CN115688420A - Escalator quality evaluation method, system, equipment and medium based on urban rail ISCS - Google Patents
Escalator quality evaluation method, system, equipment and medium based on urban rail ISCS Download PDFInfo
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- CN115688420A CN115688420A CN202211339385.5A CN202211339385A CN115688420A CN 115688420 A CN115688420 A CN 115688420A CN 202211339385 A CN202211339385 A CN 202211339385A CN 115688420 A CN115688420 A CN 115688420A
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Abstract
The method comprises the steps of obtaining ISCS data of all urban rail escalator devices connected into an ISCS system in real time, wherein the ISCS data comprise urban rail escalator real-time state data and urban rail maintenance platform account data, calculating the urban rail escalator real-time state data and the urban rail maintenance platform account data, constructing a quality evaluation index system conforming to the quality attenuation coefficient of the urban rail escalator, inputting current operation data of each urban rail escalator into the quality evaluation index system for quality evaluation, generating a quality evaluation result of each urban rail escalator, calculating the random selection probability of each urban rail escalator, sequencing the quality evaluation results of the urban rail escalator according to the random selection probability, and obtaining quality arrangement data for performing dynamic quality evaluation on all the urban rail escalators in the ISCS system. This application has the effect of being convenient for carry out the quality evaluation to a plurality of escalators in the ISCS system.
Description
Technical Field
The invention relates to the technical field of escalator quality evaluation, in particular to an escalator quality evaluation method, system, equipment and medium based on urban rail ISCS.
Background
At present, with the rapid advance of the urbanization process in China, the safety problems of public infrastructures such as escalators become the focus of extensive attention of the whole society, people injury accidents of the escalators caused by incorrect use and untimely maintenance of the escalators occur frequently, and particularly, higher requirements are put forward for the quality safety of the escalators in the operation process at urban rail transportation hubs with large concentrated passenger flow.
The existing escalator quality evaluation mode is generally that in the escalator operation process, maintenance personnel regularly perform manual inspection on an escalator, judge whether the escalator parts have aging faults and the like and perform timely replacement, generally perform maintenance inspection once every 14 days, but along with the increase of the escalator operation time and the overload of carrying personnel or the prevention of illegal operations such as opening and closing doors, the fault risk of the escalator in the operation process is easily increased, the outgoing quality of escalators of different brands is different, and the standard for synchronously evaluating the operation safety quality of escalators of multiple brands is lacked.
In view of the above-mentioned related art, the inventor believes that there is a defect that the standard for synchronously evaluating the running safety quality of escalators of different brands is lacked.
Disclosure of Invention
In order to establish an evaluation system of the operation safety quality of a plurality of brands of escalators and carry out uniform operation safety quality evaluation on the escalators of different brands, the application provides an escalator quality evaluation method, system, equipment and medium based on urban rail ISCS.
The above object of the present invention is achieved by the following technical solutions:
the escalator quality evaluation method based on the urban rail ISCS comprises the following steps:
the method comprises the steps of acquiring ISCS data of all urban rail escalator equipment accessed to an ISCS system in real time, wherein the ISCS data comprises urban rail escalator real-time state data and urban rail maintenance platform account data;
calculating the real-time state data of the urban rail escalator and the urban rail maintenance machine account data, and constructing a quality evaluation index system which accords with the quality attenuation coefficient of the urban rail escalator;
inputting the current operation data of each urban rail escalator into a quality evaluation index system for quality evaluation to generate a quality evaluation result of each urban rail escalator;
and calculating the random selection probability of each urban rail escalator, and sequencing the quality evaluation results of all urban rail escalators according to the random selection probability to obtain quality arrangement data for performing dynamic quality evaluation on all urban rail escalators in the ISCS system.
By adopting the technical scheme, as the passenger flow at the urban rail junction is large, a plurality of escalators are generally required to be arranged and serve as an electromechanical integrated product, the safety quality in the operation process is not only related to external factors such as manual operation, maintenance management and the like, but also closely related to factory quality, factory configuration and the like, so that when a plurality of brands of escalators at the same urban rail junction are evaluated by adopting the same quality evaluation standard, quality evaluation errors are easily caused by a plurality of influence factors such as factory quality, human influence and the like, therefore, quality evaluation indexes are constructed by urban rail escalator real-time state data and urban rail maintenance account data, so that quality evaluation results which accord with the actual quality attenuation coefficient of each urban rail escalator are obtained, the plurality of brands of urban rail escalators in the ISCS system can be synchronously evaluated by a quality evaluation index system, the influence of the quality evaluation results caused by the differences such as brands, quality attenuation and the like is reduced, and brand decision guidance is also provided for the selection of different escalators; and the quality evaluation results of all the urban rail escalators are dynamically sequenced through the random selection probability of each urban rail escalator by a carrier, so that the comprehensive dynamic comparison of the quality of a plurality of urban rail escalators in the ISCS system is realized, the full life cycle of all the urban rail escalators in the ISCS system is managed through dynamically performed quality sequencing data, the fit degree of the quality evaluation result of each urban rail escalator with the actual operation safety quality of each urban rail escalator is improved, and the unified operation safety quality evaluation is conveniently performed on the escalators of different brands.
The application may be further configured in a preferred example to: the method comprises the following steps of calculating the random selection probability of each urban rail escalator, sequencing the quality evaluation results of all urban rail escalators according to the random selection probability, and obtaining quality arrangement data for performing dynamic quality evaluation on all urban rail escalators in an ISCS (interference Signal code System), wherein the method specifically comprises the following steps:
according to the distribution structure of all the urban rail escalators in the ISCS system, establishing a directed distribution map among all the urban rail escalators of the ISCS system;
calculating the random selection probability of each urban rail escalator in the directed distribution map;
according to the random selection probability of each urban rail escalator, building a random selection model of the urban rail escalator of the ISCS system so as to calculate a stable distribution vector of each urban rail escalator according to the random selection model;
and inputting the quality evaluation result into the random selection model, and sequencing according to the corresponding random selection probability to obtain quality sequencing data of each urban rail escalator.
By adopting the technical scheme, the selection probability of the carried personnel of the urban rail escalator is related to the distribution position of the urban rail escalator, and the random selection probability of the carrying personnel on the urban rail escalator accords with the distribution of a directed graph, so that the directed distribution map of all the urban rail escalators is built by taking the position of each urban rail escalator as a node according to the distribution result of all the urban rail escalators in the ISCS system, and the selection possibility of the carrying personnel on the urban rail escalators is directly known according to the directed distribution map; the random selection probability of each urban rail escalator is calculated according to the distance between a carrier and the urban rail escalator and the distribution condition of the urban rail escalator experienced by the carrier from the getting-off position to the getting-off position, so that random selection models of all the urban rail escalators in the ISCS are obtained, the selection probability of the carrier to the urban rail escalator is conveniently and rapidly calculated according to the random selection models, the corresponding stable distribution vector is calculated, and the probability of each urban rail escalator being selected is favorably calculated according to the stable distribution vector; the rapid sequencing of the quality evaluation results through the randomly selected model is beneficial to dynamically monitoring the operation safety quality of all the urban rail escalators under the quality sequencing data according to the stably distributed vectors of each urban rail escalator.
The present application may be further configured in a preferred example to: the method comprises the following steps of constructing a random selection model of the urban rail escalator of the ISCS according to the random selection probability of each urban rail escalator so as to calculate a stable distribution vector of each urban rail escalator according to the random selection model, and specifically comprises the following steps:
acquiring the state transition times of each urban rail escalator, and calculating the life loss value of each urban rail escalator during each state transition;
according to the random selection probability, a transfer matrix of each urban rail escalator in the state transfer process is built, and a transfer matrix value of each urban rail escalator in the ISCS system is obtained;
iteratively calculating the transfer matrix value, the state transfer times and the corresponding life loss value to obtain an extreme vector value of each urban rail escalator in the ISCS system;
and according to the limit vector value of each urban rail escalator, building a random selection model of all urban rail escalators of the ISCS.
By adopting the technical scheme, the actual service life of the urban rail escalator can be known conveniently according to the service life loss value by calculating the state transfer frequency of each urban rail escalator and the corresponding service life loss value during state transfer, the state transfer matrix of the urban rail escalator is built according to the random selection probability of each urban rail escalator, so that the transfer matrix value of the random selection probability of all urban rail escalators in the ISCS is obtained, the state transfer distribution condition of each urban rail escalator is known conveniently according to the transfer matrix and the directed distribution map, the whole life cycle of the urban rail escalator is monitored conveniently, the transfer matrix value, the state transfer frequency and the corresponding service life loss value of the urban rail escalator are subjected to iterative calculation, the random selection probability of each urban rail escalator is converged to a stable state conveniently, the limit vector value of each urban rail escalator in the ISCS is obtained, whether the iterative calculation of the urban rail escalator stops or not is judged conveniently according to the limit vector value, the random selection model of each urban rail escalator can be used for rapidly calculating the service life attenuation degree of each urban rail escalator according to the random selection model of each urban rail escalator, and the use frequency attenuation degree of each escalator can be rapidly evaluated according to the selection of each urban rail escalator.
The present application may be further configured in a preferred example to: the method comprises the following steps of calculating the real-time state data of the urban rail escalator and the urban rail maintenance ledger data, and constructing a quality evaluation index system which accords with the quality attenuation coefficient of the urban rail escalator, wherein the method specifically comprises the following steps:
calculating the mass attenuation coefficient of each urban rail escalator according to the urban rail maintenance machine account data;
calculating the current escalator quality of the urban rail escalator in the current state according to the quality attenuation coefficient and the real-time state data of the urban rail escalator;
calculating the current escalator quality of each urban rail escalator and the corresponding original delivery quality to obtain a quality proportion parameter between the current escalator quality and the original delivery quality of each urban rail escalator;
and constructing a quality evaluation index system according with the quality attenuation coefficient of each urban rail escalator according to the quality proportion parameter of each urban rail escalator in the ISCS system.
By adopting the technical scheme, the mass attenuation coefficient of each urban rail escalator is obtained by calculating the urban rail maintenance machine account data, the historical mass attenuation condition of each urban rail escalator is favorably obtained according to the mass attenuation coefficient, the current escalator quality which accords with the mass attenuation coefficient in a real-time state is obtained according to the mass attenuation coefficient and the urban rail escalator real-time state data, the urban rail escalator is favorably maintained according to the current escalator quality as required, the maintenance and inspection cost is reduced, the mass proportion parameter is calculated according to the current escalator quality and the original delivery quality, the residual safety life of the urban rail escalator is favorably obtained according to the mass comparison parameter, the quality evaluation index systems of all urban rail escalators in the ISCS system are favorably constructed according to the mass proportion parameter, the ISCS data, the maintenance machine account data and the internal incidence relation between the service life of the urban rail escalator are favorably obtained according to the mass proportion parameter, the quality management and monitoring of the urban rail escalator in a whole life cycle are favorably carried out, the early detection and the inspection of the urban rail escalator are favorably carried out, and the real-time detection of the running state of the urban rail escalator is favorably improved.
The present application may be further configured in a preferred example to: the method for calculating the current escalator quality of the urban rail escalator in the current state according to the mass attenuation coefficient and the real-time state data of the urban rail escalator specifically comprises the following steps:
acquiring switching inertia buffer data in the real-time state data of the urban rail escalator;
calculating a state switching ideal buffer threshold value of the urban rail escalator in the current state according to the mass attenuation coefficient;
comparing the switching inertia buffer data with the state switching ideal buffer threshold value to obtain an inertia buffer comparison error value; and calculating the inertia buffer comparison error value and the original delivery quality of the corresponding urban rail escalator to obtain the current escalator quality of the urban rail escalator in the current state.
By adopting the technical scheme, the actual operation loss condition of the urban rail escalator is obtained through the switching inertia buffer data, such as buffer mileage, during state switching of the urban rail escalator, the state switching ideal buffer threshold value of the urban rail escalator in the current state is calculated through the mass attenuation coefficient, and according to the comparison between the state switching ideal buffer threshold value and the switching inertia buffer data, whether the urban rail escalator in the current state breaks down or not is judged according to the inertia buffer comparison error value, such as illegal operations of overload and the like, so that the current escalator quality of the urban rail escalator in the current state is obtained according to the calculation between the inertia buffer comparison error value and the original delivery quality, the early detection on the fault occurrence probability of the urban rail escalator is facilitated according to the current escalator quality, the fault occurrence probability is reduced, and the operation safety quality of the urban rail escalator is improved.
The application may be further configured in a preferred example to: the step of calculating the mass attenuation coefficient of each urban rail escalator according to the urban rail maintenance machine account data specifically comprises the following steps:
acquiring historical maintenance data of each time in the urban rail maintenance platform account data and maintenance time intervals between adjacent maintenance times; calculating the single mass attenuation coefficient of the urban rail escalator between adjacent maintenance times according to the historical maintenance data and the corresponding maintenance time interval;
acquiring historical maintenance times in the urban rail maintenance platform account data;
and performing average calculation according to the historical maintenance times and the single mass attenuation coefficient to obtain the mass attenuation coefficient of each urban rail escalator.
By adopting the technical scheme, as the escalator can cause certain service life loss during each maintenance, the more the maintenance times, the poorer the safe use quality of the escalator, therefore, the single quality attenuation coefficient of the urban rail escalator is calculated through the adjacent maintenance time interval, thereby being beneficial to acquiring the quality loss caused by each maintenance of the urban rail escalator according to the single quality attenuation coefficient, and obtaining the quality attenuation coefficient of each urban rail escalator according to the average value calculation of the historical maintenance times and the single quality attenuation coefficient, thereby carrying out comprehensive evaluation on the safety quality of the urban rail escalator in the current state according to the quality attenuation coefficient of the average value, and improving the comprehensive evaluation capability of the quality of the urban rail escalator.
The second objective of the present invention is achieved by the following technical solutions:
the escalator quality evaluation system based on the urban rail ISCS comprises the following components:
the data acquisition module is used for acquiring ISCS data of all urban rail escalator equipment accessed to an ISCS system in real time, wherein the ISCS data comprises urban rail escalator real-time state data and urban rail maintenance ledger data;
the data calculation module is used for calculating the real-time state data of the urban rail escalator and the urban rail maintenance platform account data and constructing a quality evaluation index system which accords with the quality attenuation coefficient of the urban rail escalator;
the quality evaluation module is used for inputting the current operation data of each urban rail escalator into a quality evaluation index system for quality evaluation and generating a quality evaluation result of each urban rail escalator;
and the quality sequencing module is used for calculating the random selection probability of each urban rail escalator and sequencing the quality evaluation results of all urban rail escalators according to the random selection probability to obtain quality sequencing data for performing dynamic quality evaluation on all urban rail escalators in the ISCS system.
By adopting the technical scheme, as the passenger flow at the urban rail junction is large, a plurality of escalators are generally required to be arranged and serve as an electromechanical integrated product, the safety quality in the operation process is not only related to external factors such as manual operation, maintenance management and the like, but also closely related to factory quality, factory configuration and the like, so that when a plurality of brands of escalators at the same urban rail junction are evaluated by adopting the same quality evaluation standard, quality evaluation errors are easily caused by a plurality of influence factors such as factory quality, human influence and the like, therefore, quality evaluation indexes are constructed by urban rail escalator real-time state data and urban rail maintenance account data, so that quality evaluation results which accord with the actual quality attenuation coefficient of each urban rail escalator are obtained, the plurality of brands of urban rail escalators in the ISCS system can be synchronously evaluated by a quality evaluation index system, the influence of the quality evaluation results caused by the differences such as brands, quality attenuation and the like is reduced, and brand decision guidance is also provided for the selection of different escalators; and the quality evaluation results of all the urban rail escalators are dynamically sequenced through the random selection probability of each urban rail escalator by a carrier, so that the comprehensive dynamic comparison of the quality of a plurality of urban rail escalators in the ISCS system is realized, the full life cycle of all the urban rail escalators in the ISCS system is managed through dynamically performed quality sequencing data, the fit degree of the quality evaluation result of each urban rail escalator with the actual operation safety quality of each urban rail escalator is improved, and the unified operation safety quality evaluation is conveniently performed on the escalators of different brands.
The present application may be further configured in a preferred example to: the quality sequencing module specifically comprises:
the directed distribution map building sub-module is used for building directed distribution maps among all the urban rail escalators of the ISCS according to the distribution structures of all the urban rail escalators in the ISCS;
the probability calculation submodule is used for calculating the random selection probability of each urban rail escalator in the directional distribution map;
the model building submodule is used for building a random selection model of the urban rail escalator of the ISCS system according to the random selection probability of each urban rail escalator so as to calculate a stable distribution vector of each urban rail escalator according to the random selection model; and the quality sequencing submodule is used for inputting the quality evaluation result into the random selection model and sequencing according to the corresponding random selection probability to obtain quality sequencing data of each urban rail escalator.
By adopting the technical scheme, the selection probability of the carried personnel of the urban rail escalator is related to the distribution position of the urban rail escalator, and the random selection probability of the carrying personnel on the urban rail escalator accords with the distribution of a directed graph, so that the directed distribution map of all the urban rail escalators is built by taking the position of each urban rail escalator as a node according to the distribution result of all the urban rail escalators in the ISCS system, and the selection possibility of the carrying personnel on the urban rail escalators is directly known according to the directed distribution map; the random selection probability of each urban rail escalator is calculated according to the distance between a carrier and the urban rail escalator and the distribution condition of the urban rail escalator experienced by the carrier from the getting-off position to the getting-off position, so that random selection models of all the urban rail escalators in the ISCS are obtained, the selection probability of the carrier to the urban rail escalator is conveniently and rapidly calculated according to the random selection models, the corresponding stable distribution vector is calculated, and the probability of each urban rail escalator being selected is favorably calculated according to the stable distribution vector; the rapid sequencing of the quality evaluation results through the randomly selected model is beneficial to dynamically monitoring the operation safety quality of all the urban rail escalators under the quality sequencing data according to the stably distributed vectors of each urban rail escalator.
The third purpose of the application is realized by the following technical scheme:
computer equipment comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor executes the computer program to realize the steps of the escalator quality evaluation method based on urban rail ISCS.
The fourth purpose of the present application is achieved by the following technical solutions:
a computer-readable storage medium, which stores a computer program, which when executed by a processor, implements the steps of the above-described escalator quality evaluation method based on urban rail ISCS.
In summary, the present application includes at least one of the following beneficial technical effects:
1. the quality evaluation index is constructed through the real-time state data of the urban rail escalator and the urban rail maintenance machine account data, so that a quality evaluation result which accords with the actual quality attenuation coefficient of each urban rail escalator is obtained, a plurality of brands of urban rail escalators in the ISCS system can be synchronously evaluated through the quality evaluation index system, the evaluation error influence on the quality evaluation result caused by different factors such as brands and quality attenuation is reduced, and decision guidance is provided for purchasing different brands of escalators; the quality evaluation results of all the urban rail escalators are dynamically sequenced through the random selection probability of each urban rail escalator by a carrier, so that the comprehensive dynamic comparison of the quality of a plurality of urban rail escalators in the ISCS system is realized, the full life cycle of all the urban rail escalators in the ISCS system is managed through the dynamically performed quality sequencing data, the fit degree of the quality evaluation result of each urban rail escalator with the actual operation safety quality of each urban rail escalator is improved, and the unified operation safety quality evaluation is conveniently performed on the escalators of different brands;
2. according to the distribution result of all the urban rail escalators in the ISCS system, the directional distribution map of all the urban rail escalators is built by taking the position of each urban rail escalator as a node, so that the selection possibility of a carrier on the urban rail escalators can be directly known according to the directional distribution map; the random selection probability of each urban rail escalator is calculated according to the distance between a carrier and the urban rail escalator and the distribution condition of the urban rail escalator experienced by the carrier from the getting-off position to the getting-off position, so that random selection models of all the urban rail escalators in the ISCS are obtained, the selection probability of the carrier to the urban rail escalator is conveniently and rapidly calculated according to the random selection models, the corresponding stable distribution vector is calculated, and the probability of each urban rail escalator being selected is favorably calculated according to the stable distribution vector; the rapid sequencing of the quality evaluation results through the randomly selected model is beneficial to dynamically monitoring the operation safety quality of all the urban rail escalators under the quality sequencing data according to the stable distribution vector of each urban rail escalator;
3. the method is characterized in that the method comprises the steps of calculating the state transfer times of each urban rail escalator and the corresponding life loss value during state transfer, facilitating to obtain the actual service life of each urban rail escalator according to the life loss value, building a state transfer matrix of each urban rail escalator according to the random selection probability of each urban rail escalator, obtaining the transfer matrix value of the random selection probability of each urban rail escalator in an ISCS (interference signal coding and noise reduction) system, obtaining the state transfer distribution condition of each urban rail escalator according to the transfer matrix and a directed distribution map, facilitating to monitor the whole life cycle of each urban rail escalator, performing iterative calculation on the transfer matrix value, the state transfer times and the corresponding life loss value of each urban rail escalator, facilitating to make the random selection probability of each urban rail escalator converge to a stable state, obtaining the limit vector value of each urban rail escalator in the ISCS system, facilitating to judge whether iterative calculation of each urban rail escalator stops according to the limit vector value, building a random selection model of each urban rail escalator according to the limit vector value, facilitating to quickly calculate the random selection model of each urban rail escalator bearing personnel to obtain the service life attenuation quality of each urban rail escalator, and rapidly obtain the use frequency of each escalator according to the use of each urban rail escalator.
Drawings
Fig. 1 is a flowchart of an implementation of an escalator quality evaluation method based on an urban rail ISCS according to an embodiment of the present application.
Fig. 2 is a flowchart of the implementation of step S20 of the escalator quality evaluation method based on urban rail ISCS according to the embodiment of the present application.
Fig. 3 is a flowchart of the implementation of step S101 of the escalator quality evaluation method based on urban rail ISCS according to the embodiment of the present application.
Fig. 4 is a flowchart of the implementation of step S102 of the escalator quality evaluation method based on urban rail ISCS according to the embodiment of the present application.
Fig. 5 is a flowchart of the implementation of step S40 of the escalator quality evaluation method based on urban rail ISCS according to the embodiment of the present application.
Fig. 6 is a flowchart of the implementation of step S403 of the escalator quality evaluation method based on urban rail ISCS according to the embodiment of the present application.
Fig. 7 is a schematic structural diagram of an escalator quality evaluation system based on an urban rail ISCS according to an embodiment of the present application.
Fig. 8 is a schematic diagram of the internal structure of computer equipment for implementing the escalator quality evaluation method based on urban rail ISCS according to an embodiment of the present application.
Detailed Description
The present application is described in further detail below with reference to the attached drawings.
In one embodiment, as shown in fig. 1, the application discloses an escalator quality evaluation method based on urban rail ISCS, which specifically includes the following steps:
s10: the method comprises the steps of acquiring ISCS data of all urban rail escalator equipment accessed to an ISCS system in real time, wherein the ISCS data comprise urban rail escalator real-time state data and urban rail maintenance ledger data.
Specifically, the operation data of all the urban rail escalator equipment connected into the ISCS system detected in the ISCS system is used as ISCS data, wherein the ISCS data comprises operation performance parameters of each urban rail escalator, such as the loss condition of escalator parts, real-time state data of the urban rail escalator, such as state switching data generated during state switching of the urban rail escalator, duration data of each state and the like, and urban rail maintenance account data, such as historical maintenance data and historical fault data of the urban rail escalator and the like.
S20: and calculating the real-time state data and the urban rail maintenance ledger data of the urban rail escalator, and constructing a quality evaluation index system which accords with the quality attenuation coefficient of the urban rail escalator.
Specifically, as shown in fig. 2, the step S20 specifically includes the following steps:
s101: and calculating the mass attenuation coefficient of each urban rail escalator according to the urban rail maintenance ledger data.
Specifically, as shown in fig. 3, the step S101 specifically includes the following steps:
s201: and obtaining historical maintenance data of each time in the urban rail maintenance ledger data and maintenance time intervals between adjacent maintenance times.
Specifically, according to the urban rail maintenance ledger data of each urban rail escalator stored in the ISCS system, and according to the unique identification code of each urban rail escalator, the corresponding historical maintenance data and the maintenance time interval between two adjacent times of maintenance are called according to the maintenance time sequence, and if the first time of maintenance of the urban rail escalator is 9 months 10, and the second time of maintenance is 9 months 24, the time interval between two adjacent times of maintenance is 14 days.
S202: and calculating the single mass attenuation coefficient of the urban rail escalator between adjacent maintenance times according to the historical maintenance data and the corresponding maintenance time interval.
Specifically, the buffer mileage of each state switching of the urban rail escalator in historical maintenance data is obtained, and a single mass attenuation coefficient is calculated according to a formula (1):
λ＝(X i -X i-1 )/t (1)
wherein, lambda represents a single mass attenuation coefficient between two adjacent maintenances, X represents a buffer mileage of each state switching, i represents the current maintenances times of the urban rail escalator from the use to the current operation time node, and t represents the maintenances time interval between two adjacent maintenances.
S203: and acquiring historical maintenance times in the urban rail maintenance standing book data.
Specifically, the historical maintenance times are the sum of all maintenance times of the urban rail escalator from being put into use to the current maintenance node, and the historical maintenance times are obtained from the urban rail maintenance ledger data according to the unique identification code of the urban rail escalator to be calculated.
S204: and performing average calculation according to the historical maintenance times and the single mass attenuation coefficient to obtain the mass attenuation coefficient of each urban rail escalator.
Specifically, the mass attenuation coefficient of each urban rail escalator is calculated according to a formula (2) as an average value:
γ＝λ/n (2)
where γ represents the mass attenuation coefficient of the mean, and n represents the historical maintenance times.
S102: and calculating the current escalator quality of the urban rail escalator in the current state according to the mass attenuation coefficient and the real-time state data of the urban rail escalator.
Specifically, as shown in fig. 4, step S102 specifically includes the following steps:
s301: and acquiring switching inertia buffer data in the real-time state data of the urban rail escalator.
Specifically, the buffer distance and the buffer time of the urban rail escalator changing from the constant speed v1 to 0 are calculated, and switching inertia buffer data including the loaded weight, the buffer distance, the buffer time, the buffer acceleration and the like during each state switching of the urban rail escalator are obtained. As shown in equation (3):
wherein, a Slow Representing the actual running buffer acceleration of the escalator of urban rails, F Buffer for storage of articles Representing the force required by an engine of an urban rail escalator to pull the escalator into motion, F Heavy load The friction force of the urban rail escalator in carrying and bearing is represented, theta represents the operation angle of the urban rail escalator, and m represents the self gravity of the urban rail escalator.
S302: and calculating the state switching ideal buffer threshold of the urban rail escalator in the current state according to the mass attenuation coefficient.
Specifically, the buffering acceleration of the urban rail escalator in an ideal state is calculated according to a formula (4):
wherein, a Theory of things Expressing ideal buffer acceleration, v, during the switching of the states of the escalator of the urban rail in the ideal state Fruit of Chinese wolfberry Representing the current running speed, v, of an urban rail escalator 0 The critical value when the state of the urban rail escalator is switched is represented, and t represents the current running speed v of the urban rail escalator Fruit of Chinese wolfberry To a critical value v of speed 0 The time required.
And calculating to obtain the state switching ideal buffer threshold value of each urban rail escalator, namely the sliding buffer mileage during state buffering according to the ideal buffer acceleration and the reaction time required by state switching.
S303: and comparing the switched inertial buffer data with the state switching ideal buffer threshold value to obtain an inertial buffer comparison error value.
Specifically, the real-time buffering mileage value in the switching inertia buffering data is compared with the ideal buffering threshold value, and an inertia buffering comparison error value is obtained according to the comparison difference value, so that the attenuation influence of the bearing weight on the safety quality of the urban rail escalator can be analyzed according to the inertia buffering comparison error value.
S304: and calculating the inertia buffer comparison error value and the original factory quality of the corresponding urban rail escalator to obtain the current escalator quality of the urban rail escalator in the current state.
Specifically, according to the carrying time of the current state, the original factory quality parameter value is calculated according to the quality attenuation coefficient corresponding to the current state, for example, 25 years, so that the ideal escalator quality in the non-interference state is obtained, the remaining safe service life of the escalator running to the current state is 20 years, the corresponding inertia buffering error value is subtracted from the ideal escalator quality value, and the inertia error fitting result during the state switching of the urban rail escalator is obtained, namely the current escalator quality after inertia error compensation is carried out.
S103: and calculating the current escalator quality of each urban rail escalator and the corresponding original delivery quality to obtain a quality proportion parameter between the current escalator quality and the original delivery quality of each urban rail escalator.
Specifically, the current escalator quality and the original factory quality of each urban rail escalator are subjected to division operation to obtain the ratio of the current escalator quality to the original factory quality, so that a quality proportion parameter between the current escalator quality and the original factory quality of each urban rail escalator is obtained.
S104: and constructing a quality evaluation index system according with the quality attenuation coefficient of each urban rail escalator according to the quality proportion parameter of each urban rail escalator in the ISCS system.
Specifically, according to the real-time state data of each urban rail escalator accessed into the ISCS system and the quality proportion parameters in the corresponding state, the running quality incidence relation of the urban rail escalator in the current state is recorded, a quality evaluation index system conforming to the current quality attenuation coefficient is constructed according to the corresponding quality incidence relation, and the quality evaluation index system is constructed according to the arrangement sequence of the selection probability of the carriers to the urban rail escalator, or the quality evaluation index system is comprehensively generated according to the incidence relation of a plurality of urban rail escalators, such as the distance close to the lower position in the distance from getting-off to leaving-off at the transportation junction, the quantity of the urban rail escalators traversed by the carriers to leave-off, and the like.
S30: and inputting the current operation data of each urban rail escalator into a quality evaluation index system for quality evaluation to generate a quality evaluation result of each urban rail escalator.
Specifically, current operation parameters of the to-be-evaluated urban rail escalator, such as operation time, real-time state data during state switching, historical maintenance data and the like, are input into a quality evaluation index system for quality evaluation, for example, the fault rate of the urban rail escalator in the current state is judged according to the operation time and the historical maintenance data, and the quality evaluation result of each urban rail escalator is obtained according to the probability of faults in the current state.
S40: and calculating the random selection probability of each urban rail escalator, and sequencing the quality evaluation results of all urban rail escalators according to the random selection probability to obtain quality arrangement data for performing dynamic quality evaluation on all urban rail escalators in the ISCS system.
Specifically, in this embodiment, the mass sequencing is performed on all the urban rail escalators in the ISCS system through the pagerank algorithm, as shown in fig. 5, step S40 specifically includes the following steps:
s401: and (3) according to the distribution structure of all the urban rail escalators in the ISCS system, constructing a directed distribution map among all the urban rail escalators of the ISCS system.
Specifically, the distribution structure of all the urban rail escalators in the ISCS system is similar to the geographical position distribution situation of all the urban rail escalators on one subway line, or the geographical position distribution situation of all the urban rail escalators at the same transportation junction position, including the distance between each urban rail escalator, the distance between each urban rail escalator and a getting-off position, the distance between each urban rail escalator and the getting-off position, and the like, and the mailbox distribution map of all the urban rail escalators in the ISCS system is built according to the selection probability of a carrier from getting-off to each urban rail escalator.
S402: and calculating the random selection probability of each urban rail escalator in the directed distribution map.
Specifically, if the number of the first-stage urban rail escalators closest to the getting-off position is 3, the random selection probability of the carrier for each first-stage urban rail escalator is 1/3, and on the outbound route, the number of the second-stage urban rail escalators at the same distance from the first-stage urban rail escalators is 4, so that the random selection probability of the carrier for each second-stage urban rail escalator after coming out of the first-stage urban rail escalator is 1/4, and so on until the carrier reaches the outbound position.
S403: and according to the random selection probability of each urban rail escalator, building a random selection model of the urban rail escalator of the ISCS system so as to calculate the stable distribution vector of each urban rail escalator according to the random selection model.
Specifically, as shown in fig. 6, step S403 specifically includes the following steps:
s501: and acquiring the state transfer times of each urban rail escalator, and calculating the service life loss value of each urban rail escalator during each state transfer.
Specifically, the state transition times of each urban rail escalator are counted in the same period, for example, the day, week or month is taken as the period, the round-trip operation times of each urban rail escalator in the period are obtained, the service life loss value is calculated according to the required reaction time, the buffering inertia data, the loss value of parts and the like of the urban rail escalator during each state transition, and the original dragging kinetic energy F of the urban rail escalator is obtained according to the set power of a dragging system of the urban rail escalator Original source Acquiring the steel rope abrasion amount during dragging according to image identification, and calculating the friction force brought by the corresponding steel rope abrasion amount to be set as F Massage device And if n is the current state transition frequency of the urban rail escalator, calculating a life attenuation value during state transition according to a formula (5), wherein the formula (5) is as follows:
s502: and according to the random selection probability, building a transfer matrix when the state of each urban rail escalator is transferred, and obtaining the transfer matrix value of each urban rail escalator in the ISCS system.
Specifically, if each urban rail escalator in the ISCS system is set as a node in a directed distribution map, and a directed edge between two nodes represents the selection probability of a carrying person for the urban rail escalator, then a transfer matrix is set according to the number of levels of the urban rail escalator in each stage, for example, if there are four levels of urban rail escalators from a get-off position to a get-off position, combining the number of the urban rail escalators in each level, where the transfer matrix is shown in the following formula (6):
wherein M represents the transfer matrix value, and the line number represents the level quantity of the urban rail escalator from the get-off position to the position of leaving a station, and the column number represents the quantity of the urban rail escalator under the same level.
S503: and carrying out iterative calculation on the transfer matrix value, the state transfer times and the corresponding life loss value to obtain the limit vector value of each urban rail escalator in the ISCS system.
Specifically, the limit vector value of each urban rail escalator is calculated according to a formula (7), wherein the formula (7) is as follows:
wherein R represents the limit vector value of each urban rail escalator, mu represents the life loss value, eta represents the state transition times, and R 0 Representing the initial vector value of the urban rail escalator.
S504: and building a random selection model of all the urban rail escalators of the ISCS system according to the limit vector value of each urban rail escalator.
Specifically, a random selection model of the carriers is built on a directed distribution map of the urban rail escalator according to the limit vector value of each urban rail escalator, the outbound selection route of the carriers is combined, and the random selection probability of the urban rail escalator traversed on the outbound selection route.
S404: and inputting the quality evaluation result into a random selection model, and sequencing according to the corresponding random selection probability to obtain quality sequencing data of each urban rail escalator.
Specifically, each quality evaluation result is input into a random selection model, sorting is carried out according to the random selection probability of each urban rail escalator on the outbound route of a carrier, and the quality sorting data of each urban rail escalator is obtained by combining the current quality attenuation condition of each urban rail escalator.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
In one embodiment, an escalator quality evaluation system based on an urban rail ISCS is provided, and the escalator quality evaluation system based on the urban rail ISCS corresponds to the escalator quality evaluation method based on the urban rail ISCS in the embodiment one to one. As shown in fig. 7, the escalator quality evaluation system based on urban rail ISCS comprises a data acquisition module, a data calculation module, a quality evaluation module and a quality sequencing module. The functional modules are explained in detail as follows:
the data acquisition module is used for acquiring ISCS data of all urban rail escalator equipment accessed to the ISCS system in real time, wherein the ISCS data comprises urban rail escalator real-time state data and urban rail maintenance ledger data.
And the data calculation module is used for calculating the real-time state data of the urban rail escalator and the urban rail maintenance ledger data and constructing a quality evaluation index system which accords with the quality attenuation coefficient of the urban rail escalator.
And the quality evaluation module is used for inputting the current operation data of each urban rail escalator into the quality evaluation index system for quality evaluation and generating a quality evaluation result of each urban rail escalator.
And the quality sequencing module is used for calculating the random selection probability of each urban rail escalator and sequencing the quality evaluation results of all the urban rail escalators according to the random selection probability to obtain quality sequencing data for performing dynamic quality evaluation on all the urban rail escalators in the ISCS system.
Preferably, the mass sorting module specifically includes:
and the directed distribution map building sub-module is used for building the directed distribution map among all the urban rail escalators of the ISCS according to the distribution structures of all the urban rail escalators in the ISCS.
And the probability calculation submodule is used for calculating the random selection probability of each urban rail escalator in the directed distribution map.
And the model building submodule is used for building a random selection model of the urban rail escalator of the ISCS system according to the random selection probability of each urban rail escalator so as to calculate the stable distribution vector of each urban rail escalator according to the random selection model.
And the quality sequencing submodule is used for inputting the quality evaluation result into the random selection model and sequencing according to the corresponding random selection probability to obtain quality sequencing data of each urban rail escalator.
Preferably, the model building submodule specifically includes:
and the state data acquisition unit is used for acquiring the state transfer times of each urban rail escalator and calculating the life loss value of each urban rail escalator during each state transfer.
And the transfer matrix building unit is used for building a transfer matrix when the state of each urban rail escalator is transferred according to the random selection probability to obtain the transfer matrix value of each urban rail escalator in the ISCS system.
And the vector value calculation unit is used for carrying out iterative calculation on the transfer matrix value, the state transfer times and the corresponding life loss value to obtain the limit vector value of each urban rail escalator in the ISCS system.
And the model building unit is used for building random selection models of all urban rail escalators of the ISCS according to the limit vector value of each urban rail escalator.
Preferably, the data calculation module specifically includes:
and the attenuation coefficient calculation submodule is used for calculating the mass attenuation coefficient of each urban rail escalator according to the urban rail maintenance ledger data.
And the current escalator quality calculating sub-module is used for calculating the current escalator quality of the urban rail escalator in the current state according to the quality attenuation coefficient and the real-time state data of the urban rail escalator.
And the mass proportion parameter calculation submodule is used for calculating the current escalator quality of each urban rail escalator and the corresponding original delivery quality to obtain a mass proportion parameter between the current escalator quality of each urban rail escalator and the original delivery quality.
And the evaluation index system building submodule is used for building a quality evaluation index system which accords with the quality attenuation coefficient of each urban rail escalator according to the quality proportion parameter of each urban rail escalator in the ISCS system.
Preferably, the current escalator quality calculation submodule specifically includes:
and the buffer data acquisition unit is used for acquiring switching inertia buffer data in the real-time state data of the urban rail escalator.
And the buffer threshold value calculating unit is used for calculating the state switching ideal buffer threshold value of the urban rail escalator in the current state according to the mass attenuation coefficient.
And the buffer data comparison unit is used for comparing the switched inertial buffer data with the state switching ideal buffer threshold value to obtain an inertial buffer comparison error value.
And the current escalator quality calculating unit is used for calculating the inertia buffer comparison error value and the original outgoing quality of the corresponding urban rail escalator to obtain the current escalator quality of the urban rail escalator in the current state.
Preferably, the attenuation coefficient calculation sub-module specifically includes:
and the maintenance data acquisition unit is used for acquiring historical maintenance data of each time in the urban rail maintenance ledger data and maintenance time intervals between adjacent maintenance times.
And the single mass attenuation coefficient calculating unit is used for calculating the single mass attenuation coefficient of the urban rail escalator between adjacent maintenance times according to the historical maintenance data and the corresponding maintenance time interval.
And the historical maintenance frequency acquisition unit is used for acquiring the historical maintenance frequency in the urban rail maintenance ledger data.
And the mass attenuation coefficient calculating unit is used for performing mean value calculation according to the historical maintenance times and the single mass attenuation coefficient to obtain the mass attenuation coefficient of each urban rail escalator.
For the specific definition of the escalator quality evaluation system based on the urban rail ISCS, reference may be made to the above definition of the escalator quality evaluation method based on the urban rail ISCS, and details are not repeated here. All or part of each module in the escalator quality evaluation system based on urban rail ISCS can be realized by software, hardware and combination thereof. The modules can be embedded in a hardware form or independent of a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 8. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing ISCS monitoring data of all urban rail escalators in an ISCS system, and the ISCS monitoring data comprises real-time state data and maintenance ledger data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to realize the escalator quality evaluation method based on the urban rail ISCS.
In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, which when executed by a processor implements the steps of the above-described escalator quality evaluation method based on urban rail ISCS.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct Rambus Dynamic RAM (DRDRAM), and Rambus Dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the system is divided into different functional units or modules to perform all or part of the above-mentioned functions.
The above-mentioned embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the embodiments of the present application, and they should be construed as being included in the present application.
Claims (10)
1. The escalator quality evaluation method based on the urban rail ISCS is characterized by comprising the following steps of:
the method comprises the steps of acquiring ISCS data of all urban rail escalator equipment accessed to an ISCS system in real time, wherein the ISCS data comprises urban rail escalator real-time state data and urban rail maintenance platform account data;
calculating the real-time state data of the urban rail escalator and the urban rail maintenance machine account data, and constructing a quality evaluation index system which accords with the quality attenuation coefficient of the urban rail escalator;
inputting the current operation data of each urban rail escalator into a quality evaluation index system for quality evaluation to generate a quality evaluation result of each urban rail escalator;
and calculating the random selection probability of each urban rail escalator, and sequencing the quality evaluation results of all urban rail escalators according to the random selection probability to obtain quality arrangement data for performing dynamic quality evaluation on all urban rail escalators in the ISCS system.
2. The escalator quality evaluation method according to claim 1 based on urban rail ISCS, wherein the calculating of the random selection probability of each urban rail escalator and the ranking of the quality evaluation results of all urban rail escalators according to the random selection probability obtain quality ranking data for performing dynamic quality evaluation on all urban rail escalators in an ISCS system specifically comprises:
according to the distribution structure of all the urban rail escalators in the ISCS system, constructing a directed distribution map among all the urban rail escalators of the ISCS system;
calculating the random selection probability of each urban rail escalator in the directed distribution map;
according to the random selection probability of each urban rail escalator, a random selection model of the urban rail escalator of the ISCS is built, so that a stable distribution vector of each urban rail escalator can be calculated according to the random selection model;
and inputting the quality evaluation result into the random selection model, and sequencing according to the corresponding random selection probability to obtain quality sequencing data of each urban rail escalator.
3. The method for evaluating the quality of an escalator based on an urban rail ISCS according to claim 2, wherein a random selection model of the urban rail escalator of the ISCS is built according to the random selection probability of each urban rail escalator, so that a stationary distribution vector of each urban rail escalator is calculated according to the random selection model, and specifically comprises the following steps:
acquiring the state transfer times of each urban rail escalator, and calculating the service life loss value of each urban rail escalator during each state transfer;
according to the random selection probability, a transfer matrix of each urban rail escalator in the state transfer process is built, and a transfer matrix value of each urban rail escalator in the ISCS system is obtained;
performing iterative calculation on the transfer matrix value, the state transfer times and the corresponding life loss value to obtain a limit vector value of each urban rail escalator in the ISCS system;
and according to the limit vector value of each urban rail escalator, building a random selection model of all urban rail escalators of the ISCS.
4. The escalator quality evaluation method based on urban rail ISCS according to claim 1, wherein said calculating the urban rail escalator real-time status data and the urban rail maintenance ledger data, constructing a quality evaluation index system that conforms to the quality attenuation coefficient of the urban rail escalator, specifically comprises:
calculating the mass attenuation coefficient of each urban rail escalator according to the urban rail maintenance machine account data;
calculating the current escalator quality of the urban rail escalator in the current state according to the quality attenuation coefficient and the real-time state data of the urban rail escalator;
calculating the current escalator quality of each urban rail escalator and the corresponding original delivery quality to obtain a quality proportion parameter between the current escalator quality and the original delivery quality of each urban rail escalator;
and constructing a quality evaluation index system according with the quality attenuation coefficient of each urban rail escalator according to the quality proportion parameter of each urban rail escalator in the ISCS system.
5. The escalator quality evaluation method based on urban rail ISCS according to claim 4, wherein said calculating the current escalator quality of the urban rail escalator in the current state according to said quality attenuation coefficient and said urban rail escalator real-time state data specifically comprises:
acquiring switching inertia buffer data in the real-time state data of the urban rail escalator;
calculating a state switching ideal buffer threshold value of the urban rail escalator in the current state according to the mass attenuation coefficient;
comparing the switching inertia buffer data with the state switching ideal buffer threshold value to obtain an inertia buffer comparison error value;
and calculating the inertia buffer comparison error value and the original factory quality of the corresponding urban rail escalator to obtain the current escalator quality of the urban rail escalator in the current state.
6. The escalator quality evaluation method based on urban rail ISCS according to claim 4, wherein the calculating of the quality attenuation coefficient of each urban rail escalator according to the urban rail maintenance ledger data specifically comprises:
acquiring historical maintenance data of each time in the urban rail maintenance platform account data and maintenance time intervals between adjacent maintenance times;
calculating the single mass attenuation coefficient of the urban rail escalator between adjacent maintenance times according to the historical maintenance data and the corresponding maintenance time interval;
acquiring historical maintenance times in the urban rail maintenance platform account data;
and performing average calculation according to the historical maintenance times and the single mass attenuation coefficient to obtain the mass attenuation coefficient of each urban rail escalator.
7. An escalator quality evaluation system based on urban rail ISCS, characterized in that, the escalator quality evaluation system based on urban rail ISCS includes:
the data acquisition module is used for acquiring ISCS data of all urban rail escalator equipment accessed to an ISCS system in real time, wherein the ISCS data comprises urban rail escalator real-time state data and urban rail maintenance ledger data;
the data calculation module is used for calculating the real-time state data of the urban rail escalator and the urban rail maintenance platform account data and constructing a quality evaluation index system which accords with the quality attenuation coefficient of the urban rail escalator;
the quality evaluation module is used for inputting the current operation data of each urban rail escalator into a quality evaluation index system for quality evaluation and generating a quality evaluation result of each urban rail escalator;
and the quality sequencing module is used for calculating the random selection probability of each urban rail escalator and sequencing the quality evaluation results of all urban rail escalators according to the random selection probability to obtain quality sequencing data for performing dynamic quality evaluation on all urban rail escalators in the ISCS system.
8. The escalator quality evaluation system based on urban rail ISCS according to claim 7, wherein said quality ranking module specifically comprises:
the directed distribution map building submodule is used for building the directed distribution maps among all the urban rail escalators of the ISCS according to the distribution structures of all the urban rail escalators in the ISCS;
the probability calculation submodule is used for calculating the random selection probability of each urban rail escalator in the directional distribution map;
the model building submodule is used for building a random selection model of the urban rail escalator of the ISCS system according to the random selection probability of each urban rail escalator so as to calculate a stable distribution vector of each urban rail escalator according to the random selection model;
and the quality sequencing submodule is used for inputting the quality evaluation result into the random selection model and sequencing according to the corresponding random selection probability to obtain quality sequencing data of each urban rail escalator.
9. Computer arrangement comprising a memory, a processor and a computer program stored in said memory and executable on said processor, characterized in that said processor when executing said computer program carries out the steps of the method for escalator quality assessment based on urban rail ISCS according to any one of claims 1 to 6.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the method for evaluating quality of an escalator based on an urban rail ISCS according to any one of claims 1 to 6.
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| CN116136987A (en) * | 2023-02-21 | 2023-05-19 | 北京思维实创科技有限公司 | PSCADA data-based power supply equipment reliability online evaluation method and system |
| CN116452187A (en) * | 2023-04-07 | 2023-07-18 | 北京思维实创科技有限公司 | Escalator fault prediction method and system based on urban rail ISCS |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116136987A (en) * | 2023-02-21 | 2023-05-19 | 北京思维实创科技有限公司 | PSCADA data-based power supply equipment reliability online evaluation method and system |
| CN116136987B (en) * | 2023-02-21 | 2023-08-15 | 北京思维实创科技有限公司 | PSCADA data-based power supply equipment reliability online evaluation method and system |
| CN116452187A (en) * | 2023-04-07 | 2023-07-18 | 北京思维实创科技有限公司 | Escalator fault prediction method and system based on urban rail ISCS |
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