CN116820014A - Intelligent monitoring and early warning method and system for traffic electromechanical equipment - Google Patents

Intelligent monitoring and early warning method and system for traffic electromechanical equipment Download PDF

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CN116820014A
CN116820014A CN202311069532.6A CN202311069532A CN116820014A CN 116820014 A CN116820014 A CN 116820014A CN 202311069532 A CN202311069532 A CN 202311069532A CN 116820014 A CN116820014 A CN 116820014A
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deviation
parameter
electromechanical
traffic
real
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CN116820014B (en
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王晓龙
杨莹
王瑜波
***
柴辉照
张佳鹏
郭晓澎
李靖宇
李赟骁
许鑫
王辉
刘少帅
杨明辉
陈小兵
霍思远
张健健
李靖博
冯永飞
樊恩成
苏贵君
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Shanxi Transportation Research Institute Group Co ltd
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Shanxi Transportation Research Institute Group Co ltd
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    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00Programme-control systems
    • G05B19/02Programme-control systems electric
    • G05B19/04Programme control other than numerical control, i.e. in sequence controllers or logic controllers
    • G05B19/042Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
    • G05B19/0428Safety, monitoring
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00Program-control systems
    • G05B2219/20Pc systems
    • G05B2219/24Pc safety
    • G05B2219/24024Safety, surveillance

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  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention discloses an intelligent monitoring and early warning method and system for traffic electromechanical equipment, which relate to the technical field of intelligent monitoring and comprise the following steps: establishing a standard operation parameter array of the electromechanical equipment; establishing a historical operation parameter matrix of the electromechanical equipment; a historical operating bias matrix for the electromechanical device; screening out the worst parameter set of the historical operation; judging whether the traffic electromechanical equipment has hidden risks or not; obtaining a real-time operation parameter matrix of the electromechanical equipment; obtaining a real-time operation deviation array; judging whether the traffic electromechanical equipment is in a normal working state or not based on the running deviation array of the electromechanical equipment; and updating the historical operation parameters of the traffic system. The invention has the advantages that: through comprehensive analysis of operation parameters of the traffic electromechanical equipment, intelligent early warning and monitoring can be effectively carried out on hidden danger existing in the traffic electromechanical equipment, so that timely troubleshooting of a traffic system is realized, and stable operation of the traffic system is ensured.

Description

Intelligent monitoring and early warning method and system for traffic electromechanical equipment
Technical Field
The invention relates to the technical field of unit monitoring, in particular to an intelligent monitoring and early warning method and system for traffic electromechanical equipment.
Background
In the prior art, aiming at the maintenance mode of the traffic electromechanical equipment, a mode of scheduled maintenance and fault rush-repair is generally adopted, the scheduled maintenance lacks comprehensive analysis of the operation parameters of the traffic electromechanical equipment, intelligent early warning is difficult to carry out according to hidden danger of the traffic electromechanical equipment, excessive maintenance is easy to generate, namely the electromechanical equipment without hidden danger is maintained, so that the waste of maintenance resources is caused, the fault rush-repair can be generally identified only when the electromechanical equipment breaks down, traffic shutdown is easy to occur during the rush-repair, and operation loss is caused.
Disclosure of Invention
In order to solve the technical problems, the technical scheme provides an intelligent monitoring and early warning method and system for the traffic electromechanical equipment, and solves the problems that in the prior art, aiming at the maintenance mode of the traffic electromechanical equipment, a mode of planned maintenance and fault rush-repair is generally adopted, the planned maintenance lacks comprehensive analysis on the operation parameters of the traffic electromechanical equipment, intelligent early warning is difficult to carry out according to hidden danger of the traffic electromechanical equipment, excessive maintenance is easy to generate, the fault rush-repair can be usually identified only when the electromechanical equipment breaks down, traffic rush-repair is easy to occur, and operation loss is caused.
In order to achieve the above purpose, the invention adopts the following technical scheme: an intelligent monitoring and early warning method for traffic electromechanical equipment comprises the following steps: acquiring standard operation parameters of all electromechanical devices in a traffic system, and establishing a standard operation parameter array of the electromechanical devices; a plurality of historical operation parameters of all electromechanical devices in the traffic system are retrieved, and a historical operation parameter matrix of the electromechanical devices is established; performing a historical operating deviation matrix of the electromechanical device based on the historical operating parameter matrix of the electromechanical device and a standard operating parameter array of the electromechanical device; screening out a history operation worst parameter set based on a history operation deviation matrix of the electromechanical equipment; judging whether the traffic electromechanical equipment has hidden risks or not based on the history operation worst parameter set, if so, outputting an early warning signal, and if not, not outputting any; the method comprises the steps of collecting operation parameters of all electromechanical devices in a traffic system in real time according to a preset time interval in a monitoring period to obtain a real-time operation parameter matrix of the electromechanical devices; based on the real-time operation parameter matrix of the electromechanical equipment, calculating an operation deviation array of the electromechanical equipment in the monitoring period to obtain a real-time operation deviation array; judging whether the traffic electromechanical equipment is in a normal working state or not based on the running deviation array of the electromechanical equipment, if so, not outputting any, and if not, outputting an alarm signal; based on the real-time operating parameter matrix of the electromechanical device, historical operating parameters of the traffic system are updated.
Preferably, the performing the historical operation deviation matrix of the electromechanical device based on the historical operation parameter matrix of the electromechanical device and the standard operation parameter array of the electromechanical device specifically includes:
based on the standard operation parameter array of the electromechanical equipment, calculating a deviation array of each group of historical operation parameters to obtain a plurality of historical operation deviation arrays
Combining all the historical operation deviation arrays into a historical operation deviation matrix
The calculating of the deviation array of each group of historical operation parameters specifically comprises:wherein (1)>Deviation value between the j-th parameter, which is the i-th set of historical operating parameters, and the standard operating parameters,/>Parameter value of the j-th parameter, which is the i-th set of historical operating parameters,/for the i-th set of historical operating parameters>Standard parameter value for the j-th parameter, < ->Is the total number of operating parameters; the historical operating deviation matrix is specifically:where n is the total number of historical operating parameter sets.
Preferably, the screening the historical operation worst parameter set based on the historical operation deviation matrix of the electromechanical device specifically includes: screening the maximum value of the deviation value of each parameter from the historical operation deviation matrix to be used as the worst deviation value of the parameter; combining the worst deviation values of all parameters into a historical operation worst parameter setThe method comprises the steps of carrying out a first treatment on the surface of the The history operation worst parameter set specifically comprises: />In the method, in the process of the invention,is the worst bias value for the j-th parameter.
Preferably, the determining whether the traffic electromechanical device has an implicit risk based on the history operation worst parameter set specifically includes: calculating the worst operation index of all electromechanical devices in the traffic system based on the historical operation worst parameter set; judging whether the worst operation index is higher than an operation index preset value, if so, judging that the traffic electromechanical equipment has hidden risk, outputting an early warning signal, and if not, judging that the traffic electromechanical equipment operates normally and does not do any output; wherein, the calculation formula of the worst operation index is as follows:in (1) the->Is the worst operation index.
Preferably, the calculating the operation deviation array of the electromechanical device in the monitoring period based on the real-time operation parameter matrix of the electromechanical device specifically includes: based on electromechanical devicesCalculating the deviation distance between each real-time operation parameter array and the standard operation parameter array of the electromechanical device through a deviation distance calculation formula to obtain a plurality of real-time deviation distance values; all the real-time deviation distance values form a real-time operation deviation array; the deviation distance calculation formula specifically comprises the following steps:in (1) the->For the offset distance between the k-th set of real-time operating parameters and the standard operating parameter set of the electromechanical device,/for>Is the parameter value of the j-th parameter in the k-th set of real-time operating parameters.
Preferably, the determining, based on the operation deviation array of the electromechanical device, whether the traffic electromechanical device is in a normal working state specifically includes: judging whether any one of the running deviation arrays has a deviation distance between the real-time running parameter array and the standard running parameter array of the electromechanical equipment or not, and judging whether the deviation distance between the real-time running parameter array and the standard running parameter array of the electromechanical equipment is larger than a running index preset value or not; if yes, judging that the working state of the traffic electromechanical equipment is abnormal; if not, judging that the working state of the traffic electromechanical equipment is normal.
Furthermore, an intelligent monitoring and early warning system for the traffic electromechanical equipment is provided, which is used for realizing the intelligent monitoring and early warning method for the traffic electromechanical equipment, and comprises the following steps: the storage module is used for storing historical operation parameters of all electromechanical devices in the traffic system and standard operation parameter arrays of the electromechanical devices; the processor is coupled with the storage module, an implicit risk analysis module and an operation monitoring module are integrated in the processor, the implicit risk analysis module is used for judging whether the traffic electromechanical device has an implicit risk or not based on the historical operation worst parameter set, and the operation monitoring module is used for judging whether the traffic electromechanical device is in a normal working state or not based on the operation deviation array of the electromechanical device; the data monitoring module is electrically connected with the processor and is used for collecting the operation parameters of all electromechanical devices in the traffic system in real time according to a preset time interval in a monitoring period; the data updating module is electrically connected with the data monitoring module and the storage module and is used for updating the historical operation parameters of the traffic system based on the real-time operation parameter matrix of the electromechanical equipment.
Optionally, the implicit risk analysis module includes: the first calculation unit is used for calculating a deviation array of each group of historical operation parameters based on a standard operation parameter array of the electromechanical equipment and combining all the historical operation deviation arrays into a historical operation deviation matrix; the screening unit is used for screening the maximum value of the deviation value of each parameter from the historical operation deviation matrix, taking the maximum value as the worst deviation value of the parameter, and combining the worst deviation values of all the parameters into a historical operation worst parameter group; the second calculation unit is used for calculating the worst operation index of all electromechanical devices in the traffic system based on the historical operation worst parameter set; the first judging unit is used for judging whether the worst operation index is higher than an operation index preset value or not.
Optionally, the operation monitoring module includes: the data processing unit is used for processing the operation parameters of the electromechanical equipment acquired by the data monitoring module into a real-time operation parameter matrix of the electromechanical equipment; the third calculation unit is used for calculating the deviation distance between each real-time operation parameter set and the standard operation parameter set of the electromechanical device through a deviation distance calculation formula based on the real-time operation parameter matrix of the electromechanical device and the standard operation parameter set of the electromechanical device, obtaining a plurality of real-time deviation distance values and forming all the real-time deviation distance values into a real-time operation deviation array; the second judging unit is used for judging whether the deviation distance between any one real-time operation parameter set in the operation deviation array and the standard operation parameter set of the electromechanical equipment is larger than the operation index preset value.
Compared with the prior art, the invention has the beneficial effects that: the invention provides an intelligent monitoring and early warning scheme of traffic electromechanical equipment, when maintenance and early warning are carried out, the historical operation parameters of the electromechanical equipment are comprehensively analyzed, the maximum value of the deviation value between the historical operation data of the electromechanical equipment and a standard operation parameter array of the electromechanical equipment is used as the worst deviation value to be comprehensively analyzed, whether the traffic electromechanical equipment has operation hidden danger is judged, the intelligent early warning is carried out according to the judging result, the maintenance is carried out according to the early warning structural domain, the hidden danger in the traffic electromechanical equipment can be effectively and pointedly maintained, the occurrence of excessive maintenance is avoided, and the maintenance resources can be effectively saved; the invention also aims at the real-time operation data of the traffic electromechanical equipment to collect and process, and identifies the abnormal state existing in the real-time operation process of the traffic electromechanical equipment, so that the abnormal state existing in the real-time operation process of the electromechanical equipment can be overhauled in time, and the traffic electromechanical equipment is prevented from being broken down, so that larger traffic operation loss is caused.
Drawings
FIG. 1 is a flow chart of an intelligent monitoring and early warning method for traffic electromechanical equipment;
FIG. 2 is a flow chart of a method of calculating a historical operating bias matrix for a computer-to-electrical device in accordance with the present invention;
FIG. 3 is a flow chart of a method for screening a history of operating worst parameter set according to the present invention;
FIG. 4 is a flow chart of a method for determining whether an implicit risk exists in a traffic electro-mechanical device according to the present invention;
FIG. 5 is a flow chart of a method of calculating an array of operating deviations of an electromechanical device during a monitoring period in accordance with the present invention;
FIG. 6 is a flow chart of a method for determining whether a traffic machine is in a normal operation state according to the present invention;
fig. 7 is a block diagram of an intelligent monitoring and early warning system of the traffic electromechanical equipment.
Detailed Description
The following description is presented to enable one of ordinary skill in the art to make and use the invention. The preferred embodiments in the following description are by way of example only and other obvious variations will occur to those skilled in the art.
Referring to fig. 1, an intelligent monitoring and early warning method for traffic electromechanical equipment includes: acquiring standard operation parameters of all electromechanical devices in a traffic system, and establishing a standard operation parameter array of the electromechanical devices; a plurality of historical operation parameters of all electromechanical devices in the traffic system are retrieved, and a historical operation parameter matrix of the electromechanical devices is established; performing a historical operating deviation matrix of the electromechanical device based on the historical operating parameter matrix of the electromechanical device and a standard operating parameter array of the electromechanical device; screening out a history operation worst parameter set based on a history operation deviation matrix of the electromechanical equipment; judging whether the traffic electromechanical equipment has hidden risks or not based on the history operation worst parameter set, if so, outputting an early warning signal, and if not, not outputting any; the method comprises the steps of collecting operation parameters of all electromechanical devices in a traffic system in real time according to a preset time interval in a monitoring period to obtain a real-time operation parameter matrix of the electromechanical devices; based on the real-time operation parameter matrix of the electromechanical equipment, calculating an operation deviation array of the electromechanical equipment in the monitoring period to obtain a real-time operation deviation array; judging whether the traffic electromechanical equipment is in a normal working state or not based on the running deviation array of the electromechanical equipment, if so, not outputting any, and if not, outputting an alarm signal; based on the real-time operating parameter matrix of the electromechanical device, historical operating parameters of the traffic system are updated.
According to the scheme, when maintenance and early warning are carried out, through comprehensively analyzing historical operation parameters of the electromechanical equipment, according to the maximum value of the deviation value between the historical operation data of the electromechanical equipment and a standard operation parameter array of the electromechanical equipment, the historical operation worst parameter set is established for comprehensive analysis, whether the traffic electromechanical equipment has operation hidden danger or not is judged, intelligent early warning is carried out according to a judging result, maintenance is carried out according to an early warning structure domain, the hidden danger in the traffic electromechanical equipment can be effectively and purposefully maintained, excessive maintenance is avoided, and maintenance resources can be effectively saved; the proposal also collects and processes the real-time operation data of the traffic electromechanical equipment, identifies the abnormal state existing in the real-time operation process of the traffic electromechanical equipment, and can timely overhaul the abnormal state existing in the real-time operation process of the electromechanical equipment, thereby avoiding the occurrence of faults of the traffic electromechanical equipment and causing larger traffic operation loss.
Referring to fig. 2, the performing the historical operating deviation matrix of the electromechanical device based on the historical operating parameter matrix of the electromechanical device and the standard operating parameter array of the electromechanical device specifically includes: based on the standard operation parameter array of the electromechanical equipment, calculating a deviation array of each group of historical operation parameters to obtain a plurality of historical operation deviation arraysThe method comprises the steps of carrying out a first treatment on the surface of the Combining all the history operation deviation arrays into a history operation deviation matrix +.>The method comprises the steps of carrying out a first treatment on the surface of the The calculating of the deviation array of each group of historical operation parameters specifically comprises: />Wherein (1)>Deviation value between the j-th parameter, which is the i-th set of historical operating parameters, and the standard operating parameters,/>Parameter value of the j-th parameter, which is the i-th set of historical operating parameters,/for the i-th set of historical operating parameters>Standard parameter value for the j-th parameter, < ->Is the total number of operating parameters; the historical operating deviation matrix is specifically:where n is the total number of historical operating parameter sets.
Referring to fig. 3, based on the historical operation deviation matrix of the electromechanical device, the screening the historical operation worst parameter set specifically includes: screening the maximum value of the deviation value of each parameter from the historical operation deviation matrix to be used as the worst deviation value of the parameter; combining the worst deviation values of all parameters into a historical operation worst parameter setThe method comprises the steps of carrying out a first treatment on the surface of the The history operation worst parameter set specifically comprises: />In (1) the->Is the worst bias value for the j-th parameter.
The parameters in the history operation worst parameter set represent the worst operation state in the history operation state of the traffic system, whether the traffic electromechanical device has hidden risks can be judged by judging the operation data of the traffic electromechanical device in the state, if the state is lower than the lowest operation standard of the electromechanical device, the hidden risks are represented by the lowest operation standard of the electromechanical device, and if the state is higher than the lowest operation standard of the electromechanical device, the hidden operation risks are not represented by the traffic system.
Referring to fig. 4, determining whether an implicit risk exists in the traffic electro-mechanical device based on the historical operation worst parameter set specifically includes: calculating the worst operation index of all electromechanical devices in the traffic system based on the historical operation worst parameter set; judging whether the worst operation index is higher than an operation index preset value, if so, judging that the traffic electromechanical equipment has hidden risk, outputting an early warning signal, and if not, judging that the traffic electromechanical equipment operates normally and does not do any output; wherein, the calculation formula of the worst operation index is:in (1) the->Is the worst operation index.
The vector distance between the worst parameter and the standard parameter value can be calculated in a combined way by comprehensively calculating the square sum of the ratio between the worst deviation value and the standard parameter value of each parameter, the vector distance is used as an index for measuring the worst running state in the traffic system, the greater the worst running index is, the farther the worst running state in the traffic system deviates from the standard running state is, the worse the worst running state of the system is, if the worst running index is greater than the preset lowest running index, the worst running state possibly existing at present in the traffic system is still above the lowest running state of the traffic system, the running state of the traffic system is good, and the hidden running risk is avoided.
Referring to fig. 5, calculating an operation deviation array of the electromechanical device in the monitoring period based on the real-time operation parameter matrix of the electromechanical device specifically includes: calculating the deviation distance between each real-time operation parameter array and the standard operation parameter array of the electromechanical device through a deviation distance calculation formula based on the real-time operation parameter matrix of the electromechanical device and the standard operation parameter array of the electromechanical device, and obtaining a plurality of real-time deviation distance values; all the real-time deviation distance values form a real-time operation deviation array C;wherein ck is the deviation distance between the k-th set of real-time operating parameters and the standard operating parameters of the electromechanical device,lthe total number of operating parameters of the electromechanical device acquired in the monitoring period; the deviation distance calculation formula specifically comprises: />In (1) the->Is the parameter value of the j-th parameter in the k-th set of real-time operating parameters.
Referring to fig. 6, determining whether the traffic electromechanical device is in a normal operating state based on the operation deviation array of the electromechanical device specifically includes: judging whether any one of the running deviation arrays has a deviation distance between the real-time running parameter array and the standard running parameter array of the electromechanical equipment or not, and judging whether the deviation distance between the real-time running parameter array and the standard running parameter array of the electromechanical equipment is larger than a running index preset value or not; if yes, judging that the working state of the traffic electromechanical equipment is abnormal; if not, judging that the working state of the traffic electromechanical equipment is normal.
By analyzing the real-time operation parameters of all electromechanical devices in the collected traffic system, the deviation distance between the real-time operation parameter set and the standard operation parameter set of the electromechanical devices is analyzed in real time, if the deviation distance between the real-time operation parameter set and the standard operation parameter set of the electromechanical devices is larger than the minimum operation standard, the operation state of the traffic system is lower than the minimum operation state of the traffic system, the traffic system is in a larger operation risk, and in order to avoid further operation faults, the traffic system needs to be overhauled integrally, so that the faults of the electromechanical devices of the traffic are avoided, and larger traffic operation losses are caused.
Further, referring to fig. 7, the present disclosure is based on the same inventive concept as the intelligent monitoring and early warning method of the traffic electromechanical device, and the present disclosure further provides an intelligent monitoring and early warning system of the traffic electromechanical device, including: the storage module is used for storing historical operation parameters of all electromechanical devices in the traffic system and standard operation parameter arrays of the electromechanical devices; the processor is coupled with the storage module, an implicit risk analysis module and an operation monitoring module are integrated in the processor, the implicit risk analysis module is used for judging whether the traffic electromechanical device has an implicit risk or not based on the historical operation worst parameter set, and the operation monitoring module is used for judging whether the traffic electromechanical device is in a normal working state or not based on the operation deviation array of the electromechanical device; the data monitoring module is electrically connected with the processor and is used for collecting the operation parameters of all electromechanical devices in the traffic system in real time according to a preset time interval in a monitoring period; the data updating module is electrically connected with the data monitoring module and the storage module and is used for updating the historical operation parameters of the traffic system based on the real-time operation parameter matrix of the electromechanical equipment.
The implicit risk analysis module comprises: the first calculation unit is used for calculating a deviation array of each group of historical operation parameters based on the standard operation parameter array of the electromechanical equipment and combining all the historical operation deviation arrays into a historical operation deviation matrix;
the screening unit is used for screening the maximum value of the deviation value of each parameter from the historical operation deviation matrix, taking the maximum value as the worst deviation value of the parameter, and combining the worst deviation values of all the parameters into a historical operation worst parameter set;
the second calculation unit is used for calculating the worst operation index of all electromechanical devices in the traffic system based on the historical operation worst parameter set;
the first judging unit is used for judging whether the worst operation index is higher than an operation index preset value.
The operation monitoring module comprises:
the data processing unit is used for processing the operation parameters of the electromechanical equipment acquired by the data monitoring module into a real-time operation parameter matrix of the electromechanical equipment;
the third calculation unit is used for calculating the deviation distance between each real-time operation parameter set and the standard operation parameter set of the electromechanical device through a deviation distance calculation formula based on the real-time operation parameter matrix of the electromechanical device and the standard operation parameter set of the electromechanical device, obtaining a plurality of real-time deviation distance values and forming all the real-time deviation distance values into a real-time operation deviation array;
the second judging unit is used for judging whether the deviation distance between any one real-time operation parameter set in the operation deviation array and the standard operation parameter set of the electromechanical equipment is larger than the operation index preset value.
The intelligent monitoring and early warning system for the traffic electromechanical equipment comprises the following use processes:
step one: the method comprises the steps that a first calculation unit retrieves historical operation parameters of the electromechanical device and standard operation parameter arrays of the electromechanical device from a memory, calculates a deviation array of each set of historical operation parameters based on the standard operation parameter arrays of the electromechanical device, and combines all the historical operation deviation arrays into a historical operation deviation matrix;
step two: the screening unit screens the maximum value of the deviation value of each parameter from the historical operation deviation matrix to be used as the worst deviation value of the parameter, and combines the worst deviation values of all the parameters into a historical operation worst parameter set;
step three: the second calculating unit calculates the worst operation index of all electromechanical devices in the traffic system based on the historical operation worst parameter set;
step four: the first judging unit judges whether the worst operation index is higher than an operation index preset value, if so, the traffic electromechanical equipment is judged to have hidden risk, an early warning signal is output, and if not, the traffic electromechanical equipment is judged to normally operate and does not do any output;
step five: the data monitoring module is used for collecting the operation parameters of all electromechanical devices in the traffic system in real time according to a preset time interval in a monitoring period, transmitting the collected operation parameters to the processor and the data updating module, and updating the historical operation parameters of the traffic system based on the real-time operation parameter matrix of the electromechanical devices by the data updating module and storing the historical operation parameters into the memory;
step six: the data processing unit processes the operation parameters of the electromechanical equipment acquired by the data monitoring module into a real-time operation parameter matrix of the electromechanical equipment;
step seven: the third calculation unit calculates the deviation distance between each real-time operation parameter array and the standard operation parameter array of the electromechanical device through a deviation distance calculation formula based on the real-time operation parameter matrix of the electromechanical device and the standard operation parameter array of the electromechanical device, obtains a plurality of real-time deviation distance values and forms all the real-time deviation distance values into a real-time operation deviation array;
step eight: the second judging unit judges whether any one of the running deviation arrays has the deviation distance between the real-time running parameter set and the standard running parameter set of the electromechanical device or not larger than the running index preset value, if so, the working state of the electromechanical device of the traffic is abnormal, and if not, the working state of the electromechanical device of the traffic is normal.
In summary, the invention has the advantages that: through comprehensive analysis of operation parameters of the traffic electromechanical equipment, intelligent early warning and monitoring can be effectively carried out on hidden danger existing in the traffic electromechanical equipment, so that timely troubleshooting of a traffic system is realized, and stable operation of the traffic system is ensured.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made therein without departing from the spirit and scope of the invention, which is defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (9)

1. An intelligent monitoring and early warning method for traffic electromechanical equipment is characterized by comprising the following steps:
acquiring standard operation parameters of all electromechanical devices in a traffic system, and establishing a standard operation parameter array of the electromechanical devices;
a plurality of historical operation parameters of all electromechanical devices in the traffic system are retrieved, and a historical operation parameter matrix of the electromechanical devices is established;
performing a historical operating deviation matrix of the electromechanical device based on the historical operating parameter matrix of the electromechanical device and a standard operating parameter array of the electromechanical device;
screening out a history operation worst parameter set based on a history operation deviation matrix of the electromechanical equipment;
judging whether the traffic electromechanical equipment has hidden risks or not based on the history operation worst parameter set, if so, outputting an early warning signal, and if not, not outputting any;
the method comprises the steps of collecting operation parameters of all electromechanical devices in a traffic system in real time according to a preset time interval in a monitoring period to obtain a real-time operation parameter matrix of the electromechanical devices;
based on the real-time operation parameter matrix of the electromechanical equipment, calculating an operation deviation array of the electromechanical equipment in the monitoring period to obtain a real-time operation deviation array;
judging whether the traffic electromechanical equipment is in a normal working state or not based on the running deviation array of the electromechanical equipment, if so, not outputting any, and if not, outputting an alarm signal;
based on the real-time operating parameter matrix of the electromechanical device, historical operating parameters of the traffic system are updated.
2. The intelligent monitoring and early warning method for the electromechanical device of the traffic according to claim 1, wherein the step of performing the historical operation deviation matrix of the electromechanical device based on the historical operation parameter matrix of the electromechanical device and the standard operation parameter array of the electromechanical device specifically comprises the steps of: based on the standard operation parameter array of the electromechanical equipment, calculating a deviation array of each group of historical operation parameters to obtain a plurality of historical operation deviation arraysThe method comprises the steps of carrying out a first treatment on the surface of the Combining all the history operation deviation arrays into a history operation deviation matrix +.>
The calculating of the deviation array of each group of historical operation parameters specifically comprises:wherein (1)>Deviation value between the j-th parameter, which is the i-th set of historical operating parameters, and the standard operating parameters,/>Parameter value of the j-th parameter, which is the i-th set of historical operating parameters,/for the i-th set of historical operating parameters>Is the firstStandard parameter values for j parameters, +.>Is the total number of operating parameters;
the historical operating deviation matrix is specifically:where n is the total number of historical operating parameter sets.
3. The intelligent monitoring and early warning method for the electromechanical traffic equipment according to claim 2, wherein the screening out the historical operation worst parameter set based on the historical operation deviation matrix of the electromechanical traffic equipment specifically comprises:
screening the maximum value of the deviation value of each parameter from the historical operation deviation matrix to be used as the worst deviation value of the parameter;
combining the worst deviation values of all parameters into a historical operation worst parameter set
The history operation worst parameter set specifically comprises:in (1) the->Is the worst bias value for the j-th parameter.
4. The intelligent monitoring and early warning method for a traffic electromechanical device according to claim 3, wherein the determining whether the traffic electromechanical device has an implicit risk based on the historical operation worst parameter set specifically comprises:
calculating the worst operation index of all electromechanical devices in the traffic system based on the historical operation worst parameter set;
judging whether the worst operation index is higher than an operation index preset value, if so, judging that the traffic electromechanical equipment has hidden risk, outputting an early warning signal, and if not, judging that the traffic electromechanical equipment operates normally and does not do any output;
wherein, the calculation formula of the worst operation index is as follows:
in (1) the->Is the worst operation index.
5. The intelligent monitoring and early warning method for the electromechanical device of the traffic according to claim 4, wherein the calculating the operation deviation array of the electromechanical device in the monitoring period based on the real-time operation parameter matrix of the electromechanical device specifically comprises:
calculating the deviation distance between each real-time operation parameter array and the standard operation parameter array of the electromechanical device through a deviation distance calculation formula based on the real-time operation parameter matrix of the electromechanical device and the standard operation parameter array of the electromechanical device, and obtaining a plurality of real-time deviation distance values; all the real-time deviation distance values form a real-time operation deviation array; the deviation distance calculation formula specifically comprises the following steps:
in (1) the->For the offset distance between the k-th set of real-time operating parameters and the standard operating parameter set of the electromechanical device,/for>Is the parameter value of the j-th parameter in the k-th set of real-time operating parameters.
6. The intelligent monitoring and early warning method for the traffic electromechanical device according to claim 5, wherein the determining whether the traffic electromechanical device is in a normal working state based on the running deviation array of the electromechanical device specifically comprises:
judging whether any one of the running deviation arrays has a deviation distance between the real-time running parameter array and the standard running parameter array of the electromechanical equipment or not, and judging whether the deviation distance between the real-time running parameter array and the standard running parameter array of the electromechanical equipment is larger than a running index preset value or not;
if yes, judging that the working state of the traffic electromechanical equipment is abnormal;
if not, judging that the working state of the traffic electromechanical equipment is normal.
7. An intelligent monitoring and early warning system for a traffic electromechanical device, for implementing the intelligent monitoring and early warning method for the traffic electromechanical device according to any one of claims 1 to 6, comprising:
the storage module is used for storing historical operation parameters of all electromechanical devices in the traffic system and standard operation parameter arrays of the electromechanical devices;
the processor is coupled with the storage module, an implicit risk analysis module and an operation monitoring module are integrated in the processor, the implicit risk analysis module is used for judging whether the traffic electromechanical device has an implicit risk or not based on the historical operation worst parameter set, and the operation monitoring module is used for judging whether the traffic electromechanical device is in a normal working state or not based on the operation deviation array of the electromechanical device;
the data monitoring module is electrically connected with the processor and is used for collecting the operation parameters of all electromechanical devices in the traffic system in real time according to a preset time interval in a monitoring period;
the data updating module is electrically connected with the data monitoring module and the storage module and is used for updating the historical operation parameters of the traffic system based on the real-time operation parameter matrix of the electromechanical equipment.
8. The intelligent monitoring and early warning system of a traffic electromechanical device according to claim 7, wherein the implicit risk analysis module comprises:
the first calculation unit is used for calculating a deviation array of each group of historical operation parameters based on a standard operation parameter array of the electromechanical equipment and combining all the historical operation deviation arrays into a historical operation deviation matrix;
the screening unit is used for screening the maximum value of the deviation value of each parameter from the historical operation deviation matrix, taking the maximum value as the worst deviation value of the parameter, and combining the worst deviation values of all the parameters into a historical operation worst parameter group;
the second calculation unit is used for calculating the worst operation index of all electromechanical devices in the traffic system based on the historical operation worst parameter set;
the first judging unit is used for judging whether the worst operation index is higher than an operation index preset value or not.
9. The intelligent monitoring and early warning system of a traffic electromechanical device according to claim 7, wherein the operation monitoring module comprises:
the data processing unit is used for processing the operation parameters of the electromechanical equipment acquired by the data monitoring module into a real-time operation parameter matrix of the electromechanical equipment;
the third calculation unit is used for calculating the deviation distance between each real-time operation parameter set and the standard operation parameter set of the electromechanical device through a deviation distance calculation formula based on the real-time operation parameter matrix of the electromechanical device and the standard operation parameter set of the electromechanical device, obtaining a plurality of real-time deviation distance values and forming all the real-time deviation distance values into a real-time operation deviation array;
the second judging unit is used for judging whether the deviation distance between any one real-time operation parameter set in the operation deviation array and the standard operation parameter set of the electromechanical equipment is larger than the operation index preset value.
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