CN116256024B - Multifunctional bow net state detection system - Google Patents
Multifunctional bow net state detection system Download PDFInfo
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- CN116256024B CN116256024B CN202310255326.8A CN202310255326A CN116256024B CN 116256024 B CN116256024 B CN 116256024B CN 202310255326 A CN202310255326 A CN 202310255326A CN 116256024 B CN116256024 B CN 116256024B
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- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/16—Information or communication technologies improving the operation of electric vehicles
Abstract
The invention provides a multifunctional bow net shape detection system, comprising: the detection module is used for arranging a plurality of detection devices on the track to acquire bow net detection data; the state analysis module is used for carrying out independent state analysis according to the bow net detection data acquired by each detection device to obtain independent state characteristics; the comprehensive analysis module is used for comprehensively analyzing all the individual state characteristics according to the state association of each individual state to obtain comprehensive state characteristics; the abnormality determining module is used for determining abnormal information of the bow net according to the independent state characteristics and the comprehensive state characteristics and combining bow net state standard parameters; the invention ensures the accuracy and the comprehensiveness of the abnormal information of the bow net and avoids the occurrence of bow net accidents.
Description
Technical Field
The invention relates to the technical field of rail transit, in particular to a multifunctional bow net shape detection system.
Background
The power source of the high-speed train is obtained through the sliding contact between the pantograph and the overhead contact system, so that the pantograph gateway system influences the running safety of the train. Because there are unsmooth positions such as wired fork, anchor section joint on the contact net, can make the high-speed train in the operation process, the contact net drills to the pantograph head below, on the other hand pantograph, contact net or the relation of the pantograph net (i.e. the contact point of the pantograph net system) all probably appear the problem, like the eccentric wear of pantograph slide, the sheep horn defect, the deformation of sheep horn, contact net foreign matter drops, contact net wearing and tearing etc. once take place, will cause serious pantograph net accident, therefore the state of real-time supervision pantograph net is very critical.
Disclosure of Invention
The invention provides a multifunctional bow net state detection system which is used for ensuring the accuracy and the comprehensiveness of bow net abnormal information and avoiding the occurrence of bow net accidents.
A multi-functional archwire state detection system comprising:
the detection module is used for arranging a plurality of detection devices on the track to acquire bow net detection data;
the state analysis module is used for carrying out independent state analysis according to the bow net detection data acquired by each detection device to obtain independent state characteristics;
the comprehensive analysis module is used for comprehensively analyzing all the individual state characteristics according to the state association of each individual state to obtain comprehensive state characteristics;
and the abnormality determination module is used for determining the abnormal information of the bow net according to the independent state characteristics and the comprehensive state characteristics and combining the bow net state standard parameters.
Preferably, the system further comprises a communication module, wherein the communication module is used for sending the abnormal information of the bow net and the data corresponding to the independent state characteristics and the comprehensive state characteristics to the ground server.
Preferably, the detection module includes:
the geometric parameter unit is used for detecting the posture change of the vehicle body in the driving process in real time;
the arc net arcing detection unit is used for detecting ultraviolet rays of corresponding wave bands released when arcing occurs;
The bow net temperature detection unit is used for constructing a global high-definition high-speed thermal imager to perform high-definition shooting on a target in a visual field range, acquiring a thermal image of a current-receiving temperature field of a contact net-pantograph operation relationship, and obtaining the bow net temperature;
the pantograph structure detection unit is used for carrying out high-definition shooting on the pantograph structure by utilizing a high-definition industrial camera, and automatically identifying and judging whether the pantograph structure is abnormal or not by comparing and analyzing the acquired image with a standard template;
and the bow net pressure hard point detection unit is used for detecting bow net pressure hard points.
Preferably, the state analysis module includes:
the data dividing unit is used for dividing the data acquired by each monitoring device according to the detection targets to obtain a plurality of groups of detection data;
the data analysis unit is used for establishing a detection model corresponding to the preset detection mode according to the preset detection mode of the detection target and combining the detection principle, inputting each group of detection data into the corresponding detection model, and outputting the detection data to obtain single-target detection data;
the state determining unit is used for determining the corresponding relation between the detection data and the single state according to the historical bow net monitoring data, and obtaining the single state characteristic under the detection target by utilizing the single-target detection data according to the corresponding relation.
Preferably, the comprehensive analysis module includes:
the structure analysis processing unit is used for determining important structure points of the bow net structure, analyzing the important structure points from the angles of distance and structural characteristics and determining state association among all the individual states;
the state analysis processing unit is used for carrying out state association among the individual states, carrying out arc burning detection on the geometric parameters, carrying out temperature detection on the pantograph net, carrying out structure detection on the pantograph net and carrying out pressure hard point association on the pantograph net, establishing a fault detection model of the pantograph net by taking the fault detection structure of the pantograph net as a reference according to the fault characteristics of the pantograph net, and obtaining comprehensive state characteristics of the pantograph net based on the association relations and the fault detection model of the pantograph net.
Preferably, the structure analysis processing unit includes:
the structure determining unit is used for obtaining a pantograph in a pantograph net, a contact net and a pantograph net structure at the joint of the pantograph and the contact net, determining important structural points of the pantograph net according to historical fault information of the pantograph net structure, and marking the important structural points of the pantograph net in the pantograph net structure to obtain a pantograph net detection structure;
the structure analysis unit is used for carrying out distance analysis on the bow net detection structure, determining the relative distance between any two adjacent bow net important structural points, and carrying out structural feature analysis on the bow net detection structure to determine the structural feature of each bow net important structural point;
The parameter dividing unit is used for dividing the bow net detection data according to the structure points and matching corresponding bow net detection parameters for each bow net important structure point;
the parameter association determining unit is used for carrying out association analysis on the bow net detection parameters of the bow net important structural points based on the relative distance and the structural characteristics, and determining parameter association conditions among the bow net important structural points;
the state association determining unit is used for determining parameter sets corresponding to the individual states, and determining state association among the individual states according to the parameter sets and the parameter association condition.
Preferably, the state analysis processing unit includes:
the state analysis unit is used for determining the association relation between any two of the geometric parameters, the bow net arcing detection, the bow net temperature detection, the pantograph structure detection and the bow net pressure hard points based on the state association;
the state fusion unit is used for determining geometrical parameters, arc burning detection of the pantograph and temperature detection of the pantograph, and fusing individual state characteristics between any two of pantograph structure detection and pantograph pressure hard points based on the association relation to establish new local state characteristics;
The weight determining unit is used for setting weight values for each local state feature and each individual state feature according to the overall influence degree of the state feature on the bow net state;
and the comprehensive analysis unit is used for establishing an arch network fault detection model by taking the arch network detection structure as a reference according to the arch network fault characteristics, inputting the local state characteristics, the independent state characteristics and the corresponding weight values into the arch network fault detection model, and outputting the comprehensive state characteristics of the arch network.
Preferably, the anomaly determination module includes:
the first sequence acquisition unit is used for acquiring an individual state time sequence corresponding to each individual state feature according to the time sequence, and extracting a first fluctuation sequence which does not meet the standard fluctuation range from the individual state time sequence according to the standard fluctuation range corresponding to each individual state feature;
the fluctuation analysis unit is used for obtaining a fluctuation score of the first fluctuation sequence according to the sequence number and the corresponding sequence length of the first fluctuation sequence at the same time, and taking the single state characteristic corresponding to the first fluctuation sequence as the bow net abnormal information if the fluctuation score is smaller than a preset score;
The second sequence acquisition unit is used for acquiring a comprehensive state time sequence corresponding to the comprehensive state characteristics according to the time sequence if the fluctuation score is not smaller than the preset score, and extracting a second fluctuation sequence which does not meet the comprehensive fluctuation range from the comprehensive state time sequence;
and the information determining unit is used for determining the abnormal information of the bow net based on the matching degree of the first fluctuation sequence and the second fluctuation sequence.
Preferably, the information determining unit includes:
the matching unit is used for matching the first fluctuation sequence with the second fluctuation sequence according to the time point to obtain a matching degree and judging whether the matching degree is larger than a preset matching degree or not;
if yes, taking the comprehensive state characteristics corresponding to the second fluctuation sequence as bow net abnormal information;
otherwise, respectively extracting an independent fluctuation sequence and a comprehensive fluctuation sequence which are not matched from the first fluctuation sequence and the second fluctuation sequence;
the information analysis unit is used for acquiring a detection target corresponding to the independent fluctuation sequence, acquiring abnormal information under the detection target, integrating the abnormal information to obtain first comprehensive abnormal information, acquiring second comprehensive abnormal information corresponding to the comprehensive fluctuation sequence, and adding target abnormal information of different first comprehensive abnormal information and second comprehensive abnormal information into the second comprehensive abnormal information to obtain bow net abnormal information.
Preferably, the method further comprises: the early warning module is used for carrying out early warning and reminding based on the bow net abnormal information;
the early warning module comprises:
the threshold setting unit is used for setting a critical threshold of fault early warning according to the historical early warning data of the bow net state;
the anomaly analysis unit is used for analyzing the bow net anomaly information to obtain various fault thresholds, and judging whether target fault thresholds larger than a critical threshold exist in all the fault thresholds;
if yes, using the bow net abnormal information corresponding to the target fault threshold value as early warning information, and carrying out first early warning reminding;
otherwise, calculating comprehensive fault values of the fault thresholds, and judging whether the comprehensive fault values are larger than a critical threshold or not;
if yes, taking all the bow net abnormal information as early warning information, and carrying out second early warning reminding, otherwise, not carrying out early warning reminding.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a block diagram of a multi-functional archwire state detection system in accordance with an embodiment of the present invention;
FIG. 2 is a block diagram of a state analysis module according to an embodiment of the present invention;
fig. 3 is a block diagram of an anomaly determination module according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Example 1
The embodiment of the invention provides a multifunctional bow net shape detection system, as shown in fig. 1, comprising:
the detection module is used for arranging a plurality of detection devices on the track to acquire bow net detection data;
the state analysis module is used for carrying out independent state analysis according to the bow net detection data acquired by each detection device to obtain independent state characteristics;
The comprehensive analysis module is used for comprehensively analyzing all the individual state characteristics according to the state association of each individual state to obtain comprehensive state characteristics;
and the abnormality determination module is used for determining the abnormal information of the bow net according to the independent state characteristics and the comprehensive state characteristics and combining the bow net state standard parameters.
In this embodiment, the plurality of detecting devices, for example, include an arc burning detection device using an ultraviolet detection technology, a real-time detection device using an infrared imaging technology to detect temperature data of a pantograph and a catenary, a real-time analysis device using a binocular vision technology to analyze contact line abrasion, a laser triangulation method to detect dynamic geometric parameters of a pantograph and a catenary, a non-contact image recognition measurement technology to detect contact pressure of the pantograph and hard points of the catenary, and a high-definition industrial camera to monitor contact suspension state.
In this embodiment, the individual status features are, for example, dynamic geometric parameters of the overhead line system, arcing of the overhead line system, and temperatures of the overhead line system, and the comprehensive status features are a set of individual status features of the overhead line system at the same detection position, and include a status in which the individual status features in the set are integrated.
The beneficial effects of above-mentioned design scheme are: the multifunctional detection of the bow net is realized through the detection module, the comprehensiveness of the detection is guaranteed, the data of the multifunctional detection are analyzed through the state analysis module and the comprehensive analysis module, the independent state characteristics and the comprehensive state characteristics of the bow net are obtained, the independent state characteristics are integrated and analyzed to obtain the comprehensive state characteristics, the efficiency of detecting data analysis is improved, the comprehensiveness of the bow net state detection is determined, the accuracy and comprehensiveness of the bow net abnormal information determined by the abnormality determination module are finally guaranteed, and the occurrence of bow net accidents is avoided.
Example 2
Based on embodiment 1, the embodiment of the invention provides a multifunctional bow net state detection system, which further comprises a communication module, wherein the communication module is used for sending the bow net abnormal information and data corresponding to the individual state characteristics and the comprehensive state characteristics to a ground server.
The beneficial effects of above-mentioned design scheme are: the fault alarm information can be seen in time. The user can confirm the fault, and if the user checks the fault information and the data and then finds that the fault is misreported, the fault is removed.
Example 3
Based on embodiment 1, an embodiment of the present invention provides a multifunctional bow net state detection system, where the detection module includes:
the geometric parameter unit is used for detecting the posture change of the vehicle body in the driving process in real time;
the arc net arcing detection unit is used for detecting ultraviolet rays of corresponding wave bands released when arcing occurs;
the bow net temperature detection unit is used for constructing a global high-definition high-speed thermal imager to perform high-definition shooting on a target in a visual field range, acquiring a thermal image of a current-receiving temperature field of a contact net-pantograph operation relationship, and obtaining the bow net temperature;
the pantograph structure detection unit is used for carrying out high-definition shooting on the pantograph structure by utilizing a high-definition industrial camera, and automatically identifying and judging whether the pantograph structure is abnormal or not by comparing and analyzing the acquired image with a standard template;
And the bow net pressure hard point detection unit is used for detecting bow net pressure hard points.
In the embodiment, the overhead contact system geometric parameter measurement module consists of a roof geometric parameter detection module and a vehicle bottom compensation module, wherein the roof geometric parameter detection module consists of a high-speed industrial camera and infrared laser, and the parameters such as a pull-out value, a guide height, a contact line horizontal distance, a contact line height difference, a wire gradient and the like of a contact line of the overhead contact system are measured by using an infrared laser triangulation method, and meanwhile, the vehicle body posture change in the driving process is detected in real time by means of the vehicle bottom compensation device, and the detection result is used as compensation data of geometric parameter detection to correct the geometric parameter measurement result.
In this embodiment, the bow net arcing detection module is composed of an ultraviolet arcing detection module; the ultraviolet arcing detection module uses an ultraviolet phototube to detect ultraviolet rays of corresponding wave bands released when arcing occurs.
In this embodiment, the image acquisition and processing speed requirements are high in order to meet the detection of lines running at high speed. Meanwhile, how to deal with high-definition and high-speed acquisition imaging of the operation relation of the overhead contact system bow net and identify the electric connection, electric burn, insulation relation and the like of a circuit is a great technical difficulty to be solved by the module. Based on the analysis of a large number of international and domestic mainstream technologies and industrial applications, a series of growths, research and development accumulation of infrared thermal image acquisition and processing technologies are carried out, and finally a high-definition high-speed infrared thermal imager-based acquisition device is constructed. In the module, a global high-definition high-speed thermal imager is built for performing high-definition shooting on a target in a visual field range, a thermal image of a current-receiving temperature field of a contact net-pantograph operation relation is obtained, and meanwhile, a high-temperature point and a distribution diagram in the accurate thermal image are provided.
In this embodiment, the pantograph structure abnormality detection uses a high-definition industrial camera to perform high-definition photographing on the pantograph structure, and automatically recognizes and judges whether there is an abnormal state such as abnormal carbon slide plate, sheep horn or loss, foreign matter invasion, etc. by comparing and analyzing the collected image with a standard template. The pantograph structure abnormality detection adopts an advanced neural network technology to carry out deep learning on a target image, and the system can automatically identify the abnormal state of a key structure of the pantograph and give an alarm for prompting. After the system collects the pantograph structure image, the key structure part of the pantograph on the image is positioned, the positioning area is classified by using a classifier algorithm, and the classification result is judged whether the abnormality exists or not. Aiming at an image positioning strategy, in order to give consideration to accuracy and efficiency, the system adopts an algorithm comprehensive evaluation mode to position a key structure of the pantograph, and a deep neural network positioning algorithm is firstly adopted to identify and position a first frame of image acquired by a camera, and the algorithm is accurate in positioning, large in calculated amount, long in time consumption and low in efficiency; therefore, the follow-up acquired image is tracked and positioned by adopting a fuzzy algorithm, and the operation efficiency is high. The two positioning algorithms are combined with each other, so that the key parts of the pantograph can be positioned quickly and accurately, and the balance of accuracy and efficiency is considered.
In the embodiment, the hard points of the bow net pressure are detected by a contact force sensor arranged in a pantograph spring cylinder and an MEMS accelerometer (single triaxial) arranged at the lower part of a pantograph carbon slide plate strip, and the fiber bragg grating is formed in the optical fiber by utilizing the thermal processing action of ultraviolet light. Bragg Gratings (FBGs) are a periodic, microstructure that acts as a wavelength selective mirror. When light reaches the grating along the fiber, only the bragg wavelength of light will be reflected by the grating and the remaining light wave will continue through the fiber to the next grating without any loss.
The beneficial effects of above-mentioned design scheme are: the multifunctional detection of the bow net is realized through the detection module, the comprehensiveness of the detection is ensured, comprehensive detection data are obtained and are concentrated together, and a foundation is provided for the follow-up comprehensive analysis of the bow net.
The multifunctional detection of the bow net is realized through the detection module, the comprehensiveness of the detection is guaranteed, the data of the multifunctional detection are analyzed through the state analysis module and the comprehensive analysis module, the independent state characteristics and the comprehensive state characteristics of the bow net are obtained, the independent state characteristics are integrated and analyzed to obtain the comprehensive state characteristics, the efficiency of detecting data analysis is improved, the comprehensiveness of the bow net state detection is determined, the accuracy and comprehensiveness of the bow net abnormal information determined by the abnormality determination module are finally guaranteed, and the occurrence of bow net accidents is avoided.
Example 4
Based on embodiment 1, an embodiment of the present invention provides a multifunctional bow net state detection system, as shown in fig. 2, a state analysis module, including:
the data dividing unit is used for dividing the data acquired by each monitoring device according to the detection targets to obtain a plurality of groups of detection data;
the data analysis unit is used for establishing a detection model corresponding to the preset detection mode according to the preset detection mode of the detection target and combining the detection principle, inputting each group of detection data into the corresponding detection model, and outputting the detection data to obtain single-target detection data;
the state determining unit is used for determining the corresponding relation between the detection data and the single state according to the historical bow net monitoring data, and obtaining the single state characteristic under the detection target by utilizing the single-target detection data according to the corresponding relation.
In this embodiment, the detection target is, for example, a pantograph structure abnormality detection, the corresponding detection data is a shot image of each angle of the pantograph structure from a high-definition camera, and is used as a set of detection data, the corresponding detection principle is that whether an abnormal state such as abnormal or lost carbon slide plate and sheep horn, foreign matter invasion exists or not is automatically identified and judged by comparing and analyzing the acquired image with a standard template, and the corresponding detection model is designed by using algorithms such as artificial intelligence, deep learning, fuzzy control and the like.
In this embodiment, the detection target may also be an arch net temperature monitoring, an arch net arcing detection, or the like.
In this embodiment, for example, the value of the first detection data corresponds to the first state, and the value of the second detection data corresponds to the second state.
The beneficial effects of above-mentioned design scheme are: the bow net detection data acquired by the detection device are divided and then input into a pre-designed detection model, so that detection data corresponding to a detection target is obtained, and finally, the independent state characteristics are obtained, the analysis of all the bow net detection data in one module is realized, the independent state characteristics are obtained, the analysis processing efficiency of the bow net detection data is improved, and a data basis is provided for the determination of the comprehensive state characteristics.
Example 5
Based on embodiment 1, an embodiment of the present invention provides a multifunctional bow net state detection system, where the comprehensive analysis module includes:
the structure analysis processing unit is used for determining important structure points of the bow net structure, analyzing the important structure points from the angles of distance and structural characteristics and determining state association among all the individual states;
the state analysis processing unit is used for carrying out state association among the individual states, carrying out arc burning detection on the geometric parameters, carrying out temperature detection on the pantograph net, carrying out structure detection on the pantograph net and carrying out pressure hard point association on the pantograph net, establishing a fault detection model of the pantograph net by taking the fault detection structure of the pantograph net as a reference according to the fault characteristics of the pantograph net, and obtaining comprehensive state characteristics of the pantograph net based on the association relations and the fault detection model of the pantograph net.
In this embodiment, the structure analysis processing unit includes:
the structure determining unit is used for obtaining a pantograph in a pantograph net, a contact net and a pantograph net structure at the joint of the pantograph and the contact net, determining important structural points of the pantograph net according to historical fault information of the pantograph net structure, and marking the important structural points of the pantograph net in the pantograph net structure to obtain a pantograph net detection structure;
the structure analysis unit is used for carrying out distance analysis on the bow net detection structure, determining the relative distance between any two adjacent bow net important structural points, and carrying out structural feature analysis on the bow net detection structure to determine the structural feature of each bow net important structural point;
the parameter dividing unit is used for dividing the bow net detection data according to the structure points and matching corresponding bow net detection parameters for each bow net important structure point;
the parameter association determining unit is used for carrying out association analysis on the bow net detection parameters of the bow net important structural points based on the relative distance and the structural characteristics, and determining parameter association conditions among the bow net important structural points;
the state association determining unit is used for determining parameter sets corresponding to the individual states, and determining state association among the individual states according to the parameter sets and the parameter association condition.
In this embodiment, the state analysis processing unit includes:
the state analysis unit is used for determining the association relation between any two of the geometric parameters, the bow net arcing detection, the bow net temperature detection, the pantograph structure detection and the bow net pressure hard points based on the state association;
the state fusion unit is used for determining geometrical parameters, arc burning detection of the pantograph and temperature detection of the pantograph, and fusing individual state characteristics between any two of pantograph structure detection and pantograph pressure hard points based on the association relation to establish new local state characteristics;
the weight determining unit is used for setting weight values for each local state feature and each individual state feature according to the overall influence degree of the state feature on the bow net state;
and the comprehensive analysis unit is used for establishing an arch network fault detection model by taking the arch network detection structure as a reference according to the arch network fault characteristics, inputting the local state characteristics, the independent state characteristics and the corresponding weight values into the arch network fault detection model, and outputting the comprehensive state characteristics of the arch network.
The beneficial effects of above-mentioned design scheme are: determining the important structural points of the bow net and analyzing the important structural points from the angles of the distance and the structural characteristics, determining the state association between each independent state, determining the association between each independent state characteristic, providing a basis for further determining the neutral state characteristic, then based on the state association between each independent state, carrying out bow net arcing detection, bow net temperature detection, association between any two of bow net pressure hard points and bow net structural detection, and establishing a bow net fault detection model based on the bow net fault characteristics and taking the bow net detection structure as a reference, obtaining the comprehensive state characteristics of the bow net based on the association and the bow net fault detection model, analyzing the specific geometric parameters, bow net arcing detection, bow net temperature detection, bow net pressure hard points, combining the association and the bow net fault detection model, obtaining the comprehensive state characteristics of the bow net, and guaranteeing the accuracy of the obtained comprehensive state characteristics.
Example 6
Based on embodiment 5, an embodiment of the present invention provides a multifunctional bow net state detection system, where the structure analysis processing unit includes:
the structure determining unit is used for obtaining a pantograph in a pantograph net, a contact net and a pantograph net structure at the joint of the pantograph and the contact net, determining important structural points of the pantograph net according to historical fault information of the pantograph net structure, and marking the important structural points of the pantograph net in the pantograph net structure to obtain a pantograph net detection structure;
the structure analysis unit is used for carrying out distance analysis on the bow net detection structure, determining the relative distance between any two adjacent bow net important structural points, and carrying out structural feature analysis on the bow net detection structure to determine the structural feature of each bow net important structural point;
the parameter dividing unit is used for dividing the bow net detection data according to the structure points and matching corresponding bow net detection parameters for each bow net important structure point;
the parameter association determining unit is used for carrying out association analysis on the bow net detection parameters of the bow net important structural points based on the relative distance and the structural characteristics, and determining parameter association conditions among the bow net important structural points;
the state association determining unit is used for determining parameter sets corresponding to the individual states, and determining state association among the individual states according to the parameter sets and the parameter association condition.
In this embodiment, the structural features of the net vital structural points are related to the structure of the net vital structural points.
In this embodiment, the parameter association between the net importance points, for example, the net pressure hard point of the first net importance point affects the net pressure hard point of the second net importance point, or the net arcing detection value of the third net importance point and the net arcing detection value of the fourth net importance point are mutually affected, and the specific extent of the influence is not only related to the structure but also to the distance between the structure points.
In this embodiment, the state correlation between the individual states is a state correlation to the neutral state of the geometric parameters, bow net arcing detection, bow net temperature detection, pantograph structure detection, and bow net pressure hard points.
The beneficial effects of above-mentioned design scheme are: the parameter association condition among important structural points of the bow net is determined by designing a specific bow net detection structure and analyzing the distance and structural characteristics of the structural points on the basis, then the parameter association condition among important structural points of the bow net is analyzed from the other aspect, namely, each independent state, the two are combined and analyzed to obtain the state association among the independent states, the obtained state association is comprehensively reflected in the association among the detection target, the detection distance and the detection structural characteristics, and a basis is provided for further determining the neutral state characteristics.
Example 7
Based on embodiment 5, an embodiment of the present invention provides a multifunctional bow net state detection system, where the state analysis processing unit includes:
the state analysis unit is used for determining the association relation between any two of the geometric parameters, the bow net arcing detection, the bow net temperature detection, the pantograph structure detection and the bow net pressure hard points based on the state association;
the state fusion unit is used for determining geometrical parameters, arc burning detection of the pantograph and temperature detection of the pantograph, and fusing individual state characteristics between any two of pantograph structure detection and pantograph pressure hard points based on the association relation to establish new local state characteristics;
the weight determining unit is used for setting weight values for each local state feature and each individual state feature according to the overall influence degree of the state feature on the bow net state;
and the comprehensive analysis unit is used for establishing an arch network fault detection model by taking the arch network detection structure as a reference according to the arch network fault characteristics, inputting the local state characteristics, the independent state characteristics and the corresponding weight values into the arch network fault detection model, and outputting the comprehensive state characteristics of the arch network.
In this embodiment, the local state features include a state fusion feature of some or all of two or more individual state features.
In this embodiment, the greater the overall degree of influence of the state features on the state of the bownet, the greater the corresponding weight value.
In this embodiment, the integrated state feature is a feature corresponding to a failure detection result of a corresponding global bow net state determined from a plurality of individual and local state features.
In this embodiment, the bownet fault detection model is specifically determined from a relationship between the bownet fault characteristics and the bownet detection structure.
The beneficial effects of above-mentioned design scheme are: the method comprises the steps of determining specific geometric parameters, detecting arcing of an arch net, detecting temperature of the arch net, detecting a pantograph structure and a hard point of the arch net pressure, setting a weight value for each local state feature and each individual state feature according to the overall influence degree of the state features on the state of the arch net, establishing an arch net fault detection model by taking the arch net detection structure as a reference, outputting and obtaining comprehensive state features of the arch net, and guaranteeing the comprehensiveness and accuracy of the obtained comprehensive state features.
Example 8
Based on embodiment 1, an embodiment of the present invention provides a multifunctional bow net state detection system, as shown in fig. 3, where the anomaly determination module includes:
the first sequence acquisition unit is used for acquiring an individual state time sequence corresponding to each individual state feature according to the time sequence, and extracting a first fluctuation sequence which does not meet the standard fluctuation range from the individual state time sequence according to the standard fluctuation range corresponding to each individual state feature;
the fluctuation analysis unit is used for obtaining a fluctuation score of the first fluctuation sequence according to the sequence number and the corresponding sequence length of the first fluctuation sequence at the same time, and taking the single state characteristic corresponding to the first fluctuation sequence as the bow net abnormal information if the fluctuation score is smaller than a preset score;
the second sequence acquisition unit is used for acquiring a comprehensive state time sequence corresponding to the comprehensive state characteristics according to the time sequence if the fluctuation score is not smaller than the preset score, and extracting a second fluctuation sequence which does not meet the comprehensive fluctuation range from the comprehensive state time sequence;
and the information determining unit is used for determining the abnormal information of the bow net based on the matching degree of the first fluctuation sequence and the second fluctuation sequence.
In this embodiment, the individual state time sequence is used to represent the individual state of the bowden at different points in time as a function of the point in time.
In this embodiment, the integrated state time sequence is used to represent the variation of the integrated state of the bowden at different time points with time points.
In this embodiment, the integrated state features are indicative of the overall bow net state, e.g. the integrated state of the bow net is derived from specific detected values of bow net temperature, bow net pressure hard points.
In this embodiment, the first fluctuation sequence is plural, and one individual state feature corresponds to one first fluctuation sequence.
In this embodiment, the integrated fluctuation range is derived from the integrated status feature.
In this embodiment, the greater the number of sequences, the greater the sequence length and the corresponding sequence score, which indicates that a plurality of individual status features are abnormal and have a longer duration, and at this time, an integrated status feature analysis is required to determine final arcade network abnormal information, which, on the contrary, indicates that fewer individual status features are abnormal and have a shorter duration, and only by using the individual status features, arcade network abnormal information can be indicated.
In this embodiment, the information determination unit includes:
the matching unit is used for matching the first fluctuation sequence with the second fluctuation sequence according to the time point to obtain a matching degree and judging whether the matching degree is larger than a preset matching degree or not;
if yes, taking the comprehensive state characteristics corresponding to the second fluctuation sequence as bow net abnormal information;
otherwise, respectively extracting an independent fluctuation sequence and a comprehensive fluctuation sequence which are not matched from the first fluctuation sequence and the second fluctuation sequence;
the information analysis unit is used for acquiring a detection target corresponding to the independent fluctuation sequence, acquiring abnormal information under the detection target, integrating the abnormal information to obtain first comprehensive abnormal information, acquiring second comprehensive abnormal information corresponding to the comprehensive fluctuation sequence, and adding target abnormal information of different first comprehensive abnormal information and second comprehensive abnormal information into the second comprehensive abnormal information to obtain bow net abnormal information.
The beneficial effects of above-mentioned design scheme are: the condition of abnormal state of the bow net is judged by analyzing the independent state characteristics according to time, if the condition is only slightly abnormal, the abnormal state of the bow net can be obtained through the independent state characteristics, so that abnormal information redundancy of the power bow net is avoided, and the view of working members is inconvenient, otherwise, the comprehensive state characteristics are required to be further analyzed, and the comprehensive state characteristics are required to be expanded according to the independent state characteristics, so that the comprehensiveness and the accuracy of the finally obtained bow net state information are ensured.
Example 9
Based on embodiment 8, an embodiment of the present invention provides a multifunctional bow net state detection system, where the information determining unit includes:
the matching unit is used for matching the first fluctuation sequence with the second fluctuation sequence according to the time point to obtain a matching degree and judging whether the matching degree is larger than a preset matching degree or not;
if yes, taking the comprehensive state characteristics corresponding to the second fluctuation sequence as bow net abnormal information;
otherwise, respectively extracting an independent fluctuation sequence and a comprehensive fluctuation sequence which are not matched from the first fluctuation sequence and the second fluctuation sequence;
the information analysis unit is used for acquiring a detection target corresponding to the independent fluctuation sequence, acquiring abnormal information under the detection target, integrating the abnormal information to obtain first comprehensive abnormal information, acquiring second comprehensive abnormal information corresponding to the comprehensive fluctuation sequence, and adding target abnormal information of different first comprehensive abnormal information and second comprehensive abnormal information into the second comprehensive abnormal information to obtain bow net abnormal information.
In this embodiment, the greater the degree of matching, the more consistent the first and second sequences of fluctuations are ensured.
The beneficial effects of above-mentioned design scheme are: the target abnormal information of the first comprehensive abnormal information and the target abnormal information of the second comprehensive abnormal information are added into the second comprehensive abnormal information, so that the redundancy of the arch network abnormal information obtained by independent and comprehensive direct superposition is avoided, the checking of staff is inconvenient, the comprehensiveness and the accuracy of the arch network abnormal information are ensured, and the occurrence of arch network accidents is avoided.
Example 10
Based on embodiment 1, an embodiment of the present invention provides a multifunctional bow net state detection system, further including: the early warning module is used for carrying out early warning and reminding based on the bow net abnormal information;
the early warning module comprises:
the threshold setting unit is used for setting a critical threshold of fault early warning according to the historical early warning data of the bow net state;
the calculation formula of the critical threshold is as follows:
wherein K is 0 A critical threshold value representing fault early warning, n 1 Indicating the times of failure of the follow-up bow net without warning in the history warning data, n 2 Indicating the times of no early warning reminding and no fault of the subsequent bow net in the history early warning data, n 3 The times of early warning reminding and fault processing by staff in the historical early warning data are represented, n 4 P represents the times of early warning reminding and the staff affirming to be erroneous judgment in the history early warning data 1 The probability that no early warning is carried out and the subsequent bow net fails in the historical early warning data is represented, P 2 The probability that no early warning reminding is carried out and no fault occurs in the subsequent bow net in the historical early warning data is represented, P 3 P represents the probability of early warning reminding and fault processing by staff in the historical early warning data 4 Representing historical early warning dataProbability of row early warning reminding and staff affirming as erroneous judgment, delta 1 Represents a first adjustment coefficient, and delta 1 >0，δ 2 Represents a second adjustment coefficient, and delta 2 The value range of (a) is (-0.1,0.1), delta 3 Represents a third adjustment coefficient, and delta 3 The value range of (a) is (-0.1,0.1), delta 4 Represents a third adjustment coefficient, and delta 4 <0，A i Representing a fault threshold value when early warning reminding is not carried out for the ith time and a follow-up bow net is in fault, B j C, representing a fault threshold value when early warning reminding is not carried out at the j th time and a follow-up bow net fails ω The fault threshold value when the early warning reminding is carried out for the omega th time and the working personnel carry out fault treatment is represented,indicate->And carrying out early warning reminding for the second time and confirming the fault threshold value when the staff confirms the fault judgment. e represents a natural constant, and the value is 2.72; / >
The anomaly analysis unit is used for analyzing the bow net anomaly information to obtain various fault thresholds, and judging whether target fault thresholds larger than a critical threshold exist in all the fault thresholds;
if yes, using the bow net abnormal information corresponding to the target fault threshold value as early warning information, and carrying out first early warning reminding;
otherwise, calculating comprehensive fault values of the fault thresholds, and judging whether the comprehensive fault values are larger than a critical threshold or not;
if yes, taking all the bow net abnormal information as early warning information, and carrying out second early warning reminding, otherwise, not carrying out early warning reminding.
In this embodiment, the first warning alert is a separate warning alert for a certain detection target, such as temperature, arcing, etc.
In this embodiment, the second early warning alert is an early warning alert for bow net shape synthesis.
The beneficial effects of above-mentioned design scheme are: through the historical early warning data according to the bow net state include do not carry out the early warning and remind and follow-up bow net break down, carry out the early warning in the historical early warning data and remind and carry out the staff and carry out the fault handling and carry out the early warning and remind and the staff confirms the number of times of four kinds of circumstances of erroneous judgement, probability and the threshold value of corresponding trouble come reasonable in design critical threshold value, the accuracy of early warning has been improved, reduce staff's work load, simultaneously can in time discover bow net trouble again, when carrying out the early warning, carry out the early warning to solitary detection target according to bow net abnormal information, still consider the comprehensive condition of bow net simultaneously and carry out the early warning, improve the precision of early warning, avoid the emergence of bow net accident.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (7)
1. A multi-functional archwire state detection system, comprising:
the detection module is used for arranging a plurality of detection devices on the track to acquire bow net detection data;
the state analysis module is used for carrying out independent state analysis according to the bow net detection data acquired by each detection device to obtain independent state characteristics;
the comprehensive analysis module is used for comprehensively analyzing all the individual state characteristics according to the state association of each individual state to obtain comprehensive state characteristics;
the abnormality determining module is used for determining abnormal information of the bow net according to the independent state characteristics and the comprehensive state characteristics and combining bow net state standard parameters;
wherein, the state analysis module includes:
the data dividing unit is used for dividing the data acquired by each monitoring device according to the detection targets to obtain a plurality of groups of detection data;
The data analysis unit is used for establishing a detection model corresponding to the preset detection mode according to the preset detection mode of the detection target and combining the detection principle, inputting each group of detection data into the corresponding detection model, and outputting the detection data to obtain single-target detection data;
the state determining unit is used for determining the corresponding relation between the detection data and the single state according to the historical bow net monitoring data and obtaining the single state characteristic under the detection target by utilizing the single target detection data according to the corresponding relation;
wherein, comprehensive analysis module includes:
the structure analysis processing unit is used for determining important structure points of the bow net structure, analyzing the important structure points from the angles of distance and structural characteristics and determining state association among all the individual states;
the state analysis processing unit is used for carrying out state association among all the independent states, carrying out arc burning detection on the geometric parameters, carrying out temperature detection on the pantograph net, carrying out structure detection on the pantograph net and carrying out pressure hard point association on the pantograph net, establishing a fault detection model of the pantograph net by taking the structure of the pantograph net as a reference according to fault characteristics of the pantograph net, and obtaining comprehensive state characteristics of the pantograph net based on the association relations and the fault detection model of the pantograph net;
Wherein, the anomaly determination module includes:
the first sequence acquisition unit is used for acquiring an individual state time sequence corresponding to each individual state feature according to the time sequence, and extracting a first fluctuation sequence which does not meet the standard fluctuation range from the individual state time sequence according to the standard fluctuation range corresponding to each individual state feature;
the fluctuation analysis unit is used for obtaining a fluctuation score of the first fluctuation sequence according to the sequence number and the corresponding sequence length of the first fluctuation sequence at the same time, and taking the single state characteristic corresponding to the first fluctuation sequence as the bow net abnormal information if the fluctuation score is smaller than a preset score;
the second sequence acquisition unit is used for acquiring a comprehensive state time sequence corresponding to the comprehensive state characteristics according to the time sequence if the fluctuation score is not smaller than the preset score, and extracting a second fluctuation sequence which does not meet the comprehensive fluctuation range from the comprehensive state time sequence;
and the information determining unit is used for determining the abnormal information of the bow net based on the matching degree of the first fluctuation sequence and the second fluctuation sequence.
2. The system of claim 1, further comprising a communication module configured to send the abnormal information of the bownet and the data corresponding to the individual status feature and the integrated status feature to a ground server.
3. A multi-functional archwire state detection system as claimed in claim 1, wherein said detection module comprises:
the geometric parameter unit is used for detecting the posture change of the vehicle body in the driving process in real time;
the arc net arcing detection unit is used for detecting ultraviolet rays of corresponding wave bands released when arcing occurs;
the bow net temperature detection unit is used for constructing a global high-definition high-speed thermal imager to perform high-definition shooting on a target in a visual field range, acquiring a thermal image of a current-receiving temperature field of a contact net-pantograph operation relationship, and obtaining the bow net temperature;
the pantograph structure detection unit is used for carrying out high-definition shooting on the pantograph structure by utilizing a high-definition industrial camera, and automatically identifying and judging whether the pantograph structure is abnormal or not by comparing and analyzing the acquired image with a standard template;
and the bow net pressure hard point detection unit is used for detecting bow net pressure hard points.
4. A multi-functional arching state detection system according to claim 1, wherein the structural analysis processing unit includes:
the structure determining unit is used for obtaining a pantograph in a pantograph net, a contact net and a pantograph net structure at the joint of the pantograph and the contact net, determining important structural points of the pantograph net according to historical fault information of the pantograph net structure, and marking the important structural points of the pantograph net in the pantograph net structure to obtain a pantograph net detection structure;
The structure analysis unit is used for carrying out distance analysis on the bow net detection structure, determining the relative distance between any two adjacent bow net important structural points, and carrying out structural feature analysis on the bow net detection structure to determine the structural feature of each bow net important structural point;
the parameter dividing unit is used for dividing the bow net detection data according to the structure points and matching corresponding bow net detection parameters for each bow net important structure point;
the parameter association determining unit is used for carrying out association analysis on the bow net detection parameters of the bow net important structural points based on the relative distance and the structural characteristics, and determining parameter association conditions among the bow net important structural points;
the state association determining unit is used for determining parameter sets corresponding to the individual states, and determining state association among the individual states according to the parameter sets and the parameter association condition.
5. A multi-functional arching state detection system according to claim 1, wherein said state analysis processing unit comprises:
the state analysis unit is used for determining the association relation between any two of the geometric parameters, the bow net arcing detection, the bow net temperature detection, the pantograph structure detection and the bow net pressure hard points based on the state association;
The state fusion unit is used for determining geometrical parameters, arc burning detection of the pantograph and temperature detection of the pantograph, and fusing individual state characteristics between any two of pantograph structure detection and pantograph pressure hard points based on the association relation to establish new local state characteristics;
the weight determining unit is used for setting weight values for each local state feature and each individual state feature according to the overall influence degree of the state feature on the bow net state;
and the comprehensive analysis unit is used for establishing an arch network fault detection model by taking the arch network detection structure as a reference according to the arch network fault characteristics, inputting the local state characteristics, the independent state characteristics and the corresponding weight values into the arch network fault detection model, and outputting the comprehensive state characteristics of the arch network.
6. A multi-functional arching state detection system according to claim 1, characterized in that the information determination unit includes:
the matching unit is used for matching the first fluctuation sequence with the second fluctuation sequence according to the time point to obtain a matching degree and judging whether the matching degree is larger than a preset matching degree or not;
if yes, taking the comprehensive state characteristics corresponding to the second fluctuation sequence as bow net abnormal information;
Otherwise, respectively extracting an independent fluctuation sequence and a comprehensive fluctuation sequence which are not matched from the first fluctuation sequence and the second fluctuation sequence;
the information analysis unit is used for acquiring a detection target corresponding to the independent fluctuation sequence, acquiring abnormal information under the detection target, integrating the abnormal information to obtain first comprehensive abnormal information, acquiring second comprehensive abnormal information corresponding to the comprehensive fluctuation sequence, and adding target abnormal information of different first comprehensive abnormal information and second comprehensive abnormal information into the second comprehensive abnormal information to obtain bow net abnormal information.
7. A multi-functional archwire state detection system as recited in claim 1, further comprising: the early warning module is used for carrying out early warning and reminding based on the bow net abnormal information;
the early warning module comprises:
the threshold setting unit is used for setting a critical threshold of fault early warning according to the historical early warning data of the bow net state;
the anomaly analysis unit is used for analyzing the bow net anomaly information to obtain various fault thresholds, and judging whether target fault thresholds larger than a critical threshold exist in all the fault thresholds;
if yes, using the bow net abnormal information corresponding to the target fault threshold value as early warning information, and carrying out first early warning reminding;
Otherwise, calculating comprehensive fault values of the fault thresholds, and judging whether the comprehensive fault values are larger than a critical threshold or not;
if yes, taking all the bow net abnormal information as early warning information, and carrying out second early warning reminding, otherwise, not carrying out early warning reminding.
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| CN103115647A (en) * | 2013-02-01 | 2013-05-22 | 赵乎 | Monitoring system for rail transit bow net operating condition |
| CN109000729A (en) * | 2018-07-31 | 2018-12-14 | 广州科易光电技术有限公司 | Vehicle-mounted contact net condition monitoring system |
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