WO2021102838A1 - 确定采集频率的方法、装置、计算设备和存储介质 - Google Patents

确定采集频率的方法、装置、计算设备和存储介质 Download PDF

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Publication number
WO2021102838A1
WO2021102838A1 PCT/CN2019/121720 CN2019121720W WO2021102838A1 WO 2021102838 A1 WO2021102838 A1 WO 2021102838A1 CN 2019121720 W CN2019121720 W CN 2019121720W WO 2021102838 A1 WO2021102838 A1 WO 2021102838A1
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Prior art keywords
frequency
state
equipment
working
time
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PCT/CN2019/121720
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English (en)
French (fr)
Inventor
张亮
孙维
王洋
胡黎红
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西门子股份公司
西门子(中国)有限公司
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Application filed by 西门子股份公司, 西门子(中国)有限公司 filed Critical 西门子股份公司
Priority to EP19954495.8A priority Critical patent/EP4050487A4/en
Priority to CN201980101661.4A priority patent/CN114600089A/zh
Priority to US17/781,222 priority patent/US20230004475A1/en
Priority to PCT/CN2019/121720 priority patent/WO2021102838A1/zh
Publication of WO2021102838A1 publication Critical patent/WO2021102838A1/zh

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/30Monitoring
    • G06F11/3003Monitoring arrangements specially adapted to the computing system or computing system component being monitored
    • G06F11/3013Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is an embedded system, i.e. a combination of hardware and software dedicated to perform a certain function in mobile devices, printers, automotive or aircraft systems
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/30Monitoring
    • G06F11/34Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3466Performance evaluation by tracing or monitoring
    • G06F11/3476Data logging
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/30Monitoring
    • G06F11/3003Monitoring arrangements specially adapted to the computing system or computing system component being monitored
    • G06F11/3006Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/30Monitoring
    • G06F11/3065Monitoring arrangements determined by the means or processing involved in reporting the monitored data
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/30Monitoring
    • G06F11/3089Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents
    • G06F11/3096Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents wherein the means or processing minimize the use of computing system or of computing system component resources, e.g. non-intrusive monitoring which minimizes the probe effect: sniffing, intercepting, indirectly deriving the monitored data from other directly available data

Definitions

  • the present disclosure generally relates to the technical field of the Internet of Things, and more specifically, to a method, an apparatus, a computing device, and a storage medium for determining the acquisition frequency.
  • Digitization is a trend in the manufacturing industry. Digitalization related to equipment is an important application in factories, especially cloud-based applications, such as equipment status monitoring, OEE (Overall Equipment Effectiveness), fault diagnosis, and predictive maintenance. Therefore, how to efficiently collect the effective field data of the equipment becomes the key to a successful digital solution, for example, at what frequency should the data be collected from the equipment.
  • OEE Old Equipment Effectiveness
  • the present disclosure provides an adaptive method for setting an appropriate data collection frequency for the device.
  • the requirements of the application and the state of the device are considered to determine the appropriate data collection frequency for the device.
  • the acquisition frequency can be automatically adjusted based on the real-time situation of the equipment.
  • a method for determining the frequency of data collection wherein the data is collected from a device and provided to an application program for the application program to monitor the device, and the method includes: determining The application program’s data collection frequency requirements for the equipment; determine the status information of the equipment; and based on the determined application program’s data collection frequency requirements for the equipment and the determined equipment status information, determine the data collection according to preset rules frequency.
  • the frequency requirements of the application for the collection of data from the device include at least one of the following: the application itself has a requirement for the collection frequency; in different states of the device, the application The demand for the acquisition frequency; and the application's demand for the acquisition frequency at different times.
  • the requirements of the application program for the collection frequency include: preferred collection frequency, minimum collection frequency, and zero frequency; the different states of the device include: working state, idle state, fault state, The maintenance status and the maintenance status have corresponding preferred collection frequency, minimum collection frequency, and zero frequency for each status of the equipment; and the time includes working time, non-working time, and all day, and has corresponding values for different times.
  • the preferred acquisition frequency, minimum acquisition frequency and zero frequency are examples of the preferred acquisition frequency, minimum acquisition frequency and zero frequency.
  • the status information of the device includes at least one of the following: working status of the device; planned working time and non-working time of the device; device performance indicators; and hardware information.
  • the working state of the device includes at least one of the following: working state, idle state, fault state, maintenance state, and maintenance state;
  • the equipment performance index includes at least one of the following Items: CPU usage, memory usage, input/output reading time, and CPU temperature;
  • the hardware information includes at least one of the following: a version of the CPU and a version of the memory.
  • the real-time performance parameter includes at least one of the following: real-time central processing unit usage rate, memory occupancy rate, network load, and response time of the device.
  • a device for determining the frequency of data collection wherein the data is collected from a device and provided to an application program for the application program to monitor the device, and the device includes : A collection frequency requirement determination unit configured to determine the collection frequency requirement of the application for the data of the device; the device status determination unit is configured to determine the status information of the device; and the collection frequency determination unit is configured to be based on the determined application
  • the program determines the data collection frequency requirements of the equipment and the determined status information of the equipment according to the preset rules.
  • the device for determining the data collection frequency further includes: a collection frequency adjustment unit configured to receive real-time performance parameters of the device, and determine whether adjustment is required according to the real-time performance parameters The acquisition frequency.
  • the frequency requirements of the application for the collection of data from the device include at least one of the following: the application itself has a requirement for the collection frequency; in different states of the device, the application The demand for the acquisition frequency; and the application's demand for the acquisition frequency at different times.
  • the application itself’s requirements for collection frequency include: preferred collection frequency, minimum collection frequency, and zero frequency; the different states of the device include: working status, idle status, fault status, and maintenance status And the maintenance state, for each state of the equipment, there are corresponding preferred collection frequency, minimum collection frequency and zero frequency; and the time includes working time, non-working time and all day, and has corresponding preferences for different times. Acquisition frequency, minimum acquisition frequency and zero frequency.
  • the status information of the device includes at least one of the following: working status of the device; planned working time and non-working time of the device; device performance indicators; and hardware information.
  • the working state of the device includes at least one of the following: working state, idle state, fault state, maintenance state, and maintenance state;
  • the equipment performance index includes at least one of the following Items: CPU usage, memory usage, input/output reading time, and CPU temperature;
  • the hardware information includes at least one of the following: a version of the central processing unit and a version of the memory.
  • the real-time performance parameter includes at least one of the following: real-time central processing unit usage rate, memory occupancy rate, network load, and response time of the device.
  • a computing device including: at least one processor; and a memory coupled with the at least one processor, the memory is used to store instructions, when the instructions are used by the at least one When the processor executes, the processor is caused to execute the method as described above.
  • a non-transitory machine-readable storage medium which stores executable instructions that, when executed, cause the machine to perform the method as described above.
  • a computer program including computer-executable instructions that, when executed, cause at least one processor to perform the method as described above.
  • a computer program product that is tangibly stored on a computer-readable medium and includes computer-executable instructions that, when executed, cause at least A processor executes the method described above.
  • the requirements of the application program can be met as much as possible while ensuring the normal operation of the device, and the interference to the normal operation of the device caused by data collection can be avoided.
  • the collection of invalid data can be avoided, so as to reduce the amount of collected data, thereby saving the cost of data communication, storage, and processing.
  • FIG. 1 is a flowchart showing an exemplary process of a method for determining a collection frequency of data according to an embodiment of the present disclosure
  • FIG. 2 is a block diagram showing an exemplary configuration of an apparatus for determining a collection frequency of data according to an embodiment of the present disclosure
  • FIG. 3 is a block diagram showing an exemplary configuration of an information processing system according to an embodiment of the present disclosure.
  • FIG. 4 shows a block diagram of a computing device that configures priority for data according to an embodiment of the present disclosure.
  • Device for determining the frequency of data collection 202 Unit for determining the frequency of collection
  • Equipment status determination unit 206 Acquisition frequency determination unit
  • Collection frequency adjustment unit 300 Information processing system
  • Equipment 304 Cloud platform
  • Gateway 400 Computing equipment
  • the term “including” and its variations mean open terms, meaning “including but not limited to”.
  • the term “based on” means “based at least in part on.”
  • the terms “one embodiment” and “an embodiment” mean “at least one embodiment.”
  • the term “another embodiment” means “at least one other embodiment.”
  • the terms “first”, “second”, etc. may refer to different or the same objects. Other definitions can be included below, whether explicit or implicit. Unless clearly indicated in the context, the definition of a term is consistent throughout the specification.
  • the present disclosure provides an adaptive method for setting an appropriate data collection frequency for the device.
  • the requirements of the application and the state of the device are considered to determine the appropriate data collection frequency for the device.
  • the acquisition frequency can be automatically adjusted based on the real-time situation of the equipment.
  • the requirements of the application program can be met as much as possible while ensuring the normal operation of the device.
  • This method greatly reduces the workload and complexity of configuring data collection solutions for thousands of devices, reduces the amount of invalid data, and at the same time ensures normal production activities.
  • FIG. 1 is a flowchart showing an exemplary process of a method 100 for determining a collection frequency of data according to an embodiment of the present disclosure.
  • the determined application program's data collection frequency requirement may include the following specific conditions.
  • the first is the requirement of the application itself for the acquisition frequency determined by the function of the application.
  • the requirements for the collection frequency of the application itself may include a preferred collection frequency, a minimum collection frequency, and a zero frequency.
  • the preferred acquisition frequency is the optimal frequency for the application, and the preferred acquisition frequency is used as long as the control system of the device can afford it.
  • the minimum acquisition frequency is used when the control system of the device is busy with normal work and cannot share resources with the data acquisition function. If the control system of the equipment cannot withstand the minimum acquisition frequency, you should try to further reduce the acquisition frequency to ensure normal production.
  • Zero frequency means that no data acquisition is required.
  • vibration data, current data, etc. require a high sampling frequency to meet the needs of subsequent data analysis; in a scene where the equipment status is transparent, high-frequency sampling is not required, usually 1Hz The sampling can meet the need for transparency of the on-site equipment status; for the energy consumption collection scenario, the current energy consumption can be obtained every hour, and even larger sampling periods can meet the needs of energy management. Data like energy consumption, You can choose to collect the equipment when it is not in production, so as not to affect the normal operation of the equipment.
  • the different states of the equipment can include: working state, idle state, fault state, maintenance state, maintenance state, and so on.
  • applications may have different data collection frequency requirements.
  • the collection frequency should be lower, and when the device is switched to working mode, the collection frequency should become higher; and for predictable maintenance applications, when the device is idle Or in maintenance mode, you may not need to collect data.
  • the data collection frequency can be greatly reduced, so as to save the cost of data communication, storage and processing. Therefore, for each state of the device, the corresponding preferred acquisition frequency, minimum acquisition frequency, and zero frequency can also be set separately. For example, when the device is in the “working state”, one of the preferred collection frequency, the minimum collection frequency and the zero frequency set for the “working state” can also be selected for data collection according to the specific working conditions of the device.
  • different working hours may be defined in the factory, including working hours, non-working hours, and 24 hours a day (such as morning shift, mid shift, and evening shift).
  • Different data collection frequencies can also be set for different times. For example, the acquisition frequency during non-working hours should be set smaller.
  • the status information of the equipment comes from, for example, the equipment on the factory site, or it is obtained from a third-party system.
  • the device information may include, for example, the following items: working status of the device; working time and non-working time of the device; device performance indicators; and hardware information, etc.
  • the working state of the device may be, for example, working state, idle state, fault state, maintenance state, maintenance state, and so on.
  • Device performance indicators include, for example, CPU usage, RAM usage, I/O reading time, and CPU temperature.
  • an experienced engineer can pre-set the threshold used to evaluate the equipment performance index, or an automatic evaluation method, such as measuring the response time of the control system of the equipment, to evaluate the performance of the equipment .
  • the hardware information may include: CPU version, memory version, etc. Using hardware information, the acquisition frequency of one device can be used as a reference for other similar devices.
  • the status information of the device is not limited to the above, and those skilled in the art can also consider other device status information that affects the data collection frequency when using the method according to the present disclosure to determine the data collection frequency, which will not be described in detail here. .
  • the data collection frequency is determined according to a preset rule.
  • the preset rules here may include, for example: the collection frequency should at least meet the minimum requirements for implementing the functions of the application; the collection frequency should not be too frequent to avoid excessive costs in the process of data transmission, storage, processing, and visualization; and the collection frequency It should avoid affecting the working performance of the equipment; different acquisition frequencies can be generated for different equipment states; for equipment with different hardware and software, the corresponding acquisition frequency can be customized.
  • appropriate rules can be set in advance by those skilled in the art based on experience, and are not limited to the preset rules described above, and then can be based on the determined application program’s data collection frequency requirements and requirements for the device.
  • the status information of the determined device automatically calculates the appropriate data collection frequency for the device.
  • the method 100 for determining the data collection frequency may further include the operation in block S108, collecting real-time performance parameters of the device, and determining whether the collection frequency needs to be adjusted according to the real-time performance parameters.
  • real-time performance parameters such as real-time CPU usage, RAM usage, network load, and response speed of the device can be collected.
  • a threshold can be set in advance, and the performance status of the device can be determined by comparing with the threshold, so that it is indeed necessary to adjust the acquisition frequency.
  • a test instruction can be sent to the device periodically, and then the response time of the device can be used to determine whether the response speed of the device is slow. For this method, a large number of tests can be performed automatically, and then the test data can be analyzed through self-learning methods to determine the threshold.
  • the data collection frequency determined by the method of the present disclosure can be provided, for example, to a gateway responsible for data collection, and the gateway performs data collection according to the determined data collection frequency, and provides it to a corresponding application program.
  • the method according to the present disclosure can monitor the usage of the device in real time. For example, when the device runs slowly, the collection frequency can be automatically reduced, and the updated collection frequency can be sent to the gateway. For different devices, there is no need to distinguish between them.
  • a balance can be made between the requirements and the actual conditions based on the requirements of the application program and the operating conditions of the field devices.
  • the requirements of the application program can be met as much as possible while ensuring the normal operation of the device, and the interference to the normal operation of the device caused by data collection can be avoided.
  • the method for determining the data collection frequency of the present disclosure high requirements for configuration personnel can be avoided, and the workload and complexity of setting an appropriate data collection frequency can be reduced, especially when there are hundreds of different types of equipment .
  • the collection of invalid data can be avoided, so as to reduce the amount of collected data, thereby saving the cost of data communication, storage, and processing.
  • FIG. 2 is a block diagram showing an exemplary configuration of an apparatus 200 for determining a collection frequency of data according to an embodiment of the present disclosure.
  • the device 200 for determining the collection frequency of data includes: a collection frequency requirement determination unit 202, an equipment state determination unit 204, and a collection frequency determination unit 206.
  • the collection frequency requirement determination unit 202 is configured to determine the collection frequency requirement of the application program for the data of the device.
  • the device state determining unit 204 is configured to determine state information of the device.
  • the collection frequency determination unit 206 is configured to determine the data collection frequency based on the determined application program's data collection frequency requirements for the device and the determined state information of the device, according to a preset rule.
  • the device 200 for determining the data collection frequency may further include: a collection frequency adjustment unit 208 configured to receive real-time performance parameters of the device, and determine whether it is necessary or not according to the real-time performance parameters. Adjust the acquisition frequency.
  • a collection frequency adjustment unit 208 configured to receive real-time performance parameters of the device, and determine whether it is necessary or not according to the real-time performance parameters. Adjust the acquisition frequency.
  • the requirements of the application program for the collection frequency of device data include at least one of the following: the application program's requirements for the collection frequency; the application program's requirements for the collection frequency in different states of the device; and at different times , The application's requirements for the acquisition frequency.
  • the requirements of the application program for the collection frequency include: preferred collection frequency, minimum collection frequency and zero frequency; the different states of the equipment include: working state, idle state, fault state, repair state and maintenance state, for each type of equipment
  • the states respectively have corresponding preferred acquisition frequency, minimum acquisition frequency, and zero frequency; and the time includes working time, non-working time, and all day, and has corresponding preferred acquisition frequency, minimum acquisition frequency, and zero frequency for different times.
  • the status information of the device includes at least one of the following: working status of the device; planned working time and non-working time of the device; equipment performance indicators; and hardware information.
  • the working state of the device includes at least one of the following: working state, idle state, fault state, maintenance state, and maintenance state;
  • the equipment performance index includes at least one of the following: CPU usage rate, memory occupation Rate, input/output reading time, and CPU temperature;
  • the hardware information includes at least one of the following: a version of the CPU and a version of the memory.
  • the real-time performance parameters include at least one of the following: real-time central processing unit usage rate, memory occupancy rate, network load, and device response time.
  • the structure of the device 200 for determining the data collection frequency shown in FIG. 2 and its constituent units are only exemplary, and those skilled in the art can modify the structure block diagram shown in FIG. 2 as needed.
  • the details of the operations and functions of the various parts of the device 200 for determining the data collection frequency may be, for example, the same as or similar to the relevant parts of the embodiment of the method 100 for determining the data collection frequency of the present disclosure described with reference to FIG. Detailed Description.
  • FIG. 3 is a block diagram showing an exemplary configuration of an information processing system 300 according to an embodiment of the present disclosure.
  • the information processing system 300 includes a field device 302, a cloud platform 304, a device 200 for determining the frequency of data collection set on the cloud platform 304, and a gateway 306.
  • the device 200 for determining the data collection frequency set on the cloud platform 304 can use the method for determining the data collection frequency described above with reference to FIG. 1 to determine the data collection frequency to be performed by the device 302.
  • the apparatus 200 may provide the determined data collection frequency to the gateway 306, and then the gateway 306 performs data collection from the device 302 according to the determined data collection frequency, and provides it to the required application.
  • the gateway 306 may also collect the real-time performance parameters of the device and provide them to the device 200 for determining the data collection frequency, so that the device 200 can determine whether the collection frequency needs to be adjusted according to the real-time performance parameters.
  • the information processing system 300 shown in FIG. 3 is only a specific application example in which the method for determining the frequency of data collection according to the present disclosure is applied. It can be understood that the device 200 for determining the frequency of data collection according to the present disclosure is not necessarily set on the cloud platform 304, but may also be set on any appropriate place such as a local server. In addition, the determined data collection frequency does not have to be provided to the gateway, but can also be provided to other third-party applications.
  • the method, device, and information processing system for determining the frequency of data collection are described.
  • the above-mentioned device for determining the frequency of data collection can be implemented by hardware, or by software or a combination of hardware and software.
  • FIG. 4 shows a block diagram of a computing device 400 for determining the collection frequency of data according to an embodiment of the present disclosure.
  • the computing device 400 may include at least one processor 402, which executes at least one computer-readable instruction stored or encoded in a computer-readable storage medium (ie, the memory 404) (ie, the above-mentioned in the form of software) Implemented elements).
  • computer-executable instructions are stored in the memory 404, which, when executed, cause at least one processor 402 to complete the following actions: determine the frequency requirements of the application for data collection of the device; determine the state information of the device; and The determined application program's data collection frequency requirements for the device and the determined status information of the device determine the data collection frequency according to a preset rule.
  • a non-transitory machine-readable medium may have machine-executable instructions (that is, the above-mentioned elements implemented in the form of software), which when executed by a machine, cause the machine to execute the various embodiments of the present disclosure in conjunction with FIGS. 1-3.
  • machine-executable instructions that is, the above-mentioned elements implemented in the form of software
  • a computer program including computer-executable instructions, which when executed, cause at least one processor to execute each of the above described in conjunction with FIGS. 1-3 in the various embodiments of the present disclosure.
  • a computer program product including computer-executable instructions, which when executed, cause at least one processor to execute the above described in conjunction with FIGS. 1-3 in the various embodiments of the present disclosure.

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Abstract

确定采集频率的方法、装置、计算设备和存储介质。确定数据的采集频率的方法,其中,数据从设备采集并提供给应用程序,以供应用程序对设备进行监控,该方法包括:确定应用程序对设备的数据的采集频率需求;确定设备的状态信息;以及基于所确定的应用程序对设备的数据的采集频率需求和所确定的设备的状态信息,根据预设规则来确定数据的采集频率。

Description

确定采集频率的方法、装置、计算设备和存储介质 技术领域
本公开通常涉及物联网技术领域,更具体地,涉及确定采集频率的方法、装置、计算设备和存储介质。
背景技术
数字化是制造工业的趋势。与设备有关的数字化是工厂中的一个重要应用,尤其是基于云的应用程序,例如设备状态监控、OEE(Overall Equipment Effectiveness,总体设备效能)、故障诊断、预见性维护等。因此,如何高效地采集设备的有效现场数据成为成功的数字化解决方案的关键,例如,应该以什么样的频率来从设备采集数据。
目前,在工厂中使用越来越多的设备,设备的类型也是多种多样的。即使对于一种类型的设备,由于不同的购买日期和不同的硬件和软件版本,硬件和控制系统的性能彼此也是非常不同的。因此,针对一个设备如何设置适当的数据采集频率成为一项复杂的工作,并且需要非常专业的技术人员来决定。
随着云上的应用程序变得越来越普遍,情况变得更糟糕。因为云应用程序的提供者/开发者关于现场设备的真实状态了解的更少。如果他们在不考虑设备的类型、硬件和软件的版本、或者设备的工作负荷等情况下,对设备采用统一的数据采集频率,那么高频率的数据采集将可能导致较低的生产效率、较高的不合格产品率,甚至导致设备损坏。
目前,通常基于应用程序、现场测试或者经验,来对一个设备设置固定的数据采集频率,这需要大量的工作和经验非常丰富的工程师。另外,需要基于试错法,例如不合格产品率变得更高、设备变得更慢等,来调整采集频率。
发明内容
在下文中给出关于本发明的简要概述,以便提供关于本发明的某些方面的基本理解。应当理解,这个概述并不是关于本发明的穷举性概述。它并不是意图确定本发明的关键或重要部分,也不是意图限定本发明的范围。其目的仅仅是以简化的形式给出某些概念,以此作为稍后论述的更详细描述的前序。
鉴于上述,本公开提供了一种针对设备设置适当的数据采集频率的自适应方法。在该方法中,考虑了应用程序的需求和设备的状态来确定针对该设备适当的数据采集频率。此外,还可以基于设备的现场实时情况来自动调节采集频率。
根据本公开的一个方面,提供了确定数据的采集频率的方法,其中,所述数据从设备采集并提供给应用程序,以供所述应用程序对所述设备进行监控,所述方法包括:确定应用程序对设备的数据的采集频率需求;确定设备的状态信息;以及基于所确定的应用程序对设备的数据的采集频率需求和所确定的设备的状态信息,根据预设规则来确定数据的采集频率。
可选地,在上述方面的一个示例中,所述应用程序对设备的数据的采集频率需求包括以下中的至少一项:应用程序本身对于采集频率的需求;在设备的不同状态下,应用程序对于采集频率的需求;以及在不同时间,应用程序对于采集频率的需求。
可选地,在上述方面的一个示例中,其中,应用程序本身对于采集频率的需求包括:优选采集频率、最小采集频率和零频率;设备的不同状态包括:工作状态、空闲状态、故障状态、维修状态以及维护状态,针对设备的每一种状态,分别具有相应的优选采集频率、最小采集频率和零频率;以及所述时间包括工作时间、非工作时间以及全天,针对不同时间分别具有相应的优选采集频率、最小采集频率和零频率。
可选地,在上述方面的一个示例中,所述设备的状态信息包括以下中的至少一项:设备的工作状态;设备的计划工作时间和非工作时间;设备性能指标;和硬件信息。
可选地,在上述方面的一个示例中,所述设备的工作状态包括以下中的至少一项:工作状态、空闲状态、故障状态、维修状态以及维护状态;设备性能指标包括以下中的至少一项:中央处理器使用率、内存占用率、 输入输出读取时间以及中央处理器温度;以及所述硬件信息包括以下中的至少一项:中央处理器的版本和内存的版本。
可选地,在上述方面的一个示例中,所述实时性能参数包括以下中的至少一项:实时中央处理器使用率、内存占用率、网络负荷、以及设备的响应时间。
根据本公开的另一方面,提供了确定数据的采集频率的装置,其中,所述数据是从设备采集并提供给应用程序,以供所述应用程序对所述设备进行监控,所述装置包括:采集频率需求确定单元,被配置为确定应用程序对设备的数据的采集频率需求;设备状态确定单元,被配置为确定设备的状态信息;以及采集频率确定单元,被配置为基于所确定的应用程序对设备的数据的采集频率需求和所确定的设备的状态信息,根据预设规则来确定数据的采集频率。
可选地,在上述方面的一个示例中,确定数据的采集频率的装置还包括:采集频率调整单元,被配置为接收所述设备的实时性能参数,并根据所述实时性能参数确定是否需要调整所述采集频率。
可选地,在上述方面的一个示例中,所述应用程序对设备的数据的采集频率需求包括以下中的至少一项:应用程序本身对于采集频率的需求;在设备的不同状态下,应用程序对于采集频率的需求;以及在不同时间,应用程序对于采集频率的需求。
可选地,在上述方面的一个示例中,应用程序本身对于采集频率的需求包括:优选采集频率、最小采集频率和零频率;设备的不同状态包括:工作状态、空闲状态、故障状态、维修状态以及维护状态,针对设备的每一种状态,分别具有相应的优选采集频率、最小采集频率和零频率;以及所述时间包括工作时间、非工作时间以及全天,针对不同时间分别具有相应的优选采集频率、最小采集频率和零频率。
可选地,在上述方面的一个示例中,所述设备的状态信息包括以下中的至少一项:设备的工作状态;设备的计划工作时间和非工作时间;设备性能指标;和硬件信息。
可选地,在上述方面的一个示例中,所述设备的工作状态包括以下中的至少一项:工作状态、空闲状态、故障状态、维修状态以及维护状态; 设备性能指标包括以下中的至少一项:中央处理器使用率、内存占用率、输入输出读取时间以及中央处理器温度;以及所述硬件信息包括以下中的至少一项:中央处理器的版本和内存的版本。
可选地,在上述方面的一个示例中,所述实时性能参数包括以下中的至少一项:实时中央处理器使用率、内存占用率、网络负荷、以及设备的响应时间。
根据本公开的另一方面,提供了计算设备,包括:至少一个处理器;以及与所述至少一个处理器耦合的一个存储器,所述存储器用于存储指令,当所述指令被所述至少一个处理器执行时,使得所述处理器执行如上所述的方法。
根据本公开的另一方面,提供了一种非暂时性机器可读存储介质,其存储有可执行指令,所述指令当被执行时使得所述机器执行如上所述的方法。
根据本公开的另一方面,提供了一种计算机程序,包括计算机可执行指令,所述计算机可执行指令在被执行时使至少一个处理器执行如上所述的方法。
根据本公开的另一方面,提供了一种计算机程序产品,所述计算机程序产品被有形地存储在计算机可读介质上并且包括计算机可执行指令,所述计算机可执行指令在被执行时使至少一个处理器执行如上所述的方法。
根据本公开的确定数据采集频率的方法,可以在确保设备的正常操作的情况下尽可能满足应用程序的要求,避免由于数据采集而引起对设备的正常操作的干扰。
根据本公开的确定数据采集频率的方法和装置,可以避免对于配置人员的高要求,降低设置适当的数据采集频率的工作量和复杂度,尤其是在有成百上千种不同类型的设备的情况下。
根据本公开的确定数据采集频率的方法,可以避免采集无效的数据,以减小采集的数据量,从而节省数据通信、存储和处理的成本。
附图说明
参照下面结合附图对本发明实施例的说明,会更加容易地理解本发明 的以上和其它目的、特点和优点。附图中的部件只是为了示出本发明的原理。在附图中,相同的或类似的技术特征或部件将采用相同或类似的附图标记来表示。
图1是示出了根据本公开的一个实施例的确定数据的采集频率的方法的示例性过程的流程图;
图2是示出了根据本公开的一个实施例的确定数据的采集频率的装置的示例性配置的框图;
图3是示出了根据本公开的一个实施例的信息处理系统的示例性配置的框图;以及
图4示出了根据本公开的实施例的为数据配置优先级的计算设备的方框图。
附图标记
100:确定数据的采集频率的方法  S102、S104、S106、S108:步骤
200:确定数据的采集频率的装置  202:采集频率需求确定单元
204:设备状态确定单元          206:采集频率确定单元
208:采集频率调整单元          300:信息处理系统
302:设备                      304:云平台
306:网关                      400:计算设备
402:处理器                    404:存储器
具体实施方式
现在将参考示例实施方式讨论本文描述的主题。应该理解,讨论这些实施方式只是为了使得本领域技术人员能够更好地理解从而实现本文描述的主题,并非是对权利要求书中所阐述的保护范围、适用性或者示例的限制。可以在不脱离本公开内容的保护范围的情况下,对所讨论的元素的功能和排列进行改变。各个示例可以根据需要,省略、替代或者添加各种过程或组件。例如,所描述的方法可以按照与所描述的顺序不同的顺序来执行,以及各个步骤可以被添加、省略或者组合。另外,相对一些示例所描述的特征在其它例子中也可以进行组合。
如本文中使用的,术语“包括”及其变型表示开放的术语,含义是“包括但不限于”。术语“基于”表示“至少部分地基于”。术语“一个实施例”和“一实施例”表示“至少一个实施例”。术语“另一个实施例”表示“至少一个其他实施例”。术语“第一”、“第二”等可以指代不同的或相同的对象。下面可以包括其他的定义,无论是明确的还是隐含的。除非上下文中明确地指明,否则一个术语的定义在整个说明书中是一致的。
如上所述,对于工厂中的各种设备,可以利用应用程序对其进行监测,例如,对设备的状态监控、确定OEE(Overall Equipment Effectiveness,总体设备效能)、进行故障诊断、预见性维护等,而这些功能都要基于从设备采集的数据来实现。本公开提供了一种针对设备设置适当的数据采集频率的自适应方法。
根据本公开的方法,考虑了应用程序的需求和设备的状态来确定针对该设备适当的数据采集频率。此外,还可以基于设备的现场实时情况来自动调节采集频率。
根据本公开的方法,可以在确保设备的正常操作的情况下尽可能满足应用程序的要求。该方法极大地减小针对成千上万的设备配置数据采集解决方案的工作量和复杂度,减小无效的数据量,并且同时确保正常的生产活动。
首先,在下面的表1中列出了在根据本公开的确定数据的采集频率的方法中所要考虑的与数据采集频率有关的一些基本规则。
Figure PCTCN2019121720-appb-000001
Figure PCTCN2019121720-appb-000002
表1
基于以上基本规则,提出了根据本公开的确定数据的采集频率的方法。图1是示出了根据本公开的一个实施例的确定数据的采集频率的方法100的示例性过程的流程图。
在图1中,首先在方框S102中,确定应用程序对设备的数据的采集频率需求。
可以理解,不同的应用程序对于数据的采集频率需求是不同的。有些应用程序需要一天采集几次,有些应用程序需要一个小时采集几次,还有一些应用程序可能需要一秒钟采集上千次。
此外,在设备的不同状态下或者在不同的时间,应用程序对于数据的采集频率需求也是不同的。
因此,在根据本公开的方法中,所确定的应用程序对数据的采集频率需求可以包括以下具体情况。
首先是由应用程序的功能而决定的应用程序本身对于采集频率的需求。
在根据本公开的方法中,应用程序本身对于采集频率的需求可以包括优选采集频率、最小采集频率和零频率。
优选采集频率是针对应用程序的最佳频率,只要设备的控制系统可以负担,就使用该优选采集频率。
最小采集频率是在设备的控制系统忙于正常工作而不能与数据采集功能分享资源时,使用该最小采集频率。如果设备的控制系统连最小采集频 率也不能承受,应该尝试进一步降低采集频率,以确保正常生产工作。
零频率是指不需要进行数据采集。
例如,设备预防性维护应用场景中,振动数据、电流数据等,都需要很高的采样频率,满足后续数据分析的需求;设备状态透明化的场景中,并不需要高频率的采样,通常1Hz的采样就能满足现场设备状态透明化的需求;而对于能耗采集的场景中,每小时获取当前能耗,甚至更大采样周期都可以满足能耗管理的需求,类似能耗这样的数据,可以选择设备不在生产的时候采集,从而不影响设备的正常工作。
其次,设备的不同状态可以包括:工作状态、空闲状态、故障状态、维修状态以及维护状态等。针对设备的不同状态,应用程序可能分别具有不同的数据采集频率需求。
例如,对于能耗监测应用程序,当设备处于空闲模式时,采集频率应该较低,当设备转换为工作模式时,采集频率应该变得更高;而对于可预测维护应用程序,当设备处于空闲或者维护模式时,可能不需要采集数据。在这种情况下可以将数据采集频率大大减小,以便节省数据通信、存储和处理的成本。因此,针对设备的每一种状态,也可以分别设置相应的优选采集频率、最小采集频率和零频率。例如,当设备处于“工作状态”中,也可以根据设备的具体工作情况而选择针对“工作状态”所设置的优选采集频率、最小采集频率和零频率中的一种频率来进行数据采集。
此外,在工厂中可能限定不同的工作时间,包括工作时间、非工作时间以及全天24小时(例如早班、中班和晚班),针对不同的时间,也可以设置不同的数据采集频率,例如非工作时间的采集频率应该设置得较小。此外,针对每个时间段也可以分别具有相应的优选采集频率、最小采集频率和零频率。
此外,针对同一个设备可能有多个应用程序,这意味着可能有多个应用程序需要同一个设备的相同的数据。在这种情况下,可以对多个应用程序的需求进行组合,使得采集的数据可以满足所有应用程序的需求。
这样,通过方框S102中的操作,可以确定一个应用程序在各种不同情况下对某一个设备的数据采集频率的需求。可以理解,应用程序对于设备的数据的采集频率的需求并不限于以上所述,本领域技术人员在利用根据 本公开的方法确定数据的采集频率时也可以考虑与应用程序有关的、可能影响数据采集频率的其他因素,在此不再详述。
接着,在方框S104中,确定设备的状态信息。
设备的状态信息是来自于例如工厂现场的设备,或者从第三方系统中获取。
设备信息例如可以包括以下各项:设备的工作状态;设备的工作时间和非工作时间;设备性能指标;和硬件信息等。
其中,设备的工作状态例如可以是:工作状态、空闲状态、故障状态、维修状态以及维护状态等。
设备性能指标例如包括:CPU使用率、RAM占用率、I/O读取时间、以及CPU温度等。
针对每一项设备性能指标,可以由经验丰富的工程师预先设置用于对该设备性能指标进行评估的阈值,也可以采用自动评估方法,例如通过测量设备的控制系统的响应时间等来评估设备性能。
硬件信息可以包括:CPU的版本、内存版本等。利用硬件信息,可以将一个设备的采集频率作为其他类似设备的参考。
可以理解,设备的状态信息并不限于以上所述,本领域技术人员在利用根据本公开的方法确定数据的采集频率时也可以考虑影响数据采集频率的其他设备状态信息,在此不再详述。
然后,在方框S106中,基于所确定的应用程序对设备的数据的采集频率需求和所确定的设备的状态信息,根据预设规则来确定数据的采集频率。
这里的预设规则例如可以包括:采集频率应该至少满足实现应用程序的功能的最低要求;采集频率应该不要过于频繁以避免在数据传输、存储、处理和可视化过程中产生过大的成本;采集频率应该避免影响设备的工作性能;针对不同的设备状态可以生成不同的采集频率;对于具有不同硬件和软件的设备,可以定制相应的采集频率等。
在根据本公开的方法中,可以由本领域技术人员根据经验预先设置适当的规则,而不限于以上所述的预设规则,然后可以基于所确定的应用程序对设备的数据的采集频率需求和所确定的设备的状态信息自动计算出针对该设备适当的数据采集频率。
在一个示例中,确定数据的采集频率的方法100还可以包括方框S108中的操作,采集设备的实时性能参数,并根据所述实时性能参数确定是否需要调整所述采集频率。
具体地,可以采集设备的实时CPU使用率、RAM占用率、网络负荷、设备的响应速度等实时性能参数。针对每一项性能参数,可以预先设置一个阈值,通过与阈值进行比较可以确定设备的性能状况,从而确实是否需要调整采集频率。
在一个示例中,可以向设备周期性地发送一条测试指令,然后通过响应时间来判断设备的响应速度是否慢。对于这样的方式,可以自动进行大量测试,然后通过自学习的方法对这些测试数据进行分析,来确定阈值。
通过这样的方式,可以根据实时性能参数判断出设备状态发生变化,或者数据采集对正常的生产生影响等情况,从而可以及时调整采集频率。
通过本公开的方法所确定的数据采集频率例如可以提供给负责进行数据采集的网关,由网关按照所确定的数据采集频率进行数据采集,并提供给相应的应用程序。
根据本公开的方法可以实时监控设备的使用情况,例如在设备运行变慢的情况下,可以自动降低采集频率,并将更新的采集频率发送给网关。对于不同的设备,也不需要区别处理。
根据本公开的确定数据采集频率的方法,可以基于应用程序的需求和现场设备的运行情况,在需求和实际状况之间做一个平衡。
根据本公开的确定数据采集频率的方法,可以在确保设备的正常操作的情况下尽可能满足应用程序的要求,避免由于数据采集而引起对设备的正常操作的干扰。
根据本公开的确定数据采集频率的方法,可以避免对于配置人员的高要求,降低设置适当的数据采集频率的工作量和复杂度,尤其是在有成百上千种不同类型的设备的情况下。
根据本公开的确定数据采集频率的方法,可以避免采集无效的数据,以减小采集的数据量,从而节省数据通信、存储和处理的成本。
图2是示出了根据本公开的一个实施例的确定数据的采集频率的装置 200的示例性配置的框图。
确定数据的采集频率的装置200包括:一个采集频率需求确定单元202、一个设备状态确定单元204和一个采集频率确定单元206。
采集频率需求确定单元202被配置为确定应用程序对设备的数据的采集频率需求。
设备状态确定单元204被配置为确定设备的状态信息。
采集频率确定单元206被配置为基于所确定的应用程序对设备的数据的采集频率需求和所确定的设备的状态信息,根据预设规则来确定数据的采集频率。
其中,确定数据的采集频率的装置200还可以包括:一个采集频率调整单元208,所述采集频率调整单元208被配置为接收所述设备的实时性能参数,并根据所述实时性能参数确定是否需要调整所述采集频率。
其中,所述应用程序对设备的数据的采集频率需求包括以下中的至少一项:应用程序本身对于采集频率的需求;在设备的不同状态下,应用程序对于采集频率的需求;以及在不同时间,应用程序对于采集频率的需求。
其中,应用程序本身对于采集频率的需求包括:优选采集频率、最小采集频率和零频率;设备的不同状态包括:工作状态、空闲状态、故障状态、维修状态以及维护状态,针对设备的每一种状态,分别具有相应的优选采集频率、最小采集频率和零频率;以及所述时间包括工作时间、非工作时间以及全天,针对不同时间分别具有相应的优选采集频率、最小采集频率和零频率。
其中,所述设备的状态信息包括以下中的至少一项:设备的工作状态;设备的计划工作时间和非工作时间;设备性能指标;和硬件信息。
其中,所述设备的工作状态包括以下中的至少一项:工作状态、空闲状态、故障状态、维修状态以及维护状态;设备性能指标包括以下中的至少一项:中央处理器使用率、内存占用率、输入输出读取时间以及中央处理器温度;以及所述硬件信息包括以下中的至少一项:中央处理器的版本和内存的版本。
所述实时性能参数包括以下中的至少一项:实时中央处理器使用率、内存占用率、网络负荷、以及设备的响应时间。
在此需要说明的是,上述应用程序对设备数据的采集频率需求的相关内容和设备的状态信息的相关内容只是举例说明,本公开并不限于此。
还需要说明的是,图2所示的确定数据的采集频率的装置200及其组成单元的结构仅仅是示例性的,本领域技术人员可以根据需要对图2所示的结构框图进行修改。
确定数据的采集频率的装置200的各个部分的操作和功能的细节例如可以与参照结合图1描述的本公开的确定数据的采集频率的方法100的实施例的相关部分相同或类似,这里不再详细描述。
图3是示出了根据本公开的一个实施例的信息处理系统300的示例性配置的框图。
信息处理系统300包括现场设备302、云平台304、设置在云平台304上的确定数据的采集频率的装置200以及网关306。
设置在云平台304上的确定数据的采集频率的装置200可以利用以上参照图1所述的确定数据的采集频率的方法来确定要从设备302进行数据采集的采集频率。装置200可以将所确定的数据采集频率提供给网关306,然后网关306按照所确定的数据采集频率从设备302进行数据采集,并且提供给需要的应用程序。
此外,还可以由网关306采集设备的实时性能参数,并提供给确定数据的采集频率的装置200,使得装置200可以根据实时性能参数确定是否需要调整所述采集频率。
本领域技术人员可以理解,图3所示的信息处理系统300仅仅是应用根据本公开的确定数据的采集频率的方法的一个具体应用示例。可以理解的是,根据本公开的确定数据的采集频率的装置200不一定设置在云平台304上,也可以设置在例如本地服务器等任何适当的地方。此外,所确定的数据采集频率不一定要提供给网关,也可以提供给其他第三方应用程序。
如上参照图1到图3,对根据本公开的实施例的确定数据的采集频率的方法、装置以及信息处理系统的实施例进行了描述。以上所述的确定数据的采集频率的装置可以采用硬件实现,也可以采用软件或者硬件和软件的组合来实现。
图4示出了根据本公开的实施例的确定数据的采集频率的计算设备400的方框图。根据一个实施例,计算设备400可以包括至少一个处理器402,处理器402执行在计算机可读存储介质(即,存储器404)中存储或编码的至少一个计算机可读指令(即,上述以软件形式实现的元素)。
在一个实施例中,在存储器404中存储计算机可执行指令,其当执行时使得至少一个处理器402完成以下动作:确定应用程序对设备的数据的采集频率需求;确定设备的状态信息;以及基于所确定的应用程序对设备的数据的采集频率需求和所确定的设备的状态信息,根据预设规则来确定数据的采集频率。
应该理解,在存储器404中存储的计算机可执行指令当执行时使得至少一个处理器402进行本公开的各个实施例中以上结合图1-3描述的各种操作和功能。
根据一个实施例,提供了一种非暂时性机器可读介质。该非暂时性机器可读介质可以具有机器可执行指令(即,上述以软件形式实现的元素),该指令当被机器执行时,使得机器执行本公开的各个实施例中以上结合图1-3描述的各种操作和功能。
根据一个实施例,提供了一种计算机程序,包括计算机可执行指令,所述计算机可执行指令在被执行时使至少一个处理器执行本公开的各个实施例中以上结合图1-3描述的各种操作和功能。
根据一个实施例,提供了一种计算机程序产品,包括计算机可执行指令,所述计算机可执行指令在被执行时使至少一个处理器执行本公开的各个实施例中以上结合图1-3描述的各种操作和功能。
上面结合附图阐述的具体实施方式描述了示例性实施例,但并不表示可以实现的或者落入权利要求书的保护范围的所有实施例。在整个本说明书中使用的术语“示例性”意味着“用作示例、实例或例示”,并不意味着比其它实施例“优选”或“具有优势”。出于提供对所描述技术的理解的目的,具体实施方式包括具体细节。然而,可以在没有这些具体细节的情况下实施这些技术。在一些实例中,为了避免对所描述的实施例的概念造成难以理解,公知的结构和装置以框图形式示出。
本公开内容的上述描述被提供来使得本领域任何普通技术人员能够实现或者使用本公开内容。对于本领域普通技术人员来说,对本公开内容进行的各种修改是显而易见的,并且,也可以在不脱离本公开内容的保护范围的情况下,将本文所定义的一般性原理应用于其它变型。因此,本公开内容并不限于本文所描述的示例和设计,而是与符合本文公开的原理和新颖性特征的最广范围相一致。

Claims (18)

  1. 确定数据的采集频率的方法,其中,所述数据从设备采集并提供给应用程序,以供所述应用程序对所述设备进行监控,所述方法包括:
    确定应用程序对设备的数据的采集频率需求;
    确定设备的状态信息;以及
    基于所确定的应用程序对设备的数据的采集频率需求和所确定的设备的状态信息,根据预设规则来确定数据的采集频率。
  2. 如权利要求1所述的方法,还包括:
    采集所述设备的实时性能参数,并根据所述实时性能参数确定是否需要调整所述采集频率。
  3. 如权利要求1或2所述的方法,其中,所述应用程序对设备的数据的采集频率需求包括以下中的至少一项:
    应用程序本身对于采集频率的需求;
    在设备的不同状态下,应用程序对于采集频率的需求;以及
    在不同时间,应用程序对于采集频率的需求。
  4. 如权利要求3所述的方法,其中,
    应用程序本身对于采集频率的需求包括:优选采集频率、最小采集频率和零频率;
    设备的不同状态包括:工作状态、空闲状态、故障状态、维修状态以及维护状态,针对设备的每一种状态,分别具有相应的优选采集频率、最小采集频率和零频率;以及
    所述时间包括工作时间、非工作时间以及全天,针对不同时间分别具有相应的优选采集频率、最小采集频率和零频率。
  5. 如权利要求1或2所述的方法,其中,所述设备的状态信息包括以下中的至少一项:
    设备的工作状态;
    设备的计划工作时间和非工作时间;
    设备性能指标;和
    硬件信息。
  6. 如权利要求5所述的方法,其中,
    所述设备的工作状态包括以下中的至少一项:工作状态、空闲状态、故障状态、维修状态以及维护状态;
    设备性能指标包括以下中的至少一项:中央处理器使用率、内存占用率、输入输出读取时间以及中央处理器温度;以及
    所述硬件信息包括以下中的至少一项:中央处理器的版本和内存的版本。
  7. 如权利要求2中所述的方法,其中,所述实时性能参数包括以下中的至少一项:
    实时中央处理器使用率、内存占用率、网络负荷、以及设备的响应时间。
  8. 确定数据的采集频率的装置(200),其中,所述数据是从设备采集并提供给应用程序,以供所述应用程序对所述设备进行监控,所述装置(200)包括:
    采集频率需求确定单元(202),被配置为确定应用程序对设备的数据的采集频率需求;
    设备状态确定单元(204),被配置为确定设备的状态信息;以及
    采集频率确定单元(206),被配置为基于所确定的应用程序对设备的数据的采集频率需求和所确定的设备的状态信息,根据预设规则来确定数据的采集频率。
  9. 如权利要求8所述的装置(200),还包括:
    采集频率调整单元(208),被配置为采集所述设备的实时性能参数, 并根据所述实时性能参数确定是否需要调整所述采集频率。
  10. 如权利要求8或9所述的装置(200),其中,所述应用程序对设备的数据的采集频率需求包括以下中的至少一项:
    应用程序本身对于采集频率的需求;
    在设备的不同状态下,应用程序对于采集频率的需求;以及
    在不同时间,应用程序对于采集频率的需求。
  11. 如权利要求10所述的装置(200),其中,
    应用程序本身对于采集频率的需求包括:优选采集频率、最小采集频率和零频率;
    设备的不同状态包括:工作状态、空闲状态、故障状态、维修状态以及维护状态,针对设备的每一种状态,分别具有相应的优选采集频率、最小采集频率和零频率;以及
    所述时间包括工作时间、非工作时间以及全天,针对不同时间分别具有相应的优选采集频率、最小采集频率和零频率。
  12. 如权利要求8或9所述的装置(200),其中,所述设备的状态信息包括以下中的至少一项:
    设备的工作状态;
    设备的计划工作时间和非工作时间;
    设备性能指标;和
    硬件信息。
  13. 如权利要求12所述的装置(200),其中,
    所述设备的工作状态包括以下中的至少一项:工作状态、空闲状态、故障状态、维修状态以及维护状态;
    设备性能指标包括以下中的至少一项:中央处理器使用率、内存占用率、输入输出读取时间以及中央处理器温度;以及
    所述硬件信息包括以下中的至少一项:中央处理器的版本和内存的版 本。
  14. 如权利要求9中所述的装置(200),其中,所述实时性能参数包括以下中的至少一项:
    实时中央处理器使用率、内存占用率、网络负荷、以及设备的响应时间。
  15. 计算设备(400),包括:
    至少一个处理器(402);以及
    与所述至少一个处理器(402)耦合的一个存储器(404),所述存储器用于存储指令,当所述指令被所述至少一个处理器(402)执行时,使得所述处理器(402)执行如权利要求1到7中任意一项所述的方法。
  16. 一种非暂时性机器可读存储介质,其存储有可执行指令,所述指令当被执行时使得所述机器执行如权利要求1到7中任意一项所述的方法。
  17. 一种计算机程序,包括计算机可执行指令,所述计算机可执行指令在被执行时使至少一个处理器执行根据权利要求1至7中任意一项所述的方法。
  18. 一种计算机程序产品,所述计算机程序产品被有形地存储在计算机可读介质上并且包括计算机可执行指令,所述计算机可执行指令在被执行时使至少一个处理器执行根据权利要求1至7中任意一项所述的方法。
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