CN109933487B - Intelligent robot monitoring method and device - Google Patents
Intelligent robot monitoring method and device Download PDFInfo
- Publication number
- CN109933487B CN109933487B CN201711378624.7A CN201711378624A CN109933487B CN 109933487 B CN109933487 B CN 109933487B CN 201711378624 A CN201711378624 A CN 201711378624A CN 109933487 B CN109933487 B CN 109933487B
- Authority
- CN
- China
- Prior art keywords
- intelligent robot
- cpu utilization
- utilization rate
- preset time
- cpu
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 65
- 238000000034 method Methods 0.000 title claims abstract description 51
- 230000002159 abnormal effect Effects 0.000 claims abstract description 41
- 230000005856 abnormality Effects 0.000 claims description 25
- 238000012806 monitoring device Methods 0.000 claims description 6
- 238000004891 communication Methods 0.000 claims description 5
- 230000000694 effects Effects 0.000 abstract description 13
- 238000012545 processing Methods 0.000 description 13
- 230000008569 process Effects 0.000 description 11
- 238000004590 computer program Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 6
- 238000004364 calculation method Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000006399 behavior Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000002411 adverse Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 238000013105 post hoc analysis Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 238000011282 treatment Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Landscapes
- Manipulator (AREA)
Abstract
The invention discloses a monitoring method and device of an intelligent robot. The method comprises the following steps: acquiring CPU utilization rate of the intelligent robot within a first preset time; determining the maximum value of CPU utilization rate of the intelligent robot within a first preset time; setting a preset threshold according to the maximum value of the CPU utilization rate, wherein the preset threshold is larger than or equal to the maximum value of the CPU utilization rate; monitoring the current CPU utilization rate of the intelligent robot at intervals of a second preset time, wherein the length of the first preset time is greater than or equal to that of the second preset time; judging whether the current CPU utilization exceeds a preset threshold value; and outputting abnormal prompt information under the condition that the preset threshold value is exceeded. The invention improves the monitoring effect on the CPU utilization rate.
Description
Technical Field
The invention relates to the field of robots, in particular to a monitoring method and device of an intelligent robot.
Background
The intelligent robot body generally uses an embedded real-time system to meet the diversity and real-time requirements. In order to improve the reliability and fault tolerance of the system, a certain fault tolerance strategy needs to be adopted by the system design. The fault-tolerant system can be realized by monitoring the system state, and when the system is abnormal, the system abnormality can be found and corresponding processing can be carried out. The CPU utilization rate of the system is an important index of whether the real-time system operates normally or not, and can represent the time characteristic and task state of the system. Monitoring CPU utilization is an effective technique for monitoring system stability.
Most existing robot systems do not consider CPU usage data. When the robot works, due to certain anomalies or system design problems, the CPU utilization rate exceeds a certain threshold value, so that the CPU is busy and cannot respond to and process other tasks in real time, customer experience and the running effect of the robot are affected, and huge losses and disasters can be brought to lives and properties of people when serious conditions exist.
Aiming at the problem of poor monitoring effect on CPU usage rate in the related art, no effective solution is proposed at present.
Disclosure of Invention
The invention mainly aims to provide a monitoring method and device for an intelligent robot, which are used for solving the problem of poor monitoring effect on CPU (central processing unit) utilization rate.
To achieve the above object, according to one aspect of the present invention, there is provided a monitoring method of an intelligent robot, the method comprising: acquiring CPU utilization rate of the intelligent robot within a first preset time; determining the maximum value of CPU utilization rate of the intelligent robot within the first preset time; setting a preset threshold according to the maximum value of the CPU utilization rate, wherein the preset threshold is greater than or equal to the maximum value of the CPU utilization rate; monitoring the current CPU utilization rate of the intelligent robot at intervals of a second preset time, wherein the length of the first preset time is greater than or equal to the length of the second preset time; judging whether the current CPU utilization rate exceeds the preset threshold value; and outputting abnormal prompt information under the condition that the preset threshold value is exceeded.
Further, before monitoring the current CPU usage of the intelligent robot at every second preset time, the method further includes: acquiring the running period of each task in the tasks currently running by the intelligent robot; and calculating the least common multiple of all task operation periods, and taking the least common multiple as the second preset time.
Further, monitoring the current CPU utilization of the intelligent robot at intervals of a second preset time includes: the current CPU utilization rate of the intelligent robot is calculated through the formula CPU_usage=100- (T×100)/1000, wherein CPU_usage represents the CPU utilization rate, and T represents the execution time of idle tasks within 1 second.
Further, outputting the abnormality notification information includes at least one of: outputting prompt information through LED warning; outputting prompt information through voice warning; and reporting the system data output prompt information under the condition that the communication channel is effective.
Further, after outputting the abnormality prompt information when the preset threshold is exceeded, the method further includes: determining an abnormal level of the intelligent robot according to the current CPU utilization rate; under the condition that the abnormal level is the first level, continuously operating the task operated in the CPU of the intelligent robot; under the condition that the abnormal level is the second level, the control system of the intelligent robot is controlled to restart; and under the condition that the abnormal level is the third level, controlling a control system of the intelligent robot to be shut down.
In order to achieve the above object, according to another aspect of the present invention, there is also provided a monitoring device of an intelligent robot, the device comprising: the first acquisition unit is used for acquiring the CPU utilization rate of the intelligent robot within a first preset time; a determining unit, configured to determine a maximum value of a CPU usage rate of the intelligent robot within the first preset time; a setting unit, configured to set a preset threshold according to a maximum value of the CPU utilization, where the preset threshold is greater than or equal to the maximum value of the CPU utilization; the monitoring unit is used for monitoring the current CPU utilization rate of the intelligent robot at intervals of a second preset time, wherein the length of the first preset time is greater than or equal to that of the second preset time; the judging unit is used for judging whether the current CPU utilization rate exceeds the preset threshold value; and the output unit is used for outputting abnormal prompt information under the condition that the preset threshold value is exceeded.
Further, the apparatus further comprises: the second acquisition unit is used for acquiring the running period of each task in the tasks currently running by the intelligent robot before monitoring the current CPU utilization rate of the intelligent robot every second preset time; the calculating unit is used for calculating the least common multiple of all task operation periods and taking the least common multiple as the second preset time.
Further, the monitoring unit is configured to: the current CPU utilization rate of the intelligent robot is calculated through the formula CPU_usage=100- (T×100)/1000, wherein CPU_usage represents the CPU utilization rate, and T represents the execution time of idle tasks within 1 second.
In order to achieve the above object, according to another aspect of the present invention, there is also provided a storage medium including a stored program, wherein the device in which the storage medium is controlled to execute the monitoring method of the intelligent robot of the present invention when the program runs.
In order to achieve the above object, according to another aspect of the present invention, there is also provided a processor for running a program, wherein the program runs while executing the monitoring method of the intelligent robot of the present invention.
The CPU utilization rate of the intelligent robot in the first preset time is obtained; determining the maximum value of CPU utilization rate of the intelligent robot within a first preset time; setting a preset threshold according to the maximum value of the CPU utilization rate, wherein the preset threshold is larger than or equal to the maximum value of the CPU utilization rate; monitoring the current CPU utilization rate of the intelligent robot at intervals of a second preset time, wherein the length of the first preset time is greater than or equal to that of the second preset time; judging whether the current CPU utilization exceeds a preset threshold value; under the condition that the preset threshold value is exceeded, abnormal prompt information is output, the problem that the monitoring effect on the CPU utilization rate is poor is solved, and the monitoring effect on the CPU utilization rate is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:
Fig. 1 is a flowchart of a monitoring method of an intelligent robot according to a first embodiment of the present invention;
fig. 2 is a flowchart of a monitoring method of an intelligent robot according to a second embodiment of the present invention; and
Fig. 3 is a schematic view of a monitoring device of an intelligent robot according to an embodiment of the present invention.
Detailed Description
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate in order to describe the embodiments of the application herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The embodiment of the invention provides a monitoring method of an intelligent robot.
Fig. 1 is a flowchart of a monitoring method of an intelligent robot according to a first embodiment of the present invention, as shown in fig. 1, the method comprising the steps of:
Step S102: acquiring CPU utilization rate of the intelligent robot within a first preset time;
Step S104: determining the maximum value of CPU utilization rate of the intelligent robot within a first preset time;
Step S106: setting a preset threshold according to the maximum value of the CPU utilization rate, wherein the preset threshold is larger than or equal to the maximum value of the CPU utilization rate;
step S108: monitoring the current CPU utilization rate of the intelligent robot at intervals of a second preset time, wherein the length of the first preset time is greater than or equal to that of the second preset time;
step S110: judging whether the current CPU utilization exceeds a preset threshold value;
Step S112: and outputting abnormal prompt information under the condition that the preset threshold value is exceeded.
According to the embodiment, the CPU utilization rate of the intelligent robot in the first preset time is obtained; determining the maximum value of CPU utilization rate of the intelligent robot within a first preset time; setting a preset threshold according to the maximum value of the CPU utilization rate, wherein the preset threshold is larger than or equal to the maximum value of the CPU utilization rate; monitoring the current CPU utilization rate of the intelligent robot at intervals of a second preset time, wherein the length of the first preset time is greater than or equal to that of the second preset time; judging whether the current CPU utilization exceeds a preset threshold value; under the condition that the preset threshold value is exceeded, abnormal prompt information is output, the problem that the monitoring effect on the CPU utilization rate is poor is solved, and the monitoring effect on the CPU utilization rate is improved.
The technical scheme of the embodiment of the invention can be applied to robots of embedded real-time operating systems (including FreeRTOS), in the embodiment of the invention, when judging whether the CPU utilization rate is abnormal, a proper threshold value is required to be set according to the actual running condition of the system, the threshold value is set too low to cause the occurrence of false reminding of which the duration exceeds the threshold value, false alarm is caused, the reminding is not timely due to the too high threshold value, and adverse effect is caused, so that the proper threshold value is required to be set. In setting the threshold, the maximum value of the CPU utilization rate of the intelligent robot in the first preset time is required to be set, for example, the maximum value, for example, 50%, of the CPU utilization rate of the intelligent robot in the time length of at least one period can be obtained, then a value higher than the maximum value is set as the threshold, so as to perform fault tolerance, for example, 60% or 70%, and the specific threshold can be set and adjusted according to the requirement of an application scene or can be reset at regular intervals according to the use time. The second preset time can be preset, the CPU utilization rate of the intelligent robot is monitored every second preset time, the CPU utilization rate is also increased when the CPU utilization rate is monitored, so that the CPU utilization rate is monitored every second preset time instead of being monitored all the time, after the CPU utilization rate of the robot is monitored, whether the utilization rate exceeds the standard or not can be judged according to a preset threshold value, if the utilization rate exceeds the preset threshold value, the utilization rate exceeds the standard, the condition that the robot can not normally operate is indicated, the robot is out of control or has abnormal autonomous behaviors, and the normal work of the robot is influenced, so that prompt information is output when the CPU utilization rate is monitored to be abnormal, and a user can deal with or process the abnormal situation in time.
Optionally, before monitoring the current CPU utilization rate of the intelligent robot at intervals of a second preset time, acquiring the running period of each task in the tasks currently running by the intelligent robot; and calculating the least common multiple of all task operation periods, and taking the least common multiple as a second preset time.
The second preset time can be determined by the running periods of all tasks, and the least common multiple of the running periods of all tasks is taken as the second preset time to ensure that the highest value of the CPU utilization rate can be acquired within the second preset time range. The second preset time may also be twice or three times the least common multiple.
Optionally, monitoring the current CPU utilization of the intelligent robot at intervals of a second preset time includes: the current CPU utilization rate of the intelligent robot is calculated through the formula CPU_usage=100- (T×100)/1000, wherein CPU_usage represents the CPU utilization rate, and T represents the execution time of idle tasks within 1 second.
Calculating the current CPU utilization of the intelligent robot by the formula cpu_usage=100- (t×100)/1000 can enable the calculation of the CPU utilization of the robot to be more accurate.
Optionally, in the case that the preset threshold is exceeded, outputting the abnormality notification information includes at least one of: outputting prompt information through LED warning; outputting prompt information through voice warning; and reporting the system data output prompt information under the condition that the communication channel is effective.
If the current CPU utilization rate of the robot exceeds a preset threshold, prompt information can be sent out to prompt a user to process in time, the prompt mode is not limited, and for example, the prompt information can be output through LED warning; or outputting prompt information through voice warning; or reporting the detailed data of the system under the condition that the communication channel is effective, so that the user can know the abnormal situation in time, and the abnormal situation can be processed in time.
Optionally, after the prompt message is output under the condition that the preset threshold value is exceeded, determining the abnormal level of the intelligent robot according to the current CPU utilization rate; under the condition that the abnormal level is the first level, continuously operating the task operated in the CPU of the intelligent robot; under the condition that the abnormal level is the second level, the control system of the intelligent robot is controlled to restart; and under the condition that the abnormal level is the third level, controlling the control system of the intelligent robot to be shut down.
Besides prompting when the CPU utilization rate exceeds a preset threshold value, the abnormal grade can be further determined according to the CPU utilization rate, for example, the abnormal grade comprises a first grade, a second grade and a third grade, wherein the first grade is a general abnormality, the second grade is a serious abnormality, the third grade is a very serious abnormality, different treatments can be carried out according to different grades so as to further improve the intelligent degree of the system, for example, under the circumstance of the general abnormality, tasks are continuously operated, only prompting is sent, an operator control instruction is waited, under the circumstance of the serious abnormality, the system can be restarted and the operation is attempted to be continued after reset, and under the circumstance of the very serious abnormality, the system can be controlled to stop so as to avoid larger losses and damages. Optionally, the running data information can also be saved before restarting or stopping for later exception analysis.
The embodiment of the invention also provides a preferred implementation mode, and the technical scheme of the embodiment of the invention is explained below in combination with the preferred implementation mode.
Taking a real-time operating system FreeRTOS as an example, a real-time CPU utilization rate calculating function is added in the system, and the system is monitored and fault-tolerant. FreeRTOS is a lightweight real-time operating system, and is widely applied to the fields of medical appliances, network equipment, robots and the like.
The CPU utilization rate calculation formula of the embodiment of the invention is as follows:
Cpu_usage= (100- (execution time within 1 second of idle task x 100)/1000)
FreeRTOS do not support CPU utilization for a single task and therefore only overall CPU utilization for the system can be calculated.
The algorithm implementation principle: when the operation system runs, the operation system is continuously switched among different tasks, the task switching scheduling is driven by the system tick, and each time the system tick is generated, the system tick judges whether task switching (the task with the highest priority which is ready to run) is needed. Because the priority of the idle task is the lowest, the CPU utilization rate of the system can be calculated by counting the running time of the idle task in a certain time (1000 tick). Typically configured as 1 tick=1 ms and 1000 tick=1000 ms in FreeRTOS.
For a determined system, if each task in the system normally operates according to the running track designed by the developer, the execution time of each task is within a corresponding nominal range; the overall system run time will also be within nominal limits for the entire system. If the CPU usage of the system or some tasks is abnormal, namely the running time of the CPU usage is beyond the nominal range, the system is indicated to be wholly or some tasks in the system are abnormal, and fault-tolerant processing is needed.
CPU usage monitors cycles. The CPU utilization rate monitoring period is important to the monitoring effect, and the period is too long, so that the obtained data may be inaccurate; if the period is too short, the system resource waste is caused. To ensure reliability of the monitoring data, the frequency of the monitoring tasks is generally set to be equal to or greater than the maximum operating frequency of other tasks in the system; the operation frequency of the monitoring task can be properly reduced in the application occasions with low requirements.
And judging the CPU utilization rate abnormality. The embedded real-time system may be in different working modes in the whole operation process, and the different working modes have different CPU use rate abnormality judgment requirements. When the working mode is switched, the corresponding abnormality judgment standard is switched. In practical applications, the embedded real-time system is generally a multi-task system, the CPU utilization rate generated by task scheduling is in the form of a periodic curve, and the period is the least common multiple of the running period of all tasks. After monitoring the normal operation data of the system for a period of time, the CPU Usage curve for the period of time may be collected, and the actual cpu_usage_max (maximum CPU Usage) and cpu_usage_min (minimum CPU Usage) for the period of time may be obtained.
Fig. 2 is a flowchart of a monitoring method of an intelligent robot according to a second embodiment of the present invention, as shown in fig. 2, the method comprising the following processes:
After the monitoring task is started, the CPU utilization rate is obtained, the CPU utilization rate abnormality judgment is carried out, if no abnormality is judged, the CPU utilization rate is continuously monitored, if the CPU utilization rate abnormality is judged, the abnormality processing is carried out, if the CPU utilization rate abnormality is judged, the system is continuously operated, prompt information can be output to prompt a user to check the processing, if the abnormality is serious and the operation cannot be continuously carried out, the field data can be saved, and the system is restarted or related to carry out protection.
Taking a simple abnormality determination as an example, the maximum THRESHOLD value (cpu_usage_threshold_max) may be set according to the actual cpu_usage_max to perform fault tolerance determination. If cpu_usage_max < =20, cpu_usage_threshold_max may be configured to be 50; if 20< cpu_use_max < = 50, cpu_usage_threshold_max may be configured to be 70; if 50< cpu_use_max < = 70, cpu_usage_threshold_max may be configured to 80. Thus, a certain error redundancy space is given to the system, and timely processing is ensured when serious errors occur. When the CPU_usage_Max is larger than the CPU_usage_threshold_MAX, exception handling is performed. With the development of technology, the frequency of the CPU is higher and the processing capacity of the CPU is higher. Generally, when designing an embedded real-time system, a proper CPU should be selected, and the maximum CPU utilization rate should not exceed 70 when the system is in normal operation, so that the system is ensured to have certain redundancy and expansibility.
CPU utilization exception handling. The abnormal CPU usage of the embedded real-time system occurs in operation and may be caused by various reasons. From the perspective of hardware, there may be differences in the operation performance of hardware devices in different environments, and some devices fail in more serious cases; from the software perspective, unexpected operations, such as abnormal scheduling of tasks, abnormal transfer parameters, etc., may be performed during the running of the software. When the CPU usage is monitored to be abnormal, the reason for the abnormality is first actively analyzed. Telling operators of system anomaly data by various means, including but not limited to: LED alert, voice alert, reporting system details if the communication channel is active. Hierarchical processing according to severity of anomaly type: general exception-the system can continue to run, waiting for operator control instructions; serious anomaly-restart after system reset can attempt to continue running; extremely serious anomalies-the system shuts down immediately, avoiding greater losses and hazards. The system is stored in the field for post-hoc analysis prior to restarting or shutdown.
In the embodiment of the invention, the CPU utilization rate calculation is different according to the precision of different embedded systems, a non-easy memory is needed to be used for storing system field data and the like, and the system can still work under certain known abnormal conditions.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
The embodiment of the invention provides a monitoring device of an intelligent robot, which can be used for executing the monitoring method of the intelligent robot.
Fig. 3 is a schematic view of a monitoring device of an intelligent robot according to an embodiment of the present invention, as shown in fig. 3, the device includes:
a first obtaining unit 10, configured to obtain a CPU utilization rate of the intelligent robot within a first preset time;
a determining unit 20, configured to determine a maximum value of CPU usage of the intelligent robot within a first preset time;
A setting unit 30, configured to set a preset threshold according to a maximum value of the CPU utilization, where the preset threshold is greater than or equal to the maximum value of the CPU utilization;
A monitoring unit 40, configured to monitor a current CPU usage rate of the intelligent robot at intervals of a second preset time, where a length of the first preset time is greater than or equal to a length of the second preset time;
a judging unit 50 for judging whether the current CPU utilization exceeds a preset threshold;
and an output unit 60 for outputting the abnormality notification information if the preset threshold is exceeded.
The embodiment adopts a first obtaining unit 10 for obtaining the CPU utilization rate of the intelligent robot within a first preset time; a determining unit 20, configured to determine a maximum value of CPU usage of the intelligent robot within a first preset time; a setting unit 30, configured to set a preset threshold according to a maximum value of the CPU utilization, where the preset threshold is greater than or equal to the maximum value of the CPU utilization; a monitoring unit 40, configured to monitor a current CPU usage rate of the intelligent robot at intervals of a second preset time, where a length of the first preset time is greater than or equal to a length of the second preset time; a judging unit 50 for judging whether the current CPU utilization exceeds a preset threshold; the output unit 60 is configured to output an abnormal prompt message when the preset threshold is exceeded, so that the problem of poor monitoring effect on the CPU utilization rate is solved, and the monitoring effect on the CPU utilization rate is further improved.
Optionally, the apparatus further comprises: the second acquisition unit is used for acquiring the running period of each task in the tasks currently running by the intelligent robot before monitoring the current CPU utilization rate of the intelligent robot every second preset time; the calculating unit is used for calculating the least common multiple of all task operation periods and taking the least common multiple as a second preset time.
Optionally, the monitoring unit 40 is configured to: the current CPU utilization rate of the intelligent robot is calculated through the formula CPU_usage=100- (T×100)/1000, wherein CPU_usage represents the CPU utilization rate, and T represents the execution time of the idle task within 1 second.
The embodiment of the invention can be used for real-time monitoring of embedded software in the robot, avoids out-of-control or autonomous behavior abnormality of the robot caused by system failure due to overhigh CPU utilization rate, ensures normal operation of the robot and provides better use experience for users.
The intelligent robot monitoring device comprises a processor and a memory, wherein the monitoring unit, the judging unit, the output unit and the like are all stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor includes a kernel, and the kernel fetches the corresponding program unit from the memory. The kernel can be provided with one or more than one, and the monitoring effect on the CPU utilization rate is improved by adjusting the kernel parameters.
The memory may include volatile memory, random Access Memory (RAM), and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), among other forms in computer readable media, the memory including at least one memory chip.
The embodiment of the invention provides a storage medium, wherein a program is stored on the storage medium, and the program is executed by a processor to realize the monitoring method of the intelligent robot.
The embodiment of the invention provides a processor which is used for running a program, wherein the monitoring method of the intelligent robot is executed when the program runs.
The embodiment of the invention provides equipment, which comprises a processor, a memory and a program stored in the memory and capable of running on the processor, wherein the processor realizes the following steps when executing the program: acquiring CPU utilization rate of the intelligent robot within a first preset time; determining the maximum value of CPU utilization rate of the intelligent robot within a first preset time; setting a preset threshold according to the maximum value of the CPU utilization rate, wherein the preset threshold is larger than or equal to the maximum value of the CPU utilization rate; monitoring the current CPU utilization rate of the intelligent robot at intervals of a second preset time, wherein the length of the first preset time is greater than or equal to that of the second preset time; judging whether the current CPU utilization exceeds a preset threshold value; and outputting abnormal prompt information under the condition that the preset threshold value is exceeded. The device herein may be a server, PC, PAD, cell phone, etc.
The application also provides a computer program product adapted to perform, when executed on a data processing device, a program initialized with the method steps of: acquiring CPU utilization rate of the intelligent robot within a first preset time; determining the maximum value of CPU utilization rate of the intelligent robot within a first preset time; setting a preset threshold according to the maximum value of the CPU utilization rate, wherein the preset threshold is larger than or equal to the maximum value of the CPU utilization rate; monitoring the current CPU utilization rate of the intelligent robot at intervals of a second preset time, wherein the length of the first preset time is greater than or equal to that of the second preset time; judging whether the current CPU utilization exceeds a preset threshold value; and outputting abnormal prompt information under the condition that the preset threshold value is exceeded.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (8)
1. The monitoring method of the intelligent robot is characterized by comprising the following steps of:
acquiring CPU utilization rate of the intelligent robot within a first preset time;
determining the maximum value of CPU utilization rate of the intelligent robot within the first preset time;
Setting a preset threshold according to the maximum value of the CPU utilization rate, wherein the preset threshold is greater than or equal to the maximum value of the CPU utilization rate;
Monitoring the current CPU utilization rate of the intelligent robot at intervals of a second preset time, including: calculating the current CPU utilization rate of the intelligent robot through a formula CPU_usage=100- (T x 100)/1000, wherein CPU_usage represents the CPU utilization rate, T represents the execution time of idle tasks within 1 second, and the length of the first preset time is greater than or equal to the length of the second preset time;
judging whether the current CPU utilization rate exceeds the preset threshold according to an abnormality judgment standard corresponding to the current working mode;
Outputting abnormal prompt information under the condition that the preset threshold value is exceeded, and determining the abnormal level of the intelligent robot according to the current CPU utilization rate; and under the condition that the abnormal level is the second level, storing the current data and controlling the control system of the intelligent robot to restart.
2. The method of claim 1, wherein prior to monitoring the current CPU usage of the intelligent robot at every second preset time, the method further comprises:
acquiring the running period of each task in the tasks currently running by the intelligent robot;
and calculating the least common multiple of all task operation periods, and taking the least common multiple as the second preset time.
3. The method of claim 1, wherein outputting an anomaly prompt message if the preset threshold is exceeded comprises at least one of:
Outputting prompt information through LED warning;
Outputting prompt information through voice warning;
And reporting the system data output prompt information under the condition that the communication channel is effective.
4. The method of claim 1, wherein said determining an anomaly level of the intelligent robot based on the current CPU utilization comprises:
under the condition that the abnormal level is the first level, continuously operating the task operated in the CPU of the intelligent robot;
And under the condition that the abnormal level is the third level, controlling a control system of the intelligent robot to be shut down.
5. An intelligent robot's monitoring devices, characterized in that includes:
the first acquisition unit is used for acquiring the CPU utilization rate of the intelligent robot within a first preset time;
a determining unit, configured to determine a maximum value of a CPU usage rate of the intelligent robot within the first preset time;
a setting unit, configured to set a preset threshold according to a maximum value of the CPU utilization, where the preset threshold is greater than or equal to the maximum value of the CPU utilization;
The monitoring unit is used for monitoring the current CPU utilization rate of the intelligent robot at intervals of a second preset time, and comprises:
Calculating the current CPU utilization rate of the intelligent robot through a formula CPU_usage=100- (T x 100)/1000, wherein CPU_usage represents the CPU utilization rate, T represents the execution time of idle tasks within 1 second, and the length of the first preset time is greater than or equal to the length of the second preset time;
the judging unit is used for judging whether the current CPU utilization rate exceeds the preset threshold value according to an abnormality judging standard corresponding to the working mode;
The output unit is used for outputting abnormal prompt information under the condition that the preset threshold value is exceeded, and determining the abnormal grade of the intelligent robot according to the current CPU utilization rate; and under the condition that the abnormal level is the second level, storing the current data and controlling the control system of the intelligent robot to restart.
6. The apparatus of claim 5, wherein the apparatus further comprises:
the second acquisition unit is used for acquiring the running period of each task in the tasks currently running by the intelligent robot before monitoring the current CPU utilization rate of the intelligent robot every second preset time;
The calculating unit is used for calculating the least common multiple of all task operation periods and taking the least common multiple as the second preset time.
7. A storage medium comprising a stored program, wherein the program, when run, controls a device in which the storage medium is located to perform the method of monitoring the intelligent robot of any one of claims 1 to 4.
8. A processor, characterized in that the processor is adapted to run a program, wherein the program, when run, performs the method of monitoring the intelligent robot according to any of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711378624.7A CN109933487B (en) | 2017-12-19 | 2017-12-19 | Intelligent robot monitoring method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711378624.7A CN109933487B (en) | 2017-12-19 | 2017-12-19 | Intelligent robot monitoring method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109933487A CN109933487A (en) | 2019-06-25 |
| CN109933487B true CN109933487B (en) | 2024-05-07 |
Family
ID=66984056
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711378624.7A Active CN109933487B (en) | 2017-12-19 | 2017-12-19 | Intelligent robot monitoring method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109933487B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114330769A (en) * | 2021-12-24 | 2022-04-12 | 深圳优地科技有限公司 | Robot fault early warning method and device, robot and server |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101178688A (en) * | 2007-11-29 | 2008-05-14 | 中兴通讯股份有限公司 | CPU occupancy rate detection method and system of system task |
| CN103178990A (en) * | 2011-12-20 | 2013-06-26 | 中国移动通信集团青海有限公司 | Network device performance monitoring method and network management system |
| CN104156266A (en) * | 2014-08-14 | 2014-11-19 | 黑龙江大学 | Method for determining real-time task or event schedulability test minimum interval |
| CN104503887A (en) * | 2014-12-15 | 2015-04-08 | 北京奇虎科技有限公司 | Method and device for showing state of computing equipment |
| CN105262634A (en) * | 2015-09-06 | 2016-01-20 | 浪潮集团有限公司 | Monitoring threshold generation method, device and system |
| AU2016202814A1 (en) * | 2015-08-21 | 2017-03-09 | Wisetech Global Limited | Systems and methods for managing cpu usage during qualitatively assessment of task data |
| CN106649054A (en) * | 2016-12-29 | 2017-05-10 | 郑州云海信息技术有限公司 | Resource alarming method and device |
| CN106713029A (en) * | 2016-12-20 | 2017-05-24 | 中国银联股份有限公司 | Method and apparatus for determining resource monitoring thresholds |
| CN107368402A (en) * | 2017-07-10 | 2017-11-21 | 中国第汽车股份有限公司 | The method for calculating cpu busy percentage |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002099432A (en) * | 2000-09-22 | 2002-04-05 | Sony Corp | System of computing processing, control method thereof, system for task control, method therefor and record medium |
-
2017
- 2017-12-19 CN CN201711378624.7A patent/CN109933487B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101178688A (en) * | 2007-11-29 | 2008-05-14 | 中兴通讯股份有限公司 | CPU occupancy rate detection method and system of system task |
| CN103178990A (en) * | 2011-12-20 | 2013-06-26 | 中国移动通信集团青海有限公司 | Network device performance monitoring method and network management system |
| CN104156266A (en) * | 2014-08-14 | 2014-11-19 | 黑龙江大学 | Method for determining real-time task or event schedulability test minimum interval |
| CN104503887A (en) * | 2014-12-15 | 2015-04-08 | 北京奇虎科技有限公司 | Method and device for showing state of computing equipment |
| AU2016202814A1 (en) * | 2015-08-21 | 2017-03-09 | Wisetech Global Limited | Systems and methods for managing cpu usage during qualitatively assessment of task data |
| CN105262634A (en) * | 2015-09-06 | 2016-01-20 | 浪潮集团有限公司 | Monitoring threshold generation method, device and system |
| CN106713029A (en) * | 2016-12-20 | 2017-05-24 | 中国银联股份有限公司 | Method and apparatus for determining resource monitoring thresholds |
| CN106649054A (en) * | 2016-12-29 | 2017-05-10 | 郑州云海信息技术有限公司 | Resource alarming method and device |
| CN107368402A (en) * | 2017-07-10 | 2017-11-21 | 中国第汽车股份有限公司 | The method for calculating cpu busy percentage |
Non-Patent Citations (4)
| Title |
|---|
| QoS based dynamic task scheduling in IaaS cloud;Anbazhagi等;IEEE;全文 * |
| RTEMS CPU利用率的研究与实现;刘立娟;;大众科技(第08期);全文 * |
| 一种VxWorks系统CPU利用率图形化显示方法的设计与实现;崔娟;;电子世界(第18期);全文 * |
| 大型物联网设备中智能嵌入式监测系统设计;田建立;李立;;现代电子技术(第24期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109933487A (en) | 2019-06-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110661659B (en) | Alarm method, device and system and electronic equipment | |
| US10558544B2 (en) | Multiple modeling paradigm for predictive analytics | |
| US9720761B2 (en) | System fault detection and processing method, device, and computer readable storage medium | |
| EP1394643B1 (en) | method and apparatus for active resource monitoring in a numerical control process | |
| US20100043004A1 (en) | Method and system for computer system diagnostic scheduling using service level objectives | |
| WO2012072363A1 (en) | A method computer program and system to optimize memory management of an application running on a virtual machine | |
| CN104778111A (en) | Alarm method and alarm device | |
| EP2955632B1 (en) | Determining and correcting software server error conditions | |
| EP3522018B1 (en) | Identification of a soft failure at a member | |
| JP2004326386A (en) | Evaluation support device, evaluation support method and evaluation support program | |
| CN110826075A (en) | PLC dynamic measurement method, device, system, storage medium and electronic equipment | |
| CN105279037A (en) | Watchdog monitoring method and system | |
| CN113672345A (en) | IO prediction-based cloud virtualization engine distributed resource scheduling method | |
| CN109933487B (en) | Intelligent robot monitoring method and device | |
| CN109766198B (en) | Stream processing method, device, equipment and computer readable storage medium | |
| Di Sanzo et al. | Machine learning for achieving self-* properties and seamless execution of applications in the cloud | |
| CN113590285A (en) | Method, system and equipment for dynamically setting thread pool parameters | |
| JP6504610B2 (en) | Processing device, method and program | |
| US8620621B2 (en) | Maintenance of intelligent assets | |
| Warriach et al. | Self-* properties in smart environments: Requirements and performance metrics | |
| CN116155766A (en) | Method and equipment for evaluating quality of park network | |
| CN115686831A (en) | Task processing method and device based on distributed system, equipment and medium | |
| KR102418892B1 (en) | Method of saving energy based on confidence interval and apparatus using the same | |
| CN111813073B (en) | Node early warning method and device | |
| WO2024000498A1 (en) | Industrial control system, edge device, cloud server, apparatus, and method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20240408 Address after: No. 816 Xinjian Street, Rixing Town, Yilong County, Nanchong City, Sichuan Province, 637600 Applicant after: Pan Mingxu Country or region after: China Address before: 518000 Guangdong, Shenzhen, Nanshan District, Nanhai Road, West Guangxi Temple Road North Sunshine Huayi Building 1 15D-02F Applicant before: SHEN ZHEN KUANG-CHI HEZHONG TECHNOLOGY Ltd. Country or region before: China |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |