CN110422189B - Online prediction method for compressor fault in air conditioning unit of railway vehicle - Google Patents
Online prediction method for compressor fault in air conditioning unit of railway vehicle Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61D—BODY DETAILS OR KINDS OF RAILWAY VEHICLES
- B61D27/00—Heating, cooling, ventilating, or air-conditioning
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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Abstract
The invention discloses an online prediction method for compressor faults in a railway vehicle air conditioning unit, which belongs to the technical field of railway vehicle air conditioners and comprises the following steps: step A, collecting exhaust pressure and suction pressure data; step B, calculating the pressure ratio difference and the average value of the pressure ratio difference of the two groups of refrigerant systems, and simultaneously calculating the current difference and the average value of the current difference; and step C, if a certain condition is met, and the absolute value of the average value of the pressure ratio difference values and the absolute value of the average value of the current difference values in n continuous data acquisition periods have an increasing trend, the air conditioning unit sends out a compressor fault early warning. The invention monitors the running state of the compressor by collecting the running data of the compressor, warns the fault of the compressor in advance, carries out active operation and maintenance based on the running state of the compressor and improves the running reliability of the air conditioner.
Description
Technical Field
The invention belongs to the technical field of rail vehicle air conditioners, and particularly relates to an online prediction method for compressor faults in a rail vehicle air conditioning unit.
Background
The rail vehicle air conditioner is a public transportation product, and the stable and safe operation of the rail vehicle air conditioner is very important. The compressor is the core component for normal operation of the air conditioner, and the faults of the compressor can influence the comfort of passengers in the vehicle and reduce the running function of the vehicle.
With the development of industrial control technology and network technology, at present, PHM (abbreviation of protocol and health Management), namely fault prediction and health Management, has been implemented step by step in the field of maintenance and repair of rail transit vehicle components, and has been in the first place successful. In view of many vehicle components, a PHM scheme of the component needs to be continuously excavated and perfected to accurately provide capabilities of fault diagnosis and fault prediction, realize predicting time and position of a fault in advance, realize maintenance judgment based on the running state of the component, reduce or eliminate the influence of the fault on the online operation of the vehicle, reduce the maintenance cost of a system and improve the maintenance accuracy.
The present maintenance of compressors for vehicle air conditioners is mainly based on the fixed repair and the troubleshooting of the component life. Once the compressor breaks down during the vehicle operation, the refrigeration function reduces or can't lose, seriously influences travelling comfort in the carriage, and serious influence vehicle operation causes great accident.
Disclosure of Invention
The technical problem to be solved by the invention is to provide an online prediction method for compressor faults in a railway vehicle air conditioning unit, which is used for monitoring the running state of a compressor, giving an early warning before the compressor is in fault, proposing an operation and maintenance suggestion, and timely replacing and maintaining the air conditioning compressor, thereby solving the passive current situation that the compressor faults cannot be quantitatively predicted at present and the compressor can be repaired and replaced after the compressor is in fault.
In order to solve the technical problems, the invention adopts the technical scheme that:
the online prediction method for the faults of the compressors in the air conditioning unit of the railway vehicle is based on the air conditioning unit with 2 groups of refrigerant circulating systems, and an exhaust pressure sensor and a suction pressure sensor are respectively arranged at an exhaust position and a suction position of each group of refrigerant circulating systems, and is characterized by comprising the following steps:
step A, collecting exhaust pressure and suction pressure data of a compressor in the operation process of an air conditioning unit according to a certain period;
step B, respectively calculating the ratio of the exhaust pressure value and the suction pressure value of the compressor in each group of refrigerant circulating systems according to a certain frequency in the acquired data, calculating the pressure ratio difference value of the two groups of refrigerant systems, then calculating the average value of the pressure ratio difference value in the data acquisition period,
while by fitting the formula y = ax2Bx + c, respectively calculating the current values of the two groups of compressors, the current difference values of the two groups of compressors and the average value of the current difference values in a data acquisition period, wherein y is current, x is condensation temperature, and a, b and c are compressor characteristic correlation coefficients;
step C, if the average value of the pressure ratio difference value is not less than a preset value C1 and the average value of the current difference value calculated through a fitting formula is not less than a preset value Z1, recording 1 time of compressor failure in the 2 nd group of refrigerant circulating systems; if the average value of the pressure ratio difference value is less than or equal to the negative number of the preset value C1 and the average value of the current difference value calculated through the fitting formula is less than or equal to the negative number of the preset value Z1, recording 1 time of compressor failure in the 1 st group of refrigerant circulating systems; if the same compressor records the failure times in n continuous data acquisition periods and the absolute value of the average value of the pressure ratio difference value and the absolute value of the average value of the current difference value both have an increasing trend, the air conditioning unit sends out compressor failure early warning, wherein the value range of n is 5-7.
The invention monitors the running state of the compressor by collecting the running data of the compressor, warns the fault of the compressor in advance, carries out active operation and maintenance based on the running state of the compressor and improves the running reliability of the air conditioner.
The present invention will be described in detail with reference to the accompanying drawings.
Drawings
FIG. 1 is a flow chart of a first embodiment of a method for online prediction of compressor failure in a rail vehicle air conditioning unit in accordance with the present invention;
fig. 2 is a flowchart of a second embodiment of the online prediction method for the fault of the compressor in the air conditioning unit of the railway vehicle according to the invention.
Detailed Description
The invention provides an online prediction method for compressor faults in a railway vehicle air conditioning unit, which is based on the air conditioning unit with 2 groups of refrigerant circulating systems. Each group of refrigerant circulating systems is provided with a compressor, and a discharge pressure sensor and a suction pressure sensor are respectively arranged at the discharge position and the suction position of the compressor.
The first embodiment is as follows:
referring to fig. 1, the method of the present invention includes the following steps.
Step A, collecting data of exhaust pressure and suction pressure of a compressor in the operation process of the air conditioning unit according to a certain period. Specifically, the period of acquisition of discharge pressure and suction pressure data of the compressor is H hours, for example, from the last working day time H1 to the current working day time H2. H. H1 and H2 can be reasonably determined according to the vehicle operation management time, for example, the collection period of the discharge pressure and suction pressure data of the compressor is 6, 12, 18 or 24 hours, and the data can be specifically adjusted according to the vehicle operation management plan.
And step B, respectively calculating the ratio of the exhaust pressure value and the suction pressure value of the compressor in each group of refrigerant circulating systems according to a certain frequency in the acquired data, calculating the pressure ratio difference of the two groups of refrigerant systems, and then calculating the average value of the pressure ratio difference in the data acquisition period.
Calculating the ratio of pressure values and other data while fitting the formula y = ax2Bx + c, respectively calculating the current values of the two groups of compressors, the current difference values of the two groups of compressors and the average value of the current difference values in the data acquisition period, wherein y is the current, x is the condensation temperature, and a, b and c are the characteristic correlation coefficients of the compressors.
Step C, if the average value of the pressure ratio difference value is not less than a preset value C1 and the average value of the current difference value calculated through a fitting formula is not less than a preset value Z1, recording 1 time of compressor failure in the 2 nd group of refrigerant circulating systems; if the average value of the pressure ratio difference value is less than or equal to the negative number of the preset value C1 and the average value of the current difference value calculated through the fitting formula is less than or equal to the negative number of the preset value Z1, recording 1 time of compressor failure in the 1 st group of refrigerant circulating systems; if the same compressor records the failure times in continuous 5 data acquisition periods and the absolute value of the average value of the pressure ratio difference value and the absolute value of the average value of the current difference value both have an increasing trend, the air conditioning unit sends out a compressor failure early warning. Wherein, C1 and Z1 are numerical values greater than zero, and since the pressure ratio and the fitting current of the fault compressor are smaller than those of the normal operation compressor when the compressor operates at a certain frequency, which compressor has a fault can be judged.
If the fault early warning is continuously recorded for 4 times for a certain compressor and the subsequent 1 time is normal, the fault count is cleared and counted again after the 5 th judgment.
Example two: different from the first embodiment, the air conditioning unit is further provided with a current transformer for collecting the current of the compressor, the accuracy of the method is further ensured by matching with the pressure sensor, and the fault detection of the compressor can be still realized when any one of the current transformer and the pressure sensor has a fault.
Referring to fig. 2, the method of the present invention includes the following steps.
And step A, acquiring exhaust pressure and suction pressure data of the compressors in the operation process of the air conditioning unit and current data of the two groups of compressors acquired by the current transformer according to a certain period. Specifically, the period of acquisition of discharge pressure and suction pressure data of the compressor is H hours, for example, from the last working day time H1 to the current working day time H2. H. H1 and H2 can be reasonably determined according to the vehicle operation management time, for example, the collection period of the discharge pressure and suction pressure data of the compressor is 6, 12, 18 or 24 hours, and the data can be specifically adjusted according to the vehicle operation management plan.
And step B, respectively calculating the ratio of the exhaust pressure value and the suction pressure value of the compressor in each group of refrigerant circulating systems according to a certain frequency in the acquired data, calculating the pressure ratio difference of the two groups of refrigerant systems, and then calculating the average value of the pressure ratio difference in the data acquisition period.
While calculating the pressure ratio difference value and the average value of the pressure ratio difference values, by fitting the formula y = ax2Bx + c, respectively calculating the current values of the two groups of compressors, the current difference values of the two groups of compressors and the average value of the current difference values in a data acquisition period, wherein y is current, x is condensation temperature, and a, b and c are compressor characteristic correlation coefficients; calculating the current difference of the two groups of compressors according to the current data of the compressors acquired by the current transformer and the average of the current difference in the data acquisition periodThe value is obtained.
And step C, if the average value of the pressure ratio difference value is larger than or equal to a preset value C1 and the average value of the current difference value calculated through a fitting formula is larger than or equal to a preset value Z1 and/or the average value of the current difference value actually measured by the current transformer is smaller than or equal to the negative number of a preset value Z2 (when the pressure sensor and the current transformer work normally, two conditions are met when a fault is recorded, and when one of the pressure sensor and the current transformer is in fault, only one corresponding condition is met), the compressor in the 2 nd group of refrigerant circulating systems is in fault for 1 time.
And if the average value of the pressure ratio difference value is less than or equal to the negative number of the preset value C1, the average value of the current difference value calculated by the fitting formula is less than or equal to the negative number of the preset value Z1 and/or the average value of the current difference value measured by the current transformer is more than or equal to the preset value Z2 (when the pressure sensor and the current transformer work normally, two conditions are met when a fault is recorded, and when one of the pressure sensor and the current transformer fails, only one corresponding condition is met), recording the 1 st group of compressor faults in the refrigerant circulating system for 1 time.
Wherein C1, Z1 and Z2 are all values greater than zero. When the compressor runs under a certain frequency, the pressure ratio and the fitting current of the fault compressor are smaller than those of the normal running compressor; but the current value of the fault compressor acquired through actual measurement of the current transformer is larger than the current value of the normal operation compressor. Thereby determining which of the compressors of the refrigeration systems is malfunctioning.
If the same compressor records the failure times in continuous 5 data acquisition periods and the absolute value of the average value of the pressure ratio difference value and the absolute value of the average value of the current difference value both have an increasing trend, the air conditioning unit sends out a compressor failure early warning.
If the fault early warning is continuously recorded for 4 times for a certain compressor, and the subsequent 1 time is normal, the fault count is cleared and counted again after the 5 th judgment.
The method can judge whether one of the compressors in the 2 groups of systems in the air conditioning unit is abnormal or not and give an alarm so as to enable maintenance personnel to detect and maintain in time.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention and not to limit it; although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art will understand that: modifications to the specific embodiments of the invention or equivalent substitutions for parts of the technical features may be made; without departing from the spirit of the present invention, it is intended to cover all aspects of the invention as defined by the appended claims.
Claims (3)
1. An online prediction method for faults of compressors in a rail vehicle air conditioning unit is based on the air conditioning unit with 2 groups of refrigerant circulating systems, and an exhaust pressure sensor and a suction pressure sensor are respectively arranged at an exhaust position and a suction position of a compressor in each group of refrigerant circulating systems, and is characterized by comprising the following steps:
step A, collecting exhaust pressure and suction pressure data of a compressor in the operation process of an air conditioning unit according to a certain period;
step B, respectively calculating the ratio of the exhaust pressure value and the suction pressure value of the compressor in each group of refrigerant circulating systems according to a certain frequency in the acquired data, calculating the pressure ratio difference value of the two groups of refrigerant systems, then calculating the average value of the pressure ratio difference value in the data acquisition period,
while fitting the formula y = ax2Bx + c, respectively calculating the current values of the two groups of compressors, the current difference values of the two groups of compressors and the average value of the current difference values in a data acquisition period, wherein y is current, x is condensation temperature, and a, b and c are compressor characteristic correlation coefficients;
step C, if the average value of the pressure ratio difference value is not less than a preset value C1 and the average value of the current difference value calculated through a fitting formula is not less than a preset value Z1, recording 1 time of compressor failure in the 2 nd group of refrigerant circulating systems;
if the average value of the pressure ratio difference value is less than or equal to the negative number of the preset value C1 and the average value of the current difference value calculated through the fitting formula is less than or equal to the negative number of the preset value Z1, recording 1 time of compressor failure in the 1 st group of refrigerant circulating systems;
if the same compressor records the failure times in n continuous data acquisition periods and the absolute value of the average value of the pressure ratio difference value and the absolute value of the average value of the current difference value both have an increasing trend, the air conditioning unit sends out compressor failure early warning, wherein the value range of n is 5-7;
wherein C1 and Z1 are both numbers greater than zero.
2. The on-line prediction method for the faults of the compressors in the air conditioning unit of the railway vehicle as claimed in claim 1, wherein in the step A, the current data of the two groups of compressors collected by the current transformer are collected while the data of the exhaust pressure and the suction pressure are collected;
in the step B, the current value is calculated through a fitting formula, and the current difference values of the two groups of compressors acquired by the current transformer and the average value of the current difference values in the data acquisition period are calculated;
in the step C, if the average value of the pressure ratio difference value is not less than the preset value C1 and the average value of the current difference value calculated through the fitting formula is not less than the preset value Z1 and/or the average value of the current difference value actually measured by the current transformer is not more than the negative number of the preset value Z2, recording 1 time of compressor failure in the 2 nd group of refrigerant circulating systems;
if the average value of the pressure ratio difference value is less than or equal to the negative number of the preset value C1, the average value of the current difference value calculated through a fitting formula is less than or equal to the negative number of the preset value Z1 and/or the average value of the current difference value measured by the current transformer is more than or equal to the preset value Z2, recording that the compressor in the 1 st group of refrigerant circulating systems fails for 1 time;
if the same compressor records the failure times in n continuous data acquisition periods and the absolute value of the average value of the pressure ratio difference value and the absolute value of the average value of the current difference value both have an increasing trend, the air conditioning unit sends out compressor failure early warning, wherein the value range of n is 5-7;
wherein C1, Z1 and Z2 are all values greater than zero.
3. The method for on-line prediction of compressor failure in air conditioning units for railway vehicles as claimed in any one of claims 1 or 2, wherein the period of collecting discharge pressure and suction pressure data of the compressor in step a is 6, 12, 18 or 24 hours.
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| CN111665067A (en) * | 2020-05-18 | 2020-09-15 | 中车青岛四方机车车辆股份有限公司 | Rail vehicle air conditioner state monitoring system and monitoring method |
| CN111723925B (en) * | 2020-06-17 | 2023-05-02 | 中南大学 | Fault diagnosis method, device, equipment and medium for on-road intelligent train air conditioning unit |
| CN111487005B (en) * | 2020-06-29 | 2020-09-22 | 新誉轨道交通科技有限公司 | Train pressure wave diagnosis method, device and equipment |
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| CN114506356B (en) * | 2022-01-13 | 2023-05-23 | 中车青岛四方机车车辆股份有限公司 | Air conditioning system of railway vehicle and operation data processing method of air conditioning system |
| CN116611819B (en) * | 2023-05-30 | 2023-12-22 | 重庆赛力斯新能源汽车设计院有限公司 | Air conditioner compressor fault prediction method, system, terminal equipment and storage medium |
| CN117114352B (en) * | 2023-09-15 | 2024-04-09 | 北京阿帕科蓝科技有限公司 | Vehicle maintenance method, device, computer equipment and storage medium |
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