Method for predicting icing degree of overhead line system based on growth coefficient

Abstract

The invention discloses a contact network icing degree prediction method based on a growth coefficient, and the method comprises the steps: building a contact network icing experiment platform, changing the internal environment parameters of an experiment box, and measuring the change condition of the icing thickness of a contact line, thereby calculating the icing growth coefficient of the contact line with respect to the temperature, humidity, rainfall and wind speed changes; and further calculating a contact line icing degree prediction coefficient, and predicting an overhead line system icing risk according to the icing degree prediction coefficient. According to the method, the icing risk of the contact line is predicted by using the icing growth coefficient and the icing degree prediction coefficient, the icing risk of the contact line in a future period of time can be rapidly predicted according to the early-stage icing condition of the contact line in a short time, and a basis is provided for maintainers to take corresponding prevention and response measures in time.

Description

Technical Field

[0001] The invention belongs to the field of catenary icing risk prediction and assessment, and in particular relates to a method for predicting catenary icing degree based on a growth coefficient. Technical Background

[0002] With the rapid development of my country's railway rail transit modernization, the contact network, as an important part of the railway electrification system, plays a key role in traction power supply. However, in cold and humid climate conditions, the contact network is easily affected by icing, which not only damages the carbon plate of the pantograph, but also affects the current collection of the pantograph network, resulting in unstable power supply. In addition, the shedding of ice may also cause the contact line to dance, and even cause irreversible damage such as broken wires. Therefore, the icing problem has become an important issue affecting railway transportation safety and operational reliability, and it is of great significance to evaluate and predict the risk of icing on the contact network.

[0003] At present, there is a relative lack of methods for predicting the degree of catenary icing. Traditional prediction of catenary icing mainly relies on empirical judgment, but this method has problems such as strong subjectivity and low accuracy. Therefore, there is an urgent need for a prediction method for the degree of catenary icing, which can quickly predict the icing risk of the catenary in the future, provide a basis for maintenance personnel to take corresponding preventive and response measures in a timely manner, and improve the accuracy and reliability of the prediction of the degree of catenary icing. Summary of the invention

[0004] In view of the above technical problems, the purpose of the present invention is to propose a method for predicting the icing degree of the contact network based on the growth coefficient, which can effectively predict the icing condition of the contact network;

[0005] The technical solution for implementing the present invention is as follows:

[0006] The first step is to build an experimental platform for catenary icing;

[0007] The contact network icing experimental platform is composed of a wind speed simulation system (1), a temperature controller (2), a humidity controller (3), a high-definition camera (4), a rainfall simulation system (5), a wind speed sensor (6), a temperature sensor (7), a humidity sensor (8), a support tower (9), a contact line (10), a computer terminal (11) and an experimental box (12), wherein:

[0008] The wind speed simulation system (1), the temperature controller (2), the humidity controller (3) and the rainfall simulation system (5) are controlled by a computer terminal (11) to adjust the internal environmental parameters of the test box (12); the wind speed sensor (6) is installed at the air outlet of the wind speed simulation system (1) for measuring the wind speed; the temperature sensor (7) and the humidity sensor (8) are installed on the right side surface of the inner wall of the test box (12) for real-time monitoring of the internal environmental temperature and humidity of the test box (12), and returning the temperature and humidity data to the computer terminal (11); the high-definition camera (4) is installed on the right side of the inner wall of the test box (12) for monitoring the ice coverage of the contact line (10), and recording the relevant parameters and returning them to the computer terminal (11);

[0009] Step 2: Calculate the ice growth coefficient of the contact line with respect to temperature change;

[0010] First, the environmental parameters around the contact line of a certain section of the contact network during the winter icing period are obtained; the actual ambient temperature around the contact line during the icing period is obtained according to the operation records, and the highest temperature is recorded as T max , the lowest temperature is recorded as T min The average temperature is The unit is K; get the actual relative humidity, the highest relative humidity is recorded as RH max , the minimum relative humidity is recorded as RH min The average relative humidity is recorded as Get the actual rainfall, the maximum rainfall is recorded as P max , the minimum rainfall is recorded as P min The average rainfall is recorded as The unit is mm; get the actual wind speed, the maximum wind speed is recorded as V max , the minimum wind speed is V min The average wind speed is The unit is m / s;

[0011] Take 5 groups of uniformly increasing experimental temperatures, T i , the unit is K, where T1 = T min , T5=T max ; Carry out a simulated icing experiment on the contact line in the test box, and set the temperature of the test box to T i , relative ambient humidity is The rainfall is Wind speed is When the internal environment of the experimental box stabilizes, the timing starts, and the experimental time is t k , the unit is h; the contact line icing condition is observed by high-definition camera, every Record the ice thickness of the contact line once, denoted as d ij (Indicates that when the experimental temperature is T iThe ice thickness of the contact line measured at the jth time, where i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5, 6);

[0012] The ice growth coefficient of the contact line with respect to temperature change is calculated using formula (1):

[0013]

[0014] Step 3: Calculate the ice growth coefficient of the contact line with respect to humidity changes;

[0015] Take 5 groups of evenly increasing relative humidity as RH i , where RH1 = RH min , RH5=RH max ; Carry out a simulated ice coating experiment on the contact line in the test box, and set the relative humidity to RH i The temperature of the test chamber is The rainfall is Wind speed is When the internal environment of the experimental box stabilizes, the timing starts, and the experimental time is t k , the unit is h; the contact line icing condition is observed by high-definition camera, every Record the ice thickness of the contact line once, denoted as d ij (Indicates that when the experimental temperature is T i The ice thickness of the contact line measured at the jth time, where i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5, 6);

[0016] Formula (2) is used to calculate the ice growth coefficient of the contact line with respect to humidity changes:

[0017]

[0018] Step 4: Calculate the ice growth coefficient of the contact line with respect to the change of rainfall;

[0019] Take 5 groups of evenly increasing rainfall amounts, namely P i , in mm, where P1 = P min , P5=P max ; Carry out a simulated icing experiment on the contact line in the test box, and set the rainfall to P i The temperature of the test chamber is The relative humidity is Wind speed is When the internal environment of the experimental box stabilizes, the timing starts, and the experimental time is t k , the unit is h; the contact line icing condition is observed by high-definition camera, every Record the ice thickness of the contact line once, denoted as d ij (Indicates that when the experimental temperature is Ti The ice thickness of the contact line measured at the jth time, where i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5, 6);

[0020] Formula (3) is used to calculate the ice growth coefficient of the contact line with respect to rainfall changes:

[0021]

[0022] Step 5: Calculate the ice growth coefficient of the contact line with respect to wind speed changes;

[0023] Take 5 groups of uniformly increasing wind speeds, V i , the unit is m / s, where V1=V min , V5=V max ; Carry out a simulated icing experiment on the contact line in the test box, and set the wind speed to V i The temperature of the test chamber is The relative humidity is The rainfall is When the internal environment of the experimental box stabilizes, the timing starts, and the experimental time is t k , the unit is h; the contact line icing condition is observed by high-definition camera, every Record the ice thickness of the contact line once, denoted as d ij (Indicates that when the experimental temperature is T i The ice thickness of the contact line measured at the jth time, where i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5, 6);

[0024] Formula (4) is used to calculate the ice growth coefficient of the contact line with respect to wind speed changes:

[0025]

[0026] Step 6: Calculate the contact line ice coverage prediction coefficient;

[0027] The contact line icing degree prediction coefficient is calculated using formula (5):

[0028]

[0029] Step 7: Predict the contact line icing risk based on the contact line icing degree prediction coefficient;

[0030] If η≤0.36, the contact network under test has a slight risk of icing in the future; if 0.36<η≤1.71, the contact network under test has a moderate risk of icing in the future; if 1.71<η, the contact network under test has a severe risk of icing in the future.

[0031] The beneficial effect of the present invention is that by building a contact network icing experimental platform, the influence of temperature and humidity, rainfall and wind speed on contact network icing is simulated, and the two parameters of icing growth coefficient and icing degree prediction coefficient are integrated to provide a contact network icing degree prediction method based on growth coefficient, which can effectively predict the icing risk of the contact network in the future according to the icing situation of the contact network in the early short period of time, and provide a basis for maintenance personnel to take corresponding preventive and countermeasures in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It represents the constructed catenary icing experimental platform;

[0033] Figure 2 It shows a flow chart of a method for predicting the degree of catenary icing based on growth coefficient. DETAILED DESCRIPTION

[0034] The present invention will be further described below in conjunction with the accompanying drawings and specific implementation processes.

[0035] The first step is to build an experimental platform for catenary icing;

[0036] The contact network icing experimental platform is composed of a wind speed simulation system (1), a temperature controller (2), a humidity controller (3), a high-definition camera (4), a rainfall simulation system (5), a wind speed sensor (6), a temperature sensor (7), a humidity sensor (8), a support tower (9), a contact line (10), a computer terminal (11) and an experimental box (12), wherein:

[0037] The wind speed simulation system (1), the temperature controller (2), the humidity controller (3) and the rainfall simulation system (5) are controlled by a computer terminal (11) to adjust the internal environmental parameters of the test box (12); the wind speed sensor (6) is installed at the air outlet of the wind speed simulation system (1) for measuring the wind speed; the temperature sensor (7) and the humidity sensor (8) are installed on the right side surface of the inner wall of the test box (12) for real-time monitoring of the internal environmental temperature and humidity of the test box (12), and returning the temperature and humidity data to the computer terminal (11); the high-definition camera (4) is installed on the right side of the inner wall of the test box (12) for monitoring the ice coverage of the contact line (10), and recording the relevant parameters and returning them to the computer terminal (11);

[0038] Step 2: Calculate the ice growth coefficient of the contact line with respect to temperature change;

[0039] First, the environmental parameters around the contact line of a certain section of the contact network during the winter icing period are obtained; the actual ambient temperature around the contact line during the icing period is obtained according to the operation records, and the highest temperature is recorded as T max , the lowest temperature is recorded as T min, the average temperature is recorded as T, the unit is K; get the actual relative humidity, the maximum relative humidity is recorded as RH max , the minimum relative humidity is recorded as RH min , the average relative humidity is recorded as RH; the actual rainfall is obtained, and the maximum rainfall is recorded as P max , the minimum rainfall is recorded as P min , the average rainfall is recorded as P, the unit is mm; get the actual wind speed, the maximum wind speed is recorded as V max , the minimum wind speed is V min The average wind speed is The unit is m / s;

[0040] Take 5 groups of uniformly increasing experimental temperatures, T i , the unit is K, where T1 = T min , T5=T max ; Carry out a simulated icing experiment on the contact line in the test box, and set the temperature of the test box to T i , relative ambient humidity is The rainfall is Wind speed is When the internal environment of the experimental box stabilizes, the timing starts, and the experimental time is t k , the unit is h; the contact line icing condition is observed by high-definition camera, every Record the ice thickness of the contact line once, denoted as d ij (Indicates that when the experimental temperature is T i The ice thickness of the contact line measured at the jth time, where i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5, 6);

[0041] The ice growth coefficient of the contact line with respect to temperature change is calculated using formula (1):

[0042]

[0043] Step 3: Calculate the ice growth coefficient of the contact line with respect to humidity changes;

[0044] Take 5 groups of evenly increasing relative humidity as RH i , where RH1 = RH min , RH5=RH max ; Carry out a simulated ice coating experiment on the contact line in the test box, and set the relative humidity to RH i The temperature of the test chamber is The rainfall is Wind speed is When the internal environment of the experimental box stabilizes, the timing starts, and the experimental time is t k , the unit is h; the contact line icing condition is observed by high-definition camera, every Record the ice thickness of the contact line once, denoted as d ij (Indicates that when the experimental temperature is T i The ice thickness of the contact line measured at the jth time, where i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5, 6);

[0045] Formula (2) is used to calculate the ice growth coefficient of the contact line with respect to humidity changes:

[0046]

[0047] Step 4: Calculate the ice growth coefficient of the contact line with respect to the change of rainfall;

[0048] Take 5 groups of uniformly increasing rainfall amounts, namely P i , in mm, where P1 = P min , P5=P max ; Carry out a simulated icing experiment on the contact line in the test box, and set the rainfall to P i The temperature of the test chamber is The relative humidity is Wind speed is When the internal environment of the experimental box stabilizes, the timing starts, and the experimental time is t k , the unit is h; the contact line icing condition is observed by high-definition camera, every Record the ice thickness of the contact line once, denoted as d ij (Indicates that when the experimental temperature is T i The ice thickness of the contact line measured at the jth time, where i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5, 6);

[0049] Formula (3) is used to calculate the ice growth coefficient of the contact line with respect to rainfall changes:

[0050]

[0051] Step 5: Calculate the ice growth coefficient of the contact line with respect to wind speed changes;

[0052] Take 5 groups of uniformly increasing wind speeds, V i , the unit is m / s, where V1=V min , V5=V max ; Carry out a simulated icing experiment on the contact line in the test box, and set the wind speed to V i The temperature of the test chamber is The relative humidity is The rainfall is When the internal environment of the experimental box stabilizes, the timing starts, and the experimental time is t k , the unit is h; the contact line icing condition is observed by high-definition camera, every Record the ice thickness of the contact line once, denoted as d ij (Indicates that when the experimental temperature is T i The ice thickness of the contact line measured at the jth time, where i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5, 6);

[0053] Formula (4) is used to calculate the ice growth coefficient of the contact line with respect to wind speed changes:

[0054]

[0055] Step 6: Calculate the contact line ice coverage prediction coefficient;

[0056] The contact line icing degree prediction coefficient is calculated using formula (5):

[0057]

[0058] Step 7: Predict the contact line icing risk based on the contact line icing degree prediction coefficient;

[0059] If η≤0.36, the contact network under test has a slight risk of icing in the future; if 0.36<η≤1.71, the contact network under test has a moderate risk of icing in the future; if 1.71<η, the contact network under test has a severe risk of icing in the future.

Claims

1. A method for predicting the degree of catenary icing based on growth coefficient, characterized in that: The following steps are involved: The first step is to build an experimental platform for catenary icing; The contact network icing experimental platform is composed of a wind speed simulation system (1), a temperature controller (2), a humidity controller (3), a high-definition camera (4), a rainfall simulation system (5), a wind speed sensor (6), a temperature sensor (7), a humidity sensor (8), a support tower (9), a contact line (10), a computer terminal (11) and an experimental box (12), wherein: The wind speed simulation system (1), the temperature controller (2), the humidity controller (3) and the rainfall simulation system (5) are controlled by a computer terminal (11) to adjust the internal environmental parameters of the test box (12); the wind speed sensor (6) is installed at the air outlet of the wind speed simulation system (1) for measuring the wind speed; the temperature sensor (7) and the humidity sensor (8) are installed on the right side surface of the inner wall of the test box (12) for real-time monitoring of the internal environmental temperature and humidity of the test box (12), and returning the temperature and humidity data to the computer terminal (11); the high-definition camera (4) is installed on the right side of the inner wall of the test box (12) for monitoring the ice coverage of the contact line (10), and recording the relevant parameters and returning them to the computer terminal (11); Step 2: Calculate the ice growth coefficient of the contact line with respect to temperature change; First, the environmental parameters around the contact line of a certain section of the contact network during the winter icing period are obtained; the actual ambient temperature around the contact line during the icing period is obtained according to the operation records, and the highest temperature is recorded as T max , the lowest temperature is recorded as T min The average temperature is The unit is K; get the actual relative humidity, the highest relative humidity is recorded as RH max , the minimum relative humidity is recorded as RH min The average relative humidity is recorded as Get the actual rainfall, the maximum rainfall is recorded as P max , the minimum rainfall is recorded as P min The average rainfall is recorded as The unit is mm; get the actual wind speed, the maximum wind speed is recorded as V max , the minimum wind speed is V min The average wind speed is The unit is m / s; Take 5 groups of uniformly increasing experimental temperatures, namely T i , the unit is K, where T1 = T min , T5=T max ; Carry out a simulated icing experiment on the contact line in the test box, and set the temperature of the test box to T i , relative ambient humidity is The rainfall is Wind speed is When the internal environment of the experimental box stabilizes, the timing starts, and the experimental time is t k , the unit is h; the contact line icing condition is observed by high-definition camera, every Record the ice thickness of the contact line once, denoted as d ij (Indicates that when the experimental temperature is T i The ice thickness of the contact line measured at the jth time, where i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5, 6); Formula (1) is used to calculate the ice growth coefficient of the contact line with respect to temperature change: Step 3: Calculate the ice growth coefficient of the contact line with respect to humidity changes; Take 5 groups of evenly increasing relative humidity as RH i , where RH1 = RH min , RH5=RH max ; Carry out a simulated ice coating experiment on the contact line in the test box, and set the relative humidity to RH i The temperature of the test chamber is The rainfall is Wind speed is When the internal environment of the experimental box stabilizes, the timing starts, and the experimental time is t k , the unit is h; the contact line icing condition is observed by high-definition camera, every Record the ice thickness of the contact line once, denoted as d ij (Indicates that when the experimental temperature is T i The ice thickness of the contact line measured at the jth time, where i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5, 6); Formula (2) is used to calculate the ice growth coefficient of the contact line with respect to humidity changes: Step 4: Calculate the ice growth coefficient of the contact line with respect to the change of rainfall; Take 5 groups of evenly increasing rainfall amounts, namely P i , in mm, where P1 = P min , P5=P max ; Carry out a simulated icing experiment on the contact line in the test box, and set the rainfall to P i The temperature of the test chamber is The relative humidity is Wind speed is When the internal environment of the experimental box stabilizes, the timing starts, and the experimental time is t k , the unit is h; the contact line icing condition is observed by high-definition camera, every Record the ice thickness of the contact line once, denoted as d ij (Indicates that when the experimental temperature is T i The ice thickness of the contact line measured at the jth time, where i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5, 6); Formula (3) is used to calculate the ice growth coefficient of the contact line with respect to rainfall changes: Step 5: Calculate the ice growth coefficient of the contact line with respect to wind speed changes; Take 5 groups of uniformly increasing wind speeds, V i , the unit is m / s, where V1=V min , V5=V max ; Carry out a simulated icing experiment on the contact line in the test box, and set the wind speed to V i The temperature of the test chamber is The relative humidity is The rainfall is When the internal environment of the experimental box stabilizes, the timing starts, and the experimental time is t k , the unit is h; the contact line icing condition is observed by high-definition camera, every Record the ice thickness of the contact line once, denoted as d ij (Indicates that when the experimental temperature is T i The ice thickness of the contact line measured at the jth time, where i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5, 6); Formula (4) is used to calculate the ice growth coefficient of the contact line with respect to wind speed changes: Step 6: Calculate the contact line ice coverage prediction coefficient; The contact line icing degree prediction coefficient is calculated using formula (5): Step 7: Predict the contact network icing risk based on the contact line icing degree prediction coefficient.

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