CN115826443A - Tunnel intelligent controller based on Hongmon operating system - Google Patents
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Abstract
The invention relates to the technical field of control, in particular to a tunnel intelligent controller based on a Hongmon operating system, which is used for intelligently controlling electromechanical systems in all tunnels distributed in a set area range and comprises a sensor unit, a control unit and a data processing unit; the hong meng internet of things IOT platform sends out a control command according to the collected data and the data prompt obtained by processing. The tunnel intelligent controller is independently installed aiming at the electromechanical system installed at the front end in the tunnel, and realizes multiple working modes of the electromechanical system based on different control modes, thereby realizing the elastic access of intelligent traffic infrastructure; the edge computing power can be distributed as required, and the requirement of large-scale development is met; the intelligent traffic equipment can integrate software and hardware capabilities of various sensor data, information and the like, the use cost of the intelligent traffic equipment is reduced, and service application is more open and efficient through the Hongmon Internet of things IOT platform.
Description
Technical Field
The invention relates to the technical field of control, in particular to an intelligent tunnel controller based on a Hongmon operating system.
Background
The hong meng system (Harmony OS) is a brand-new distributed operating system oriented to a whole scene, and through hong meng transformation aiming at a front-end electromechanical system, unified intelligent control of various electromechanical systems based on the hong meng system can be realized.
For example, for an electromechanical system including a lighting system, a ventilation system and the like in a tunnel in a traffic system, the operation state of each device can be read and controlled based on a Hongmon system (Harmony OS) by modification, so that the safe and reliable operation of the device can be guaranteed; digital control networks such as daily ventilation of tunnel and functional illumination are built through the tunnel intelligent controller, full digitalization transformation of tunnel traditional equipment is realized, and powerful support can be provided for large-scale application of realizing digital tunnel equipment networking.
For the specific application case of the digital green tunnel, the electromechanical system used in the tunnel is more definite, and the conventional system comprises a traffic control system, a ventilation control system and a lighting control system; currently, although the hong meng system (Harmony OS) is widely applied to many fields including smart homes, safe driving, and the like, there is no tunnel intelligent controller which is dedicated to intelligently controlling the above electromechanical systems in the digital tunnel, so as to ensure the effective operation of the above electromechanical systems.
Disclosure of Invention
The invention provides a tunnel intelligent controller based on a Hongmon operating system, thereby effectively solving the problems pointed out in the background art.
In order to achieve the purpose, the invention adopts the technical scheme that:
a tunnel intelligent controller based on a Hongmon operating system is used for intelligently controlling electromechanical systems in all tunnels distributed in a set region range, is independently installed for each tunnel, is connected with an IOT (Internet of things) platform of the Hongmon, and comprises a sensor unit, a control unit and a data processing unit;
the sensor unit is used for acquiring data of a working result of the electromechanical system and transmitting the data to the control unit and the data processing unit respectively;
the control unit transmits the data acquired by the sensor unit and the processing result of the data processing unit to the hong meng IOT platform, and controls the electromechanical system according to a control command from the hong meng IOT platform;
the processing of the data from the sensor unit by the data processing unit comprises:
the control unit calls the same type of data in the same acquisition time range in other tunnels connected with the Hongmon Internet of things IOT platform; calculating first variances of all homogeneous data; comparing the first variance with a first set threshold; when the first variance is larger than or equal to the first set threshold, the data processing unit sends an abnormal data prompt to the control unit; when the first variance is smaller than the first set threshold, the data processing unit sends a normal data prompt to the control unit;
the hong meng IOT platform sends out a control command according to the collected data and the data prompt obtained by processing.
Furthermore, aiming at each tunnel, the acquisition frequency and the acquisition time of the same type of data are the same.
Further, the control command of the hong meng internet of things IOT platform is based on the collected data and the abnormal data prompt, and specifically includes:
and extracting abnormal data aiming at the same-type data acquired at the same time, and performing differentiation control on the electromechanical system acquiring the abnormal data relative to the electromechanical system acquiring normal data.
Further, the extracting of the abnormal data comprises:
calculating an extraction base number, wherein the calculation formula is as follows:
wherein ,
an extraction base number for abnormal data; a is a first set threshold;
the average value of each collected data is obtained;
and determining a data selection range, wherein the determination process is based on the extraction base number, data in the range is considered as normal data, and data out of the range is considered as abnormal data.
Further, determining the data selection range according to the extraction cardinality comprises:
the extraction base number is reduced according to a first proportion to obtain a lower data limit, and the extraction base number is enlarged according to a second proportion to obtain an upper data limit, and the data selection range is as follows: greater than the lower data limit and less than the upper data limit;
wherein the first ratio and the second ratio are both positive values, and the ratio of the second ratio/the first ratio is positively correlated with the first variance.
Further, the control of the electromechanical system that obtains the abnormal data is independent control.
Further, the control command of the hong meng internet of things IOT platform is based on the collected data and the normal data prompt, and specifically includes: all the electromechanical systems which acquire normal data are controlled to the same working state.
Further, the hong meng internet of things IOT platform controls the electromechanical system with normal data after extracting the abnormal data when receiving the abnormal data prompt, and controls the electromechanical system with normal data when receiving the normal data prompt in the same control process.
Further, the control command of the hong meng internet of things IOT platform is based on the collected data and the abnormal data prompt, and specifically includes:
the control of all electromechanical systems that acquire data is independent.
Through the technical scheme of the invention, the following technical effects can be realized:
the tunnel intelligent controller is independently installed aiming at the electromechanical system installed in the tunnel, and it needs to be explained that the existing electromechanical system does not need to be changed in the installation process, and various working modes of the electromechanical system can be realized based on different control modes; the intelligent tunnel controller provided by the invention can pertinently realize the control of an electromechanical system in the tunnel, realize the elastic access of intelligent traffic infrastructure, and the edge computing capability can be distributed as required, thereby meeting the requirement of large-scale development; the intelligent traffic equipment can integrate software and hardware capabilities of various sensor data, information and the like, the use cost of the intelligent traffic equipment is reduced, and service application is more open and efficient through the Hongmon Internet of things IOT platform.
In the invention, the data processing unit can realize the targeted data processing of the specific working conditions of the tunnel, and considering that the tunnel is a large-scale engineering building, the actual control requirements of different tunnels are unified to a certain extent in a certain area, but differences possibly exist in the special conditions.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a distribution of multiple Hongmon operating system based tunnel intelligent controllers;
FIG. 2 is a block diagram of a Hongmon operating system based tunnel intelligent controller;
FIG. 3 is a flow chart of data processing from the sensor unit by the data processing unit;
FIG. 4 shows the data processing procedure of the data processing unit and the detailed control steps of the Hongmon IOT platform when there is abnormal data;
reference numerals: 01. a tunnel; 02. an Hongmon Internet of things IOT platform; 03. an electromechanical system; 04. a sensor unit; 05. a control unit; 06. and a data processing unit.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
As shown in fig. 1 and fig. 2, an intelligent tunnel controller based on a hongmeng operating system is used for intelligently controlling electromechanical systems 03 in tunnels 01 distributed in a set area range, wherein the selection of the area range refers to the number of tunnels 01 in the area range, and is more significant for the present invention when at least 3 tunnels 01 exist, or preferably, the number of tunnels 01 is more than 5; the tunnel intelligent controller is independently installed for each tunnel 01, is connected with the Hongmon Internet of things IOT platform 02 and comprises a sensor unit 04, a control unit 05 and a data processing unit 06; the sensor unit 04 acquires data of the working result of the electromechanical system 03 and respectively transmits the data to the control unit 05 and the data processing unit 06; the control unit 05 transmits the data acquired by the sensor unit 04 and the processing result of the data processing unit 06 to the hong meng internet of things IOT platform 02, and controls the electromechanical system 03 according to a control command from the hong meng internet of things IOT platform 02.
The data processing unit 06 processes the data from the sensor unit 04 and transmits the processed data to the control unit 05, as shown in fig. 3, the processing including:
s01: the same data in the same acquisition time range in other tunnels 01 connected with the Hongmon Internet of things IOT platform 02 are called through the control unit 05;
s02: calculating first variances of all homogeneous data;
s03: comparing the first variance with a first set threshold;
when the first variance is equal to or greater than the first set threshold, step S041 is executed: the data processing unit 06 issues an abnormal data prompt to the control unit 05;
when the first variance is smaller than the first set threshold, step S042 is performed: the data processing unit 06 issues a normal data prompt to the control unit 05.
The hong meng internet of things IOT platform 02 issues control commands based on data prompts obtained from the collected data and processing.
The tunnel intelligent controller is independently installed for the electromechanical system 03 installed in the tunnel 01, and it should be noted that the existing electromechanical system 03 does not need to be changed in the installation process, and multiple working modes of the electromechanical system 03 can be realized based on different control modes; the intelligent tunnel controller provided by the invention can pertinently realize the control of the electromechanical system 03 in the tunnel 01, realize the elastic access of intelligent traffic infrastructure, and the edge computing capability can be distributed as required, thereby meeting the requirement of large-scale development; the system can integrate software and hardware capabilities such as various sensor data and information, reduce the use cost of intelligent traffic equipment, and enable service application to be more open and efficient through the Hongmon Internet of things IOT platform 02.
In the above embodiment, the data of the electromechanical system 03 in the working process mainly refers to the collection of relevant working parameters in the running process of the equipment, such as the running states of traffic lights in a traffic control system (such as passing, forbidding, etc.), the running states of fans in a ventilation control system (such as forward rotation, reverse rotation, failure, energy consumption, etc.), the running states of loops in a lighting control system (such as the brightness level of lights in a lighting loop), and the like; the working result data mainly refers to parameter changes of the tunnel 01 environment, such as brightness, carbon monoxide CO concentration, visibility VI, wind speed WS and the like in the tunnel 01, caused by the work of the electromechanical system 03; the type of the sensor can be flexibly selected for different electromechanical systems 03, and all the sensors jointly serve as a sensing layer to participate in intelligent control of the tunnel 01.
In this embodiment, it should be further described that the tunnel intelligent controllers are installed in one-to-one correspondence with the tunnels 01, but a plurality of sensors in the tunnels 01 may be set according to actual use requirements, and the sensors of different types may be set to the same number, may also be set to different numbers, may be installed at the same position, may also be installed at different positions, and specifically, are selected comprehensively according to the size, the geographic environment, and the like of the tunnels 01.
In the invention, the data processing unit 06 can realize the targeted data processing of the specific working condition of the tunnel 01, considering that the tunnel 01 is a relatively large engineering building, the actual control requirements of different tunnels 01 are unified to a certain extent in a certain area, however, for special conditions, differences may be required, for example, data change caused by damage of a certain electromechanical system 03 in a certain tunnel 01, or data change caused by congestion and surge of vehicles in a certain tunnel 01, and the like, all need to be controlled differently than other tunnels 01. In view of the above requirements, the present invention provides a specific data processing method, as shown in fig. 3: during data processing, the variance is passedWhether abnormal data exist is judged by calculation and comparison, and an abnormal data prompt and a normal data prompt are sent out in a targeted manner; the first variance calculation process is to record the same kind of data collected in each tunnel 01 as X 1 、X 2 、X 3 、X 4 ……X n Then the first variance of each data is:
in this embodiment, n is a positive integer of 3 or more.
The hong meng internet of things IOT platform 02 synthesizes the collected data and the data obtained by processing to prompt a control command to be sent, and finally distinguishes which targeted control is performed on the electromechanical system 03 of the data source through the difference of the command, or realizes the unified control of all the electromechanical systems 03.
In the data acquisition process, the acquisition time range can be specified as the time source of the same type of data, when the time range is small enough, the data change caused by the time change in the environment where each sensor is located can be determined to be negligible, and as a more accurate mode, the acquisition frequency and the acquisition time of the same type of data are the same for each tunnel 01. This way it is clear that a fully corresponding data set can be established, which is more advantageous for an accurate control.
Based on the above embodiment, as a specific optimization mode, the control command of the hong meng internet of things IOT platform 02 is prompted according to the collected data and the abnormal data, specifically:
and abnormal data are extracted aiming at the same-type data collected at the same time, and the electromechanical system 03 for obtaining the abnormal data is subjected to differentiation control relative to the electromechanical system 03 for obtaining normal data.
In the preferred embodiment, a specific control feedback is provided for the abnormal data prompt, that is, in the implementation process, when the abnormal data prompt is generated, the following specific steps need to be additionally performed:
a01: extracting abnormal data;
a02: a first control mode is adopted for the electromechanical system 03 generating abnormal data;
a03: a second control mode is taken for the electromechanical system 03 generating normal data.
Wherein, the steps A02 and A03 can be carried out synchronously or by adjusting the sequence.
As a preference of the above embodiment, the extracting of the abnormal data includes:
calculating an extraction base number, wherein the calculation formula is as follows:
wherein ,
an extraction base number for abnormal data; a is a first set threshold;
the average value of each collected data is obtained;
the data selection range is determined, and the determination process is based on the extraction base, data within the range is considered normal data, and data outside the range is considered abnormal data.
According to the above-mentioned extraction method of the abnormal data, when there is abnormal data, the data processing process of the data processing unit 06 and the specific control method of the hong meng internet of things IOT platform 02 may be as shown in fig. 4, and include the following steps:
b01: the same type of data X in the same acquisition time range in other tunnels 01 connected with the Hongmon Internet of things IOT platform 02 are called through the control unit 05 1 、X 2 、X 3 、X 4 ……X n ；
B02: calculating first variances of all homogeneous data; the calculation formula is as follows:
b03: comparing the first variance with a first set threshold, wherein the first variance is greater than or equal to the first set threshold, and the data processing unit 06 sends an abnormal data prompt to the control unit 05;
b04: the control unit 05 aims at the same-type data X collected at the same time 1 、X 2 、X 3 、X 4 ……X n Calculating an extraction base number; the calculation formula is as follows:
wherein ,
an extraction base number for the abnormal data; a is a first set threshold;
the average value of each collected data is obtained;
b05: determining a data selection range according to the extraction base, wherein data in the range is determined as normal data, and data out of the range is determined as abnormal data, and in the process of determining the data selection range, as a specific implementation mode, determining the data selection range according to the extraction base comprises the following steps:
b051: narrowing the extraction base number according to the first proportion to obtain a lower data limit;
b052: amplifying the extraction base number according to a second proportion to obtain an upper data limit;
b053: determining the data selection range as follows: greater than a lower data limit and less than an upper data limit;
wherein the first proportion and the second proportion are both positive values, and the ratio of the second proportion/the first proportion is positively correlated with the first square error.
The first ratio narrows down the number of extraction bases by a value smaller than 1, and the second ratio enlarges the number of extraction bases by a value larger than 1, so that a data selection range for distinguishing normal data from abnormal data can be obtained; in the step, the ratio of the second proportion to the first proportion is positively correlated with the first variance, so that when the data fluctuation is large, the requirement for data selection is reduced by properly increasing the data range, and when the data fluctuation is small, the requirement for data selection is increased by properly decreasing the data range, the process is a dynamic control process for abnormal data extraction, and the requirement for data can be gradually met in multiple data acquisition and processing processes; of course, the above-mentioned positive correlation control method is for continuous control of the same kind of data, the degree of positive correlation for different kinds of data may be the same or different, and the first ratio and the second ratio may be affected by parameters such as the data type and the electromechanical system 03 type in addition to the above-mentioned positive correlation control method.
B06: the electromechanical system 03 that obtains the abnormal data is subjected to differential control with respect to the electromechanical system 03 that obtains the normal data.
When the abnormal data extraction is completed, as a preferable mode, on the one hand, the control of the electromechanical system 03 for obtaining the abnormal data is independent control. The independent control in the preferred scheme is one-to-one targeted control, and the difference caused by the data deviation is controlled in a targeted manner to obtain accurate control and adjustment, so that the method is particularly critical to the discovery and the solution of abnormal conditions, and the effectiveness of the control of the electromechanical system 03 in the tunnel 01 can be ensured to a certain extent; of course, the independent control in the preferred embodiment may be manual control, or may be an automatic control program preset for different parameters, where the independent control only indicates differentiation with respect to the electromechanical systems 03 in other tunnels 01.
In the data processing process, as the same tunnel 01 may have a plurality of sensors of the same type to acquire a plurality of data of the same type at the same time, in the application, the extraction of abnormal data may indicate that only part of the parameters at the positions in the same tunnel 01 are abnormal, and certainly, the situation needs to be identified by pertinence judgment; however, when the sensor unit 04 is regarded as a whole, the electromechanical system as a whole is also subjected to targeted control.
When the abnormal data extraction is completed, as a preferable mode, on the other hand, the electromechanical system 03 which obtains the normal data is controlled to the same working state.
In the above optimization scheme, the data is screened secondarily for abnormal situations, and on one hand, the screening process is to reduce the difficulty of control, because the requirement of one-to-one control for different tunnels 01 for road management and control personnel is higher, and reducing the situation is obviously beneficial to the configuration of human resources; on the other hand, the intelligent control mode is based on data closed-loop control, and the control precision is better than that of the manual control mode.
In the above preferred solution, a control process of obtaining the abnormal data prompt is provided, and different from the above control process, the control command of the hong meng internet of things IOT platform 02 is based on the normal data prompt, which specifically includes: all the same electromechanical systems 03 acquiring normal data are controlled to the same working state. The method can effectively reduce the control difficulty of the electromechanical systems 03 in all the tunnels 01; in this case, the control criteria may be set empirically or programmatically, or selected based on pre-established data-to-control parameter relationships, etc.
The hong meng internet of things IOT platform 02 controls the electromechanical system 03 with normal data after extracting abnormal data when receiving the prompt of the abnormal data, and controls the electromechanical system 03 with normal data when receiving the prompt of the normal data in the same control process.
That is, when the abnormal data prompt is sent out and the abnormal data is removed, the electromechanical system 03 with the normal data and the electromechanical system 03 without the abnormal data prompt are sent out in the same control mode, which is more convenient for the control process, and in the multiple control and data feedback processing processes, the number of the abnormal data is gradually reduced, so that the various electromechanical systems 03 in the tunnels 01 gradually generate the same working process and/or the same control result in the continuous closed-loop control process.
In the above-described embodiment, when abnormal data is generated, a part of the data is revised to normal data by secondary screening through extraction of the abnormal data, thereby reducing the difficulty of control through unified control over the electromechanical system 03 generating the part of the data; the calculation mode for extracting the base number in the mode is set manually, and is selected according to the setting of the first set threshold, the mode is more effective for controlling the working result of the electromechanical system 03, the specific working result corresponds to the specific parameter, and the change of the specific working result is limited in the appropriate tunnel 01 environment, so that the relatively accurate result can be obtained easily by selecting the first set threshold aiming at the single parameter.
In another aspect, when the control process is performed on the working process of the electromechanical system 03, the acquired parameters are working process parameters of the electromechanical system 03, in such a case, due to equipment damage, abnormal power supply, equipment failure, or the like, the first difference may change greatly, and the degree of the change is possibly large relative to the degree of change of the normal operation, so that it may be difficult to obtain an objective value due to the difference between the normal operation and the abnormal operation in selecting the first setting threshold, and in such a case, as another control method when an abnormal data prompt is generated, the control command of the hong meng internet of things IOT platform 02 is based on the acquired data and the abnormal data prompt, and specifically: the control of all the electromechanical systems 03 acquiring data is independent.
The independent control in this case may be understood as a unified control performed after the last data acquisition is exited, and instead, the control states are independent from each other, it should be noted that the independent control may obtain the same control result or different control results, and the control may be initiated in the same control state. In this control mode, as compared with the above embodiment, the extraction of abnormal data is not performed, but all the data are independently determined as the abnormal data identified in the above embodiment, and the abnormal condition can be resolved based on the determination result.
The different modes can be specifically selected according to different electromechanical system 03 types, different parameter types and the like.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (9)
1. The tunnel intelligent controller based on the Hongmon operating system is used for intelligently controlling electromechanical systems in all tunnels distributed in a set area range, is independently installed for each tunnel, is connected with an IOT (Internet of things) platform of the Hongmon Internet of things, and comprises a sensor unit, a control unit and a data processing unit;
the sensor unit is used for acquiring data of a working result of the electromechanical system and transmitting the data to the control unit and the data processing unit respectively;
the control unit transmits the data acquired by the sensor unit and the processing result of the data processing unit to the hong meng IOT platform, and controls the electromechanical system according to a control command from the hong meng IOT platform;
the processing of the data from the sensor unit by the data processing unit comprises:
the control unit calls the same type of data in the same acquisition time range in other tunnels connected with the Hongmon Internet of things IOT platform; calculating first variances of all homogeneous data; comparing the first variance with a first set threshold; when the first variance is larger than or equal to the first set threshold, the data processing unit sends an abnormal data prompt to the control unit; when the first variance is smaller than the first set threshold, the data processing unit sends a normal data prompt to the control unit;
the hong meng IOT platform sends out a control command according to the collected data and the data prompt obtained by processing.
2. The hong meng operating system-based tunnel intelligent controller as claimed in claim 1, wherein the acquisition frequency and the acquisition time of the same kind of data are the same for each tunnel.
3. The hong meng operating system-based tunnel intelligent controller according to claim 2, wherein the control command of the hong meng internet of things IOT platform is based on the collected data and the abnormal data prompt, and specifically comprises:
and extracting abnormal data aiming at the same-type data acquired at the same time, and performing differentiation control on the electromechanical system acquiring the abnormal data relative to the electromechanical system acquiring normal data.
4. The Hongmon operating system-based tunnel intelligent controller of claim 3, wherein the extraction of the anomaly data includes:
calculating an extraction base number, wherein the calculation formula is as follows:
wherein ,
an extraction base number for the abnormal data; a is a first set threshold;
the average value of each collected data is obtained;
and determining a data selection range, wherein the determination process is based on the extraction base number, data in the range is considered as normal data, and data out of the range is considered as abnormal data.
5. The Hongmon operating system-based tunnel intelligence controller of claim 4, wherein determining a data selection range from the extraction cardinality comprises:
the extraction base number is reduced according to a first proportion to obtain a lower data limit, and the extraction base number is enlarged according to a second proportion to obtain an upper data limit, and the data selection range is as follows: greater than the lower data limit and less than the upper data limit;
wherein the first proportion and the second proportion are both positive values, and the ratio of the second proportion/the first proportion is positively correlated with the first variance.
6. A tunnel intelligent controller based on a Hongmon operating system as claimed in any one of claims 3 to 5, wherein the control of the electromechanical system for obtaining the abnormal data is independent control.
7. The hong meng operating system-based tunnel intelligent controller as claimed in claim 2, wherein the control command of the hong meng internet of things IOT platform is based on the collected data and the normal data prompt, and specifically comprises: all the electromechanical systems which acquire normal data are controlled to the same working state.
8. A Hongmon operating system-based tunnel intelligent controller as claimed in claim 7, wherein the Hongmon Internet of things IOT platform is the same control process for the control of the electromechanical system with normal data after abnormal data extraction in case of receiving the abnormal data prompt and for the control of the electromechanical system with normal data in case of receiving the normal data prompt.
9. The hong meng operating system-based tunnel intelligent controller according to claim 2, wherein the control command of the hong meng internet of things IOT platform is based on the collected data and the abnormal data prompt, and specifically comprises:
the control of all electromechanical systems that acquire data is independent.
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