Rail transit equipment health degree assessment method based on operation data

Abstract

The invention discloses a rail transit equipment health degree evaluation method based on operation data. The method comprises the following steps: determining data attributes participating in health degree calculation in rail transit equipment types; acquiring equipment operation data in unit time, and calculating alarm times and a data mean value; calculating a health assessment value of each data semaphore; calculating the final equipment health degree; and performing health grade division on the health degree of the equipment. According to the method, the health state of the equipment is comprehensively evaluated by comprehensively considering factors such as the fault frequency, the operation data and the fault severity of the equipment, so that early warning and evaluation of equipment faults are provided, and technical support is provided for upgrading from fault repair to state repair.

Description

Technical Field

[0001] The present invention belongs to the technical field of equipment health analysis, and in particular relates to a method for evaluating the health of rail transit equipment based on operation data. Background Art

[0002] The traditional maintenance method for rail transit equipment is usually called fault repair, which is a method of repairing and maintaining the equipment only after it fails. The basic concept of this maintenance method is "no repair if it is not broken", that is, necessary maintenance work will only be carried out when the equipment fails and affects normal operation.

[0003] The fault repair method has obvious limitations. First, it may reduce the reliability and safety of equipment, because faults are often discovered and handled after the equipment has been damaged or its performance has degraded, which may increase the risk of equipment failure and may even lead to more serious consequences, such as train derailment and signal system failure. Second, the fault repair method may increase maintenance costs. Although it seems to save maintenance costs in the short term, in the long run, the total cost may be higher due to the downtime, repair costs and other failures that may be caused by equipment failure. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a rail transit equipment health assessment method based on operating data, so as to solve the problems of inaccurate, untimely and lack of data support in the prior art of rail transit equipment health assessment; the present invention comprehensively assesses the health status of the equipment by comprehensively considering factors such as the number of equipment failures, operating data and the severity of the failures, and then provides early warning and assessment of equipment failures, providing technical support for upgrading from fault repair to condition repair.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A rail transit equipment health assessment method based on operation data of the present invention comprises the following steps:

[0007] 1) Confirm the data attributes involved in the health calculation of rail transit equipment types;

[0008] 2) Collect equipment operation data within a unit time and calculate the number of alarms and data average;

[0009] 3) Calculate the health assessment value of each data signal;

[0010] 4) Calculate the final equipment health;

[0011] 5) Classify the health level of the equipment.

[0012] Furthermore, in the step 1), the rail transit equipment type includes digital signal quantities and analog signal quantities, and signals closely related to equipment failures are selected for health calculation. The digital signal quantities include communication fault point signals and overload fault point signals; the analog signal quantities include working current values ​​and working voltage values; when the digital signal quantity value changes to 1, it indicates that a fault has occurred; the analog signal quantity is evaluated based on the minimum value, standard value, and maximum value of the data range, and the three values ​​are determined based on the equipment specifications and technical parameters.

[0013] Furthermore, in the step 2), the equipment operation data within a unit time is collected. If the operation data is a digital signal quantity, the number of alarms within a unit time is calculated; if the operation data is an analog signal quantity, the data mean within a unit time is calculated, specifically including:

[0014] The data sampling type is digital signal quantity;

[0015] 21) In the time period from t1 to t2, the digital signal is sampled n times to obtain the value set D of the overload fault point in the time period = {d1, d2, ..., d n};

[0016] 22) Set a counter to record the number of position change alarms C; initially, C = 0;

[0017] 23) For each sampling point d in the value set in step 21) i , when i=2,3,...,n, compare d i and d i-1 If the value of d i ≠d i-1 , then the digital signal quantity has changed during the time period, and the counter value C is increased by 1;

[0018] 24) After traversing the entire sampling value sequence, the value of C is the number of position change alarms;

[0019] 25) Calculate the maximum number of position change alarms of the digital signal quantity of all devices of the same device type C max ;

[0020] The data sampling type is analog signal quantity;

[0021] 26) In the time period from t1 to t2, the analog signal is sampled n times to obtain the data set A = {a1, a2, ..., a n};

[0022] 27) Calculate the sum S of all data in data set A:

[0023]

[0024] 28) Calculate the mean μ of the data within the time period:

[0025]

[0026] Furthermore, in step 3), respectively calculating the digital signal health assessment value h(t) and the analog signal health assessment value H(t) includes:

[0027] 31) The calculation method of the digital signal health assessment value is as follows:

[0028] Combine the displacement alarm times C calculated in step 24) with the maximum displacement alarm value C of the same type of equipment calculated in step 25) max , the digital signal health assessment value h(t) is calculated using the linear interpolation method as follows:

[0029]

[0030] 32) The calculation method of the analog signal health assessment value is as follows:

[0031] Combine the data mean μ calculated in step 28) with the minimum value X of the analog signal data range min , standard value W, maximum value X max To perform the calculation, the three values ​​are known values, which are determined according to the factory specifications and technical parameters of the equipment. The calculation expression is as follows:

[0032]

[0033] Wherein, H(t) is the health assessment value of the analog signal after the device is calculated by piecewise function.

[0034] Furthermore, the step 4) calculates the final device health assessment value DEV_H(t) in combination with the weighted coefficient, specifically including:

[0035] 41) Using the method of step 31), calculate the communication fault evaluation h1(t) and the overload fault evaluation h2(t); using the method of step 32), calculate the working current value evaluation H3(t) and the working voltage value evaluation H4(t);

[0036] The digital signal health assessment value DI_H(t) and the analog signal health assessment value AI_H(t) are calculated respectively as follows:

[0037] DI_H(t)=h1(t)*0.3+h2(t)*0.7

[0038] AI_H(t)=H3(t)*0.4+H4(t)*0.6

[0039] Calculate the final device health assessment value DEV_H(t) as follows:

[0040] DEV_H(t)=DI_H(t)*0.7+AI_H(t)*0.3.

[0041] Furthermore, in step 5), the health status of the device is determined according to the final device health evaluation value DEV_H(t), specifically including:

[0042] If 0≤DEV_H(t)≤0.3, the equipment health warning level is level 4, the health status is faulty, and a fault work order is manually issued;

[0043] If 0.3≤DEV_H(t)≤0.45, the device health warning level is level 3 and the health status is unhealthy;

[0044] If 0.45≤DEV_H(t)≤0.65, the equipment health warning level is level 2 and the health status is sub-healthy;

[0045] If 0.65≤DEV_H(t)≤1, the device health warning level is level 1, and the device status is healthy.

[0046] Beneficial effects of the present invention:

[0047] The present invention can monitor the operating status of the equipment in real time or periodically, quantify and evaluate the health status of the equipment in combination with weighted parameters formulated by equipment design parameters, and promptly discover potential faults and problems of the equipment.

[0048] Based on the health assessment results, the present invention can formulate a preventive maintenance plan to extend the service life of the equipment and reduce maintenance costs.

[0049] The present invention is applicable to various types of equipment scenarios, including mechanical equipment, electronic equipment, chemical equipment, etc., and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 The schematic diagram of the method of the present invention is shown in FIG. DETAILED DESCRIPTION

[0051] In order to facilitate the understanding of those skilled in the art, the present invention is further described below in conjunction with embodiments and drawings. The contents mentioned in the implementation modes are not intended to limit the present invention.

[0052] Reference Figure 1 As shown, a rail transit equipment health assessment method based on operation data of the present invention comprises the following steps:

[0053] 1) Confirm the data attributes involved in the health calculation of rail transit equipment types;

[0054] Among them, in the step 1), the rail transit equipment type includes digital signal quantities and analog signal quantities, and signals closely related to equipment failures are selected for health calculation. Digital signal quantities include communication fault point signals and overload fault point signals; analog signal quantities include working current values ​​and working voltage values; when the digital signal value changes to 1, it indicates that a fault has occurred; the analog signal quantity is evaluated based on the minimum value, standard value, and maximum value of the data range, and the three values ​​are determined based on the equipment specifications and technical parameters.

[0055] 2) Collect equipment operation data within a unit time and calculate the number of alarms and data average;

[0056] Wherein, in the step 2), the equipment operation data within a unit time is collected. If the operation data is a digital signal quantity, the number of alarms within a unit time is calculated; if the operation data is an analog signal quantity, the data mean within a unit time is calculated, specifically including:

[0057] The data sampling type is digital signal quantity;

[0058] 21) In the time period from t1 to t2, the digital signal quantity (such as the overload fault point) is sampled n times to obtain the overload fault point value set D = {d1, d2, ..., d n};

[0059] 22) Set a counter to record the number of position change alarms C; initially, C = 0;

[0060] 23) For each sampling point d in the value set in step 21) i , when i=2,3,...,n, compare d i and d i-1 If the value of d i ≠d i-1 , then the digital signal quantity has changed during the time period, and the counter value C is increased by 1;

[0061] 24) After traversing the entire sampling value sequence, the value of C is the number of position change alarms;

[0062] 25) Calculate the maximum number of position change alarms of the digital signal quantity of all devices of the same device type C max ;

[0063] The data sampling type is analog signal quantity;

[0064] 26) In the time period from t1 to t2, the analog signal is sampled n times to obtain the data set A = {a1, a2, ..., a n};

[0065] 27) Calculate the sum S of all data in data set A:

[0066]

[0067] 28) Calculate the mean μ of the data within the time period:

[0068]

[0069] 3) Calculate the health assessment value of each data signal;

[0070] Wherein, in step 3), respectively calculating the digital signal health assessment value h(t) and the analog signal health assessment value H(t) includes:

[0071] 31) The calculation method of the digital signal health assessment value is as follows:

[0072] Combine the displacement alarm times C calculated in step 24) with the maximum displacement alarm value C of the same type of equipment calculated in step 25) max , the digital signal health assessment value h(t) is calculated using the linear interpolation method as follows:

[0073]

[0074] 32) The calculation method of the analog signal health assessment value is as follows:

[0075] Combine the data mean μ calculated in step 28) with the minimum value X of the analog signal data range min , standard value W, maximum value X max To perform the calculation, the three values ​​are known values, which are determined according to the factory specifications and technical parameters of the equipment. The calculation expression is as follows:

[0076]

[0077] Wherein, H(t) is the health assessment value of the analog signal after the device is calculated by piecewise function.

[0078] 4) Calculate the final equipment health;

[0079] The step 4) combines the weighted coefficient to calculate the final device health assessment value DEV_H(t), specifically including:

[0080] 41) Using the method of step 31), calculate the communication fault evaluation h1(t) (weighted value is 0.3) and the overload fault evaluation h2(t) (weighted value is 0.7); using the method of step 32), calculate the working current value evaluation H3(t) (weighted value is 0.4) and the working voltage value evaluation H4(t) (weighted value is 0.6);

[0081] The digital signal health assessment value DI_H(t) and the analog signal health assessment value AI_H(t) are calculated respectively as follows:

[0082] DI_H(t)=h1(t)*0.3+h2(t)*0.7

[0083] AI_H(t)=H3(t)*0.4+H4(t)*0.6

[0084] Calculate the final device health assessment value DEV_H(t) as follows:

[0085] DEV_H(t)=DI_H(t)*0.7+AI_H(t)*0.3.

[0086] 5) Classify the health level of the equipment;

[0087] According to the final device health evaluation value DEV_H(t), the health status of the device is determined, including:

[0088] If 0≤DEV_H(t)≤0.3, the equipment health warning level is level 4, the health status is faulty (urgently in need of repair), and a fault work order is manually issued;

[0089] If 0.3≤DEV_H(t)≤0.45, the device health warning level is level 3, and the health status is unhealthy (focus on attention);

[0090] If 0.45≤DEV_H(t)≤0.65, the equipment health warning level is level 2, and the health status is sub-healthy (strengthen inspection);

[0091] If 0.65≤DEV_H(t)≤1, the device health warning level is level 1, and the device status is healthy.

[0092] The present invention has many specific application paths. The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements can be made without departing from the principle of the present invention. These improvements should also be regarded as the protection scope of the present invention.

Claims

1. A rail transit equipment health assessment method based on operation data, characterized in that: Here are the steps: 1) Confirm the data attributes involved in the health calculation of rail transit equipment types; 2) Collect equipment operation data within a unit time and calculate the number of alarms and data average; 3) Calculate the health assessment value of each data signal; 4) Calculate the final equipment health; 5) Classify the health level of the equipment.

2. The rail transit equipment health assessment method based on operation data according to claim 1 is characterized in that: In the step 1), the rail transit equipment type includes digital signal quantities and analog signal quantities, and signals closely related to equipment failures are selected for health calculation. The digital signal quantities include communication fault point signals and overload fault point signals; the analog signal quantities include working current values ​​and working voltage values; The analog signal quantity is evaluated based on the minimum value, standard value, and maximum value of the data range. The three values ​​are determined based on the equipment specifications and technical parameters.

3. The rail transit equipment health assessment method based on operation data according to claim 1 is characterized in that: In the step 2), the equipment operation data within a unit time is collected, and if the operation data is a digital signal, the number of alarms within a unit time is calculated; If the operating data is an analog signal, the mean value of the data per unit time is calculated, including: The data sampling type is digital signal quantity; 21) In the time period from t1 to t2, the digital signal is sampled n times to obtain the value set D of the overload fault point in the time period = {d1, d2, ..., d n }; 22) Set a counter to record the number of position change alarms C; initially, C = 0; 23) For each sampling point d in the value set in step 21) i , when i=2,3,...,n, compare d i and d i-1 If the value of d i ≠d i-1 , then the digital signal quantity has changed during the time period, and the counter value C is increased by 1; 24) After traversing the entire sampling value sequence, the value of C is the number of position change alarms; 25) Calculate the maximum number of position change alarms of the digital signal quantity of all devices of the same device type C max ; The data sampling type is analog signal quantity; 26) In the time period from t1 to t2, the analog signal is sampled n times to obtain the data set A = {a1, a2, ..., a n }; 27) Calculate the sum S of all data in data set A: 28) Calculate the mean μ of the data within the time period:

4. The rail transit equipment health assessment method based on operation data according to claim 3 is characterized in that: In the step 3), the digital signal health assessment value h(t) and the analog signal health assessment value H(t) are calculated respectively, which specifically includes: 31) The calculation method of the digital signal health assessment value is as follows: Combine the displacement alarm times C calculated in step 24) with the maximum displacement alarm value C of the same type of equipment calculated in step 25) max , the digital signal health assessment value h(t) is calculated using the linear interpolation method as follows: 32) The calculation method of the analog signal health assessment value is as follows: Combine the data mean μ calculated in step 28) with the minimum value X of the analog signal data range min , standard value W, maximum value X max To perform the calculation, the three values ​​are known values, which are determined according to the factory specifications and technical parameters of the equipment. The calculation expression is as follows: Wherein, H(t) is the health assessment value of the analog signal after the device is calculated by piecewise function.

5. The rail transit equipment health assessment method based on operation data according to claim 4 is characterized in that: The step 4) combines the weighted coefficient to calculate the final device health assessment value DEV_H(t), specifically including: 41) Using the method of step 31), calculate the communication fault evaluation h1(t) and the overload fault evaluation h2(t); using the method of step 32), calculate the working current value evaluation H3(t) and the working voltage value evaluation H4(t); The digital signal health assessment value DI_H(t) and the analog signal health assessment value AI_H(t) are calculated respectively as follows: DI_H(t)=h1(t)*0.3+h2(t)*0.7 AI_H(t)=H3(t)*0.4+H4(t)*0.6 Calculate the final device health assessment value DEV_H(t) as follows: DEV_H(t)=DI_H(t)*0.7+AI_H(t)*0.

3.

6. The rail transit equipment health assessment method based on operation data according to claim 1 is characterized in that: In step 5), the health status of the device is determined according to the final device health evaluation value DEV_H(t), specifically including: If 0≤DEV_H(t)≤0.3, the device health warning level is level 4 and the health status is faulty; If 0.3≤DEV_H(t)≤0.45, the device health warning level is level 3 and the health status is unhealthy; If 0.45≤DEV_H(t)≤0.65, the equipment health warning level is level 2 and the health status is sub-healthy; If 0.65≤DEV_H(t)≤1, the device health warning level is level 1, and the device status is healthy.

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