CN105370609B - High aititude cluster ventilation intelligence control system and its method - Google Patents
High aititude cluster ventilation intelligence control system and its method Download PDFInfo
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- CN105370609B CN105370609B CN201510863803.4A CN201510863803A CN105370609B CN 105370609 B CN105370609 B CN 105370609B CN 201510863803 A CN201510863803 A CN 201510863803A CN 105370609 B CN105370609 B CN 105370609B
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Abstract
The present invention relates to High aititude cluster ventilation intelligence control system and its method.Existing tunnel ventilated control system personnel's effect is low, blower fan entry condition False Rate high.The present invention gathers fan parameter information by fan condition acquisition module, by user data module summarizing；The information that data analysis comparing module is provided according to user data module, parameter setting module, standard database, forms and compares analysis；Data prediction management module, which is received, compares analysis information, and prediction generation operational order is learnt automatically according to true train travel situations and environmental change, and adjusting parameter sets, corrects database, be transferred to result output module.The present invention compares ventilating system data, rationally tunnel blower equipment is run according to train operating data and controlled, can reaction type adjusting parameter set, amendment database, realize optimal ventilation and energy-saving effect, reduce the influence to railway supply and distribution network, reduce personnel labor intensity and realize energy-saving run to greatest extent.
Description
Technical field
The invention belongs to tunnel ventilation control technology field, and in particular to a kind of High aititude cluster ventilation intelligence control system
And its method.
Background technology
The High aititude diesel traction tunnel operation of concentrating type distribution, distribution is supplied when there is big fan capacity, startup to railway
Network-impacting influence it is serious the problems such as, but existing tunnel ventilated control system and its method exist labor intensive resource it is many, manually
Labor intensity is big, personnel's effect is low, ambient influnence is big, blower fan entry condition False Rate is high, maintenance difficulty is big and judges reliability
Not high the problems such as, therefore how effectively to realize to the safe, reliable and effective control of tunnel inner blower, while reducing to railway for matching somebody with somebody
The influence of electric network, and reduce personnel labor intensity and realize energy-saving run to greatest extent, realize informationization, digitize, automatically
Change, the interactive tunnel cluster ventilation intelligent monitor system being characterized, are that High aititude diesel traction tunnel cluster ventilating system must
The problem of must solving.
The content of the invention
It is an object of the invention to provide a kind of High aititude cluster ventilation intelligence control system and its method, tunnel blower is set
Standby start and stop on demand, realize optimal ventilation and energy-saving effect.
The technical solution adopted in the present invention is：
High aititude cluster ventilation intelligence control system, it is characterised in that：
The system includes fan condition acquisition module, user data module, data analysis comparing module, parameter setting mould
Block, standard database, data prediction management module, result output module；
Fan condition acquisition module, for gathering High aititude cluster draft fan parameter information, including running status, failure
Situation, ambient parameter and wind speed；
User data module, the fan parameter finish message for fan condition acquisition module to be gathered is concluded；
Parameter setting module, for using operation and environment effect information arrange parameter according to user；
Standard database, for setting up the standard information in standard device, including Centralized Monitoring, on-line monitoring, blower fan fortune
Row state and ambient parameter；
Data analysis comparing module, for the letter provided according to user data module, parameter setting module, standard database
Breath, forms and compares analysis information；
Data prediction management module, the comparison for data analysis comparing module to be inputted analyzes information management and according to reality
Border service condition learns prediction generation operational order automatically, is set for adjusting parameter, corrects database and to be transferred to result defeated
Go out module；
As a result output module, rationally runs for entering the operating instructions control blower fan.
The control method of High aititude cluster ventilation intelligence control system, it is characterised in that：
Comprise the following steps：
The fan parameter information of High aititude cluster draft fan, including operation shape are gathered by fan condition acquisition module
State, failure situation, ambient parameter and wind speed, and input user data module progress summarizing；
With reference to user's actual use operation and ambient influnence situation adjusting parameter setup module, arrange parameter；
Set up the standard database of standard device, including Centralized Monitoring, on-line monitoring, fan operation state, ambient parameter
Standard information, input is to data analysis comparing module；
The information that data analysis comparing module is provided according to user data module, parameter setting module, standard database, will
Equipment state overhauling historical data, fan operation state data, environmental change data, railroad train service data, natural wind are lived
Wind data information incorporating parametric is filled in set and standard database formation comparison analysis；
Data prediction management module receives the comparison analysis information of data analysis comparing module input, according to true train row
Sail situation and environmental change and learn prediction generation operational order automatically, set for adjusting parameter, correct database and be transferred to
As a result output module.
The present invention has advantages below：
The invention provides a kind of High aititude cluster ventilated control system with analysis expert learning functionality, overcome existing
The deficiency that technology is present, carries out rationalization control to tunnel blower, realizes optimal ventilation and energy-saving effect, it is ensured that railways are set
Stable operation is applied, tunnel ventilation quality and efficiency is improved, ensures that tunnel ventilation is safe and reliable.
Brief description of the drawings
Fig. 1 is present system structure chart.
Embodiment
With reference to embodiment, the present invention will be described in detail.
High aititude cluster ventilation intelligence control system of the present invention, including fan condition acquisition module, user data
Module, data analysis comparing module, parameter setting module, standard database, data prediction management module, result output module.
Fan condition acquisition module, for gathering High aititude cluster draft fan fan parameter information, including running status
（The data such as voltage, electric current, frequency, run time and the change of period waveform）, failure situation（It is voltage, current break, out of service
The data such as time, device temperature）, ambient parameter（The content of material such as environment temperature, appropriateness, dust, sulfur dioxide, oxygen, an oxygen
Change the data such as the gas contents such as carbon）, wind speed；
User data module, the fan parameter finish message for fan condition acquisition module to be gathered is concluded；
Parameter setting module, for, using operation and environment effect information arrange parameter, user to be according to height above sea level according to user
Highly, the factor such as railway operation arrangement of time, environment temperature, wind speed and season sets the threshold parameter of start and stop blower fan；
Standard database, for setting up the standard information in standard device, including Centralized Monitoring（According to the railway operation time
Situation, by the running status of blower fan Centralized Monitoring blower fan, including start-stop time, voltage x current, frequency, environment temperature for along
Degree, wind speed, the gas content such as sulfur dioxide, oxygen, carbon monoxide in High aititude tunnel, and set up standard information, when reaching mark
Quasi- threshold value then centralized Control fan operation）, on-line monitoring（Operating personnel can remote on-line monitoring fan operation situation, and online
Control, having tackled live emergency case needs start and stop blower fan）, fan operation state（Voltage, electric current, frequency, run time and phase
Between waveform change）And ambient parameter（The gas such as the content of material such as environment temperature, appropriateness, dust, sulfur dioxide, oxygen, carbon monoxide
Body content）；
Data analysis comparing module, for the letter provided according to user data module, parameter setting module, standard database
Breath, forms and compares analysis information；The blower fan start and stop threshold parameter that user is set according to railway operation demand, includes the electricity of blower fan
The content of material such as pressure, current break, time out of service, device temperature parameter, environment temperature, appropriateness, dust, sulfur dioxide,
The gas contents such as oxygen, carbon monoxide, analysis is compared with the above-mentioned parameter of standard state, at or below given threshold situation
Under to blower fan carry out start stop operation；
Data prediction management module, the comparison for data analysis comparing module to be inputted analyzes information management and according to reality
Border service condition learns prediction automatically（Blower fan start and stop shape in the operation of information and actual railway is analyzed in the comparison that upper level is generated
State, voltage x current, ambient parameter are combined, if default start and stop running situation is consistent with actual conditions, maintain existing fortune
Row mode, if inconsistent with actual conditions, the deviation of analysis blower fan start and stop situation and reality, prediction need to be shifted to an earlier date in before setting value
Start or startup, fall-back, high-speed cruising, and change information feedback higher level is subjected to parameters revision afterwards, make system more
Meet the rule and environmental change situation of railroad train process）Generate operational order（To blower fan fall-back, high-speed cruising or
Start, stop）, set for adjusting parameter, correct database and be transferred to result output module；
As a result output module, rationally runs for entering the operating instructions control blower fan.
The control method of above-mentioned High aititude cluster ventilation intelligence control system, comprises the following steps：
The fan parameter information of High aititude cluster draft fan, including operation shape are gathered by fan condition acquisition module
State, failure situation, ambient parameter, Current Voltage and wind speed, and input user data module progress summarizing；
With reference to user's actual use operation and ambient influnence situation adjusting parameter setup module, arrange parameter；
Set up the standard database of standard device, including Centralized Monitoring, on-line monitoring, fan operation state, ambient parameter
Standard information, input is to data analysis comparing module；
The information that data analysis comparing module is provided according to user data module, parameter setting module, standard database, will
Equipment state overhauling historical data, fan operation state data, environmental change data, railroad train service data, natural wind are lived
Wind data information incorporating parametric is filled in set and standard database formation comparison analysis；
Data prediction management module receives the comparison analysis information of data analysis comparing module input, according to true train row
Sail situation and environmental change and learn prediction generation operational order automatically, set for adjusting parameter, correct database and be transferred to
As a result output module.
The High aititude diesel traction tunnel operation of concentrating type distribution, distribution is supplied when there is big fan capacity, startup to railway
Network-impacting influence it is serious the problems such as, but existing tunnel ventilated control system and its method exist labor intensive resource it is many, manually
Labor intensity is big, personnel's effect is low, ambient influnence is big, blower fan entry condition False Rate is high, maintenance difficulty is big and judges reliability
Not high the problems such as.
In face of these problems, by user according to height above sea level, railway operation arrangement of time, environment temperature, wind speed and season
The factors such as section set the threshold parameter of start and stop blower fan, with start-stop time in canonical parameter, voltage x current, frequency, environment temperature, wind
The gas content such as sulfur dioxide, oxygen, carbon monoxide is compared to pair in speed, High aititude tunnel, and the comparison that upper level is generated is analyzed
With actual railway, blower fan start and stop states, voltage x current, ambient parameter are combined information in operation, if default start and stop are run
Situation is consistent with actual conditions, then maintains existing operational mode, if inconsistent with actual conditions, analysis blower fan start and stop situation and reality
The deviation on border, prediction need to be shifted to an earlier date in starting or startup, fall-back, high-speed cruising afterwards before setting value, obtains blower fan
Centralized Monitoring, improves operational efficiency, more meets the rule and environmental change situation of railroad train process, and reduction high altitude localities is thin
The energy resource consumption of light current net.
And operating personnel can remote on-line monitoring blower fan and railway operation situation, and On-line Control blower fan concentrate operation,
Live accident is tackled（Such as train occurs in out of service in tunnel, terrible weather）Need the situation of start and stop blower fan.
Therefore how effectively to realize to the safe, reliable and effective control of tunnel inner blower, while reducing to railway distribution network
The influence of network, and reduce personnel labor intensity and realize energy-saving run to greatest extent, realize information-based, digitlization, automate, mutually
The dynamic tunnel cluster ventilation intelligent monitor system for turning to feature, is that High aititude diesel traction tunnel cluster ventilating system must be solved
The problem of.
Present disclosure is not limited to cited by embodiment, and those of ordinary skill in the art are by reading description of the invention
And any equivalent conversion taken technical solution of the present invention, it is that claim of the invention is covered.
Claims (1)
- The control method of intelligence control system 1. High aititude cluster is divulged information, it is characterised in that：Comprise the following steps：The fan parameter information of High aititude cluster draft fan, including running status, event are gathered by fan condition acquisition module Barrier situation, ambient parameter and wind speed, and input user data module progress summarizing；With reference to user's actual use operation and ambient influnence situation adjusting parameter setup module, i.e., user is according to height above sea level, iron Road run time arrangement, environment temperature, wind speed and seasonal factor set the threshold parameter of start and stop blower fan；Set up the standard database of standard device, including Centralized Monitoring information, on-line monitoring information, the standard of ambient parameter letter Breath, input to data analysis comparing module；The Centralized Monitoring is：According to railway operation time situation, by the operation shape of blower fan Centralized Monitoring blower fan for along State, sets up standard information, when railway operation temporal information and fan operation state information reach level threshold value then centralized Control wind Machine is run；The on-line monitoring is：Operating personnel's remote on-line monitoring fan operation situation, and On-line Control, reply scene are prominent Heat condition start and stop blower fan；The information that data analysis comparing module is provided according to user data module, parameter setting module, standard database, by equipment Repair based on condition of component historical data, fan operation state data, environmental change data, railroad train service data, natural wind Piston Action Wind Data message combines the parameter set and standard database formation compares analysis；Data prediction management module receives the comparison analysis information of data analysis comparing module input, and feelings are travelled according to true train Condition and environmental change learn prediction generation operational order automatically, set for adjusting parameter, correct database and be transferred to result Output module；The automatic study is predicted as：Comparison analysis information and the blower fan start and stop shape in actual railway operation that upper level is generated State, voltage x current, ambient parameter are combined, if default start and stop running situation is consistent with actual conditions, maintain existing fortune Row mode, if inconsistent with actual conditions, analysis blower fan start and stop situation and actual deviation, prediction be need to shift to an earlier date in setting value it Preceding to start or start afterwards, prediction needs fall-back or high-speed cruising, and change information feedback higher level is carried out into parameter Amendment.
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| CN108246104B (en) * | 2017-12-30 | 2023-07-21 | 利穗科技(苏州)有限公司 | Digital ultrafiltration system and method |
| CN109441519B (en) * | 2018-10-18 | 2021-01-26 | 谢国兵 | Tunnel internal environment prediction regulation and control method and device |
| CN110442018A (en) * | 2019-08-15 | 2019-11-12 | 赵亮 | Mining equipment on-off transducer self study working method |
| CN110519389B (en) * | 2019-09-03 | 2022-09-20 | 三一重机有限公司 | Parameter adjusting method and device for engineering equipment, engineering equipment and storage medium |
| WO2021073714A2 (en) * | 2019-10-14 | 2021-04-22 | Huawei Technologies Co., Ltd. | Network node and method for network telemtry |
| CN112598209A (en) * | 2020-10-23 | 2021-04-02 | 河北新天科创新能源技术有限公司 | Evaluation and early warning method for generator heat dissipation system of wind turbine generator |
| CN112904905A (en) * | 2021-01-22 | 2021-06-04 | 广东美智智能科技有限公司 | Control method and control device applied to intelligent closestool |
| CN113431791A (en) * | 2021-06-25 | 2021-09-24 | 中国大唐集团科学技术研究院有限公司西北电力试验研究院 | Differentiation control method of direct air cooling fan |
| CN115620417A (en) * | 2022-12-19 | 2023-01-17 | 成都四为电子信息股份有限公司 | Automatic inspection system and method for railway tunnel electromechanical equipment |
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| CA2735062A1 (en) * | 2008-08-22 | 2010-02-25 | Ansaldo Sts S.P.A. | Ventilation system for railway tunnels |
| CN101581940B (en) * | 2009-06-05 | 2011-04-27 | 西安电子科技大学 | Tunnel event detection method based on integrated learning time sequence prediction |
| CN102472105B (en) * | 2009-10-05 | 2014-05-07 | 株式会社创发系统研究所 | Tunnel ventilation control system of two-way tunnel using jet fan |
| CN103543697B (en) * | 2012-07-16 | 2016-04-06 | 上海宝信软件股份有限公司 | Traffic tunnel device clusters formula intelligent control method |
| CN104533499A (en) * | 2015-01-23 | 2015-04-22 | 贵州现代物流工程技术研究有限责任公司 | Intelligent expressway tunnel ventilation device and intelligent expressway tunnel ventilation method |
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