CN112660199A - Data storage and pre-alarming method for monitoring rail transit traction motor bearing state - Google Patents
Data storage and pre-alarming method for monitoring rail transit traction motor bearing state Download PDFInfo
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Abstract
The invention relates to a data storage and warning method for monitoring the condition of a traction motor bearing, in particular to a data storage and warning method for monitoring the condition of a traction motor bearing in rail transit. The invention provides a novel data storage and warning method for monitoring the bearing state of a rail transit traction motor, aiming at solving the problems that the existing data storage method for monitoring the bearing state of the traction motor and the warning method have a plurality of defects, wherein the data storage comprises the storage of the bearing temperature, the rotating speed, the characteristic index, the vibration acceleration data and the vibration acceleration data during the fault, by different storage modes, the effectiveness of data is ensured, the minimum data quantity is also ensured, the pre-alarm comprises a temperature pre-alarm and a vibration pre-alarm, and the problem of low pre-alarm accuracy rate caused by the same threshold value due to individual difference of traction motor bearings is avoided by adopting a method of comparing the pre-alarm with the self-obtained alarm initial value, meanwhile, the reliability of judgment based on the temperature threshold value is improved by compensating the temperature measurement value of the installation position of the sensor.
Description
Technical Field
The invention relates to data storage and early warning for monitoring the condition of a traction motor bearing, in particular to a data storage and early warning method for monitoring the condition of the traction motor bearing, and particularly relates to a data storage and early warning method for monitoring the condition of the traction motor bearing in rail transit.
Background
The traction motor bearing is used as a key core component of a rail transit vehicle, and the running and health conditions of the traction motor bearing directly influence the running safety of a train. In order to ensure the operation safety, bearing state monitoring equipment is installed on the rail transit vehicle, data storage and pre-alarming are carried out on the data of the traction motor bearing through the bearing state monitoring equipment, vibration and temperature data in the running process of the traction motor bearing are monitored, and the health state of the traction motor bearing is diagnosed and evaluated in real time.
In the prior art, two parameters of temperature and vibration are generally adopted for monitoring the fault of a traction motor bearing in an online manner, for example, in a monitoring system of a running part of a locomotive 6A, an acquisition mechanism is that when the speed of the locomotive is lower than 20km/h, only the temperature of each measuring point is detected, when the speed of the locomotive is higher than 20km/h, vibration impact and temperature detection of each measuring point are carried out, temperature data are acquired and stored in real time, and vibration acceleration data are acquired and stored at intervals in real time; the judgment standard of temperature and vibration pre-alarming generally sets absolute threshold values of temperature and vibration as a judgment basis for a certain model of product, and when the absolute threshold values exceed the limit values, the temperature and vibration pre-alarming is carried out, wherein the temperature data of the temperature pre-alarming is the temperature data on a bearing seat of the traction motor close to an outer ring of a bearing.
The prior art has the following disadvantages: the hardware requirement is too high due to large real-time storage data volume, and the simple interval storage in the prior art cannot ensure that the stored data meets the requirement of a fault diagnosis algorithm on stable working conditions, so that the prior storage method is difficult to accurately identify and judge the stable working condition data required by the fault diagnosis algorithm; the alarm threshold value of the vibration is an absolute threshold value, so that the problem that the vibration difference in the monitoring operation process is caused by the individual difference and the circuit difference of traction motor products cannot be solved, the individualized and targeted design and formulation are difficult to realize, and the accuracy of vibration pre-alarm is influenced; because the installation position of the sensor is limited, the temperature of the outer ring of the bearing cannot be directly tested, so that the temperature value acquired by the temperature sensor is different from the actual temperature value of the bearing, the actual temperature value of the bearing cannot be accurately reflected, and the accuracy of temperature pre-alarming is influenced.
Disclosure of Invention
The invention provides a novel data storage and warning method for monitoring the bearing state of a rail transit traction motor, aiming at solving the problem that the existing data storage and warning method for monitoring the bearing state of the traction motor has the defects.
The invention is realized by adopting the following technical scheme:
the data storage and warning method for monitoring the bearing state of the rail transit traction motor is characterized in that the data storage and warning are realized through a bearing state monitoring device, the data storage comprises the storage of bearing temperature, rotating speed, characteristic indexes, vibration acceleration and fault vibration acceleration data, and the concrete storage methods are respectively as follows:
1) storing temperature and rotating speed data: temperature and speed data interval t1Second storage t2Second data, t1And t2The value of (a) is determined according to the storage space of the bearing state monitoring equipment and the bearing fault diagnosis requirement (how to determine t according to the storage space of the bearing state monitoring equipment and the bearing fault diagnosis requirement1And t2The values of (a) belong to the common general knowledge of a person skilled in the art);
2) storing characteristic index data and vibration acceleration data:
the multi-variable working condition storage mode comprises the following steps: the mode is suitable for storing bearing data when the traction motor operates under a variable working condition, and comprises the following specific steps:
the method comprises the following steps: setting at least one reference speed n1，n1Is determined according to the bearing fault diagnosis requirement (how to determine n according to the bearing fault diagnosis requirement1The values of (a) belong to the common general knowledge of a person skilled in the art);
step two: the current rotating speed n2And arrangementIs closest to the reference rotational speed n1Comparing, if the current rotating speed n2Satisfies n1*(1-A% )≤n2≤n1(1+ A%), where A is the rotational speed deviation, then t3Judging the current rotating speed n in the second period2Whether or not n is satisfied1*(1-A% )≤n2≤n1(1+ A%), if not, continuing to judge the next one by t3The second is the current rotating speed of the period, and so on until the condition is met, if the condition is met, the third step is executed, wherein A and t3The value of (A) and (t) are determined according to the actual operation condition of the traction motor3The values of (a) are common general knowledge of a person skilled in the art);
step three: continuing to judge the next time by t3Current speed n of revolution in cycles of seconds2If the conditions are met, the judging method is executed according to the step two, and when the judging time meeting the conditions is accumulated enough for t4Store t after minute4Last t in minutes5Vibration acceleration data of second, and according to t5Calculating characteristic index data from the second vibration acceleration data (how to calculate the characteristic index data is common knowledge of those skilled in the art), and storing the calculated characteristic index data, wherein t4、t5The value of (t) is determined according to the actual operation condition of the traction motor (how to determine t according to the actual operation condition of the traction motor)4、t5The values of (a) belong to the common general knowledge of a person skilled in the art);
step four: repeatedly executing the step three until the traction motor stops running;
3) and (3) storing fault vibration acceleration data:
when vibration pre-alarming occurs, the time before and after pre-alarming is stored as t6Vibration acceleration data in minutes, t6Is determined according to the bearing fault diagnosis requirement (how to determine t according to the bearing fault diagnosis requirement6The values are common knowledge of the technicians in the field, and in addition, the storage of the fault vibration acceleration data provides more effective and comprehensive data for the follow-up fault diagnosis algorithm）；
The stable working condition storage mode comprises the following steps: the mode is suitable for storing bearing data under the condition that the traction motor runs stably, and t is arranged at intervals4Minute memory t4After t in minutes5Vibration acceleration data of second, and according to t5Calculating characteristic index data according to the second vibration acceleration data, and storing the calculated characteristic index data;
the pre-alarming comprises temperature pre-alarming and vibration pre-alarming, and the specific pre-alarming method is designed as follows:
the temperature pre-alarm method is to compare the temperature data with a temperature alarm threshold (the temperature alarm threshold is common knowledge of the technicians in the field), and when the temperature alarm threshold is exceeded, the temperature pre-alarm is triggered;
the vibration prediction warning method is characterized in that characteristic indexes acquired at different times are compared with an initial value of a pre-warning index set initially, and if the initial value of the pre-warning index exceeds the initial value of the pre-warning index by multiplying a pre-warning multiple M, vibration pre-warning is triggered, wherein the pre-warning multiple M is determined by establishing a bearing life-cycle regression curve according to a bearing life-cycle regression test (how to determine the pre-warning multiple M according to the bearing life-cycle regression test belongs to the common knowledge of technicians in the field), the determination methods of the initial value of the pre-warning index are divided into three methods, each determination method is a mode, and the three modes are switched according to actual conditions:
1) in the first mode: the method is suitable for the situation that the actual line data accumulation of the rail transit vehicle is insufficient or a brand new traction motor is used and the running line of the rail transit vehicle is not fixed, and firstly, the average value Y of all characteristic index values on the first day is calculated according to all the characteristic index values stored on the first day1Then, the average value Y of all the characteristic index values stored in the next day is calculated2If the content satisfies-B% < Y ≦ (1-Y2）/Y1Less than or equal to + B%, wherein B is characteristic index deviation, and the initial value of the pre-alarm index is Y2(ii) a If not, calculating the average value Y of all the characteristic index values on the third day3Is a reaction of Y3And Y2Make a comparison ifSatisfies that-B% is less than or equal to (Y)2-Y3）/Y2If the sum of the pre-alarm index and the alarm index is less than or equal to B percent, the initial value of the pre-alarm index is Y3And the rest can be analogized, wherein the value B is set according to the actual working condition of the traction motor (how to set the value B according to the actual working condition of the traction motor is common knowledge of the technical personnel in the field);
2) in the second mode: the method is suitable for the situation that the actual line data accumulation of the rail transit vehicle is insufficient or a brand new traction motor is used and the running line of the rail transit vehicle is fixed, and calculates the average value Y of all the characteristic index values stored in the D days according to all the characteristic index values stored in the D daysDIf the pre-alarm index initial value is YDWherein the value of D is set according to the actual working condition of the traction motor (how to set the value of D according to the actual working condition of the traction motor is common knowledge of technicians in the field);
3) the third mode: the method is suitable for the condition that the rail transit vehicle actual line data are accumulated to be capable of summarizing a typical value (the typical value is an empirical value obtained according to the rail transit vehicle actual line data, which is common knowledge of a person skilled in the art), and the initial value of the pre-alarm index is the typical value.
The invention relates to a method for storing and identifying vibration data of a stable working condition required by a fault diagnosis algorithm under the condition of a complex and changeable working condition of a rail transit vehicle, which also comprises a mode of storing the vibration data at intervals according to the condition of meeting the rotating speed and storing the vibration data in a fault state, and meets the requirement of the fault diagnosis algorithm of a traction motor bearing of the rail transit vehicle on data storage; meanwhile, the invention solves the problem of false pre-alarm caused by the fact that the running vibration of the traction motor bearing in the normal running state exceeds an absolute threshold value due to individual difference and different running circuit states by setting the initial values of the alarm indexes in three different modes; in addition, the invention carries out long-time temperature rise test on the traction motor, compares the temperature of the outer ring of the bearing of the traction motor with the temperature collected by the sensor, calculates the temperature difference of two measuring points, carries out temperature measurement value compensation of the installation position of the sensor and improves the reliability of temperature pre-alarm.
Further, t1The value range is 20-60, t2The value range is 1-5, t3The value range is 2-5, t4The value range is 1-3, t5The value range is 1-5, t6The value range is 10-30, the value range of A is 2-5, the value range of M is 1-6, the value range of B is 1-10, and the value range of D is 1-10.
Furthermore, the data storage also comprises vehicle positioning storage, so that the storage requirement of vibration acceleration data of a specific place is met, and the inaccuracy of the fault diagnosis data of the traction motor bearing caused by the data difference of a specific place is prevented.
Further, the temperature data storage value = the actual measurement value + C of the sensor, wherein C is the temperature difference between the bearing room temperature obtained according to the long-time temperature rise experiment and the actual measurement value of the sensor, so that the accuracy of the temperature data is improved, the accuracy of the temperature pre-alarm is improved, and meanwhile, the reliability of the stored temperature data for carrying out the fault diagnosis of the traction motor bearing is also improved.
Furthermore, the pre-alarm multiples M are three and are M1, M2 and M3 respectively, the M1 pre-alarm index initial value is a primary pre-alarm, the M2 pre-alarm index initial value is a secondary pre-alarm, and the M3 pre-alarm index initial value is a tertiary pre-alarm, so that the pre-alarm level can be adjusted conveniently according to the actual running condition of the traction motor.
Further, when fault vibration acceleration data is stored, when the pre-alarm level is not changed, the fault vibration acceleration data is not stored again, when the pre-alarm level is changed, the fault vibration acceleration data is stored again, and the time t before and after the pre-alarm level is stored6Vibration acceleration data in minutes.
The beneficial effects produced by the invention are as follows:
1) the method solves the problems that the operation working conditions of the rail transit traction motor are variable, and the bearing fault diagnosis algorithm has higher validity requirement on the stored data.
2) The self-comparison mode is adopted, and the problems that vibration acceleration is originally different when each train and each traction motor bearing normally run due to the difference of the manufacturing assembly and the line state of the traction motor bearing, the same absolute alarm is used for products of the same type, and the accuracy is low are solved.
3) Through a long-time temperature rise test of the traction motor, the difference value between the temperature of the outer ring of the bearing and the temperature of the measuring position of the sensor is determined, temperature measurement value compensation is carried out, and the accuracy of temperature pre-alarming is improved.
Detailed Description
The data storage and warning method for monitoring the bearing state of the rail transit traction motor is characterized in that the data storage and warning are realized through a bearing state monitoring device, the data storage comprises the storage of the bearing temperature, the rotating speed, the characteristic index, the vibration acceleration data and the fault vibration acceleration data, and the specific storage method comprises the following steps:
1) storing temperature and rotating speed data: temperature and speed data interval t1Second storage t2Second data, t1And t2The value of the fault diagnosis method is determined according to the storage space of the bearing state monitoring equipment and the bearing fault diagnosis requirement;
2) storing characteristic index data and vibration acceleration data:
the multi-variable working condition storage mode comprises the following steps: the mode is suitable for storing bearing data when the traction motor operates under a variable working condition, and comprises the following specific steps:
the method comprises the following steps: setting at least one reference speed n1，n1The value of (A) is determined according to the bearing fault diagnosis requirement;
step two: the current rotating speed n2Closest reference speed n to the set1Comparing, if the current rotating speed n2Satisfies n1*(1-A% )≤n2≤n1(1+ A%), where A is the rotational speed deviation, then t3Judging whether the current rotating speeds all meet n or not in second period1*(1-A% )≤n2≤n1(1+ A%), if not, continuing to judge the next one by t3The current rotating speed of the second period is obtained, and so on until the condition is met, if the condition is met, the operation is executedStep three, wherein A and t3The value of the traction motor is determined according to the actual operation condition of the traction motor;
step three: continuing to judge the next time by t3Whether the current rotating speed with the second period meets the condition or not is judged according to the step two, and when the judgment time meeting the condition is accumulated to be t enough4Store t after minute4Last t of minute5Vibration acceleration data of second, and according to t5Calculating characteristic index data from the second vibration acceleration data, and storing the calculated characteristic index data, wherein t4、t5The value of the traction motor is determined according to the actual operation condition of the traction motor;
step four: step four: repeatedly executing the step three until the traction motor stops running;
the stable working condition storage mode comprises the following steps: the mode is suitable for storing bearing data under the condition that the traction motor runs stably, and t is arranged at intervals4Minute memory t4After t in minutes5Vibration acceleration data of second, and according to t5Calculating characteristic index data according to the second vibration acceleration data, and storing the calculated characteristic index data;
3) and (3) storing fault vibration acceleration data:
when vibration pre-alarming occurs, the time before and after pre-alarming is stored as t6Vibration acceleration data in minutes, t6The value of (A) is determined according to the bearing fault diagnosis requirement;
the pre-alarming comprises temperature pre-alarming and vibration pre-alarming, and the specific pre-alarming method is designed as follows:
the temperature pre-alarming method is that the temperature data is compared with a temperature alarming threshold value, and when the temperature data exceeds the temperature alarming threshold value, the temperature pre-alarming is triggered;
the vibration prediction warning method is characterized in that characteristic indexes acquired at different times are compared with initial values of pre-warning indexes set initially, if the initial values of the pre-warning indexes exceed the initial values of the pre-warning indexes and are multiplied by a pre-warning multiple M, vibration pre-warning is triggered, wherein the pre-warning multiple M is determined by establishing a bearing life-cycle regression curve according to a bearing life-cycle regression test, the determination method of the initial values of the pre-warning indexes is divided into three methods, each determination method is a mode, and the three modes can be switched according to actual conditions:
1) in the first mode: the method is suitable for the situation that the actual line data accumulation of the rail transit vehicle is insufficient or a brand new traction motor is used and the running line of the rail transit vehicle is not fixed, and firstly, the average value Y of all characteristic index values on the first day is calculated according to all the characteristic index values stored on the first day1Then, the average value Y of all the characteristic index values stored in the next day is calculated2If the content satisfies-B% < Y ≦ (1-Y2）/Y1Less than or equal to + B%, wherein B is characteristic index deviation, and the initial value of the pre-alarm index is Y2(ii) a If not, calculating the average value Y of each characteristic index value on the third day3Is a reaction of Y3And Y2Comparing, if the content satisfies-B% < Y ≦ (Y)2-Y3）/Y2If the sum of the pre-alarm index and the alarm index is less than or equal to B percent, the initial value of the pre-alarm index is Y3And the rest is done in sequence, wherein the value B is set according to the actual working condition of the traction motor;
2) in the second mode: the method is suitable for the situation that the actual line data accumulation of the rail transit vehicle is insufficient or a brand new traction motor is used and the running line of the rail transit vehicle is fixed, and calculates the average value Y of the stored characteristic index values in the D days according to the characteristic index values stored in the D daysDIf the pre-alarm index initial value is YDWherein the value of D is set according to the actual working condition of the traction motor;
3) the third mode: the method is suitable for the condition that the data of the actual line of the rail transit vehicle are accumulated to be capable of summarizing the typical value, and the initial value of the pre-alarm index is the typical value.
In specific practice, t1The range of values is 10-60 (e.g., 10,15,20,21,28, 30,40,45, 50,58, 60), t2The value range is 1-5, t3The value range is 2-5 (if 2,2.3, 3,3.5,4, 5) t4The value range is 1-3 (if 1,1.1, 1.5, 2,2.5, 3) t5The value range is 1-5, t6The value range is 10-30 (if 10,12,15,28,20,21,23,28,29, 30 is adopted), and the value range of A is 2-5 (if 2,2.5,3,3.5,4,4.1,5, 30 is adopted)) M ranges from 1 to 6 (e.g., 1,2,3,4,5,6 is used), B ranges from 1 to 10 (e.g., 1,2,3,4,5,6, 7,8,9,10 is used), and D ranges from 1 to 10 (e.g., 1,2, 2.3, 3,4,5,6,7,8,9,10 is used).
During specific implementation, the data storage also comprises vehicle positioning storage, so that the storage requirement of vibration acceleration data of a specific place is met, and the inaccuracy of the fault diagnosis data of the traction motor bearing caused by the data difference of a specific place is prevented.
During specific implementation, the temperature data storage value = the actual measurement value + C of the sensor, wherein C is the temperature difference between the bearing room temperature obtained according to a long-time temperature rise experiment and the actual measurement value of the sensor, so that the accuracy of the temperature data is improved, the accuracy of temperature pre-alarming is improved, and meanwhile, the reliability of the stored temperature data for fault diagnosis of the traction motor bearing is also improved.
In specific implementation, the pre-alarm multiples M are three and are M1, M2 and M3 respectively, the M1 pre-alarm index initial value is a primary pre-alarm, the M2 pre-alarm index initial value is a secondary pre-alarm, and the M3 pre-alarm index initial value is a tertiary pre-alarm, so that the pre-alarm level can be adjusted conveniently according to the actual running condition of the traction motor.
In specific implementation, when fault vibration acceleration data are stored, the data are not stored again when the pre-alarm level is not changed, and are stored again when the pre-alarm level is changed, wherein the time before and after the pre-alarm level is stored is t6Vibration acceleration data in minutes.
In this embodiment, C is 15 ℃ and the reference rotation speed n12950 rpm.
Claims (10)
1. The data storage and warning method for monitoring the bearing state of the rail transit traction motor is characterized in that the data storage and warning are realized through bearing state monitoring equipment, the data storage comprises the storage of bearing temperature, rotating speed, characteristic indexes, vibration acceleration data and fault vibration acceleration data, and the specific storage methods are respectively as follows:
1) storing temperature and rotating speed data: temperature and speed of rotationData mean interval t1Second storage t2Second data, t1And t2The value of the fault diagnosis method is determined according to the storage space of the bearing state monitoring equipment and the bearing fault diagnosis requirement;
2) storing characteristic index data and vibration acceleration data:
the multi-variable working condition storage mode comprises the following steps: the mode is suitable for storing bearing data when the traction motor operates under a variable working condition, and comprises the following specific steps:
the method comprises the following steps: setting at least one reference speed n1，n1The value of (A) is determined according to the bearing fault diagnosis requirement;
step two: the current rotating speed n2Closest reference speed n to the set1Comparing, if the current rotating speed n2Satisfies n1*(1-A% )≤n2≤n1(1+ A%), where A is the rotational speed deviation, then t3Judging whether the current rotating speeds all meet n or not in second period1*(1-A% )≤n2≤n1(1+ A%), if not, continuing to judge the next one by t3The second is the current rotating speed of the period, the analogy is carried out until the condition is met, if the condition is met, the third step is executed, wherein A and t3The value of the traction motor is determined according to the actual operation condition of the traction motor;
step three: continuing to judge the next time by t3Whether the current rotating speed with the second period meets the condition or not is judged according to the step two, and when the judgment time meeting the condition is accumulated to be t enough4Store t after minute4Last t of minute5Vibration acceleration data of second, and according to t5Calculating characteristic index data from the second vibration acceleration data, and storing the calculated characteristic index data, wherein t4、t5The value of the traction motor is determined according to the actual operation condition of the traction motor;
step four: step four: repeatedly executing the step three until the traction motor stops running;
the stable working condition storage mode comprises the following steps: the mode is suitable for storing bearing data under the condition that the traction motor runs stably, and t is arranged at intervals4Minute memory t4In the minuteAfter t of5Vibration acceleration data of second, and according to t5Calculating characteristic index data according to the second vibration acceleration data, and storing the calculated characteristic index data;
3) and (3) storing fault vibration acceleration data:
when vibration pre-alarming occurs, the time before and after pre-alarming is stored as t6Vibration acceleration data in minutes, t6The value of (A) is determined according to the bearing fault diagnosis requirement;
the pre-alarming comprises temperature pre-alarming and vibration pre-alarming, and the specific pre-alarming method is designed as follows:
the temperature pre-alarming method is that the temperature data is compared with a temperature alarming threshold value, and when the temperature data exceeds the temperature alarming threshold value, the temperature pre-alarming is triggered;
the vibration prediction alarm method is characterized in that characteristic indexes acquired at different times are compared with an initial set alarm index value, if the initial value of the alarm index is exceeded by multiplying a pre-alarm multiple M, vibration pre-alarm is triggered, wherein the pre-alarm multiple M is determined by establishing a bearing life-cycle decline curve according to a bearing life-cycle decline test, the determination methods of the initial value of the pre-alarm index are divided into three, each determination method is a mode, and the three modes can be switched according to actual conditions:
1) in the first mode: the method is suitable for the situation that the actual line data accumulation of the rail transit vehicle is insufficient or a brand new traction motor is used and the running line of the rail transit vehicle is not fixed, and firstly, the average value Y of all characteristic index values on the first day is calculated according to all the characteristic index values stored on the first day1Then, the average value Y of all the characteristic index values stored in the next day is calculated2If the content satisfies-B% < Y ≦ (1-Y2）/Y1Less than or equal to + B%, wherein B is characteristic index deviation, and the initial value of the alarm index is Y2(ii) a If not, calculating the average value Y of each characteristic index value on the third day3Is a reaction of Y3And Y2Comparing, if the content satisfies-B% < Y ≦ (Y)2-Y3）/Y2If the sum of the pre-alarm index and the alarm index is less than or equal to B percent, the initial value of the pre-alarm index is Y3By analogy, it isThe value B is set according to the actual working condition of the traction motor;
2) in the second mode: the method is suitable for the situation that the actual line data accumulation of the rail transit vehicle is insufficient or a brand new traction motor is used and the running line of the rail transit vehicle is fixed, and calculates the average value Y of the stored characteristic index values in the D days according to the characteristic index values stored in the D daysDIf the pre-alarm index initial value is YDWherein the value of D is set according to the actual working condition of the traction motor;
3) the third mode: the method is suitable for the condition that the data of the actual line of the rail transit vehicle are accumulated to be capable of summarizing the typical value, and the initial value of the early warning index is reported to be the typical value.
2. The rail transit traction motor bearing condition monitoring data storage and warning method according to claim 1, characterized in that t is t1The value range is 20-60, t2The value range is 1-5, t3The value range is 2-5, t4The value range is 1-3, t5The value range is 1-5, t6The value range is 10-30, the value range of A is 2-5, the value range of M is 1-6, the value range of B is 1-10, and the value range of D is 1-10.
3. The rail transit traction motor bearing condition monitoring data storage and pre-warning method according to claim 1 or 2, wherein the data storage further comprises vehicle positioning storage, so that storage requirements of vibration acceleration data of a specific place are met.
4. The data storage and pre-alarm method for monitoring the condition of the rail transit traction motor bearing according to claim 1 or 2, characterized in that the temperature data storage value = sensor actual measurement value + C, where C is the temperature difference between the bearing room temperature and the sensor actual measurement value obtained from long-time temperature rise experiments.
5. The data storage and pre-warning method for monitoring the condition of the rail transit traction motor bearing according to claim 3, wherein the temperature data storage value = sensor actual measurement value + C, wherein C is the temperature difference between the bearing room temperature and the sensor actual measurement value obtained from long-time temperature rise experiments.
6. The data storage and pre-alarm method for monitoring the bearing state of the rail transit traction motor according to claim 1 or 2, wherein the pre-alarm multiple M is three and is M1, M2 and M3 respectively, the initial value of the M1 pre-alarm index is a primary pre-alarm, the initial value of the M2 pre-alarm index is a secondary pre-alarm, and the initial value of the M3 pre-alarm index is a tertiary pre-alarm.
7. The data storage and pre-alarm method for monitoring the bearing state of the rail transit traction motor according to claim 3, wherein the pre-alarm multiple M is three and is M1, M2 and M3 respectively, the initial value of the M1 pre-alarm index is a primary pre-alarm, the initial value of the M2 pre-alarm index is a secondary pre-alarm, and the initial value of the M3 pre-alarm index is a tertiary pre-alarm.
8. The data storage and pre-alarm method for monitoring the bearing state of the rail transit traction motor according to claim 4, wherein the pre-alarm multiple M is three and is M1, M2 and M3 respectively, the initial value of the M1 pre-alarm index is a primary pre-alarm, the initial value of the M2 pre-alarm index is a secondary pre-alarm, and the initial value of the M3 pre-alarm index is a tertiary pre-alarm.
9. The data storage and pre-alarm method for monitoring the bearing state of the rail transit traction motor according to claim 5, wherein the pre-alarm multiple M is three and is M1, M2 and M3 respectively, the initial value of the M1 pre-alarm index is a primary pre-alarm, the initial value of the M2 pre-alarm index is a secondary pre-alarm, and the initial value of the M3 pre-alarm index is a tertiary pre-alarm.
10. The rail transit traction motor bearing condition monitoring data storage and pre-warning method of claim 9, wherein the approach isWhen fault vibration acceleration data is stored, the data is not stored again when the pre-alarm grade is not changed, and is stored again when the pre-alarm grade is changed, and the time before and after the pre-alarm grade is stored is t6Vibration acceleration data in minutes.
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