CN113051133A - Remote equipment monitoring method, device, equipment and storage medium - Google Patents
Remote equipment monitoring method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention belongs to the technical field of equipment management and discloses a method, a device, equipment and a storage medium for monitoring remote equipment. The method comprises the steps of obtaining equipment state information collected by a field sensor arranged on equipment to be monitored; determining a state parameter value and a state parameter change value according to the equipment state information, and fuzzifying the state parameter value and the state parameter change value to obtain a state parameter output value; acquiring a preset reference range, and judging whether the state parameter output value is in the preset reference range; and when the output value of the state parameter is not in the preset reference range, judging that the equipment to be monitored has a fault. Compared with the existing method that the equipment fault is judged only after the equipment is abnormal, the method judges the running state of the equipment by comparing the fuzzified state information of the equipment with the preset reference range, can prejudge the running state of the equipment in advance, enables the equipment to be more convenient to monitor, and avoids the loss caused by the fact that the equipment is closed only after the equipment is abnormal.
Description
Technical Field
The present invention relates to the field of device management technologies, and in particular, to a method, an apparatus, a device, and a storage medium for remote device monitoring.
Background
In the operation process of the equipment, it is necessary to regularly patrol the equipment, in the patrol process, the operation data and the state of the equipment need to be checked, and whether the current operation state of the equipment is normal or not is judged according to experience.
At present, with the increasing quantity and types of field devices, the workload of routing inspection is larger and larger, the current operation state of the device is difficult to judge according to an empirical value, and once the operation state of the device is abnormal, operation and maintenance personnel can not find the operation state in the first time, so that the existing device state monitoring has certain problems. Therefore, a method for helping operation and maintenance personnel to realize remote monitoring and early warning of equipment is urgently needed, and no related technical scheme exists in the field at present.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a method, a device, equipment and a storage medium for monitoring remote equipment, and aims to solve the technical problems that the running state of the equipment cannot be predicted in advance, the quantity of the equipment is large, and each piece of equipment cannot be checked in a short distance in the prior art.
In order to achieve the above object, the present invention provides a remote device monitoring method, including the steps of:
acquiring equipment state information acquired by a field sensor arranged on equipment to be monitored;
determining a state parameter value and a state parameter change value according to the equipment state information, and fuzzifying the state parameter value and the state parameter change value to obtain a state parameter output value;
acquiring a preset reference range, and judging whether the state parameter output value is in the preset reference range;
and when the state parameter output value is not in the preset reference range, judging that the equipment to be monitored has a fault.
Optionally, the step of determining a state parameter value and a state parameter change value according to the device state information includes:
determining a state parameter value and a historical state parameter value corresponding to the state parameter value according to the equipment state information;
determining a state parameter value difference value according to the state parameter value and the historical state parameter value;
and determining a state parameter change value according to the state parameter value difference.
Optionally, the step of fuzzifying the state parameter value and the state parameter variation value to obtain a state parameter output value includes:
determining a state parameter value range corresponding to the state parameter value;
determining a feasible interval according to the value range of the state parameter value;
determining a parameter value membership interval of the state parameter value according to the feasible interval and the state parameter value;
determining a state parameter change value membership interval of the state parameter change value according to the feasible interval and the state parameter change value;
and determining the state parameter output value according to a preset fuzzy rule table, the state parameter value, the state parameter change value, the state parameter value membership interval and the state parameter change value membership interval.
Optionally, the step of determining the output value of the state parameter according to a preset fuzzy rule table, the value of the state parameter, the change value of the state parameter, the membership interval of the value of the state parameter, and the membership interval of the change value of the state parameter includes:
determining parameter value membership degrees corresponding to the state parameter values according to the state parameter value membership intervals and the state parameter values;
determining the parameter variation value membership degree corresponding to the state parameter variation value according to the state parameter variation value membership interval and the state parameter variation value;
searching a corresponding membership value in the preset fuzzy rule table according to the status parameter value membership interval and the status parameter change value membership interval;
and determining the state parameter output value according to the parameter value membership degree, the parameter change value membership degree and the membership value.
Optionally, before the step of obtaining the preset reference range, the method further includes:
acquiring normal state information of the equipment to be monitored in normal operation;
fuzzifying the normal state information to obtain a fuzzy result;
determining a state reference value corresponding to the normal state information according to the fuzzy result and the preset fuzzy rule table;
and constructing a preset reference range according to the state reference value.
Optionally, after the step of determining whether the state parameter output value is within the preset reference range, the method further includes:
when the state parameter output value is within the preset reference range, generating a monitoring record of the equipment to be monitored;
and sending the monitoring record to a target user terminal.
Optionally, after the step of determining that the device to be monitored is faulty when the state parameter output value is not within the preset reference range, the method further includes:
sending parameter information corresponding to the state parameter output value which is not in the preset reference range to an equipment maintenance terminal;
and after a maintenance completion instruction based on the equipment maintenance terminal feedback is received, the equipment to be monitored is patrolled and examined to generate a patrol and examine record.
In addition, in order to achieve the above object, the present invention further provides a remote device monitoring apparatus, which includes an obtaining module, a fuzzy module, a judging module and a failure module;
the acquisition module is used for acquiring equipment state information acquired by a field sensor arranged on the equipment to be monitored;
the fuzzy module is used for determining a state parameter value and a state parameter change value according to the equipment state information, and fuzzifying the state parameter value and the state parameter change value to obtain a state parameter output value;
the judging module is used for acquiring a preset reference range and judging whether the state parameter output value is in the preset reference range;
and the fault module is used for judging that the equipment to be monitored is in fault when the state parameter output value is not in the preset reference range.
In addition, to achieve the above object, the present invention further provides a remote device monitoring device, including: a memory, a processor, and a remote device monitoring program stored on the memory and executable on the processor, the remote device monitoring program configured to implement the steps of the remote device monitoring method as described above.
In addition, to achieve the above object, the present invention further provides a storage medium having a remote device monitoring program stored thereon, wherein the remote device monitoring program, when executed by a processor, implements the steps of the remote device monitoring method as described above.
The invention belongs to the technical field of equipment management and discloses a method, a device, equipment and a storage medium for monitoring remote equipment. The method comprises the steps of obtaining equipment state information collected by a field sensor arranged on equipment to be monitored; determining a state parameter value and a state parameter change value according to the equipment state information, and fuzzifying the state parameter value and the state parameter change value to obtain a state parameter output value; acquiring a preset reference range, and judging whether the state parameter output value is in the preset reference range; and when the state parameter output value is not in the preset reference range, judging that the equipment to be monitored has a fault. Compared with the prior art that the equipment fault is judged only after the equipment is abnormal, the method provided by the invention judges the running state of the equipment by fuzzifying the state information of the equipment and comparing the fuzzified state information with the preset reference range.
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FIG. 1 is a schematic diagram of a remote device monitoring apparatus for a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a monitoring method of a remote device according to a first embodiment of the present invention;
FIG. 3 is a flowchart illustrating a remote device monitoring method according to a second embodiment of the present invention;
FIG. 4 is a table of predefined fuzzy rules in a second embodiment of a remote device monitoring method according to the present invention;
FIG. 5 is a diagram illustrating a membership range of a status parameter value and membership values corresponding to the membership range of a status parameter variation value in a second embodiment of the remote device monitoring method according to the present invention;
FIG. 6 is a flowchart illustrating a monitoring method for remote devices according to a third embodiment of the present invention;
fig. 7 is a block diagram of a first embodiment of the remote device monitoring apparatus according to the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a remote device monitoring device of a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the remote device monitoring apparatus may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a Random Access Memory (RAM) Memory, or may be a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in FIG. 1 does not constitute a limitation of a remote device monitoring apparatus, and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, the memory 1005, which is a storage medium, may include therein an operating system, a data storage module, a network communication module, a user interface module, and a remote device monitoring program.
In the remote device monitoring apparatus shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the remote device monitoring apparatus of the present invention may be disposed in the remote device monitoring apparatus, and the remote device monitoring apparatus calls the remote device monitoring program stored in the memory 1005 through the processor 1001 and executes the remote device monitoring method provided in the embodiment of the present invention.
Based on the remote device monitoring device, an embodiment of the present invention provides a remote device monitoring method, and referring to fig. 2, fig. 2 is a flowchart illustrating a first embodiment of the remote device monitoring method according to the present invention.
In this embodiment, the remote device monitoring method includes the following steps:
step S10: and acquiring equipment state information acquired by a field sensor arranged on the equipment to be monitored.
It should be noted that the execution main body of the embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, an upper computer, or an electronic device or a remote monitoring device capable of implementing the above functions. The present embodiment and the following embodiments will be described below by taking the remote monitoring apparatus as an example.
It should be understood that the device to be monitored may be a device to be monitored, and may be an electronic device, a mechanical device, or the like. The field sensor may be a sensor provided on the device to be monitored, and the sensor may be a temperature sensor, a gas sensor, a composite sensor, or the like. In practical application, a proper sensor can be selected according to the data needing to be monitored currently. The device status information may be status information of the device to be monitored, such as amplitude, temperature, rotation speed, and the like.
In specific implementation, the remote monitoring device acquires the device state information of the device to be monitored according to the field sensor arranged on the device to be monitored.
Step S20: and determining a state parameter value and a state parameter change value according to the equipment state information, and fuzzifying the state parameter value and the state parameter change value to obtain a state parameter output value.
It should be noted that the state parameter value may be a parameter value corresponding to a parameter in the device state information, for example, the value is equivalent to a rotation speed of 1100r/min and a temperature of 30 ℃. The state parameter variation value may be an absolute value of a difference between a parameter value acquired this time and a parameter value acquired last time, for example, taking the parameter of temperature as an example, the state parameter variation value is 10 if the value acquired this time is 30 degrees celsius and the value acquired last time is 20 degrees celsius.
It should be noted that, the fuzzifying the state parameter value and the state parameter variation value may be to determine a range interval corresponding to the state parameter value according to the state parameter value, for example, a temperature variation is between 0 and 100, the range interval corresponding to the temperature parameter value is 0 to 100, determine an affiliated interval corresponding to the state parameter value and the state parameter variation value according to the range interval, the affiliated interval may be a small interval divided according to the range interval, for example, the range interval is 1 to 100, the range interval is divided into 10 small intervals, that is, 0 to 10 are the first small interval, and so on, 91 to 100 are the 10 th small interval, determine the affiliated interval of the state parameter value and the state parameter variation value, compare the affiliated interval with an interval to which the device normally operates, and determine whether the device is abnormal, the state parameter output value may be a value obtained by blurring the state parameter value and the state parameter variation value.
Further, in order to obtain a more accurate result of the remote monitoring, the step of determining the value of the status parameter and the value of the change of the status parameter according to the status information of the device includes: determining a state parameter value and a historical state parameter value corresponding to the state parameter value according to the equipment state information; determining a state parameter value difference value according to the state parameter value and the historical state parameter value; and determining a state parameter change value according to the state parameter value difference.
It should be understood that the historical state parameter value may be a state parameter value acquired last time of a parameter corresponding to the state parameter value, taking temperature as an example, the result of the current acquisition of the temperature parameter value is 20 degrees celsius, the temperature acquired last time is 30 degrees celsius, the state parameter value is 20 degrees, the historical state parameter value is 30 degrees celsius, a state parameter value difference value calculated by the state parameter value 20 and the historical state parameter value 30 is-10, and determining the state parameter change value according to the state parameter value difference value may be to use an absolute value of the state parameter value difference value as the state parameter change value, that is, the absolute value of the state parameter change value is-10.
Step S30: and acquiring a preset reference range, and judging whether the state parameter output value is in the preset reference range.
It should be noted that the preset reference range may be a reference range calculated according to data collected during normal operation of the device. The judging whether the state parameter output value is within the preset reference range may be comparing the state parameter output value with the preset reference range, and determining whether the state parameter output value is within the preset reference range.
Step S40: and when the state parameter output value is not in the preset reference range, judging that the equipment to be monitored has a fault.
It should be understood that when the determined output value of the state parameter is within the preset reference range, the device to be monitored may be determined to be normal, or the fault risk of the device to be monitored may be determined with reference to the preset reference range, for example, the determined output value of the state parameter, although still within the preset reference range, is not yet within the preset reference range, and monitoring or early maintenance of the device may be enhanced. The maintenance of the equipment may also be to perform maintenance on a component corresponding to a parameter that is not within the preset reference range, for example, if the output value of the state parameter corresponding to the temperature of the equipment is not within the preset reference range, only whether the component corresponding to the temperature is damaged is maintained and controlled, for example, whether a water tank or a fan is in fault is checked.
The method comprises the steps of obtaining equipment state information collected by a field sensor arranged on equipment to be monitored; determining a state parameter value and a state parameter change value according to the equipment state information, and fuzzifying the state parameter value and the state parameter change value to obtain a state parameter output value; acquiring a preset reference range, and judging whether the state parameter output value is in the preset reference range; and when the state parameter output value is not in the preset reference range, judging that the equipment to be monitored has a fault. For just judging equipment trouble after the unusual condition appears in current equipment, the running state of equipment is judged through the state information fuzzification and then with the contrast of predetermined reference range to this embodiment above-mentioned mode of equipment, and this embodiment above-mentioned mode can be in advance prejudged the running state of equipment to adopt remote monitoring, the equipment monitoring that makes is more convenient, just closes the loss that leads to after avoiding equipment unusual.
Referring to fig. 3, fig. 3 is a flowchart illustrating a remote device monitoring method according to a second embodiment of the present invention.
Based on the first embodiment described above, in the present embodiment, the step S20 includes:
step S201: and determining a state parameter value and a state parameter change value according to the equipment state information, and determining a state parameter value range corresponding to the state parameter value.
It should be noted that the device state parameter value acquired by the field sensor is in a range, that is, may be a state parameter value range, for example, the state parameter value range corresponding to the temperature parameter is 0 to 100, the amplitude state parameter value range is 0 to 12, then 0 to 100, 0 to 12 are the temperature parameter, and the state parameter value range corresponding to the amplitude parameter.
Step S202: and determining a feasible interval according to the value range of the state parameter value.
It should be noted that the feasible interval may be an interval obtained by equally dividing the value range of the state parameter value into a preset number of intervals according to the number of preset intervals, where a difference value of each interval is the feasible interval, for example, the value range of the state parameter value is 1 to 12, the value range of the state parameter value is divided into 8 intervals, which are respectively 0 to 1.5, 1.5 to 3, 3 to 4.5, 4.5 to 6, 6 to 7.5, 7.5 to 9, 9 to 10.5, and 10.5 to 12, the feasible interval is 1.5, and then 1.5, 3, 4.5, 6, 7.5, 9, and 10.5 are respectively represented by corresponding NB, NM, NS, ZO, PS, PM, and PB in a preset fuzzy rule table. The preset number of intervals may be the number of intervals determined according to a preset fuzzy rule table, and the preset fuzzy rule table has 7 values NB, NM, NS, ZO, PS, PM, PB, which correspond to 1.5, 3, 4.5, 6, 7.5, 9, 10.5, respectively, and represent 8 intervals: 0-1.5,1.5-3,3-4.5,4.5-6,6-7.5, 7.5-9,9-10.5, 10.5-12. The preset fuzzy rule table is shown in fig. 4, and fig. 4 is the preset fuzzy rule table in the second embodiment of the remote device monitoring method of the present invention, where E in the table represents the state parameter value, EC represents the state parameter variation value, and U represents the state parameter value and the membership value in the table corresponding to the state parameter variation value. The membership value corresponds to a value corresponding to a crossing point in a preset fuzzy rule table according to the state parameter value and the state parameter variation value, for example, when E is 1.5, it corresponds to NB, when EC is 1.5, it also corresponds to NB, according to the preset fuzzy rule table, the membership value in the preset fuzzy rule table of fig. 4 corresponding to the state parameter value represented by U and the state parameter variation value is PB, and according to the above description, the value corresponding to PB is 10.5.
Step S203: and determining a parameter value membership interval of the state parameter value according to the feasible interval and the state parameter value.
It should be noted that the parameter value membership interval may be a membership interval corresponding to the state parameter value in the preset fuzzy rule table, for example, when the state parameter value is 4, the value range of the state parameter value is 1-12, and the feasible interval is 1.5, then NB, NM, NS, ZO, PS, PM, PB in the preset fuzzy rule table respectively correspond to 1.5, 3, 4.5, 6, 7.5, 9, 10.5, it is known that the state parameter value 4 is between 3 and 4.5, and the parameter value membership interval corresponding to the state parameter value 4 is between NM and NS in the corresponding fuzzy rule table.
Step S204: and determining a state parameter change value membership interval of the state parameter change value according to the feasible interval and the state parameter change value.
It should be noted that the state parameter change value membership interval may be a membership interval corresponding to the state parameter change value in the preset fuzzy rule table, for example, when the state parameter change value is 4, the value range of the state parameter change value and the value range of the state parameter value are the same as 1 to 12, the feasible interval of the state parameter change value and the feasible interval of the state parameter value are the same as 1.5, then NB, NM, NS, ZO, PS, PM, PB in the EC in the first row in the preset fuzzy rule table correspond to 1.5, 3, 4.5, 6, 7.5, 9, 10.5, respectively, and it is known that the state parameter change value 4 is between 3 and 4.5, and the corresponding membership interval between NM and NS in the fuzzy rule table is NM and NS, then the state parameter change value membership interval corresponding to the state parameter change value 4 is NM and NS.
Step S205: and determining the state parameter output value according to a preset fuzzy rule table, the state parameter value, the state parameter change value, the state parameter value membership interval and the state parameter change value membership interval.
Further, the step of determining the output value of the state parameter according to a preset fuzzy rule table, the value of the state parameter, the variation value of the state parameter, the membership interval of the value of the state parameter and the membership interval of the variation value of the state parameter includes:
step S2050: and determining the parameter value membership degree corresponding to the state parameter value according to the state parameter value membership interval and the state parameter value.
It should be understood that NB, NM, NS, ZO, PS, PM, PB in the preset fuzzy rule table represent specific values, and the status parameter values are not necessarily exactly equal to the values corresponding to NB, NM, NS, ZO, PS, PM, PB in the preset fuzzy rule table, so that, in most cases, the status parameter values occupy two intervals in the preset fuzzy rule table, for example, NB corresponds to 1.5, NM corresponds to 3, and the status parameter value is 2, and the status parameter value is between NB and NM, at this time, the parameter value membership degree of the two intervals corresponding to the status parameter values respectively needs to be calculated, the parameter value membership degree of the status parameter value belonging to the NB (1.5) interval is calculated as (2-1.5)/(3-1.5) 1/3, the membership degree of the status parameter value belonging to the NM (3) interval is calculated as (3-2)/(3-1.5) 1/3, in some cases, the possible state parameter values are exactly equal to the values corresponding to NB, NM, NS, ZO, PS, PM, PB in the preset fuzzy rule table, for example, when the value corresponding to NS is 4.5, the state parameter values are exactly equal to 4.5, at this time, only one parameter value membership interval in the fuzzy rule table corresponding to the state parameter values is NS, and the membership degree of the corresponding parameter value is 1.
Step S2051: and determining the parameter variation value membership degree corresponding to the state parameter variation value according to the state parameter variation value membership interval and the state parameter variation value.
It should be understood that NB, NM, NS, ZO, PS, PM, PB in the preset fuzzy rule table represent specific values, and the state parameter variation value does not necessarily exactly equal to the corresponding value of NB, NM, NS, ZO, PS, PM, PB in the preset fuzzy rule table, so that in most cases, the state parameter variation value occupies two intervals in the preset fuzzy rule table, for example, NB corresponds to 1.5, NM corresponds to 3, the state parameter variation value is 2, the state parameter variation value is between NB and NM, at this time, the parameter variation value membership degrees of the two intervals corresponding to the state parameter variation values respectively need to be calculated, the parameter variation value membership degree of the state parameter variation value belonging to the NB (1.5) interval is calculated as (2-1.5)/(3-1.5)/(1/3), and the parameter variation value of the state parameter variation value (3) interval is calculated as (3-2)/(3-2.5)/(3-2) 1/3, in some cases, the value of the state parameter variation may be just equal to the value corresponding to NB, NM, NS, ZO, PS, PM, PB in the preset fuzzy rule table, for example, when the value corresponding to NS is 4.5, the value of the state parameter variation is just equal to 4.5, and at this time, the value of the parameter variation in the fuzzy rule table corresponding to the state parameter variation is only NS, and the degree of membership of the corresponding parameter variation is 1.
Step S2052: and searching a corresponding membership value in the preset fuzzy rule table according to the status parameter value membership interval and the status parameter change value membership interval.
It should be noted that the membership value is a cross part of the status parameter value membership interval and the status parameter change value membership interval in the preset fuzzy rule table, for example, the status parameter value membership interval is NB and NM, and the status parameter change value membership interval is NS and ZO, and then according to the preset fuzzy rule table, the corresponding membership value is: PB, PM. As shown in fig. 5, fig. 5 is a schematic diagram of membership values corresponding to a status parameter value membership interval and a status parameter variation value membership interval in a second embodiment of the remote device monitoring method according to the present invention.
Step S2053: and determining the state parameter output value according to the parameter value membership degree, the parameter change value membership degree and the membership value.
It should be noted that, the determining the output value of the state parameter according to the membership degree of the parameter value, the membership degree of the parameter variation value and the membership value may be according to a preset fuzzy rule table, and multiplying the membership degrees corresponding to the membership values in the table respectively and adding them together, for example, as shown in fig. 5, the membership interval of the state parameter variation value is NB and NM, and the membership interval of the state parameter value is NS and ZO, and according to the preset fuzzy rule table, the corresponding membership values are: PB and PM. Assuming that the membership degree of the state parameter value belonging to NB is a, it is known that the membership degree of the state parameter value belonging to NM is 1-a, which can be obtained by calculation, but in practice, when the state parameter value belongs to two intervals, the membership degrees of the state parameter values belonging to the two intervals are added to be 1, for convenience of explanation, it is directly explained by a and 1-a, the change value of the state parameter belonging to NS is b, and it is 1-b, and at this time, calculation is performed according to the corresponding membership value in the fuzzy rule table, the calculation formula of the output value of the state parameter is PB a + PM (1-a) + PM (1-b) + PM (1-a), and finally, the values of PM and PB can be substituted into the numerical value formula corresponding to the values of PM and PB, and obtaining the final state parameter output value.
Further, to better illustrate the determination of the state parameter output value, in some cases, for example, the state parameter value is exactly equal to the value of the corresponding NS in the fuzzy rule table, assuming that 4.5 is used, the state parameter value membership range is NS, the parameter value membership degree corresponding to the state parameter value is 1, at this time, the state parameter change value membership range corresponding to the state parameter change value 5 is NS (4.5) and ZO (6), the corresponding parameter change value membership degrees are 1/3 and 2/3, the corresponding membership values of the state parameter value membership range and the state parameter change value membership range in the preset fuzzy rule table are PM and PS, and the state parameter output value is PM 1 1/3+ PS 1 2/3 ═ 9 + 1/3+7.5 ═ 2/3 ═ 8.
The embodiment determines a value range of the state parameter value corresponding to the state parameter value; determining a feasible interval according to the value range of the state parameter value; determining a parameter value membership interval of the state parameter value according to the feasible interval and the state parameter value; determining a state parameter change value membership interval of the state parameter change value according to the feasible interval and the state parameter change value; and determining the state parameter output value according to a preset fuzzy rule table, the state parameter value, the state parameter change value, the state parameter value membership interval and the state parameter change value membership interval. The running state of the equipment to be monitored is judged according to the state parameter output value, the running state of the equipment can be predicted in advance, early warning work is well done, and loss caused by the fact that the equipment can be found and stopped running when the equipment breaks down is reduced.
Referring to fig. 6, fig. 6 is a flowchart illustrating a remote device monitoring method according to a third embodiment of the present invention.
Based on the foregoing embodiments, in this embodiment, before the step S30, the method further includes:
step S206: and acquiring normal state information of the equipment to be monitored in normal operation.
It should be noted that the normal state information may be device operation information acquired by the device to be monitored during normal operation, and may be information of amplitude, temperature, rotation speed, and the like, as well as information acquired in history, which is not limited herein. The determination of whether the device is operating normally may be based on manual determination or other manners, and the embodiment is not limited herein.
Step S207: and fuzzifying the normal state information to obtain a fuzzy result.
It should be understood that, the step of fuzzifying the normal state information to obtain the fuzzy result may be to obtain a normal parameter value and a normal parameter variation value according to the normal state information, and use the normal parameter value and the normal parameter variation value as the state parameter value and the state parameter variation value, and fuzzify the normal state information according to the step of fuzzifying the state parameter value and the state parameter variation value in the above embodiment to obtain the fuzzy result. The fuzzy result may be an interval in a preset fuzzy rule table corresponding to a normal parameter value and a normal parameter variation value in the normal state information, respectively.
Step S208: and determining a state reference value corresponding to the normal state information according to the fuzzy result and the preset fuzzy rule table.
It should be noted that the state reference value may be a state parameter output value corresponding to the normal state information determined according to the fuzzy result and the preset fuzzy rule table. The step may be actually to change the device status information in the step S10 to the normal status information and execute the step S20 to obtain the status parameter output value corresponding to the normal status information. And taking the state parameter output value obtained by calculation according to the normal state information as the state reference value.
Step S209: and constructing a preset reference range according to the state reference value.
It should be understood that the data generated by the device may be considered as normal as long as the data is within a certain range, and therefore, the device may not only rely on a group of normal data as a reference value, and a preset reference range should be constructed by collecting a large amount of state data of the device in normal operation, for example, after the above processing of the normal state information of the device to be monitored, the obtained state reference values are 1.1,2.3,4.0,3.3.. are all between 1 and 4, 1 to 4 are taken as the state reference values, and when the state parameter output value calculated according to the device state information of the device to be monitored does not belong to 1 to 4, it may be determined that the device to be monitored is abnormal, and the reason of the abnormality may be damage of the control component or damage of other components of the parameter corresponding to the state parameter output value, for example, the parameter currently used to calculate the state parameter output value is temperature, it can be determined that the temperature control part of the device to be monitored is damaged.
Further, in order that a user can more intuitively know the operation condition of the device, after the step of judging whether the output value of the state parameter is within the preset reference range, the method further comprises: when the state parameter output value is within the preset reference range, generating a monitoring record of the equipment to be monitored; and sending the monitoring record to a target user terminal.
It should be understood that the monitoring record may include currently monitored parameters such as temperature, amplitude, rotational speed, etc. And the output value of the state parameter corresponding to the parameter, such as 1.2 of the state parameter corresponding to the temperature, 4 of the state parameter corresponding to the amplitude, and the like, and the preset reference range corresponding to each parameter. So that the user can know the working state of each component of the equipment and the relation with the preset reference range according to the monitoring record. In special cases, when the output value of the state parameter is not about to be within the preset reference range, the maintenance can be started.
Further, in order to reduce the loss caused by the operation of the device when the device is failed and the loss caused by the failure of the device to be monitored, after the step of determining that the device to be monitored is failed when the output value of the state parameter is not within the preset reference range, the method further includes: sending parameter information corresponding to the state parameter output value which is not in the preset reference range to an equipment maintenance terminal; and after a maintenance completion instruction based on the equipment maintenance terminal feedback is received, the equipment to be monitored is patrolled and examined to generate a patrol and examine record.
It should be understood that the equipment maintenance terminal may be a terminal of a maintenance person corresponding to the equipment to be monitored, for example, a computer, a mobile phone, so that the maintenance personnel can perform corresponding maintenance according to the parameter information, wherein the parameter information can be parameters and parameter values corresponding to the state parameter output values which are not in the preset reference range, and the state parameter output values and the preset reference range corresponding to the parameters, the polling of the device to be monitored may be to acquire device state information acquired by a field sensor provided on the device to be monitored after receiving a maintenance completion instruction fed back by the device maintenance terminal, and determining the state parameter output value of each parameter of the equipment to be monitored according to the equipment state information, and generating a routing inspection record according to the state parameter output value and a preset reference range.
In the embodiment, normal state information of the device to be monitored during normal operation is acquired; fuzzifying the normal state information to obtain a fuzzy result; determining a state reference value corresponding to the normal state information according to the fuzzy result and the preset fuzzy rule table; and constructing a preset reference range according to the state reference value. In the embodiment, the preset reference range is established through the normal state information of the to-be-monitored equipment in normal operation, the preset reference range is compared with the state parameter output value determined by the equipment state information acquired by the field sensor arranged on the to-be-monitored equipment, whether the to-be-monitored equipment is abnormal or not is judged, the monitoring record of the to-be-monitored equipment is generated, when the to-be-monitored equipment is judged to be in fault, the operation of the to-be-monitored equipment is stopped in time, maintenance personnel is notified to maintain, the loss in the process of equipment fault is reduced, and a user judges whether the equipment is about to be in fault or not according to the monitoring.
Referring to fig. 7, fig. 7 is a block diagram of a first embodiment of the remote device monitoring apparatus according to the present invention.
As shown in fig. 7, a remote device monitoring apparatus according to an embodiment of the present invention includes an obtaining module 10, a fuzzy module 20, a determining module 30, and a failure module 40;
the acquiring module 10 is configured to acquire device state information acquired by a field sensor arranged on a device to be monitored;
the fuzzy module 20 is configured to determine a state parameter value and a state parameter change value according to the device state information, and perform fuzzification on the state parameter value and the state parameter change value to obtain a state parameter output value;
the judging module 30 is configured to obtain a preset reference range, and judge whether the state parameter output value is within the preset reference range;
and the fault module 40 is configured to determine that the device to be monitored is faulty when the state parameter output value is not within the preset reference range.
The method comprises the steps of obtaining equipment state information collected by a field sensor arranged on equipment to be monitored; determining a state parameter value and a state parameter change value according to the equipment state information, and fuzzifying the state parameter value and the state parameter change value to obtain a state parameter output value; acquiring a preset reference range, and judging whether the state parameter output value is in the preset reference range; and when the state parameter output value is not in the preset reference range, judging that the equipment to be monitored has a fault. For just judging equipment trouble after the unusual condition appears in current equipment, the running state of equipment is judged through the state information fuzzification and then with the contrast of predetermined reference range to this embodiment above-mentioned mode of equipment, and this embodiment above-mentioned mode can be in advance prejudged the running state of equipment to adopt remote monitoring, the equipment monitoring that makes is more convenient, just closes the loss that leads to after avoiding equipment unusual.
It should be noted that the above-described work flows are only exemplary, and do not limit the scope of the present invention, and in practical applications, a person skilled in the art may select some or all of them to achieve the purpose of the solution of the embodiment according to actual needs, and the present invention is not limited herein.
In addition, the technical details that are not described in detail in this embodiment may refer to the parameter operation method provided in any embodiment of the present invention, and are not described herein again.
Based on the first embodiment of the remote device monitoring apparatus of the present invention, a second embodiment of the remote device monitoring apparatus of the present invention is provided.
In this embodiment, the fuzzy module 20 is further configured to determine a status parameter value and a historical status parameter value corresponding to the status parameter value according to the device status information; determining a state parameter value difference value according to the state parameter value and the historical state parameter value; and determining a state parameter change value according to the state parameter value difference.
Further, the fuzzy module 20 is further configured to determine a value range of the state parameter corresponding to the state parameter; determining a feasible interval according to the value range of the state parameter value; determining a parameter value membership interval of the state parameter value according to the feasible interval and the state parameter value; determining a state parameter change value membership interval of the state parameter change value according to the feasible interval and the state parameter change value; and determining the state parameter output value according to a preset fuzzy rule table, the state parameter value, the state parameter change value, the state parameter value membership interval and the state parameter change value membership interval.
Further, the fuzzy module 20 is further configured to determine a parameter value membership degree corresponding to the state parameter value according to the state parameter value membership interval and the state parameter value; determining the parameter variation value membership degree corresponding to the state parameter variation value according to the state parameter variation value membership interval and the state parameter variation value; searching a corresponding membership value in the preset fuzzy rule table according to the status parameter value membership interval and the status parameter change value membership interval; and determining the state parameter output value according to the parameter value membership degree, the parameter change value membership degree and the membership value.
Further, the fuzzy module 20 is further configured to obtain normal state information of the device to be monitored during normal operation; fuzzifying the normal state information to obtain a fuzzy result; determining a state reference value corresponding to the normal state information according to the fuzzy result and the preset fuzzy rule table; and constructing a preset reference range according to the state reference value.
Further, the fault module 40 is further configured to generate a monitoring record of the device to be monitored when the state parameter output value is within the preset reference range; and sending the monitoring record to a target user terminal.
Further, the fault module 40 is further configured to send parameter information corresponding to the state parameter output value that is not within the preset reference range to an equipment maintenance terminal; and after a maintenance completion instruction based on the equipment maintenance terminal feedback is received, the equipment to be monitored is patrolled and examined to generate a patrol and examine record.
Other embodiments or specific implementation manners of the remote device monitoring apparatus of the present invention may refer to the above method embodiments, and are not described herein again.
In addition, an embodiment of the present invention further provides a storage medium, where a remote device monitoring program is stored on the storage medium, and the remote device monitoring program, when executed by a processor, implements the steps of the remote device monitoring method described above.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system 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 system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., a rom/ram, a magnetic disk, an optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A remote device monitoring method, comprising the steps of:
acquiring equipment state information acquired by a field sensor arranged on equipment to be monitored;
determining a state parameter value and a state parameter change value according to the equipment state information, and fuzzifying the state parameter value and the state parameter change value to obtain a state parameter output value;
acquiring a preset reference range, and judging whether the state parameter output value is in the preset reference range;
and when the state parameter output value is not in the preset reference range, judging that the equipment to be monitored has a fault.
2. The remote device monitoring method of claim 1, wherein said step of determining a value of a status parameter and a value of a change in a status parameter based on said device status information comprises:
determining a state parameter value and a historical state parameter value corresponding to the state parameter value according to the equipment state information;
determining a state parameter value difference value according to the state parameter value and the historical state parameter value;
and determining a state parameter change value according to the state parameter value difference.
3. The remote device monitoring method of claim 1, wherein said step of obfuscating said status parameter value and said status parameter change value to obtain a status parameter output value comprises:
determining a state parameter value range corresponding to the state parameter value;
determining a feasible interval according to the value range of the state parameter value;
determining a parameter value membership interval of the state parameter value according to the feasible interval and the state parameter value;
determining a state parameter change value membership interval of the state parameter change value according to the feasible interval and the state parameter change value;
and determining the state parameter output value according to a preset fuzzy rule table, the state parameter value, the state parameter change value, the state parameter value membership interval and the state parameter change value membership interval.
4. The remote device monitoring method of claim 3, wherein the step of determining the output value of the state parameter according to a preset fuzzy rule table, the value of the state parameter, the variation value of the state parameter, the membership interval of the value of the state parameter, and the membership interval of the variation value of the state parameter comprises:
determining parameter value membership degrees corresponding to the state parameter values according to the state parameter value membership intervals and the state parameter values;
determining the parameter variation value membership degree corresponding to the state parameter variation value according to the state parameter variation value membership interval and the state parameter variation value;
searching a corresponding membership value in the preset fuzzy rule table according to the status parameter value membership interval and the status parameter change value membership interval;
and determining the state parameter output value according to the parameter value membership degree, the parameter change value membership degree and the membership value.
5. The remote device monitoring method of claim 1, wherein said step of obtaining a preset reference range is preceded by the method further comprising:
acquiring normal state information of the equipment to be monitored in normal operation;
fuzzifying the normal state information to obtain a fuzzy result;
determining a state reference value corresponding to the normal state information according to the fuzzy result and the preset fuzzy rule table;
and constructing a preset reference range according to the state reference value.
6. The remote device monitoring method of any one of claims 1 to 5, wherein after the step of determining whether the state parameter output value is within the preset reference range, the method further comprises:
when the state parameter output value is within the preset reference range, generating a monitoring record of the equipment to be monitored;
and sending the monitoring record to a target user terminal.
7. The remote device monitoring method according to any one of claims 1 to 6, wherein after the step of determining that the device to be monitored is malfunctioning when the state parameter output value is not within the preset reference range, the method further comprises:
sending parameter information corresponding to the state parameter output value which is not in the preset reference range to an equipment maintenance terminal;
and after a maintenance completion instruction based on the equipment maintenance terminal feedback is received, the equipment to be monitored is patrolled and examined to generate a patrol and examine record.
8. A remote equipment monitoring device is characterized by comprising an acquisition module, a fuzzy module, a judgment module and a fault module;
the acquisition module is used for acquiring equipment state information acquired by a field sensor arranged on the equipment to be monitored;
the fuzzy module is used for determining a state parameter value and a state parameter change value according to the equipment state information, and fuzzifying the state parameter value and the state parameter change value to obtain a state parameter output value;
the judging module is used for acquiring a preset reference range and judging whether the state parameter output value is in the preset reference range;
and the fault module is used for judging that the equipment to be monitored is in fault when the state parameter output value is not in the preset reference range.
9. A remote device monitoring apparatus, the apparatus comprising: memory, a processor and a remote device monitoring program stored on the memory and executable on the processor, the remote device monitoring program being configured to implement the steps of the remote device monitoring method according to any of claims 1 to 7.
10. A storage medium having stored thereon a remote device monitoring program which, when executed by a processor, carries out the steps of the remote device monitoring method according to any one of claims 1 to 7.
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