CN103487125A - Method and system for remote vehicle deadweight detection - Google Patents
Method and system for remote vehicle deadweight detection Download PDFInfo
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- CN103487125A CN103487125A CN201310463804.0A CN201310463804A CN103487125A CN 103487125 A CN103487125 A CN 103487125A CN 201310463804 A CN201310463804 A CN 201310463804A CN 103487125 A CN103487125 A CN 103487125A
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Abstract
The invention discloses a method and system for remote vehicle deadweight detection. The method comprises the steps that A1 a vehicle deadweight module collects vehicle deadweight characteristic information in real time and sends the vehicle deadweight characteristic information to a cloud server, A2 the cloud server carries out data storage, analysis and matching on the vehicle deadweight characteristic information and outputs a matching result to a control center, and A3 the control center carries out monitoring and reminding on vehicle load bearing conditions. The vehicle deadweight characteristic information can be collected in real time and output to the cloud server, after the cloud server carries out data storage, analysis and matching, changing conditions of the weight of a vehicle and vehicle deadweight information in the running process is remotely detected, the judge accuracy rate can be improved based on data matching after cloud calculation, and remote monitoring and early-warning purposes are achieved.
Description
Technical field
The present invention relates to a kind of remote detecting method and system, especially relate to a kind of vehicle load remote detecting method and system.
Background technology
All the time, the vehicle overload overload transportation has all caused very big harm to traffic safety, transport market, has brought out a large amount of traffic safety accidents, to people's lives and properties, has caused massive losses.Badly damaged highway foundation facility, caused huge loss to country.Overload of vehicle has caused the harmful competition of Market of Roadway Transportation, causes vehicle " large ton small tenon " to spread unchecked.Destroy normal social economic order, also seriously jeopardized the country and people's the security of the lives and property.For now, the existing measurement to overloaded vehicle, major part is to utilize large-scale weighbridge or utilize monolateral truck scale to be measured the weight of automobile under known automobile axle load prerequisite.But these two kinds of detection methods, all need monitor vehicle is carried out to independent measurement, and efficiency is very low, need to expend a large amount of manpowers and time, this does not reach the fast development in city and the scale requirement of vehicle flowrate far away.These two kinds of detection methods often have a large amount of fish that has escape the net simultaneously, cause serious hidden trouble of traffic.Simultaneously vehicle occurs that in the operation process it is also the vehicle of running at high speed on large a hidden trouble of traffic, particularly highway that article are lost, as occurs the article vehicle that other are travelled that comes off and be absolutely unsafe.Particularly continue in that travelling the to come off vehicle of article, if the driver is not warned timely, make corresponding processing, and consequence is hardly imaginable.
Summary of the invention
The object of the invention is to overcome above-mentioned deficiency of the prior art, a kind of vehicle load remote detecting method and system are provided, the method and system can realize the load condition of driving vehicle is carried out to real time monitoring, judge warning when having automobile overload or have article to come off, effectively guaranteed road driving safety.
The embodiment of the present invention provides a kind of vehicle load remote detecting method, comprising:
A1, the vehicle-mounted characteristic information of vehicle module Real-time Collection, and described vehicle-mounted characteristic information is sent to Cloud Server;
A2, described Cloud Server carry out data storage, analysis and coupling to described vehicle-mounted characteristic information, and the result after coupling is outputed to control center;
A3, described control center carry out monitoring and early warning to vehicle load-bearing situation.
Correspondingly, the embodiment of the present invention also provides a kind of vehicle load remote detecting system, comprising:
Vehicle module, also send to Cloud Server by described vehicle-mounted characteristic information for the vehicle-mounted characteristic information of Real-time Collection;
Cloud Server, for carrying out data storage, analysis and coupling to described vehicle-mounted characteristic information; And the data after processing are outputed to control center;
Control center carries out monitoring and early warning to vehicle load-bearing situation.
A kind of vehicle load remote detecting method and system that the embodiment of the present invention provides, can the vehicle-mounted characteristic information of Real-time Collection, and by above-mentioned information output to Cloud Server, after being stored, analyzed and mated by Cloud Server, the remote detection vehicle is the situation of change of own wt and on-vehicle information in the process of moving, can the Data Matching based on cloud computing improve judging nicety rate, and realize remote monitoring and early warning purpose by control center.
The accompanying drawing explanation
Fig. 1 is the process flow diagram of a kind of vehicle load remote detecting method of the present invention embodiment mono-;
Fig. 2 is a schematic diagram of a kind of vehicle load remote detecting system of the present invention;
Fig. 3 is another schematic diagram of a kind of vehicle load remote detecting system of the present invention;
Fig. 4 is another schematic diagram of a kind of vehicle load remote detecting system of the present invention;
Fig. 5 is another schematic diagram of a kind of vehicle load remote detecting system of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is only the present invention's part embodiment, rather than whole embodiment.Embodiment based in the present invention, those of ordinary skills, not making under the creative work prerequisite the every other embodiment obtained, belong to the scope of protection of the invention.
A kind of vehicle load remote detecting method and system are provided in the embodiment of the present invention, its main thought is Real-time Collection vehicle load-bearing information and characteristic information, and by above-mentioned information output to Cloud Server, after being stored, analyzed and mated by Cloud Server, the remote detection vehicle is the situation of change of own wt and on-vehicle information in the process of moving, effectively carry out Data Matching by the large data processing function of Cloud Server and can improve judging nicety rate, thereby realize quick and precisely remote monitoring and control purpose.Below be elaborated respectively.
Embodiment of the method one:
As shown in Figure 1, the invention provides a kind of vehicle load remote detecting method, comprise the following steps:
A1, the vehicle-mounted characteristic information of Real-time Collection also send to Cloud Server by vehicle-mounted characteristic information;
In this step, collection period is decided to be 2 minutes.
In this step, vehicle-mounted characteristic information comprises vehicle load-bearing information and vehicle characteristics information, wherein vehicle characteristics information comprises: vehicle motor frequency, throttle noise energy, axletree moment of torsion and load, tyre curvature radius and tire and contact area of ground, and above-mentioned vehicle characteristics information all can be to identification and the correction of vehicle load; Wherein axletree moment of torsion and load obtain by axletree moment of torsion and load sensor, and tyre curvature radius and contact area can be extracted by the video monitoring supplemental characteristic, through the Cloud Server image recognition, calculate.
A2, Cloud Server carry out data storage, analysis and coupling to vehicle-mounted characteristic information; And the result after coupling is outputed to control center;
In this step, Cloud Server carries out data analysis to described vehicle-mounted characteristic information and comprises pre-service and feature extraction, described pre-service comprises that mark the one processing (the characteristic unification be about under different scalars facilitates data identification to same dimension), Data Dimensionality Reduction are (because vehicle-mounted characteristic information comprises especially big multidimensional information, need to reduce data dimension, improve the data accuracy rate), described feature extraction comprises redundance extraction (removing redundant information, the useful information that the information extraction entropy is larger), correlation analysis, non-linear extraction.
In this step, Cloud Server carries out Data Matching to described vehicle-mounted characteristic information and comprises the vehicle-mounted feature set of data referencing through pre-service and feature extraction, and wherein vehicle-mounted feature set comprises that vehicle model collection, contour of the vehicle collection, onboard sensor collection, human pilot collection, Vehicle Driving Cycle card appraise and decide load-carrying collection, current road surface and allow load-bearing collection etc., carry out tagsort, ownership judgement and classifier evaluation.Wherein, tagsort comprises sorter, the sorter based on Hidden Markov Model (HMM), the sorter based on artificial neural network and support vector machine based on template matches, the ownership judgement is for Data Matching, match that load-carrying is normal, the load-carrying that exceeds the quata, slightly fall that slag, moderate fall slag, severe is fallen slag and these several classifications of major accident, classifier evaluation is calibrated the robustness of judgement, meets the Dynamic Matching function.
A3, control center carry out monitoring and early warning to vehicle load-bearing situation.
In this step, above-mentioned control center carries out monitoring and reminding to vehicle load-bearing situation, comprise the monitoring under the load condition that exceeds the quata and/or fall the early warning in the slag situation, monitoring under the above-mentioned load condition that exceeds the quata comprises that Cloud Server determines the vehicle position, send the described load condition that exceeds the quata to the control center of relevant range, by control center, described vehicle is monitored; Early warning under the above-mentioned load condition that exceeds the quata comprises that control center sends to described car-mounted terminal by information, carries out the phonetic warning prompting by car-mounted terminal.
In embodiment of the method two, the present embodiment, vehicle belongs to cargo vehicle, and in overload condition.
B1, vehicle module Real-time Collection vehicle load-bearing information and characteristic information;
In this step, by weight sensor collection vehicle load-bearing information, by information acquisition unit collection vehicle characteristic information, because vehicle in the present embodiment is cargo vehicle, vehicle characteristics information comprises: vehicle motor frequency, throttle noise energy, axletree moment of torsion and load, tyre curvature radius and tire and contact area of ground.
B2, vehicle module send to Cloud Server by above-mentioned vehicle load-bearing information and characteristic information;
B3, Cloud Server carry out data storage, analysis and coupling to vehicle load-bearing information and characteristic information, if there is overload, result are outputed to control center;
According to " assert vehicle overload overload standard " 1. diaxon vehicle, its car goods gross weight surpasses 20 tons; 2. six-wheel vehicle, its car goods gross weight surpasses (the duplex axle calculates according to 2 axles, and three shaft couplings calculate according to 3 axles, lower together) of 30 tons; 3. four-axle vehicle, its car goods gross weight surpasses 40 tons; 4. 5-axle car, its car goods gross weight surpasses 50 tons; 5. six axles and the above vehicle of six axles, its car goods gross weight surpasses 55 tons; 6., though surpass above-mentioned 5 kinds of situations, loading mass surpasses driving license and appraises and decides mounted mass more than 30%.
In this step, data are stored, are obtained data value after pre-service and feature extraction and be:, carry out tagsort, compare with vehicle-mounted feature set, vehicle-mounted feature set comprises the rolling stock information of storing in Cloud Server, and described information of vehicles comprises vehicle essential information, vehicle dynamic information, vehicle attitude information.Because vehicle in the present embodiment belongs to 2 axle cars, and the vehicle load-bearing information that it obtains by weight sensor has surpassed 20 tons of standards in " assert the standard of vehicle overload overload ", therefore the ownership of mating in the present embodiment judgment result is that the load-carrying that exceeds the quata.
B3, described control center are monitored the overload of vehicle situation.
In this step, Cloud Server, according to the positioning unit on vehicle module, is determined the vehicle position, associated vehicle overload situation is issued to the control center of relevant range, by control center, vehicle is monitored.
In embodiment of the method three, the present embodiment, vehicle belongs to dump truck, has occurred falling the slag situation midway.
C1, vehicle module Real-time Collection vehicle load-bearing information and characteristic information; In this step, vehicle module gathered once vehicle-mounted characteristic information every 2 minutes.
C2, vehicle module send to Cloud Server by above-mentioned vehicle-mounted characteristic information;
In this step, in the present embodiment, vehicle-mounted characteristic information comprises vehicle load-bearing information and vehicle characteristics information, and vehicle characteristics information comprises vehicle motor frequency, throttle noise energy, axletree moment of torsion and load, tyre curvature radius and tire and contact area of ground.
C3, Cloud Server carry out data storage, analysis and coupling to vehicle load-bearing information and characteristic information, judge that vehicle load-bearing information change scope, whether in secure threshold, if exceeded secure threshold, outputs to control center by result; In the present embodiment, secure threshold is determined by vehicle characteristics information, is specially: surpass vehicle and appraise and decide load value and surpass track and forever permitted current load value and be considered as overweightly, given the alarm to control center and car-mounted terminal; Describedly fall the slag scope and comprise that vehicle-mounted road load-carrying, non-normal stop goods reduce, vehicle load is less than original vehicle load-carrying scope 0.1% and is considered as slightly falling slag, being less than original vehicle load-carrying scope 0.5% belongs to moderate and falls slag, be less than original vehicle load-carrying scope 1% and belong to severe and fall slag, be greater than original vehicle load-carrying scope 1% and belong to major accident.
C4, control center fall the slag situation to vehicle and carry out the early warning prompting.
In the present embodiment, owing to belonging to severe, fall slag, control center sends to car-mounted terminal by information, by car-mounted terminal, carries out the phonetic warning prompting.Control center, according to the positioning unit of car-mounted terminal, determines vehicle location simultaneously, carries out the road safety monitoring.
Device embodiment mono-:
The invention provides a kind of vehicle load remote detection device, as shown in Figure 2, comprising:
Vehicle module, also send to Cloud Server by described vehicle-mounted characteristic information for the vehicle-mounted characteristic information of Real-time Collection;
Cloud Server, for carrying out data storage, analysis and coupling to described vehicle-mounted characteristic information; And the data after processing are outputed to control center;
Control center carries out monitoring and reminding to vehicle load-bearing situation.
Device embodiment bis-:
The invention provides a kind of vehicle load remote detection device, as shown in Figure 3,
Described vehicle-mounted characteristic information comprises vehicle load-bearing information and vehicle characteristics information;
Wherein, vehicle module comprises: weight sensor, information acquisition unit, vehicular control unit and wireless communication unit, and weight sensor is for collection vehicle load-bearing information and output to vehicular control unit; Information acquisition unit is for the collection vehicle characteristic information and output to vehicular control unit; Vehicular control unit is for being input to wireless communication unit by described vehicle load-bearing information and characteristic information; Wireless communication unit is for sending to described Cloud Server by vehicle load-bearing information and characteristic information.
Device embodiment tri-:
The invention provides a kind of vehicle load remote detection device, as shown in Figure 4, wherein, Cloud Server comprises storage unit, analytic unit and matching unit,
Described storage unit is for receiving and store data;
Described analytic unit comprises pre-service and feature extraction for described vehicle-mounted characteristic information is carried out to data analysis, and described pre-service comprises that mark one is processed, Data Dimensionality Reduction, and described feature extraction comprises redundance extraction, correlation analysis, non-linear extraction;
Described matching unit comprises the vehicle-mounted feature set of data referencing through pre-service and feature extraction, carries out tagsort, ownership judgement and classifier evaluation for described vehicle-mounted characteristic information being carried out to Data Matching.
Device embodiment tetra-:
The invention provides a kind of vehicle load remote detection device, as shown in Figure 5, wherein control center comprises wireless communication unit, control module and administrative unit, and described wireless communication unit is for communicating with vehicle module; Described control module is for carrying out alternately with Cloud Server; Described administrative unit is for showing information of vehicles.
Further, car-mounted terminal also comprises positioning unit and audio alert unit, wherein positioning unit can adopt GPS, dipper system or Galileo device to realize, the laggard lang sound of the information early warning that wherein the audio alert unit is receiving control center and sends.
Above control channel detection method and the device that the embodiment of the present invention is provided is described in detail, applied specific case herein principle of the present invention and embodiment are set forth, the explanation of above embodiment is just for helping to understand method of the present invention and core concept thereof; , for one of ordinary skill in the art, according to thought of the present invention, all will change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention simultaneously.
Claims (11)
1. a vehicle load remote detecting method, is characterized in that, comprising:
A1, the vehicle-mounted characteristic information of vehicle module Real-time Collection, and described vehicle-mounted characteristic information is sent to Cloud Server;
A2, described Cloud Server carry out data storage, analysis and coupling to described vehicle-mounted characteristic information, and the result after coupling is outputed to control center;
A3, described control center carry out monitoring and early warning to vehicle load-bearing situation.
2. a kind of vehicle load remote detecting method as claimed in claim 1, it is characterized in that, described vehicle-mounted characteristic information comprises: vehicle load information and vehicle characteristics information, described vehicle characteristics information comprises: vehicle motor frequency, throttle noise energy, axletree moment of torsion and load, tyre curvature radius and tire and contact area of ground.
3. a kind of vehicle load remote detecting method as claimed in claim 1, it is characterized in that, described Cloud Server carries out data analysis to described vehicle-mounted characteristic information and comprises pre-service and feature extraction, described pre-service comprises that mark one is processed, Data Dimensionality Reduction, and described feature extraction comprises redundance extraction, correlation analysis, non-linear extraction.
4. a kind of vehicle load remote detecting method as claimed in claim 3, it is characterized in that, described Cloud Server carries out Data Matching to described vehicle-mounted characteristic information to comprise the vehicle-mounted feature set of data referencing through pre-service and feature extraction, carries out tagsort, ownership judgement and classifier evaluation.
5. a kind of vehicle load remote detecting method as claimed in claim 4, is characterized in that, described tagsort comprises sorter, the sorter based on Hidden Markov Model (HMM), the sorter based on artificial neural network and support vector machine based on template matches.
6. a kind of vehicle load remote detecting method as claimed in claim 4, is characterized in that, the judgement of described ownership comprises that load-carrying is normal, the load-carrying that exceeds the quata, slightly fall that slag, moderate fall slag, severe is fallen slag and major accident.
7. a kind of vehicle load remote detecting method as claimed in claim 1, it is characterized in that, described control center carries out monitoring and early warning to vehicle load-bearing situation, comprise the monitoring under the load condition that exceeds the quata and/or fall the early warning in the slag situation, monitoring under the described load condition that exceeds the quata comprises that Cloud Server determines the vehicle position, send the described load condition that exceeds the quata to the control center of relevant range, by control center, described vehicle is monitored; Early warning under the described load condition that exceeds the quata comprises that control center sends to described car-mounted terminal by information, carries out the phonetic warning prompting by car-mounted terminal.
8. a vehicle load remote detecting system, is characterized in that, comprising:
Vehicle module, also send to Cloud Server by described vehicle-mounted characteristic information for the vehicle-mounted characteristic information of Real-time Collection;
Cloud Server, for carrying out data storage, analysis and coupling to described vehicle-mounted characteristic information; And the data after processing are outputed to control center;
Control center carries out monitoring and early warning to vehicle load-bearing situation.
9. a kind of vehicle load remote detecting system as claimed in claim 8, is characterized in that,
Described vehicle-mounted characteristic information comprises vehicle load-bearing information and vehicle characteristics information;
Described vehicle module comprises: weight sensor, information acquisition unit, vehicular control unit and wireless communication unit, and described weight sensor is for collection vehicle load-bearing information and output to vehicular control unit; Described information acquisition unit is for the collection vehicle characteristic information and output to vehicular control unit; Described vehicular control unit is for being input to wireless communication unit by described vehicle-mounted characteristic information; Wireless communication unit is for sending to described Cloud Server by described vehicle-mounted characteristic information.
10. a kind of vehicle load remote detecting system as claimed in claim 8, is characterized in that, described Cloud Server comprises storage unit, analytic unit and matching unit,
Described storage unit is for receiving and store data;
Described analytic unit comprises pre-service and feature extraction for described vehicle-mounted characteristic information is carried out to data analysis; Described pre-service comprises that mark one is processed, Data Dimensionality Reduction, and described feature extraction comprises redundance extraction, correlation analysis, non-linear extraction;
Described matching unit comprises the vehicle-mounted feature set of data referencing through pre-service and feature extraction, carries out tagsort, ownership judgement and classifier evaluation for described vehicle-mounted characteristic information being carried out to Data Matching.
11. a kind of vehicle load remote detecting system as claimed in claim 8 is characterized in that described control center comprises wireless communication unit, control module and administrative unit,
Described wireless communication unit is for communicating with vehicle module;
Described control module is for carrying out alternately with Cloud Server;
Described administrative unit is for showing information of vehicles.
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Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105444856A (en) * | 2015-11-12 | 2016-03-30 | 云南电网有限责任公司物流服务中心 | Tire pressure dynamic weighing device based on neural network |
| CN105678862A (en) * | 2016-01-06 | 2016-06-15 | 浪潮集团有限公司 | Freight car detection device based on large data |
| CN105718956A (en) * | 2016-01-26 | 2016-06-29 | 上海经达信息科技股份有限公司 | Overload determining method based on support vector machine |
| CN106918459A (en) * | 2016-06-26 | 2017-07-04 | 黑龙江工程学院 | Overloading wagon decision method |
| CN107680375A (en) * | 2017-09-29 | 2018-02-09 | 深圳市易成自动驾驶技术有限公司 | A kind of vehicle load computational methods, device and storage medium |
| CN110231077A (en) * | 2018-03-05 | 2019-09-13 | 山西国强高科股份有限公司 | Intelligent weighing system remote monitoring device |
| CN110361082A (en) * | 2019-06-26 | 2019-10-22 | 麦德荣 | A kind of monitoring system and monitoring method of real-time measurement gross combination weight |
| CN110672192A (en) * | 2019-10-10 | 2020-01-10 | 英华达（南京）科技有限公司 | Road surface load monitoring method, device, system, electronic equipment and storage medium |
| CN110823339A (en) * | 2018-08-10 | 2020-02-21 | 河南工业大学 | Granary state detection method and system based on two circles of pressure sensors on bottom surface |
| CN112435463A (en) * | 2020-10-20 | 2021-03-02 | 北京科技大学 | Vehicle type and vehicle weight classification method based on road internet of things monitoring |
| CN112903077A (en) * | 2021-01-26 | 2021-06-04 | 李乐 | Cargo weight remote monitoring system and monitoring method |
| CN112964345A (en) * | 2021-02-07 | 2021-06-15 | 广东电子工业研究院有限公司 | Freight car weighing system and weighing method thereof |
| CN112964343A (en) * | 2021-02-07 | 2021-06-15 | 广东电子工业研究院有限公司 | Freight car weighing monitoring system and monitoring method thereof |
| CN113155255A (en) * | 2020-01-22 | 2021-07-23 | 四川物软网联科技有限公司 | Vehicle load monitoring system and method and vehicle |
| CN113272157A (en) * | 2018-11-14 | 2021-08-17 | 米其林集团总公司 | Method for determining ground hardness |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH07318406A (en) * | 1994-05-30 | 1995-12-08 | Yazaki Corp | Loading weight measuring device |
| JPH085446A (en) * | 1994-06-17 | 1996-01-12 | Yazaki Corp | Loaded weight measuring instrument |
| CN102019872A (en) * | 2009-09-21 | 2011-04-20 | 中国国际海运集装箱(集团)股份有限公司 | Vehicle weight monitoring method and system and transport vehicle with the system |
| CN202614347U (en) * | 2012-06-18 | 2012-12-19 | 长安大学 | Real-time overload monitoring and warning system for automobile |
| CN103108042A (en) * | 2013-01-30 | 2013-05-15 | 无锡南理工科技发展有限公司 | Vehicle-mounted information collection system |
-
2013
- 2013-10-09 CN CN201310463804.0A patent/CN103487125B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH07318406A (en) * | 1994-05-30 | 1995-12-08 | Yazaki Corp | Loading weight measuring device |
| JPH085446A (en) * | 1994-06-17 | 1996-01-12 | Yazaki Corp | Loaded weight measuring instrument |
| CN102019872A (en) * | 2009-09-21 | 2011-04-20 | 中国国际海运集装箱(集团)股份有限公司 | Vehicle weight monitoring method and system and transport vehicle with the system |
| CN202614347U (en) * | 2012-06-18 | 2012-12-19 | 长安大学 | Real-time overload monitoring and warning system for automobile |
| CN103108042A (en) * | 2013-01-30 | 2013-05-15 | 无锡南理工科技发展有限公司 | Vehicle-mounted information collection system |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105444856A (en) * | 2015-11-12 | 2016-03-30 | 云南电网有限责任公司物流服务中心 | Tire pressure dynamic weighing device based on neural network |
| CN105678862A (en) * | 2016-01-06 | 2016-06-15 | 浪潮集团有限公司 | Freight car detection device based on large data |
| CN105718956A (en) * | 2016-01-26 | 2016-06-29 | 上海经达信息科技股份有限公司 | Overload determining method based on support vector machine |
| CN106918459B (en) * | 2016-06-26 | 2020-02-07 | 哈尔滨明公科技有限公司 | Truck overload judgment method |
| CN106918459A (en) * | 2016-06-26 | 2017-07-04 | 黑龙江工程学院 | Overloading wagon decision method |
| CN107680375A (en) * | 2017-09-29 | 2018-02-09 | 深圳市易成自动驾驶技术有限公司 | A kind of vehicle load computational methods, device and storage medium |
| CN107680375B (en) * | 2017-09-29 | 2020-07-17 | 深圳市易成自动驾驶技术有限公司 | Vehicle load calculation method and device and storage medium |
| CN110231077A (en) * | 2018-03-05 | 2019-09-13 | 山西国强高科股份有限公司 | Intelligent weighing system remote monitoring device |
| CN110823339B (en) * | 2018-08-10 | 2021-04-09 | 河南工业大学 | Granary state detection method and system based on two circles of pressure sensors on bottom surface |
| CN110823339A (en) * | 2018-08-10 | 2020-02-21 | 河南工业大学 | Granary state detection method and system based on two circles of pressure sensors on bottom surface |
| CN113272157A (en) * | 2018-11-14 | 2021-08-17 | 米其林集团总公司 | Method for determining ground hardness |
| CN110361082A (en) * | 2019-06-26 | 2019-10-22 | 麦德荣 | A kind of monitoring system and monitoring method of real-time measurement gross combination weight |
| CN110361082B (en) * | 2019-06-26 | 2021-05-14 | 麦德荣 | Monitoring system and monitoring method for measuring total weight of vehicle in real time |
| CN110672192A (en) * | 2019-10-10 | 2020-01-10 | 英华达（南京）科技有限公司 | Road surface load monitoring method, device, system, electronic equipment and storage medium |
| CN113155255A (en) * | 2020-01-22 | 2021-07-23 | 四川物软网联科技有限公司 | Vehicle load monitoring system and method and vehicle |
| CN112435463A (en) * | 2020-10-20 | 2021-03-02 | 北京科技大学 | Vehicle type and vehicle weight classification method based on road internet of things monitoring |
| CN112903077A (en) * | 2021-01-26 | 2021-06-04 | 李乐 | Cargo weight remote monitoring system and monitoring method |
| CN112964345A (en) * | 2021-02-07 | 2021-06-15 | 广东电子工业研究院有限公司 | Freight car weighing system and weighing method thereof |
| CN112964343A (en) * | 2021-02-07 | 2021-06-15 | 广东电子工业研究院有限公司 | Freight car weighing monitoring system and monitoring method thereof |
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