CN109405889B - System and method for predicting fault of working arm reducer of heading machine - Google Patents
System and method for predicting fault of working arm reducer of heading machine Download PDFInfo
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Abstract
The invention discloses a system and a method for predicting the fault of a reducer of a working arm of a heading machine. The system realizes the monitoring of the state parameters and the prediction of potential faults of the working arm gear box of the development machine, the vehicle-mounted unit collects the using state parameters of the working arm gear box of the development machine in real time, the feature extraction and alarm judgment are carried out on the using state parameters, the alarm part is determined and the maintenance suggestion code is generated; and the ground system downloads the data acquired by the vehicle-mounted part, analyzes the data and realizes the prediction of potential faults and the positioning of sent faults of key components. The system and the method improve the economical efficiency and the safety of the operation of the heading machine.
Description
Technical Field
The invention relates to the field of fault prediction, in particular to a system and a method for predicting faults of a reducer of a working arm of a heading machine.
Background
The modern heading machine is an engineering device with a complex structure, and the structure of the modern heading machine is provided with a mechanical transmission part and automatic devices such as hydraulic and control circuits. The operation field of the development machine is usually positioned dozens of meters or even hundreds of meters below the ground, the temperature is high, the humidity is high, more stones fall, more dust is generated, explosive gas is often accompanied, and the working environment is very severe. The working task of the heading machine is mainly to open the working face in advance to realize path exploration for larger mining equipment or excavating equipment, taking the heading machine for coal mining as an example, the working period of the heading machine is usually as long as several months, the heading machine advances in a single direction until the end point, and the working environment and the working characteristics of the heading machine cause great economic loss and even cause safety accidents once the heading machine fails in the working process. The importance degree of the current society on safety production can be unprecedented, and how to ensure that the development machine does not have serious faults in the using process is ensured, so that the safety accident rate caused by equipment faults is reduced, and the development machine is the first problem to be considered in the automatic, information and intelligent design process of the development machine of the new generation.
The reducer of the heading machine is composed of a large number of shafts, bearings and gear transmission components in principle, corresponding use and maintenance instructions are provided for equipment when the equipment leaves a factory, and the traditional regular inspection and replacement operation is also provided for equipment maintenance except some simple fault removal methods. In addition, in a mine tunnel with poor operation conditions, an operator is often careless for equipment maintenance, and emergency measures for replacing parts are started until the mine tunnel is stopped due to failure, so that huge economic cost is often paid for recovering production as soon as possible. With the continuous deep understanding of failure laws of people and the wide application of the reliability theory in the maintenance field, a maintenance idea taking reliability as a center is gradually formed for the maintenance and the maintenance of the tunneling equipment, namely, the situation-based maintenance or the situation-based maintenance, which is a core performance improvement to be realized by the intelligent development of the tunneling machine. In order to realize the improvement of the intelligent level of the development machine, the use monitoring and the fault early warning are carried out on core components represented by a speed reducer, and the development machine becomes an engineering technical problem which is urgently needed to be solved by designers and users.
Disclosure of Invention
The invention aims to provide a system and a method for predicting the fault of a reducer of a working arm of a heading machine.
The technical scheme for solving the technical problem of the invention is as follows:
a system for predicting the fault of a reducer of a working arm of a heading machine comprises a vehicle-mounted part and a ground part;
the vehicle-mounted part comprises a vibration sensor, a rotating speed sensor, a temperature sensor, an angle sensor, a pressure sensor and a vehicle-mounted acquisition alarm device;
the vibration sensor is a three-axis vibration sensor, and the mounting position of the vibration sensor is arranged on the outer end face of the power input end of the working arm speed reducer;
the rotating speed sensor is an inductive eddy current type rotating speed sensor, the installation position of the rotating speed sensor is arranged on the outer end face of the power output end of the working arm motor, the signal transmitting end of the sensor is positioned right above the level of the coupler, and a steel tooth-shaped ring is adhered to the surface of the periphery of the coupler;
the temperature sensor is arranged on the left side of the horizontal bottom end of the working arm speed reducer, the sensor is in a thermocouple type, and a sensor probe extends into a speed reducer cavity and invades into lubricating oil;
the pressure sensor is arranged on the right side of the horizontal bottom end of the working arm speed reducer, and a sensor probe penetrates into a speed reducer cavity and invades into lubricating oil;
the angle sensor is arranged below the shell of the speed reducer;
the vehicle-mounted acquisition warning device is arranged behind the operator seat;
the vibration sensor, the rotating speed sensor, the temperature sensor and the angle sensor are communicated with corresponding interfaces on the vehicle-mounted acquisition warning device through sensor leads at respective positions;
the ground part comprises a quick access recording card and a ground data processing system;
the quick access record card receives the information recorded by the collector through the Ethernet;
and the ground data processing system reads the quick access record card information to obtain the data of the gearbox of the working arm of the heading machine, and generates a data report according to the processing and analyzing result.
The vehicle-mounted acquisition monitoring alarm device adopts a bottom plate slot type structure, and is provided with one power supply board, one signal conditioning board and one acquisition processing and monitoring alarm board; the power panel, the signal conditioning panel and the acquisition processing and monitoring alarm panel are sequentially arranged on the bottom plate slot, and the three panels realize power supply and signal transmission through the interfaces. The quick access recording card comprises a CF card and a solid state disk.
A method for predicting the fault of a reducer of a working arm of a heading machine comprises the following steps:
step 1, acquiring the vibration state of a speed reducer through a vibration sensor, acquiring the rotating speed parameter of an input shaft of the speed reducer through a rotating speed sensor, acquiring the swing angle of a working arm through an angle sensor, acquiring the oil pressure force of a cavity of the speed reducer through a pressure sensor, acquiring the oil temperature inside the speed reducer through a temperature sensor, and transmitting all signal parameters to a vehicle-mounted acquisition alarm device through cables;
step 2, the vehicle-mounted acquisition alarm device acquires, processes, analyzes and stores vibration, rotating speed, angle, pressure and temperature signals, and carries out overrun judgment to determine fault level and alarm output;
step 3, the quick access recording card receives the information stored by the vehicle-mounted acquisition alarm device;
and 4, the ground data processing system obtains sensor data acquired on the vehicle by reading the information of the quick access recording card, diagnoses the sent fault and analyzes the trend of the potential fault by using the original data directly output by the sensor, and generates a data report according to the processing result.
The processing method of the rotating speed parameter in the step 2 comprises the following steps:
step 1), carrying out voltage limiting and shaping processing on a rotating speed signal of an input shaft of the speed reducer by a signal conditioning board;
step 2) changing the differential voltage signal into a pulse signal;
and 3) calculating a speed value according to the tooth number of the gear ring and the number of pulses.
The method for processing and analyzing the vibration signal in the step 2 comprises the following steps:
step 1), noise reduction is carried out on the vibration signal by a signal conditioning board;
step 2), low-pass filtering is carried out;
step 3) performing time domain synchronous averaging;
step 4), extracting characteristic values;
and 5) carrying out alarm judgment and storage by the vehicle-mounted acquisition alarm device.
In the step 4), the extracted features comprise time domain features, frequency domain features and time-frequency domain features, and the time domain feature indexes comprise waveform indexes, pulse indexes, kurtosis indexes, margin indexes and peak-to-peak values; the frequency domain indexes comprise center-of-gravity frequency, mean square frequency, root-mean-square frequency, frequency variance and frequency standard deviation; the time-frequency domain features include wavelet energy spectra.
In the step 5), the vehicle-mounted acquisition alarm device performs alarm judgment including threshold generation and alarm processing judgment; generating a threshold value based on a statistical distribution method, and performing alarm judgment by adopting an overrun judgment method;
the alarm grades are divided into two types, the first-level alarm aims at slight faults, namely the fault does not have shutdown influence on the operation task on the day; the secondary alarm aims at serious faults, and the operation task is stopped after the faults occur; the threshold values used for generating the two alarms are different, the threshold value setting method used for the first-level alarm is a statistical distribution 3 sigma method, and the threshold value setting method used for the second-level alarm is a 5 sigma method or a 6 sigma method.
The method for measuring the temperature signal in the step 2 comprises the following steps:
step 1), noise reduction is carried out on the temperature signal by a signal conditioning board;
step 2) extracting characteristic values;
and 3) carrying out alarm judgment and storage by the vehicle-mounted acquisition alarm device.
The angle and pressure signal measuring method in the step 2 comprises the following steps:
step 1), carrying out noise reduction on angle and pressure signals by a signal conditioning board;
step 2) extracting characteristic values;
step 3) recording and storing the pressure value when the horizontal angle is 0 to +/-3 degrees;
step 4) converting the pressure value into an oil quantity value; calculating an oil quantity value according to a function formed by fitting an oil quantity-pressure curve in a static state of the gearbox;
and 5) performing alarm processing when the oil quantity value is lower than the minimum oil quantity requirement.
The fault diagnosis of step 4 includes: power spectral analysis, side-band analysis, cepstral analysis, as well as neural networks, expert systems, deep learning methods.
The trend analysis method of the step 4 comprises the following steps: time series, support vector machines, gaussian mixture models, hidden markov models, deep learning methods.
In step 4, the process flow of the potential fault is as follows: the transmitted state parameter information is input into a trend analysis model or a prediction model, and the health state of the speed reducer is evaluated by combining historical detection maintenance data and historical state parameter information of the speed reducer, so that the prediction of typical faults is realized; when the potential fault information exists in the speed reducer, the ground software determines the hazard level of the potential fault and generates corresponding maintenance suggestions at the same time.
Compared with the prior art, the invention has the following remarkable advantages: the invention only carries out fault alarm on site, realizes fault diagnosis and fault prediction through ground software, completes most of work on the ground, reduces the condition requirements on the operation site and the configuration requirements on the acquisition alarm device, and has wide application range for most of the mine tunnel environments in China at present. Compared with the traditional heading machine, the novel heading machine avoids the typical fault without foreboding, reduces the unplanned maintenance time and unnecessary emergency cost, and improves the operation production efficiency and the operation production safety.
Drawings
Fig. 1 is a schematic diagram of a fault prediction system for a working arm reducer of a heading machine.
Fig. 2 is a flow chart of the fault prediction method of the heading machine working arm reducer.
Detailed Description
The invention relates to a system for predicting the fault of a reducer of a working arm of a heading machine, which takes the reducer of the heading machine as an object, and elaborates the implementation mode of online monitoring and alarming and the detailed flow of realizing fault early warning. The system consists of a vehicle-mounted part and a ground part. The vehicle-mounted part comprises a vibration sensor, a rotating speed sensor, a temperature sensor, an angle sensor, a pressure sensor and a vehicle-mounted acquisition alarm device. The vehicle-mounted acquisition warning device is composed of a data processing module and sensor nodes. The system is based on the mature development of an information processing technology, a set of monitoring and early warning system for the use state of the speed reducer of the heading machine is constructed, the running state of a gear and a bearing of the speed reducer is monitored in real time, off-line fault diagnosis is realized, fault prediction is realized for a core assembly, serious safety accidents and great economic losses caused by further fault occurrence are avoided, the intelligent level of the heading machine is improved, and the transition from the original traditional timing maintenance to the visual maintenance of the heading engineering equipment is supported.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
The invention discloses a method for predicting the fault of a working arm reducer of a heading machine, which comprises the following steps:
s1: the acquisition alarm device and the vehicle-mounted motor control unit realize data transmission of the encoder through an SSI bus, and realize alarm signal transmission through a CAN bus or a 485 serial port.
S2: the acquisition warning device stores and analyzes and processes data transmitted by all the sensors in real time, and judges the current running state of the speed reducer.
When the state parameter information of the speed reducer is in an abnormal state, the acquisition warning device determines the fault grade level according to the abnormal state information, and then transmits the fault abnormal information to the warning device in a discrete quantity mode.
When the speed reducer state parameter information is in a normal state, the acquisition warning device stores the speed reducer state parameter information and the normal state information in the data cache card according to a preset data storage mode. Then, the potential fault of the speed reducer is predicted through ground software by manually copying the potential fault to a ground data station.
Furthermore, the acquisition and alarm device is composed of a miniature minimum single chip microcomputer system and mainly realizes acquisition and processing of sensor data.
Further, the state parameter information collected by the sensor in the step S2 includes a vibration parameter, a rotation speed parameter, a temperature parameter, an angle parameter, and a pressure parameter of the speed reducer.
Further, the information interaction between the alarm device and the ground data station in step S2 is implemented by manual copying, but not by the only way, and if the operation condition allows, the transmission may be implemented by wire communication or wireless communication.
Further, the ground data station and the software in the step S2 mainly have the functions of storing the operation data of the heading machine speed reducer to the local, extracting the characteristics of the obtained data, inputting the extracted data to the fault prediction model, generating a prediction result, and giving a corresponding maintenance suggestion for an abnormal result.
Examples
As shown in fig. 1, the system for predicting the fault of the reducer of the working arm of the heading machine in the invention comprises a vehicle-mounted part (a vehicle-mounted acquisition alarm processing device, a sensor and a quick access card) and a ground part (a ground data hard disk and ground data processing software).
As shown in fig. 2, the embodiment of the method of the present invention based on the system structure comprises the following steps:
s1: the vehicle-mounted acquisition alarm processing device acquires data for 50 hours in advance, stores the data in a ground data station, and generates an initial threshold value by using data processing software, wherein the threshold value is updated every 500 hours later.
S2: the vehicle-mounted acquisition alarm processing device analyzes and processes the state parameter information transmitted by the sensor in real time and judges whether the health characteristics of the current speed reducer exceed the standard or not.
When the health characteristics of the speed reducer are abnormal, the vehicle-mounted acquisition alarm processing device determines the fault grade level according to the abnormal state information, then the vehicle-mounted alarm outputs the alarm discrete quantity, and the alarm discrete quantity is stored in the quick access card and transmitted to the ground system.
When the health characteristics of the speed reducer are in a normal state, the vehicle-mounted acquisition alarm processing device stores the state parameter information and the normal state information of the speed reducer in the quick access card and transmits the state parameter information and the normal state information to the ground system. Then, the ground analysis processing software adopts a prediction method preset in advance to predict the potential fault of the speed reducer.
In the specific implementation process, the data acquisition warning device is composed of a miniature minimum single chip microcomputer system, and is mainly used for processing data acquired by a sensor and converting the data into digital signals, carrying out abnormity judgment based on a system stability control theory, storing results in a quick access card and generating warning discrete quantities.
Further, the state parameter information collected by the sensor in the step S2 includes a vibration parameter, a rotation speed parameter, a temperature parameter, an angle parameter, and a pressure parameter of the speed reducer.
Further, the information interaction between the alarm device and the ground data station in step S2 is implemented by manual copying, but not by the only way, and if the operation condition allows, the transmission may be implemented by wire communication or wireless communication.
Further, the faults in the step S2 are divided into two stages, the first-stage fault is a slight fault, and the occurrence of the fault does not have a shutdown effect on the operation task on the same day; the secondary fault is a serious fault, and after the fault occurs, the task of the operation is stopped, and worse results are caused.
Further, the specific content of the potential fault pre-determination mechanism in step S2 is:
and inputting the transmitted state parameter information into a speed reducer health prediction model, and evaluating the health state of the speed reducer by combining historical detection maintenance data and historical state parameter information of the speed reducer to realize the prediction of typical faults. When the latent fault information exists in the speed reducer, the ground software determines the grade of the latent fault and generates corresponding maintenance suggestions.
Further, the ground data station and the software in the step S2 mainly have the functions of storing the operation data of the heading machine speed reducer to the local, extracting the characteristics of the obtained data, inputting the extracted data to the fault prediction model, generating a prediction result, and giving a corresponding maintenance suggestion for an abnormal result.
Claims (9)
1. The utility model provides a system for be used for entry driving machine work arm reduction gear trouble prediction which characterized in that: comprises a vehicle-mounted part and a ground part;
the vehicle-mounted part comprises a vibration sensor, a rotating speed sensor, a temperature sensor, an angle sensor, a pressure sensor and a vehicle-mounted acquisition alarm device;
the vibration sensor is a three-axis vibration sensor, and the mounting position of the vibration sensor is arranged on the outer end face of the power input end of the working arm speed reducer;
the rotating speed sensor is an inductive eddy current type rotating speed sensor, the installation position of the rotating speed sensor is arranged on the outer end face of the power output end of the working arm motor, the signal transmitting end of the sensor is positioned right above the level of the coupler, and a steel tooth-shaped ring is adhered to the surface of the periphery of the coupler;
the temperature sensor is arranged on the left side of the horizontal bottom end of the working arm speed reducer, the sensor is in a thermocouple type, and a sensor probe extends into a speed reducer cavity and invades into lubricating oil;
the pressure sensor is arranged on the right side of the horizontal bottom end of the working arm speed reducer, and a sensor probe penetrates into a speed reducer cavity and invades into lubricating oil;
the angle sensor is arranged below the shell of the speed reducer; when the horizontal angle is 0 to +/-3 degrees, recording and storing the pressure value at the moment;
the vehicle-mounted acquisition warning device is arranged behind the operator seat; collecting, processing, analyzing and storing vibration, rotating speed, angle, pressure and temperature signals, and carrying out overrun judgment to determine fault level and alarm output; the vehicle-mounted acquisition alarm device converts the pressure value into an oil quantity value, calculates the oil quantity value according to a function formed by fitting an oil quantity-pressure curve when the gearbox is static, and performs alarm processing when the oil quantity value is lower than the minimum requirement of the oil quantity;
the vibration sensor, the rotating speed sensor, the temperature sensor and the angle sensor are communicated with corresponding interfaces on the vehicle-mounted acquisition warning device through sensor leads at respective positions;
the vehicle-mounted acquisition alarm device performs alarm judgment including threshold generation and alarm processing judgment; generating a threshold value based on a statistical distribution method, and performing alarm judgment by adopting an overrun judgment method; the alarm grades are divided into two types, the first-level alarm aims at slight faults, namely the fault does not have shutdown influence on the operation task on the day; the secondary alarm aims at serious faults, and the operation task is stopped after the faults occur; the threshold values used for generating two alarms are different, the threshold value setting method used for the first-level alarm is a statistical distribution 3 sigma method, and the threshold value setting method used for the second-level alarm is a 5 sigma method or a 6 sigma method; "
The vehicle-mounted acquisition alarm processing device acquires data for 50 hours in advance, stores the data in a ground data station, and generates an initial threshold value by using data processing software, wherein the threshold value is updated every 500 hours later;
the ground part comprises a quick access recording card and a ground data processing system;
the quick access recording card receives the information acquired by the collector from the sensor;
the ground data processing system reads the quick access recording card information, obtains the heading machine working arm gear box data, inputs the transmitted state parameter information into a trend analysis model or a prediction model, evaluates the health state of the speed reducer by combining historical detection maintenance data and historical state parameter information of the speed reducer, and generates a data report by processing the analysis result to realize the prediction of typical faults.
2. The system of claim 1, wherein: the vehicle-mounted acquisition monitoring alarm device adopts a bottom plate slot type structure, and is provided with one power supply board, one signal conditioning board and one acquisition processing and monitoring alarm board; the power panel, the signal conditioning panel and the acquisition processing and monitoring alarm panel are sequentially arranged on the bottom plate slot, and the three panels realize power supply and signal transmission through the interfaces.
3. The system of claim 1, wherein: the quick access recording card comprises a CF card and a solid state disk.
4. A method for predicting the fault of a reducer of a working arm of a heading machine is characterized by comprising the following steps:
step 1, acquiring the vibration state of a speed reducer through a vibration sensor, acquiring the rotating speed parameter of an input shaft of the speed reducer through a rotating speed sensor, acquiring the swing angle of a working arm through an angle sensor, acquiring the oil pressure force of a cavity of the speed reducer through a pressure sensor, acquiring the oil temperature inside the speed reducer through a temperature sensor, and transmitting all signal parameters to a vehicle-mounted acquisition alarm device through cables;
step 2, the vehicle-mounted acquisition alarm device acquires, processes, analyzes and stores vibration, rotating speed, angle, pressure and temperature signals, and carries out overrun judgment to determine fault level and alarm output; a method of processing and analyzing a vibration signal, comprising:
step 1), noise reduction is carried out on the vibration signal by a signal conditioning board;
step 2), low-pass filtering is carried out;
step 3) performing time domain synchronous averaging;
step 4), extracting characteristic values;
step 5), the vehicle-mounted acquisition alarm device carries out alarm judgment and storage; the vehicle-mounted acquisition alarm device performs alarm judgment including threshold generation and alarm processing judgment; generating a threshold value based on a statistical distribution method, and performing alarm judgment by adopting an overrun judgment method;
the alarm grades are divided into two types, the first-level alarm aims at slight faults, namely the fault does not have shutdown influence on the operation task on the day; the secondary alarm aims at serious faults, and the operation task is stopped after the faults occur; the threshold values used for generating two alarms are different, the threshold value setting method used for the first-level alarm is a statistical distribution 3 sigma method, and the threshold value setting method used for the second-level alarm is a 5 sigma method or a 6 sigma method;
a method of measuring angle and pressure signals, comprising:
step 1), carrying out noise reduction on angle and pressure signals by a signal conditioning board;
step 2) extracting characteristic values;
step 3) recording and storing the pressure value when the horizontal angle is 0 to +/-3 degrees;
step 4) converting the pressure value into an oil quantity value; calculating an oil quantity value according to a function formed by fitting an oil quantity-pressure curve in a static state of the gearbox;
step 5) performing alarm processing when the oil quantity value is lower than the minimum oil quantity requirement;
step 3, the quick access recording card receives the information stored by the vehicle-mounted acquisition alarm device;
step 4, the ground data processing system obtains sensor data acquired on the vehicle by reading the information of the quick access recording card, diagnoses the sent fault and analyzes the trend of the potential fault by using the original data directly output by the sensor, and generates a data report according to the processing result; the transmitted state parameter information is input into a trend analysis model or a prediction model, and the health state of the speed reducer is evaluated by combining historical detection maintenance data and historical state parameter information of the speed reducer, so that the prediction of typical faults is realized;
the vehicle-mounted acquisition alarm processing device acquires data for 50 hours in advance, stores the data in a ground data station, and generates an initial threshold value by using data processing software, wherein the threshold value is updated every 500 hours later.
5. The method according to claim 4, wherein the processing method of the rotation speed parameter in the step 2 is as follows:
step 1), carrying out voltage limiting and shaping processing on a rotating speed signal of an input shaft of the speed reducer by a signal conditioning board;
step 2) changing the differential voltage signal into a pulse signal;
and 3) calculating a speed value according to the tooth number of the gear ring and the number of pulses.
6. The method of claim 4, wherein: in the step 4), the extracted features comprise time domain features, frequency domain features and time-frequency domain features, and the time domain feature indexes comprise waveform indexes, pulse indexes, kurtosis indexes, margin indexes and peak-to-peak values; the frequency domain indexes comprise center-of-gravity frequency, mean square frequency, root-mean-square frequency, frequency variance and frequency standard deviation; the time-frequency domain features include wavelet energy spectra.
7. The method of claim 4, wherein the step 2 temperature signal measuring method comprises:
step 1), noise reduction is carried out on the temperature signal by a signal conditioning board;
step 2) extracting characteristic values;
and 3) carrying out alarm judgment and storage by the vehicle-mounted acquisition alarm device.
8. The method of claim 4, wherein the step 4 fault diagnosis comprises: power spectral analysis, side-band analysis, cepstral analysis, as well as neural networks, expert systems, deep learning methods.
9. The method of claim 4, wherein the trend analysis method of step 4 comprises: time series, support vector machines, gaussian mixture models, hidden markov models, deep learning methods.
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| CN110132628A (en) * | 2019-05-31 | 2019-08-16 | 河南科技大学 | A combine harvester assembly quality inspection device and method |
| CN111337767B (en) * | 2020-02-25 | 2023-07-18 | 河北工业大学 | A Fault Analysis Method of Resonant Wave Reducer |
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