not working properly, where the preset condition is that the actual value of the current high-pressure parameter is not equal to the set value of the current high-pressure parameter and the running difference of the current high-pressure parameter is not equal to the running difference of the previous high-pressure parameter; it is determined whether the difference obtained by subtracting the running difference of the high-pressure parameter collected last time from the running difference of the high-pressure parameter collected each time is less than the preset difference. If so, it is determined that the spraying robot is not working properly; it is determined whether the actual value of the high-pressure parameter collected each time is less than the set value of the high-pressure parameter collected each time. If so, it is determined that the spraying robot is not working properly.

[0053] In an embodiment of the present invention, the above-mentioned abnormal detection method for a spraying robot further includes:

[0054] If it is determined that a certain spraying robot on the line is not working properly, the abnormal operation parameters and the fault types of the abnormal operation parameters are determined according to the operation data of the spraying robot in the running state.

[0055] According to the abnormal operation parameters and the fault types of the abnormal operation parameters, the abnormal cause is determined.

[0056] In an embodiment of the present invention, the second preset table stores the corresponding relationships among operation parameters, fault types, and abnormal causes. According to the second preset table, the abnormal cause corresponding to the abnormal operation parameters and the fault types of the abnormal operation parameters can be determined.

[0057] Among them, the abnormal operation parameter is an operation parameter that satisfies any one of the above 5 situations.

[0058] If the abnormal operation parameter satisfies that the actual value of each time of this operation parameter is greater than the set value of each time of this operation parameter, the fault type of this abnormal operation parameter is the first fault type;

[0059] If the abnormal operation parameter satisfies that the running difference of each time of this operation parameter is greater than the running difference of the previous time of this operation parameter, the fault type of this abnormal operation parameter is the second fault type;

[0060] If the number of times that the actual value of an abnormal operating parameter satisfies the preset condition with respect to the set value of the operating parameter is greater than a preset number of times, the fault type of the abnormal operating parameter is the third fault type;

[0061] If the difference obtained by subtracting the running difference of the operating parameter last time from the running difference of the operating parameter each time for an abnormal operating parameter is less than a preset difference each time, the fault type of the abnormal operating parameter is the fourth fault type;

[0062] If the actual value of an abnormal operating parameter is less than the set value of the operating parameter each time, the fault type of the abnormal operating parameter is the fifth fault type.

[0063] Among them, the first fault type can be a positive value type, as shown in ① in Figure 3 The second fault type can be an ascending type, as shown in ② in Figure 3 The third fault type can be a fluctuating type, as shown in ④ in Figure 3 The fourth fault type can be a descending type, as shown in ③ in Figure 3 The fifth fault type can be a negative value type, as shown in ⑤ in Figure 3 shown in

[0064] In an embodiment of the present invention, the above spray robot abnormal detection method further includes:

[0065] Obtain the name of the spray robot that is not working properly;

[0066] Send the name of the spray robot that is not working properly, the abnormal operating parameter, the fault type of the abnormal operating parameter, and the abnormal cause to a specified terminal.

[0067] In an embodiment of the present invention, while giving an alarm, it further includes:

[0068] Record the alarm time and send the alarm time to a specified terminal.

[0069] In an embodiment of the present invention, the vehicle body information includes a vehicle identification number and a vehicle number;

[0070] Determining the vehicle identification number of the vehicle affected by the spray robot that is not working properly according to the vehicle body information of each vehicle on the line includes:

[0071] Obtain a first preset table, where the first preset table stores the correspondence between the running times of the spray robot that is not working properly and the start running time;

[0072] According to the alarm time and the first preset table, determine the target running times of the spray robot that is not working properly at the time of alarm;

[0073] Determine the vehicle identification number corresponding to the vehicle number equal to the target number of runs as the vehicle identification number of the vehicle affected by the malfunctioning spraying robot.

[0074] Among them, the first preset table is shown in Table 1.

[0075] Table 1 First Preset Table

[0076]

[0077] In the embodiment of the present invention, when abnormal operation data of the spraying robot is detected, an alarm is immediately issued and the alarm time is recorded. Therefore, the current alarm time is between the start time of the current run ID_START_TIME and the start time of the next run ID+1_START_TIME, that is, ID_START_TIME ≤ current alarm time < ID+1_START_TIME. Therefore, the target number of runs at which the malfunctioning spraying robot is located at the time of alarm can be determined according to the alarm time.

[0078] For the same vehicle, the vehicle number AVI.ID in its vehicle body information is equal to the value of the number of runs of each spraying robot spraying robot run.ID, that is, AVI.ID = spraying robot run.ID. Therefore, the vehicle identification number corresponding to the vehicle number equal to the target number of runs is the vehicle identification number of the vehicle affected by the malfunctioning spraying robot.

[0079] In addition to the above-mentioned operation parameters, the operation data may also include vehicle type brush number, spraying color, spraying configuration, spraying vehicle type, current, pressure, start signal, number of runs, start time of operation, etc.

[0080] The above-mentioned operation data can be stored in the device operation data table, and the data structure of the device operation data table can be as Figure 4 shown. The name, alarm time, abnormal operation parameters, fault type and abnormal cause of the above-mentioned malfunctioning spraying robot can be stored in the abnormal data table.

[0081] Among them, the relationship effect diagram of the AVI data table, the device operation data table and the abnormal data table is as Figure 5 shown. The target number of runs can be determined according to the alarm time in the abnormal data table and the start time of each run of the spraying robot in the device operation data table. The corresponding vehicle number and its corresponding vehicle identification number can be found from the AVI data table according to the target number of runs. Obtain the vehicle identification number from the AVI data table, obtain the name, abnormal operation parameters, fault type, abnormal cause and alarm time of the malfunctioning spraying robot from the abnormal data table, and uniformly send the obtained information to the specified terminal.

[0082] Exemplarily, the information received by the specified terminal can be as follows Figure 6 shown, where the device name is the name of the spray painting robot that is working properly; Molding record: no abnormality, indicating that the molding parameters of the spray painting robot are normal, so the corresponding failure factor is none; Speed record: no abnormality, indicating that the speed parameters of the spray painting robot are normal, so the corresponding failure factor is none; High voltage record: negative value, fluctuation, indicating that the failure type of the high voltage parameter is the negative value type and the fluctuation type; The failure factor is the possible abnormal cause corresponding to the abnormal high voltage parameter; The acquisition time can be the above alarm time or the acquisition time of the abnormal data.

[0083] The above operation data can be displayed to the staff in the form of a chart for convenient problem tracing. As Figure 7 shown, the solid line in the figure represents the set value of the corresponding parameter, and the dotted line represents the actual value of the corresponding parameter.

[0084] The embodiment of the present invention can monitor the operation data of the spray painting robot throughout the process, compare the difference between the actual value and the set value, display it through a data report, establish the historical data and the cause of the equipment problem, and complete the correction of the equipment failure cause data.

[0085] The embodiment of the present invention can automatically collect the operation data of the spray painting robot during the working process, analyze and alarm the operation situation through the monitored data, which can save a large amount of quality inspection man-hours and effectively improve the quality of body painting at the same time.

[0086] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiment of the present invention.

[0087] Corresponding to the above spray painting robot abnormal detection method, an embodiment of the present invention also provides a spray painting robot abnormal detection device, which has the same beneficial effects as the above spray painting robot abnormal detection method. Figure 8 FIG. is a schematic block diagram of a spray painting robot abnormal detection device provided by an embodiment of the present invention. For the convenience of description, only the parts related to the embodiment of the present invention are shown.

[0088] In the embodiment of the present invention, the spray painting robot abnormal detection device 30 may include an abnormal detection module 301, an alarm module 302, and an information sending module 303.

[0089] Among them, the abnormal detection module 301 is used to collect the body information of each vehicle on the line and the operation data of each spray painting robot on the line during the running state for each line, and determine whether each spray painting robot is working properly according to the operation data of each spray painting robot during the running state;

[0090] An alarm module 302, configured to alarm if it is determined that a certain spraying robot on the production line is not working properly.

[0091] An information sending module 303, configured to determine the vehicle identification numbers of the vehicles affected by the spraying robot that is not working properly according to the body information of each vehicle on the production line, and send the vehicle identification numbers of the vehicles affected by the spraying robot that is not working properly to a specified terminal.

[0092] In an embodiment of the present invention, the operation data includes the actual values of each operation parameter and the set values of each operation parameter.

[0093] The abnormality detection module 301 can also be configured to:

[0094] For each operation parameter of each spraying robot, in consecutive preset times of operation data collection, if the actual value of each operation parameter is greater than the set value of each operation parameter each time, or, the operation difference of each operation parameter is greater than the operation difference of the previous operation parameter each time, or, the number of times that the actual value of the operation parameter satisfies a preset condition is greater than a preset number of times, or, the difference obtained by subtracting the operation difference of the previous operation parameter from the operation difference of each operation parameter each time is less than a preset difference, or, the actual value of each operation parameter is less than the set value of each operation parameter each time, it is determined that the spraying robot is not working properly.

[0095] Wherein, the operation difference of the operation parameter is the actual value of the operation parameter minus the set value of the operation parameter; the preset condition is that the actual value of the operation parameter this time is not equal to the set value of the operation parameter this time and the operation difference of the operation parameter this time is not equal to the operation difference of the previous operation parameter.

[0096] In an embodiment of the present invention, the operation parameters include at least one of a high-voltage parameter, a speed parameter, and a forming parameter.

[0097] In an embodiment of the present invention, the spraying robot abnormality detection device 30 may further include an abnormality cause determination module.

[0098] The abnormality cause determination module can be configured to:

[0099] If it is determined that a certain spraying robot on the production line is not working properly, determine the abnormal operation parameter and the fault type of the abnormal operation parameter according to the operation data when the spraying robot that is not working properly is in an operating state.

[0100] Determine the cause of the abnormality according to the abnormal operation parameter and the fault type of the abnormal operation parameter.

[0101] In one embodiment of the present invention, the information sending module 303 may further be configured to:

[0102] Obtain the name of the spraying robot that is not working properly;

[0103] Send the name of the spraying robot that is not working properly, the abnormal operation parameters, the fault type of the abnormal operation parameters, and the abnormal cause to a specified terminal.

[0104] In one embodiment of the present invention, the alarm module 302 may further be configured to:

[0105] Record the alarm time and send the alarm time to a specified terminal.

[0106] In one embodiment of the present invention, the vehicle body information includes a vehicle identification number and a vehicle number;

[0107] The information sending module 303 may further be configured to:

[0108] Obtain a first preset table, where the first preset table stores the correspondence between the number of running times of the spraying robot that is not working properly and the start running time;

[0109] Determine the target number of running times of the spraying robot that is not working properly at the time of alarm according to the alarm time and the first preset table;

[0110] Determine the vehicle identification number corresponding to the vehicle number equal to the target number of running times as the vehicle identification number of the vehicle affected by the spraying robot that is not working properly.

[0111] Those skilled in the art can clearly understand that for the convenience and conciseness of description, only the above-mentioned division of each functional unit and module is used as an example. In practical applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the spraying robot abnormal detection device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in one processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of the present application. The specific working processes of the units and modules in the above device can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0112] Figure 9 is a schematic block diagram of a terminal device provided by an embodiment of the present invention. As Figure 9As shown, the terminal device 40 of this embodiment includes: one or more processors 401, a memory 402, and a computer program 403 stored in the memory 402 and executable on the processor 401. When the processor 401 executes the computer program 403, it implements the steps in the above-mentioned embodiments of the abnormal detection method for each spraying robot. For example Figure 1 the steps S101 to S103 shown. Alternatively, when the processor 401 executes the computer program 403, it implements the functions of each module / unit in the above-mentioned embodiment of the abnormal detection device for spraying robots. For example Figure 8 the functions of the modules 301 to 303 shown.

[0113] Exemplarily, the computer program 403 can be divided into one or more modules / units. The one or more modules / units are stored in the memory 402 and executed by the processor 401 to complete this application. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program 403 in the terminal device 40. For example, the computer program 403 can be divided into an abnormal detection module, an alarm module, and an information sending module. The specific functions of each module are as follows:

[0114] The abnormal detection module is used to collect, for each line body, the body information of each vehicle on the line body and the operation data of each spraying robot on the line body during the operation state, and determine whether each spraying robot is working properly according to the operation data of each spraying robot during the operation state;

[0115] The alarm module is used to give an alarm if it is determined that a certain spraying robot on the line body is not working properly;

[0116] The information sending module is used to determine the vehicle frame numbers of the vehicles affected by the spraying robot that is not working properly according to the body information of each vehicle on the line body, and send the vehicle frame numbers of the vehicles affected by the spraying robot that is not working properly to a specified terminal.

[0117] Other modules or units can refer to Figure 8 the description in the embodiment shown, and will not be elaborated here.

[0118] The terminal device 40 can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal device 40 includes but is not limited to the processor 401 and the memory 402. Those skilled in the art can understand, Figure 9This is only an example of the terminal device 40, which does not constitute a limitation on the terminal device 40. It may include more or fewer components than those shown in the figure, or combine certain components, or different components. For example, the terminal device 40 may further include an input device, an output device, a network access device, a bus, etc.

[0119] The processor 401 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0120] The memory 402 may be an internal storage unit of the terminal device 40, such as the hard disk or memory of the terminal device 40. The memory 402 may also be an external storage device of the terminal device 40, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal device 40. Further, the memory 402 may also include both the internal storage unit and the external storage device of the terminal device 40. The memory 402 is used to store the computer program 403 and other programs and data required by the terminal device 40. The memory 402 may also be used to temporarily store the data that has been output or will be output.

[0121] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0122] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0123] In the embodiments provided in this application, it should be understood that the disclosed abnormal detection device and method for a spraying robot can be implemented in other ways. For example, the embodiments of the abnormal detection device for a spraying robot described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling, direct coupling, or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the devices or units can be in electrical, mechanical, or other forms.

[0124] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0125] In addition, each functional unit in the various embodiments of this application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0126] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-mentioned method embodiments of this application, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0127] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included within the protection scope of the present application.

Claims

1. An abnormal detection method for a spraying robot, characterized in that, Including: For each production line, the body information of each vehicle on the production line and the operation data of each spraying robot on the production line during the operation state are collected in real time, and it is determined whether each spraying robot is working properly according to the operation data of each spraying robot during the operation state; the body information includes the vehicle identification number and the vehicle number; If it is determined that a certain spraying robot on the production line is not working properly, an alarm is given; the situation of not working properly means a failure occurs; According to the body information of each vehicle on the production line, the vehicle identification numbers of the vehicles affected by the spraying robot that is not working properly are determined, and the vehicle identification numbers of the vehicles affected by the spraying robot that is not working properly are sent to a designated terminal; Among them, the determining of the vehicle identification numbers of the vehicles affected by the spraying robot that is not working properly according to the body information of each vehicle on the production line includes: Obtaining a first preset table, which stores the corresponding relationship between the operation times and the start operation times of the spraying robot that is not working properly; According to the alarm time and the first preset table, the target operation times of the spraying robot that is not working properly at the time of alarm are determined; the alarm time is the time when the spraying robot that is not working properly gives an alarm; The vehicle identification numbers corresponding to the vehicle numbers equal to the target operation times are determined as the vehicle identification numbers of the vehicles affected by the spraying robot that is not working properly; among them, the vehicle number of a vehicle is equal to the operation times when each spraying robot sprays the vehicle.

2. The abnormal detection method of the spraying robot according to claim 1, wherein, The operation data includes the actual values of each operation parameter and the set values of each operation parameter; The determining of whether each spraying robot is working properly according to the operation data of each spraying robot during the operation state includes: For each operation parameter of each spraying robot, in continuous preset times of operation data collection, if the actual value of each operation parameter is greater than the set value of each operation parameter every time, or the operation difference of each operation parameter is greater than the operation difference of the operation parameter last time every time, or the number of times that the actual value of the operation parameter meets the preset condition is greater than the preset number of times, or the difference obtained by subtracting the operation difference of the operation parameter last time from the operation difference of the operation parameter every time is less than the preset difference, or the actual value of each operation parameter is less than the set value of each operation parameter every time, it is determined that the spraying robot is not working properly; Among them, the operation difference of the operation parameter is the actual value of the operation parameter minus the set value of the operation parameter; the preset condition is that the actual value of the operation parameter this time is not equal to the set value of the operation parameter this time and the operation difference of the operation parameter this time is not equal to the operation difference of the operation parameter last time.

3. The abnormal detection method of the spraying robot according to claim 2, characterized in that, The operation parameters include at least one of a high-pressure parameter, a speed parameter, and a forming parameter.

4. The abnormal detection method of the spraying robot according to claim 1, characterized in that, The spraying robot abnormal detection method further includes: If it is determined that a certain spraying robot on the production line is not working properly, the abnormal operation parameter and the fault type of the abnormal operation parameter are determined according to the operation data of the spraying robot that is not working properly during the operation state; According to the abnormal operation parameter and the fault type of the abnormal operation parameter, the abnormal cause is determined.

5. The abnormal detection method of the spraying robot according to claim 4, wherein The abnormal detection method of the spraying robot further includes: Obtaining the name of the spraying robot that fails to work properly; Sending the name of the spraying robot that fails to work properly, the abnormal operation parameters, the fault type of the abnormal operation parameters, and the abnormal reason to the specified terminal.

6. The abnormal detection method of the spraying robot according to any one of claims 1 to 5, characterized in that, While giving the alarm, it further includes: Recording the alarm time and sending the alarm time to the specified terminal.

7. An abnormal detection device for a spraying robot, characterized in that, It includes: An abnormal detection module, which is used to collect the body information of each vehicle on the line body and the operation data of each spraying robot on the line body during the operation state in real time for each line body, and determine whether each spraying robot works properly according to the operation data of each spraying robot during the operation state; the body information includes the vehicle identification number and the vehicle number; An alarm module, which is used to give an alarm if it is determined that a certain spraying robot on the line body fails to work properly; the failure to work properly means a fault occurs; An information sending module, which is used to determine the vehicle identification number of the vehicle affected by the spraying robot that fails to work properly according to the body information of each vehicle on the line body, and send the vehicle identification number of the vehicle affected by the spraying robot that fails to work properly to the specified terminal; The information sending module is further used for: Obtaining a first preset table, which stores the corresponding relationship between the operation times and the start operation time of the spraying robot that fails to work properly; Determining the target operation times of the spraying robot that fails to work properly at the time of alarm according to the alarm time and the first preset table; the alarm time is the time of the spraying robot that fails to work properly at the time of alarm; Determining the vehicle identification number corresponding to the vehicle identification number equal to the target operation times as the vehicle identification number of the vehicle affected by the spraying robot that fails to work properly; wherein, the vehicle number of the vehicle is equal to the operation times when each spraying robot sprays the vehicle.

8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the spraying robot abnormal detection method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by one or more processors, it implements the steps of the spraying robot abnormal detection method according to any one of claims 1 to 6.

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