Fault prediction device and method, train and electronic device

Abstract

The invention provides a fault prediction device which can be applied to the technical field of fault prediction. The fault prediction device may comprise: a sensor for generating an air pressure signal according to the air pressure inside a cylinder when a first solenoid valve provided at a vent of a train cylinder acts; the air vent is used for transmitting air from an air source into the air cylinder, so that the internal air pressure of the air cylinder meets a preset condition; the processor is connected to the sensor and used for determining actual performance index information of the first electromagnetic valve according to the air pressure signal; the number of actions completed by the first electromagnetic valve is determined, and ideal performance index information is determined according to the number of actions; and generating a fault prediction result of the first solenoid valve according to the ideal performance index information and the actual performance index information. The invention further provides a fault prediction method, a train and electronic equipment.

Description

Technical Field

[0001] The present disclosure relates to the technical field of fault prediction, and more particularly, to a fault prediction device, method, train, and electronic device. Background Art

[0002] The solenoid valves deployed in the train system are important for the stable operation of the train system. However, with the repeated use of the solenoid valves, the performance of the solenoid valves may decline, and even faults may occur, thus affecting the stable operation of the train system. Therefore, it is necessary to take maintenance measures in a timely manner for the solenoid valves with the possibility of faults. However, in the related art, it is difficult to accurately predict the fault possibility of the solenoid valves. Summary of the Invention

[0003] In view of this, the present disclosure provides a fault prediction device, method, train, and electronic device.

[0004] One aspect of the present disclosure provides a fault prediction device, including: a sensor, configured to generate a pressure signal according to the air pressure inside the cylinder when a first solenoid valve disposed at the air vent of the cylinder of the train operates; the air vent is configured to transmit the gas from the gas source into the cylinder so that the internal air pressure of the cylinder meets a predetermined condition; a processor, connected to the sensor, configured to: determine the actual performance index information of the first solenoid valve according to the pressure signal; determine the number of operations completed by the first solenoid valve, and determine the ideal performance index information according to the number of operations; and generate a fault prediction result of the first solenoid valve according to the ideal performance index information and the actual performance index information.

[0005] According to an embodiment of the present disclosure, the processor is further configured to: process the number of operations by using a predetermined correlation to obtain the ideal performance index information; the predetermined correlation characterizes the relationship between the number of operations of the solenoid valve and the performance index information of the solenoid valve; determine the difference information between the ideal performance index information and the actual performance index information; and generate a fault prediction result of the first solenoid valve according to the difference information.

[0006] According to an embodiment of the present disclosure, the processor is further configured to: obtain the type information of the first solenoid valve and the usage duration information of the first solenoid valve; and generate a fault prediction result of the first solenoid valve according to the type information, the usage duration information, and the difference information.

[0007] According to an embodiment of the present disclosure, the operation of the first solenoid valve includes an opening operation; the actual performance index information includes the actual response duration; the processor is further configured to, when the first solenoid valve performs the opening operation: receive N air pressure signals from the sensor and determine the reception times of the N air pressure signals, where N is an integer greater than 1; determine a first target time and a second target time from the reception times of the N air pressure signals according to the air pressure values of the N air pressure signals; the first target time represents the time when the cylinder starts to receive gas; the second target time represents the time when the internal air pressure of the cylinder meets a predetermined condition; generate the actual response duration of the first solenoid valve according to the first target time and the second target time.

[0008] According to an embodiment of the present disclosure, the processor is further configured to: compare the air pressure value of the (n - 1)-th air pressure signal among the N air pressure signals with the air pressure value of the n-th air pressure signal to determine the (n - 1)-th comparison result, where n is a positive integer greater than 1 and less than or equal to N; determine the first target time from the reception times of the N air pressure signals according to the N - 1 comparison results; when the n-th comparison result indicates that the air pressure value of the (n + 1)-th air pressure signal is greater than the air pressure value of the n-th air pressure signal, determine the reception time of the (n + 1)-th air pressure signal as the first target time; determine a target air pressure signal from the N air pressure signals according to the air pressure values of the N air pressure signals; the internal air pressure of the cylinder corresponding to the target air pressure signal meets a predetermined condition; determine the reception time of the target air pressure signal as the second target time.

[0009] According to an embodiment of the present disclosure, the operation of the first solenoid valve further includes a closing operation; the actual performance index information further includes the actual gas leakage; when the first solenoid valve is already closed: the sensor is further configured to collect J air pressure signals within a predetermined time period, where J is an integer greater than 1; the processor is further configured to determine the actual gas leakage of the first solenoid valve according to the air pressure difference between the air pressure value of the first air pressure signal and the air pressure value of the J-th air pressure signal among the J air pressure signals.

[0010] According to an embodiment of the present disclosure, the sensor is further configured to generate an air pressure signal in the form of an electrical signal according to the internal air pressure of the cylinder; the processor is further configured to: perform smoothing filtering on the air pressure signal to obtain a filtered air pressure signal; determine the actual performance index information of the first solenoid valve according to the filtered air pressure signal.

[0011] Another aspect of the present disclosure provides a fault prediction method, including: when a first solenoid valve disposed at an air vent of a cylinder of a train operates, generating a pressure signal according to the air pressure on the side of the first solenoid valve close to the air vent; the air vent is used to transmit the gas from the gas source into the cylinder so that the internal air pressure of the cylinder meets a predetermined condition; determining the actual performance index information of the first solenoid valve according to the pressure signal; determining the number of operations completed by the first solenoid valve, and determining the ideal performance index information according to the number of operations; and generating a fault prediction result of the first solenoid valve according to the ideal performance index information and the actual performance index information.

[0012] Another aspect of the present disclosure provides a train, including a cylinder, a gas source, a gas transmission channel connecting the gas source and the cylinder, and a solenoid valve disposed in the gas transmission channel; and any one of the above-mentioned fault prediction devices.

[0013] Another aspect of the present disclosure provides an electronic device, including: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method as described above.

[0014] According to an embodiment of the present disclosure, when the solenoid valve operates, the sensor collects the air pressure inside the cylinder and generates a pressure signal. The processor can determine the actual performance index information of the first solenoid valve according to the pressure signal, and then determine the ideal performance index information of the first solenoid valve under ideal conditions according to the number of operations completed by the first solenoid valve, so that it is possible to determine whether the first solenoid valve has a potential fault risk according to the ideal performance index information and the actual performance index information, realizing accurate fault prediction of the solenoid valve. In addition, the fault detection device based on the processor and the sensor has a high degree of intelligence, is easy to carry, and can be integrated into the solenoid valve performance inspection platform. Description of the Drawings

[0015] Through the following description of the embodiments of the present disclosure with reference to the drawings, the above and other objects, features and advantages of the present disclosure will become clearer. In the drawings:

[0016] Figure 1 Schematically shows a schematic diagram of a fault prediction device according to an embodiment of the present disclosure.

[0017] Figure 2 Schematically shows a flowchart of a method for determining actual performance index information according to an embodiment of the present disclosure.

[0018] Figure 3 Schematically shows a schematic diagram of determining difference information according to an embodiment of the present disclosure.

[0019] Figure 4A schematic diagram of a fault prediction device according to another embodiment of the present disclosure is shown.

[0020] Figure 5 A schematic diagram of a fault prediction method according to an embodiment of the present disclosure is shown.

[0021] Figure 6 A schematic diagram of a train according to an embodiment of the present disclosure is shown.

[0022] Figure 7 A block diagram of an electronic device suitable for implementing the fault prediction method according to an embodiment of the present disclosure is shown. Detailed implementation manners

[0023] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the following detailed description, for the sake of explanation, many specific details are set forth in order to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is obvious that one or more embodiments can also be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily obscuring the concepts of the present disclosure.

[0024] The terms used herein are merely for describing specific embodiments and are not intended to limit the present disclosure. The terms "including", "comprising" and the like used herein indicate the presence of the described features, steps, operations and / or components, but do not exclude the presence or addition of one or more other features, steps, operations or components.

[0025] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0026] In the case of using expressions such as "at least one of A, B, and C", generally, it should be interpreted according to the meaning commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but not be limited to a system having only A, having only B, having only C, having A and B, having A and C, having B and C, and / or having A, B, and C).

[0027] In the embodiments of the present disclosure, in aspects such as the collection, update, analysis, processing, use, transmission, provision, disclosure, storage, etc. of the involved data (for example, including but not limited to user personal information), it complies with the provisions of relevant laws and regulations, is used for legal purposes, and does not violate public order and good customs. In particular, necessary measures are taken for user personal information to prevent illegal access to user personal information data and to safeguard user personal information security, network security, and national security.

[0028] In the embodiments of the present disclosure, before obtaining or collecting user personal information, the authorization or consent of the user is obtained.

[0029] In the process of implementing the inventive concept of the present disclosure, the inventors found that some fault prediction devices can only complete basic fault detection and it is difficult to accurately predict the potential fault risks of solenoid valves. In view of this, the embodiments of the present disclosure provide a fault prediction device that can accurately predict the potential fault risks of solenoid valves.

[0030] Figure 1 A schematic diagram of a fault prediction device according to an embodiment of the present disclosure is schematically shown.

[0031] As Figure 1 shown, the fault prediction device 100 of this embodiment includes a connected sensor 110 and a processor 120. For example, the sensor 110 and the processor 120 can be electrically connected or communicatively connected. For example, the processor 120 can be a terminal device, etc., which is not limited herein.

[0032] In the embodiments of the present disclosure, the fault prediction device 100 can be arranged on a train. The cylinder 130 of the train is provided with a ventilation port. The ventilation port of the train is connected to a gas source 150 via a gas transmission channel. The ventilation port can transmit the gas from the train gas source 150 into the cylinder 130 to increase the air pressure in the cylinder 130, so that the internal air pressure of the cylinder 130 can meet a predetermined condition. For example, when the air pressure value inside the cylinder 130 is greater than or equal to a predetermined air pressure value, it can be determined that the internal air pressure of the cylinder 130 meets the predetermined condition. For example, the cylinder 130 can be a pneumatic buffer cylinder 130, etc., which is not limited in the present disclosure.

[0033] A first solenoid valve 140 can be arranged at the ventilation port (for example, on the side of the ventilation port facing outside the cylinder 130). The first solenoid valve 140 can control the opening and closing of the ventilation port. The above-mentioned sensor 110 can be arranged inside the cylinder 130, for example, at positions around the ventilation port and other positions where the air pressure inside the cylinder 130 can be detected. For example, the sensor 110 can be a pressure sensor.

[0034] When the first solenoid valve 140 operates, the sensor 110 can generate a pressure signal based on the air pressure on the side of the solenoid valve 140 close to the air vent (e.g., the air pressure in the cylinder 130), and send the pressure signal to the processor 120. For example, the operation of the solenoid valve 140 can include an opening operation and a closing operation. The pressure signal represents the air pressure value inside the cylinder 130.

[0035] The processor 120 can receive the pressure signal and determine the actual performance index information of the first solenoid valve 140 based on the pressure signal. For example, the actual performance index information represents the performance of the solenoid valve. For example, the performance index information of the solenoid valve can include response duration information and gas leakage amount, etc. The response duration information can refer to the duration from when the valve core of the solenoid valve starts to move until the air pressure value rises to a predetermined air pressure value. During this period, the air pressure system of the train may be preparing to complete a certain operation or waiting for the response of other components to start the next working cycle. The gas leakage amount can refer to the amount of gas leaking through the valve under the condition of no gas flow (e.g., the solenoid valve is closed). The gas leakage amount can be used as an index to evaluate the performance of the solenoid valve. For example, when the air pressure value in the cylinder 130 drops by 5 mL of gas volume within 1 minute, it can be determined that there is a fault in the solenoid valve.

[0036] In addition, the processor 120 can also determine the number of operations completed by the first solenoid valve 140. For example, when the change amount of the air pressure value of the pressure signal is greater than or equal to the change amount threshold, it can be determined that the first solenoid valve 140 has completed one operation, and this operation can be counted, so that the number of operations completed by the first solenoid valve 140 can be obtained. It should be understood that whether the solenoid valve performs an opening operation or a closing operation, this operation needs to be counted.

[0037] After determining the number of operations of the first solenoid valve 140, the processor 120 can also determine the ideal performance index information based on the number of operations. For example, an association relationship between the number of operations and the ideal performance index information of the solenoid valve can be constructed in advance based on the number of operations and the performance index information of a second solenoid valve different from the first solenoid valve, and then this association relationship can be used to determine the ideal performance index information corresponding to this number of operations according to the number of operations of the first solenoid valve 140. The ideal performance index information can refer to the performance index information that a normal solenoid valve should have after the above number of operations. A normal solenoid valve refers to a solenoid valve without potential fault risks.

[0038] The processor 120 may generate a fault prediction result of the first solenoid valve 140 based on the ideal performance index information and the actual performance index information. For example, the processor 120 may compare the ideal performance index information and the actual performance index information of the same type to obtain a comparison result, and then generate a fault prediction result of the first solenoid valve 140 based on the comparison result. For example, the ideal performance index information may include an ideal response duration and an ideal gas leakage amount. The ideal response duration may be compared with the actual response duration to obtain a comparison result. The ideal gas leakage amount may also be compared with the actual gas leakage amount to obtain a comparison result.

[0039] When the comparison result indicates that the difference between the ideal performance index information and the actual performance index information is greater than or equal to a predetermined difference, a fault prediction result indicating that there is a fault risk in the first solenoid valve 140 may be generated; when the comparison result indicates that the difference between the ideal performance index information and the actual performance index information is less than the predetermined difference, a fault prediction result indicating that there is no fault risk in the first solenoid valve 140 may be generated.

[0040] According to an embodiment of the present disclosure, when the solenoid valve is actuated, the sensor 110 collects the air pressure inside the cylinder 130 and generates an air pressure signal. The processor 120 may determine the actual performance index information of the first solenoid valve 140 according to the air pressure signal, and then determine the ideal performance index information of the first solenoid valve 140 under ideal conditions according to the number of completed actions of the first solenoid valve 140, so that it is possible to determine whether the first solenoid valve 140 has a potential fault risk according to the ideal performance index information and the actual performance index information, realizing accurate fault prediction of the solenoid valve. In addition, the fault detection device based on the processor 120 and the sensor 110 has a high degree of intelligence, is easy to carry, and can be integrated into the solenoid valve performance inspection platform.

[0041] Figure 2 A flowchart of a method for determining actual performance index information according to an embodiment of the present disclosure is schematically shown.

[0042] As Figure 2 shown, the method for determining actual performance index information in this embodiment includes operations S210 to S220.

[0043] In operation S210, the sensor generates an air pressure signal in the form of an electrical signal according to the air pressure inside the cylinder.

[0044] In operation S220, the processor performs smoothing filtering on the air pressure signal to obtain a filtered air pressure signal.

[0045] In operation S230, the processor determines the actual performance index information of the first solenoid valve according to the filtered air pressure signal.

[0046] In an embodiment of the present disclosure, the sensor may also generate a pressure signal in the form of an electrical signal according to the air pressure inside the cylinder and send the pressure signal to the processor. The processor may also receive the pressure signal and perform smoothing filtering on the pressure signal to obtain a filtered pressure signal. For example, the processor may perform smoothing filtering on the pressure signal by using a filtering algorithm based on moving average to obtain a filtered pressure signal. For example, the algorithm may be an SG (Savitzky Golay Filter) filtering algorithm or the like.

[0047] The processor may also determine the actual performance index information of the first solenoid valve according to the filtered pressure signal. For example, according to the filtered pressure signal, the pressure change amount and the pressure change duration within a predetermined period in the cylinder may be determined. Then, according to the pressure change duration, the response duration information of the first solenoid valve may be determined. Also, according to the pressure change amount in the cylinder, the gas leakage amount of the first solenoid valve may be determined. Thus, the response duration information and the opening duration information of the first solenoid valve are obtained.

[0048] In actual situations, the pressure signal may be subject to various interferences. For example, all circuits and devices other than the sensor may be regarded as a dynamic system, and this dynamic system will generate process noises including power supply interference, signal line interference, equipment vibration interference, etc. Due to issues such as accuracy, the sensor itself will generate measurement noises during the process of collecting data. These two types of noises will reduce the accuracy of the collected pressure signal. Thus, by using the method of smoothing filtering, the present disclosure can improve the accuracy of the collected pressure signal, thereby improving the accuracy of the performance index information, and further improving the accuracy of the generated fault prediction result.

[0049] According to an embodiment of the present disclosure, the processor may also process the number of actions by using a predetermined relationship model to obtain ideal performance index information. The predetermined correlation relationship represents the relationship between the number of actions of the solenoid valve and the performance index information of the solenoid valve. For example, the predetermined correlation relationship may include a relationship curve. For example, the relationship curve may be obtained by fitting according to the number of actions and the performance index information of multiple second solenoid valves by using a regression method.

[0050] The processor may determine the difference information between the ideal performance index information and the actual performance index information, and generate a fault prediction result of the first solenoid valve according to the difference information. For example, the ideal performance index information may be the ideal response duration information and the ideal gas leakage amount information of the solenoid valve, etc.

[0051] Figure 3 Schematically shows a schematic diagram of determining the difference information according to an embodiment of the present disclosure.

[0052] As Figure 3As shown, the number of operations 310 of the second solenoid valve and the performance index information 320 of the second solenoid valve under each operation can be obtained. Then, according to the number of operations 310 of the second solenoid valve and the performance index information 320 of the second solenoid valve, a relationship curve of the second solenoid valve is obtained by fitting. In this curve, the number of operations can be the abscissa, and the performance index information can be the ordinate. For example, the response duration or the gas leakage amount can be the ordinate. Thus, a curve library can be constructed according to the relationship curves of multiple second solenoid valves. The multiple second solenoid valves can include solenoid valves with potential failure risks and can also include solenoid valves without potential failure risks. The ideal performance index information corresponding to the number of operations 330 can be queried from the curve library according to the number of operations 330 of the first solenoid valve. For example, according to the number of operations 330 of the first solenoid valve, the performance index information of multiple curves at this number of operations can be queried from the curve library. The ideal performance index information can be determined according to the average value of the performance index information of the multiple curves. It should be understood that the performance index information calculated here is the same type of performance index information. The process of calculating the performance index information in other embodiments of the present disclosure is the same, and the present disclosure will not be elaborated.

[0053] Thus, the difference information between the ideal performance index information and the actual performance index information can be determined, and thus a fault prediction result of the first solenoid valve can be generated according to the difference information. For example, the duration difference information can be obtained as the above difference information according to the difference between the ideal response duration information and the actual response duration information. The leakage amount difference can also be obtained as the above difference information according to the difference between the ideal gas leakage amount and the actual gas leakage amount. For example, in the case where at least one of the above two difference information is greater than or equal to a predetermined difference, a fault prediction result indicating that the first solenoid valve has a potential failure risk can be generated; in the case where both of the above two difference information are less than the predetermined difference, a fault prediction result indicating that the first solenoid valve has no potential failure risk can be generated.

[0054] According to an embodiment of the present disclosure, by using a pre-constructed predetermined association relationship to determine the ideal performance index information corresponding to the number of operations, the efficiency and accuracy of determining the ideal performance index information are improved, and thus a fault detection result is generated according to the difference information between the ideal performance index information and the actual performance index information, improving the accuracy and generation efficiency of the fault detection result.

[0055] According to an embodiment of the present disclosure, the processor can also obtain the type information of the first solenoid valve and the usage duration information of the first solenoid valve. For example, the type information of the first solenoid valve can include the model information of the first solenoid valve, etc. The usage duration information of the first solenoid valve represents the duration for which the first solenoid valve has been used. For example, the usage duration information of the first solenoid valve can be determined based on the difference between the moment of the first operation of the first solenoid valve and the current moment.

[0056] The processor can also generate a fault prediction result for the first solenoid valve based on the type information, usage duration information, and difference information. For example, when at least one of the following conditions is met: the difference information is greater than or equal to a predetermined threshold, the type information indicates that the first solenoid valve is a target type with a high risk of failure, and the usage duration is greater than or equal to a predetermined duration, a fault prediction result indicating that the first solenoid valve has a potential fault risk is generated. Otherwise, a fault prediction result indicating that the first solenoid valve has no potential fault risk can be generated. In the embodiments of the present disclosure, the fault prediction result can be displayed on a display electrically connected or communicatively connected to the processor, and the type information and usage duration information of the first solenoid valve can also be selectively displayed together.

[0057] According to an embodiment of the present disclosure, by generating the fault prediction result of the first solenoid valve based on the combination of the type information, usage duration information, and difference information, the accuracy of the fault prediction result is improved.

[0058] According to an embodiment of the present disclosure, when the first solenoid valve performs an opening action, the processor can: receive N air pressure signals from a sensor and determine the receiving times of the N air pressure signals, where N is an integer greater than 1. Then, based on the air pressure values of the N air pressure signals, a first target time and a second target time are determined from the receiving times of the N air pressure signals. Among them, the first target time represents the time when the cylinder starts to receive gas. The second target time represents the time when the internal air pressure of the cylinder meets a predetermined condition. For example, when the air pressure value of the air pressure signal suddenly rises after maintaining a certain fixed value for a certain period of time, the initial time of the rising process can be determined as the first target time. When the air pressure value of the air pressure signal rises to a predetermined air pressure value, the time when the air pressure value rises to the predetermined air pressure value can be determined as the second target time. The processor can also generate the actual response duration of the first solenoid valve based on the first target time and the second target time.

[0059] According to an embodiment of the present disclosure, when the first solenoid valve performs an opening operation, the processor determines the first target time and the second target time based on the receiving times of the air pressure signals of the receiving cylinder, so that based on the first target time and the second target time, an accurate response duration of the first solenoid valve can be generated.

[0060] According to an embodiment of the present disclosure, the processor can also compare the air pressure value of the (n - 1)-th air pressure signal and the air pressure value of the n-th air pressure signal among the N air pressure signals to determine the (n - 1)-th comparison result, where n is a positive integer greater than 1 and less than or equal to N. For example, the generated comparison result can be a result indicating that the air pressure value of the n-th air pressure signal is greater than the air pressure value of the (n - 1)-th air pressure signal, or a result indicating that the air pressure value of the n-th air pressure signal is less than or equal to the air pressure value of the (n - 1)-th air pressure signal.

[0061] The processor can also determine the first target moment from the receiving moments of the N pneumatic signals according to the N - 1 comparison results. For example, since the pneumatic signal continuously rises after the solenoid valve is opened, the processor can determine a plurality of consecutive candidate moments after comparing the pneumatic values of adjacent pneumatic signals one by one. These multiple candidate moments correspond to pneumatic values that rise in sequence. Thus, the candidate moment at the earliest time among the multiple candidate moments can be determined as the first target moment.

[0062] The processor can also determine a target pneumatic signal from the N pneumatic signals according to the pneumatic values of the N pneumatic signals, and determine the receiving moment of the target pneumatic signal as the second target moment. Wherein, the internal air pressure of the cylinder corresponding to the target pneumatic signal meets a predetermined condition. For example, when the pneumatic value of the target pneumatic signal is equal to a predetermined pneumatic value, the internal air pressure of the cylinder corresponding to the target pneumatic signal meets the predetermined condition.

[0063] According to an embodiment of the present disclosure, by comparing the N pneumatic signals one by one, an accurate first target moment can be determined. And, by according to the pneumatic values of the N pneumatic signals, an accurate second target moment can be determined, so that the accuracy of the response duration of the generated first solenoid valve can be improved.

[0064] According to an embodiment of the present disclosure, when the first solenoid valve is already closed, the sensor can also collect J pneumatic signals within a predetermined time period and send the J pneumatic signals to the processor, where J is an integer greater than 1. The processor can also determine the actual gas leakage amount of the first solenoid valve according to the pneumatic pressure difference between the pneumatic value of the first pneumatic signal and the pneumatic value of the Jth pneumatic signal among the J pneumatic signals. For example, the actual gas leakage amount of the first solenoid valve can be determined according to this pneumatic pressure difference and the duration of the predetermined time period.

[0065] According to an embodiment of the present disclosure, when the solenoid valve is closed, by according to the pneumatic pressure difference between the pneumatic value of the first pneumatic signal and the pneumatic value of the Jth pneumatic signal among the J pneumatic signals collected within the predetermined time period, the actual gas leakage amount of the accurate first solenoid valve can be determined.

[0066] Figure 4 Schematically shows a schematic diagram of a fault prediction device according to another embodiment of the present disclosure.

[0067] As Figure 4As shown in the figure, in addition to the processor and sensors, the fault detection device of the present disclosure may further include a logic control development board, a relay, a 110V power supply, a 5V power supply, a data acquisition card, and so on. For example, the logic control development board may execute corresponding control logic according to a predetermined algorithm, output a control signal to the relay, and then accurately control the energization time and operating frequency of the solenoid valve. The relay may convert a low-power signal into a high-power signal under the control of an instruction from the development board, and then control the opening and closing operations of the solenoid valve circuit loop. The 110V power supply may output a stable 110V DC voltage based on an alternating current of 220V (volts), supply the solenoid valve, the sensor, and the relay loop, and provide operating voltage for each device. The 5V power supply may output a stable 5V voltage based on the 110V DC voltage output by the 110V power supply and provide operating voltage for the logic control development board. The constant-pressure gas source may transmit gas to the cylinder via a first-stage pressure regulating valve, a balanced pressure gas tank, a second-stage pressure regulating valve, and the solenoid valve. In this way, the gas sensor may collect the air pressure signal. The data acquisition card receives the air pressure signal of 10k / s from the gas sensor and sends the air pressure signal to the processor for fault prediction. In addition, the device may further include an air pump, which may be used for airtightness detection.

[0068] Figure 5 Schematically shows a schematic diagram of a fault prediction method according to an embodiment of the present disclosure.

[0069] As Figure 5 shown, the fault prediction method of this embodiment includes operations S510 to S550.

[0070] In operation S510, when the first solenoid valve at the air vent of the cylinder provided on the train operates, an air pressure signal is generated according to the air pressure inside the cylinder.

[0071] In operation S520, according to the air pressure signal, the actual performance index information of the first solenoid valve is determined.

[0072] In operation S530, the number of completed operations of the first solenoid valve is determined.

[0073] In operation S540, according to the number of operations, the ideal performance index information is determined.

[0074] In operation S550, according to the ideal performance index information and the actual performance index information, a fault prediction result of the first solenoid valve is generated.

[0075] It should be noted that the part of the fault prediction method in the embodiment of the present disclosure corresponds to the part of the fault prediction device in the embodiment of the present disclosure. The description of the fault prediction device part details the fault prediction method part, which will not be repeated here.

[0076] Figure 6A schematic diagram showing a train according to an embodiment of the present disclosure is schematically illustrated.

[0077] As Figure 6 shown, a fault prediction device 610 may be deployed on the train 600. The fault prediction device 610 may be any of the fault prediction devices described above. In addition, the fault prediction device may further include a cylinder, a gas source, a gas transmission channel connecting the gas source and the cylinder, and a solenoid valve provided in the gas transmission channel, etc., which are not shown in Figure 6 the figure.

[0078] Figure 7 A block diagram of an electronic device suitable for implementing the fault prediction method according to an embodiment of the present disclosure is schematically illustrated. Figure 7 The electronic device shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present disclosure.

[0079] As Figure 7 shown, the electronic device 700 according to an embodiment of the present disclosure includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage section 708 into a random access memory (RAM) 703. The processor 701 may include, for example, a general microprocessor (such as a CPU), an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (such as an application specific integrated circuit (ASIC)), etc. The processor 701 may also include on-board memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0080] In the RAM 703, various programs and data required for the operation of the electronic device 700 are stored. The processor 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. The processor 701 performs various operations of the method flow according to an embodiment of the present disclosure by executing the programs in the ROM 702 and / or the RAM 703. It should be noted that the programs may also be stored in one or more memories other than the ROM 702 and the RAM 703. The processor 701 may also perform various operations of the method flow according to an embodiment of the present disclosure by executing the programs stored in the one or more memories.

[0081] According to an embodiment of the present disclosure, the electronic device 700 may further include an input / output (I / O) interface 705, and the input / output (I / O) interface 705 is also connected to the bus 704. The electronic device 700 may further include one or more of the following components connected to the input / output (I / O) interface 705: an input portion 706 including a keyboard, a mouse, etc.; an output portion 707 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage portion 708 including a hard disk, etc.; and a communication portion 709 including a network interface card such as a LAN card, a modem, etc. The communication portion 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the input / output (I / O) interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed so that a computer program read from it can be installed into the storage portion 708 as needed.

[0082] According to an embodiment of the present disclosure, the method flow according to the embodiment of the present disclosure may be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program includes program codes for executing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 709, and / or installed from the removable medium 711. When the computer program is executed by the processor 701, the above functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the above-described system, device, apparatus, module, unit, etc. may be implemented by computer program modules.

[0083] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist separately without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0084] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include but is not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0085] For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include one or more memories other than the above-described ROM 702 and / or RAM 703 and / or ROM 702 and RAM 703.

[0086] Embodiments of the present disclosure also include a computer program product, which includes a computer program. The computer program contains program code for executing the method provided by the embodiments of the present disclosure. When the computer program product runs on an electronic device, the program code is used to cause the electronic device to implement the fault prediction method provided by the embodiments of the present disclosure.

[0087] When the computer program is executed by the processor 701, the above functions defined in the system / apparatus of the embodiments of the present disclosure are executed. According to an embodiment of the present disclosure, the above-described systems, apparatuses, modules, units, etc. may be implemented by computer program modules.

[0088] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices and magnetic storage devices. In another embodiment, the computer program may also be transmitted and distributed in the form of a signal on a network medium, and be downloaded and installed through the communication part 709, and / or be installed from the removable medium 711. The program code contained in the computer program may be transmitted by any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0089] According to embodiments of the present disclosure, program code for executing the computer programs provided by the embodiments of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. The programming languages include, but are not limited to, programming languages such as Java, C++, Python, the "C" language, or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (for example, by using an Internet service provider to connect through the Internet).

[0090] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and combinations of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions. Those skilled in the art can understand that the features described in various embodiments of the present disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present disclosure. In particular, without departing from the spirit and teachings of the present disclosure, the features described in various embodiments of the present disclosure can be combined and / or combined in various ways. All such combinations and / or combinations fall within the scope of the present disclosure.

[0091] The above describes the embodiments of the present disclosure. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in each embodiment cannot be used advantageously in combination. Without departing from the scope of the present disclosure, those skilled in the art can make various substitutions and modifications, and all such substitutions and modifications should fall within the scope of the present disclosure.

Claims

1. A fault prediction device, characterized in that: include: a sensor for generating a pressure signal according to the air pressure inside the cylinder when a first solenoid valve provided at an air vent of an air cylinder of the train is actuated; the air vent is used to transmit gas from an air source into the cylinder so that the internal air pressure of the cylinder meets a predetermined condition; A processor, connected to the sensor, configured to: Determining actual performance index information of the first solenoid valve according to the air pressure signal; Determining the number of actions that the first solenoid valve has completed, and determining ideal performance indicator information based on the number of actions; as well as A fault prediction result of the first solenoid valve is generated according to the ideal performance index information and the actual performance index information.

2. The fault prediction device according to claim 1, characterized in that: The processor is further configured to: The predetermined association relationship is used to process the number of actions to obtain the ideal performance index information; the predetermined association relationship represents the relationship between the number of actions of the solenoid valve and the performance index information of the solenoid valve; Determine difference information between the ideal performance indicator information and the actual performance indicator information; A fault prediction result of the first solenoid valve is generated according to the difference information.

3. The fault prediction device according to claim 2, characterized in that: The processor is further configured to: Acquire type information of the first solenoid valve and usage time information of the first solenoid valve; A fault prediction result of the first solenoid valve is generated according to the type information, the usage time information and the difference information.

4. The fault prediction device according to any one of claims 1 to 3, characterized in that: The action of the first solenoid valve includes an opening action; the actual performance index information includes an actual response time; The processor is further configured to: when the first solenoid valve is opened: receiving N air pressure signals from the sensor and determining the receiving time of the N air pressure signals, where N is an integer greater than 1; According to the air pressure values ​​of the N air pressure signals, determining a first target time and a second target time from the reception times of the N air pressure signals; the first target time represents the time when the cylinder starts to receive the gas; the second target time represents the time when the internal air pressure of the cylinder meets the predetermined condition; An actual response duration of the first solenoid valve is generated according to the first target time and the second target time.

5. The fault prediction device according to claim 4, characterized in that: The processor is further configured to: Compare the air pressure value of the n-1th air pressure signal among the N air pressure signals with the air pressure value of the nth air pressure signal to determine the n-1th comparison result, where n is a positive integer greater than 1 or less than or equal to N; Determine the first target time from the reception times of the N air pressure signals according to N-1 comparison results; Air pressure signal Air pressure signal Air pressure signal Determine a target air pressure signal from the N air pressure signals according to the air pressure values ​​of the N air pressure signals; The internal air pressure of the cylinder corresponding to the target air pressure signal satisfies the predetermined condition; The receiving time of the target air pressure signal is determined as the second target time.

6. The fault prediction device according to any one of claims 1 to 3, characterized in that: The action of the first solenoid valve also includes a closing action; the actual performance index information also includes an actual gas leakage amount; When the first solenoid valve is closed: The sensor is also used to collect J air pressure signals within a predetermined period of time, where J is an integer greater than 1; The processor is further configured to determine an actual gas leakage amount of the first solenoid valve according to a pressure difference between a pressure value of a first pressure signal and a pressure value of a Jth pressure signal among the J pressure signals.

7. The fault prediction device according to any one of claims 1 to 3, characterized in that: The sensor is also used to generate the air pressure signal in the form of an electrical signal according to the air pressure inside the cylinder; The processor is further configured to: Performing smoothing filtering on the air pressure signal to obtain a filtered air pressure signal; According to the filtered air pressure signal, actual performance index information of the first solenoid valve is determined.

8. A fault prediction method, characterized in that: include: When a first solenoid valve provided at a vent of an air cylinder of the train is actuated, an air pressure signal is generated according to the air pressure inside the air cylinder; The vent is used to transmit gas from a gas source into the cylinder so that the internal gas pressure of the cylinder meets a predetermined condition; Determining actual performance index information of the first solenoid valve according to the air pressure signal; Determining the number of actions that the first solenoid valve has completed, and determining ideal performance indicator information based on the number of actions; as well as A fault prediction result of the first solenoid valve is generated according to the ideal performance index information and the actual performance index information.

9. A train, characterized in that: It comprises a gas cylinder, a gas source, a gas transmission channel connecting the gas source and the gas cylinder, and a solenoid valve arranged in the gas transmission channel; and A fault prediction device according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method of claim 8.

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