Automatic edge diagnostic analysis system and method for gas turbine

Abstract

The invention provides an automatic edge diagnostic analysis system and method for a gas turbine. The edge automatic diagnosis and analysis system is isolated from a public network, the edge automatic diagnosis and analysis system comprises a gas turbine data acquisition system, a data storage system, a diagnosis and analysis system and a display unit, and the gas turbine data acquisition system and the diagnosis and analysis system are both connected with the data storage system; the data acquisition system and the diagnostic analysis system are connected with the display unit; the data storage system is used for storing the working condition data of the gas turbine in a time sequence database in a time sequence data form, and the time sequence data is a data set arranged according to a time sequence; and the diagnostic analysis system is used for receiving and analyzing the time sequence data stored by the data storage system and outputting an analysis result obtained by carrying out diagnostic analysis on the working condition data of the gas turbine. Through the arrangement mode disclosed by the invention, the working condition data of the gas turbine can be diagnosed and analyzed automatically and quickly.

Description

Technical Field

[0001] The present disclosure relates to an automatic diagnosis and analysis system for a gas turbine, and in particular to an edge automatic diagnosis and analysis system and method for a gas turbine. Background Art

[0002] At present, in order to ensure the security of power plant operation data, power plant data is generally stored as local data and isolated from the public network environment. In this way, manual analysis of daily operation data is required when diagnosing power plant faults.

[0003] However, adopting such data analysis method will lead to delay in data analysis and fail to realize the analysis of long-term operation data of power plants. In addition, the existing diagnostic analysis process mainly relies on manual experience and fails to obtain more professional analysis and diagnosis suggestions. Summary of the invention

[0004] In order to overcome the above-mentioned defects existing in the prior art, the present disclosure provides an edge automatic diagnosis and analysis system for a gas turbine, wherein the edge automatic diagnosis and analysis system is isolated from a public network, and the edge automatic diagnosis and analysis system comprises a gas turbine data acquisition system, a data storage system, a diagnosis and analysis system and a display unit, wherein the gas turbine data acquisition system and the diagnosis and analysis system are both connected to the data storage system, and the data acquisition system and the diagnosis and analysis system are connected to the display unit; the gas turbine data acquisition system is used to collect the operating data of the gas turbine, wherein the operating data comprises the operating data and combustion data of the gas turbine, and the gas turbine data acquisition system comprises at least two operating data acquisition sensors, a combustion data acquisition sensor and a local operating system, and at least two of the operating data acquisition sensors and the combustion data acquisition sensor are connected to the local operating system. The operation data acquisition sensors are all arranged on the gas turbine to detect and collect the operation data in real time, at least one of the operation data acquisition sensors is connected to the local operating system, the local operating system is used to collect and store at least part of the operation data, and the combustion data acquisition sensor is arranged on the gas turbine to detect and collect the combustion data in real time; the data storage system is used to store the operating data of the gas turbine in the form of time series data in a time series database, and the time series data is a data set arranged in chronological order; the diagnosis and analysis system is used to receive and analyze the time series data stored in the data storage system and output the analysis results of the diagnosis and analysis of the operating data of the gas turbine; the display unit is used to receive and display the analysis results. Accordingly, the edge automatic diagnosis and analysis system for gas turbines can be effectively isolated from the public network, and can quickly diagnose and analyze the time series data stored in the data storage system, so as to realize rapid diagnosis and analysis of power plant operation.

[0005] Furthermore, the analysis result at least includes a statistical report of the preset period operation status of the gas turbine, fault discovery and prediction of the gas turbine, and operating performance parameters of the gas turbine. Accordingly, it is convenient for the staff to quickly know the statistical report of the preset period operation status of the gas turbine, fault analysis discovery and prediction, and operating performance parameters, so as to provide certain guidance to the staff's work.

[0006] Further, the diagnostic analysis system includes: a report creation module, the report creation module is used to obtain the operating data of the gas turbine in the predetermined period corresponding to the time series database, and generate the preset period operation status statistical report of the gas turbine according to the operating data of the gas turbine; wherein the preset period operation status statistical report at least includes a time series graph generated by the power change data of the gas turbine, a time series graph generated by the temperature change data of the gas turbine, a time series graph generated by the vibration change data of the gas turbine, a time series graph generated by the operation efficiency change data of the gas turbine, a time series graph generated by the power change data of the gas turbine, a time series graph generated by the start-up state change data of the gas turbine, a time series graph generated by the operation time change data of the gas turbine, and a time series graph generated by the real-time performance change data of the gas turbine. Accordingly, it is convenient for the staff to intuitively know the power change, temperature change, vibration change and operation efficiency change, which is helpful for the staff to carry out daily operation and maintenance work.

[0007] Furthermore, the diagnostic analysis system includes: a fault prediction analysis module, which uses a fault prediction analysis model to perform fault analysis on the time series data of the time series database to obtain and output fault analysis findings and predictions of the gas turbine; wherein the fault prediction analysis model includes at least one of the following models: a sensor health diagnosis model, which predicts the acquisition trend of sensor signals through a time series prediction algorithm and diagnoses the health of sensor hardware; a combustion state warning model, which determines the combustion state of the gas turbine based on the trend prediction of combustion data and recommends combustion optimization parameters; a combustion state warning model, which predicts the combustion state of the gas turbine based on the trend prediction of combustion data and recommends combustion optimization parameters; a combustion state warning model, which predicts the combustion state of the gas turbine based on the trend prediction of combustion data and recommends combustion optimization parameters; a combustion state warning model, which predicts the combustion state of the gas turbine based on the trend prediction of combustion data and recommends combustion optimization parameters; a combustion state warning model, which predicts the combustion state of the gas turbine based on the trend prediction of combustion data and recommends combustion optimization parameters; a combustion state warning model, which predicts the combustion state of the gas turbine based on the trend prediction of combustion data and recommends combustion optimization parameters; a combustion state warning model, which predicts the acquisition trend of sensor signals through a time series prediction algorithm and diagnoses the health of sensor hardware ... A burner status diagnosis model, wherein the burner status diagnosis model determines the blockage and degradation of the burner by analyzing the exhaust temperature at the outlet of the gas turbine and the trend of some combustion data collected by sensors related to the burner of the gas turbine; a gas turbine emission optimization model, wherein the gas turbine emission optimization model recommends combustion optimization data by analyzing the emission data and combustion data of the gas turbine to optimize the emission level of the gas turbine; a gas turbine vibration early warning model, wherein the gas turbine vibration early warning model determines the vibration trend of the gas turbine based on the analysis of the vibration data of the gas turbine to warn of vibration hazards and analyze the vibration faults that occur. Accordingly, it is possible to facilitate fault prediction and analysis of sensor health, combustion status, burner status, gas turbine emissions, and gas turbine vibration conditions, so as to timely discover fault hazards and quickly analyze fault problems that have already occurred.

[0008] Furthermore, the diagnostic analysis system includes: a calculation analysis module, which is used to calculate the time series data of the time series database to obtain the working performance parameters of the gas turbine. Accordingly, it is convenient for the staff to know the working performance of the gas turbine in time, which is convenient for daily maintenance work.

[0009] Furthermore, the display unit is also used to receive and display the operating data of the gas turbine in real time, thereby making it convenient for the staff to view the operating data of the gas turbine in real time, and facilitating real-time management and monitoring.

[0010] Furthermore, there are at least two local operating systems; at least two local operating systems are used to collect and store at least part of the operation data, and at least two local operating systems have different data collection frequencies. Accordingly, data with different data collection frequencies can be obtained, so as to better optimize the accuracy of data collection and facilitate subsequent accurate judgment.

[0011] Furthermore, at least two of the operation data acquisition sensors include an acceleration sensor for acquiring acceleration data of the impeller of the gas turbine, a speed sensor for acquiring speed data of the impeller of the gas turbine, an angle sensor for acquiring angle data of the gas turbine, and a vibration sensor for acquiring vibration data of the gas turbine; wherein the acceleration sensor, the speed sensor and the angle sensor are all connected to the local operating system, and the vibration sensor is connected to the data storage system. Accordingly, it is convenient to fully acquire the operation data of the gas turbine and to accurately calculate the corresponding power data.

[0012] Furthermore, the combustion data includes temperature data, pressure data and combustion performance data; the combustion data acquisition sensors are at least two, and the at least two combustion data acquisition sensors include a temperature sensor for acquiring the temperature data of the gas turbine and a pressure sensor for acquiring the pressure data of the gas turbine; the gas turbine data acquisition system also includes a combustion data storage and calculation module, the combustion data storage and calculation module is connected to the data storage system, and at least two of the combustion data acquisition sensors are connected to the combustion data storage and calculation module; wherein the combustion data storage and calculation module is used to store the temperature data and the pressure data, and calculate the combustion performance data according to the temperature data and the pressure data. Accordingly, it is convenient to fully acquire the combustion data of the gas turbine, so as to calculate the corresponding combustion performance data and efficiency data.

[0013] The present disclosure also provides an edge automatic diagnosis and analysis method for a gas turbine, which utilizes the edge automatic diagnosis and analysis system for a gas turbine provided above, and the edge automatic diagnosis and analysis method for a gas turbine includes the following steps: S10, collecting the operating data of the gas turbine through at least two operating data acquisition sensors, combustion data acquisition sensors and local operating system of the gas turbine data acquisition system, the operating data of the gas turbine at least including the operating data and combustion data of the gas turbine; S20, storing the operating data of the gas turbine in the form of time series data to a time series database through a data storage system, the time series data being a data set arranged in time sequence; S30, receiving and analyzing the time series database stored in the data storage system through a diagnosis and analysis system and outputting the analysis result of the diagnosis and analysis of the operating data of the gas turbine; S40, receiving and displaying the analysis result through a display unit. Accordingly, the edge automatic diagnosis and analysis method for a gas turbine can quickly realize the diagnosis and analysis of the time series data stored in the data storage system, so as to provide the corresponding diagnosis and analysis results to the staff in a timely manner.

[0014] Further, the step S30 includes: S31, acquiring the operating data of the gas turbine in a predetermined time period corresponding to the time series database through the report creation module of the diagnostic analysis system, and generating a preset time period operating status statistical report of the gas turbine according to the operating data of the gas turbine; wherein the preset time period operating status statistical report at least includes a time series graph generated by the power change data of the gas turbine, a time series graph generated by the temperature change data of the gas turbine, a time series graph generated by the vibration change data of the gas turbine, a time series graph generated by the operating efficiency change data of the gas turbine, a time series graph generated by the power change data of the gas turbine, a time series graph generated by the startup state change data of the gas turbine, and a time series graph generated by the operating time change data of the gas turbine. A column chart and a time series chart generated by the real-time performance change data of the gas turbine; and / or, S32, the fault prediction analysis module of the diagnostic analysis system uses a fault prediction analysis model to perform fault analysis on the time series database to obtain and output the fault discovery and prediction of the gas turbine; wherein the fault analysis and prediction of the gas turbine includes the fault analysis and prediction of the valve of the gas turbine, the fault analysis and prediction of the operation data acquisition sensor, the fault analysis and prediction of the combustion data acquisition sensor, the combustion fault analysis and prediction of the gas turbine, the performance degradation analysis and prediction of the compressor of the gas turbine, and the emission fault analysis and prediction of the gas turbine; and / or, S33, the calculation analysis module of the diagnostic analysis system calculates the time series database to obtain the working performance parameters of the gas turbine. Accordingly, it is convenient to provide the staff with a preset time period operating status statistical report and / or fault analysis discovery and prediction and / or working performance parameters of the gas turbine, so as to provide the staff with more accurate and professional daily maintenance or repair suggestions. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the present disclosure. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure. In the accompanying drawings:

[0016] Figure 1 is a schematic diagram showing an edge automatic diagnosis and analysis system for a gas turbine according to the present disclosure;

[0017] Figure 2 is a flow chart showing an edge automatic diagnosis analysis method for a gas turbine according to the present disclosure.

[0018] List of reference numerals:

[0019] 01. Gas turbine data acquisition system;

[0020] 02. Data storage system;

[0021] 03. Diagnostic analysis system;

[0022] 04. Display unit. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present disclosure will be described in detail below in conjunction with the drawings in the embodiments of the present disclosure. It should be noted that the embodiments and features in the embodiments of the present disclosure can be combined with each other without conflict.

[0024] In the following detailed description, reference is made to the accompanying drawings that form a part of this specification, in which specific embodiments in which the present disclosure may be implemented are shown by way of example. With respect to the accompanying drawings, directional terms such as "top", "bottom", "inside", "outside", "up", "down", "front", "back", etc. are used with reference to the direction of the accompanying drawings being described. Since the components of the embodiments of the present disclosure may be placed in many different directions, the directional terms are used for illustration only and are not intended to be limiting. It should be understood that other embodiments may be used and that structural or logical changes may be made without departing from the scope of the present disclosure. Therefore, the following detailed description should not be construed in a limiting sense, and the present disclosure is defined by the appended claims.

[0025] Reference Figure 1The present disclosure proposes an edge automatic diagnosis and analysis system 03 for a gas turbine. The edge automatic diagnosis and analysis system 03 is isolated from a public network. The edge automatic diagnosis and analysis system 03 includes a gas turbine data acquisition system 01, a data storage system 02, a diagnosis and analysis system 03, and a display unit 04. The gas turbine data acquisition system 01 and the diagnosis and analysis system 03 are both connected to the data storage system 02, and the data acquisition system and the diagnosis and analysis system 03 are connected to the display unit 04; the gas turbine data acquisition system 01 is used to collect the operating data of the gas turbine, and the operating data includes the operating data and combustion data of the gas turbine. The gas turbine data acquisition system 01 includes at least two operating data acquisition sensors, a combustion data acquisition sensor, and a local operation system The system comprises at least two operation data acquisition sensors arranged on the gas turbine to detect and collect operation data in real time, at least one operation data acquisition sensor is connected to the local operation system, the local operation system is used to collect and store at least part of the operation data, and the combustion data acquisition sensor is arranged on the gas turbine to detect and collect combustion data in real time; the data storage system 02 is used to store the operating data of the gas turbine in the form of time series data to the time series database, and the time series data is a data set arranged in time order; the diagnosis and analysis system 03 is used to receive and analyze the time series data stored in the data storage system 02 and output the analysis results of the diagnosis and analysis of the operating data of the gas turbine; the display unit 04 is used to receive and display the analysis results. Accordingly, the edge automatic diagnosis and analysis system 03 for the gas turbine can be effectively isolated from the public network, and can automatically realize the rapid diagnosis and analysis of the time series data stored in the data storage system 02, so as to realize the rapid diagnosis and analysis of the operation of the power plant.

[0026] Specifically, the combustion data is data related to the combustion of the gas turbine, and the combustion data at least includes temperature data and pressure data. The operation data is data related to the actual power operation of the gas turbine, and the operation data at least includes acceleration data, vibration data, angle data and speed data. Specifically, different data are detected by different sensors.

[0027] The edge automatic diagnosis and analysis system 03 for gas turbines provided by the present disclosure can automatically realize the collection, storage, diagnosis and analysis and display of the operating data of the gas turbine through the gas turbine data acquisition system 01, the data storage system 02, the diagnosis and analysis system 03 and the display unit 04, realize the rapid diagnosis and analysis of local data, and provide professional diagnosis and analysis for the daily maintenance or repair work of the staff. Since there is no need for manual empirical calculation, the whole analysis process will not be slow and inefficient, and there will be no serious data delay. In addition, since the diagnosis and analysis system 03 is isolated from the public network, the security of the data is also guaranteed.

[0028] Specifically, the use of a time series database can facilitate the import, cleaning and archiving of all operating data from different customer sites. The time series database is isolated from the public Internet, effectively achieving data security.

[0029] Specifically, the analysis results at least include the statistical report of the gas turbine's operating status during the preset period, the gas turbine's fault analysis discovery and prediction, and the gas turbine's operating performance parameters. With such a setting, it is convenient for the staff to comprehensively analyze and monitor the daily operation and maintenance of the gas turbine, so as to carry out the corresponding maintenance or repair work, greatly reducing the operating risk of the gas turbine.

[0030] Specifically, the diagnostic analysis system 03 includes a report creation module, which is used to obtain the operating data of the gas turbine in a predetermined period corresponding to the time series database, and generate a preset period operating state statistical report of the gas turbine according to the operating data of the gas turbine; wherein the preset period operating state statistical report at least includes a time series graph generated by the power change data of the gas turbine, a time series graph generated by the temperature change data of the gas turbine, a time series graph generated by the vibration change data of the gas turbine, a time series graph generated by the operating efficiency change data of the gas turbine, a time series graph generated by the power change data of the gas turbine, a time series graph generated by the start-up state change data of the gas turbine, a time series graph generated by the running time change data of the gas turbine, and a time series graph generated by the real-time performance change data of the gas turbine. With such a setting, it is convenient to more comprehensively feedback the time series graphs of different operating data of the gas turbine to the staff, so that the staff can more fully know the changing trend of different operating data of the gas turbine during operation, so as to provide certain guidance and suggestions for the maintenance or repair work of the staff.

[0031] Specifically, the preset period in the preset period operation status statistical report can be set accordingly according to the specific needs of the staff, for example, the preset period can be a time unit such as a week, a month, or a year. When the preset period is a month, the corresponding preset period operation status statistical report is a monthly report, and the monthly report includes a time series graph generated by the power change data of the gas turbine within a month, a time series graph generated by the temperature change data of the gas turbine within a month, a time series graph generated by the vibration change trend of the gas turbine within a month, and a time series graph generated by the operation efficiency change data of the gas turbine within a month.

[0032] Specifically, the power and operating efficiency can be calculated according to conventional calculation formulas based on the operating data of the gas turbine collected by the data collection system.

[0033] In this embodiment, the diagnostic analysis system 03 includes a fault prediction analysis module, which uses a fault prediction analysis model to perform fault analysis on the time series data of the time series database to obtain and output the fault analysis discovery and prediction of the gas turbine; the fault prediction analysis model includes at least one of the following models: a sensor health diagnosis model, a combustion state warning model, a burner state diagnosis model, a gas turbine emission optimization model, and a gas turbine vibration warning model. The above-mentioned fault prediction model can be used to facilitate fault prediction and analysis of sensor health, combustion state, burner state, gas turbine emissions, and gas turbine vibration conditions, so as to timely discover potential faults and quickly analyze existing fault problems.

[0034] Specifically, the sensor health diagnosis model predicts the collection trend of sensor signals through a time series prediction algorithm, and diagnoses the health of the sensor hardware. The "collection trend of sensor signals" here can be understood to include the changing trend of the operating data collected by the operating data acquisition sensor and the changing trend of the combustion data collected by the combustion data acquisition sensor. The diagnostic results of the sensor health include inaccurate sensor detection accuracy, sensor failure, disconnection of the sensor connection line, etc. The above diagnostic results can all be predicted based on the sensor detection data. Specifically, in order to facilitate better prediction of the health of sensors of the same type, multiple sensors of the same type can be set to detect the same data.

[0035] Specifically, the combustion state warning model determines the combustion state of the gas turbine according to the trend prediction of the combustion data and recommends the combustion optimization parameters. Specifically, the combustion state warning model can also make predictions and judgments through the time series prediction algorithm to predict the combustion state of the gas turbine according to the judgment of the change trend of the combustion data, and determine the corresponding combustion optimization parameters (the combustion optimization parameters correspond to a better combustion state) according to the operating state of the gas turbine, so as to adjust the combustion state to a better state through the combustion optimization parameters. The combustion optimization parameters may include the supply amount of natural gas and the combustion temperature, and the combustion state is adjusted by changing the supply amount of natural gas and the combustion temperature.

[0036] Specifically, the burner status diagnosis model determines the blockage and degradation of the burner by analyzing the exhaust temperature at the outlet of the gas turbine and the trend of partial combustion data collected by sensors related to the burner of the gas turbine. "Sensors related to the burner of the gas turbine" can be understood as sensors installed on the gas turbine for collecting partial combustion data, which belong to combustion data collection sensors. The burner status diagnosis model can also make predictions and judgments through a time series prediction algorithm, and judge the condition of the burner based on the combustion data. Specifically, the condition inside the burner is predicted and inferred by whether the relevant combustion data such as combustion temperature and combustion pressure are within the normal data range.

[0037] Specifically, the gas turbine emission optimization model recommends combustion optimization data by analyzing the emission data and combustion data of the gas turbine to optimize the emission level of the gas turbine. The emission data of the gas turbine can be collected by a combustion data sensor set on the gas turbine. The emission data can specifically include temperature value data and pressure value data of the exhaust gas of the gas turbine. The model can predict the emission data of the gas turbine through a time series prediction algorithm, and optimize the combustion data to obtain combustion optimization data based on the prediction of the emission data and the correlation between the emission data and the combustion data.

[0038] Specifically, the gas turbine vibration early warning model determines the vibration trend of the gas turbine based on the analysis of the vibration data of the gas turbine, so as to warn of the vibration hidden dangers and analyze the vibration faults that occur. The vibration data of the gas turbine can be collected by the operation data sensor set on the gas turbine. The vibration data here is mainly the vibration data of the bearing of the gas turbine, specifically including the vibration frequency and / or vibration amplitude. The gas turbine vibration early warning model can predict the vibration data of the gas turbine through the time series prediction algorithm, and judge whether the predicted vibration data is within the normal allowable vibration data range, and determine whether the vibration hidden danger occurs based on the comparison between the predicted vibration data and the normal allowable vibration data range. The specific data of the vibration fault that has occurred is analyzed, and combined with the specific data of the existing vibration fault in the expert rule base and the corresponding fault problem, a combined judgment is made to determine the type of vibration fault. The fault types of the bearings of the gas turbine include loose bearing installation, bearing structure damage, etc. The specific fault type can be determined based on the specific situation of the vibration frequency and amplitude and combined with the data in the transfer rule base for combined judgment and analysis.

[0039] In the above fault prediction and analysis models, specific data and expert rule bases can be combined to perform fault prediction and diagnosis analysis. Specifically, the expert rule base includes algorithms, empirical data, correlations between different data, and data threshold ranges.

[0040] Among them, the fault analysis and prediction of the gas turbine includes the fault analysis and prediction of the valve of the gas turbine, the fault analysis and prediction of the operation data acquisition sensor, the fault analysis and prediction of the combustion data acquisition sensor, the combustion fault analysis and prediction of the gas turbine, the performance degradation analysis and prediction of the compressor of the gas turbine, and the emission fault analysis and prediction of the gas turbine. In this way, it is convenient to provide the staff with the fault analysis findings and predictions of the gas turbine in a timely manner, so that the staff can make corresponding feedback and adjustments according to the fault analysis findings and predictions, so as to make it easier for the staff to quickly make maintenance and diagnosis judgments on various parts of the gas turbine and improve work efficiency. Specifically, the fault analysis model here can be a conventional fault analysis model for fault judgment of the gas turbine, and the conventional fault analysis model is established based on the common fault scenarios and root causes of the gas turbine.

[0041] Specifically, the diagnostic analysis system 03 includes: a calculation analysis module, which is used to calculate the time series data of the time series database to obtain the working performance parameters of the gas turbine. In this way, it is convenient for the staff to perform daily operations, maintenance, repairs, etc. according to the working performance parameters of the gas turbine. Specifically, the calculation analysis module can use the calculation formula or calculation model of the conventional working performance parameters of the gas turbine for calculation analysis.

[0042] In this embodiment, the display unit 04 is also used to receive and display the operating data of the gas turbine in real time, so that the staff can know the real-time operating status of the gas turbine, thereby facilitating the staff to monitor the operation of the gas turbine in real time.

[0043] Specifically, the display unit 04 may be a dashboard, through which real-time information and analysis results can be displayed to the staff in real time, thereby saving the staff's time for data processing, analysis, drawing and collating reports.

[0044] Specifically, there are at least two local operating systems, and the at least two local operating systems are used to collect and store at least part of the operation data; wherein the data collection frequencies of the at least two local operating systems are different. In this way, it is convenient to collect temperature data and pressure data with different collection frequencies, so as to obtain more comprehensive and sufficient operation data and improve the accuracy of data collection.

[0045] Specifically, at least two local operating systems may be a WinTS system and a T3000 system, respectively, and the operation data of the gas turbine (including speed data, acceleration data, etc.) are stored in the WinTS system and the T3000 system.

[0046] Specifically, at least two operating data acquisition sensors include an acceleration sensor for acquiring acceleration data of the impeller of the gas turbine, a speed sensor for acquiring speed data of the impeller of the gas turbine, an angle sensor for acquiring the operating angle of the gas turbine, and a vibration sensor for acquiring vibration data of the gas turbine; wherein the acceleration sensor, the speed sensor, and the angle sensor are all connected to the local operating system, and the vibration sensor is connected to the data storage system. In this way, the acceleration data, the speed data, and the angle data are transmitted to the data storage system through the local operating system, and the vibration data is directly transmitted to the data storage system.

[0047] In the present disclosure, combustion data includes temperature data, pressure data and combustion performance data. There are at least two types of combustion data acquisition sensors, and the at least two combustion data acquisition sensors include a temperature sensor for acquiring temperature data of the gas turbine and a pressure sensor for acquiring pressure data of the gas turbine. The gas turbine data acquisition system also includes a combustion data storage and calculation module, which is connected to the data storage system, and at least two combustion data acquisition sensors are connected to the combustion data storage and calculation module. Among them, the combustion data storage and calculation module is used to store temperature data and pressure data, and calculate the combustion performance data based on the temperature data and pressure data. In this way, it is convenient to obtain combustion data more comprehensively and to better analyze the combustion performance of the gas turbine.

[0048] Reference Figure 2 The present disclosure also proposes an edge automatic diagnosis and analysis method for a gas turbine, which utilizes the edge automatic diagnosis and analysis system 03 for a gas turbine provided above. The edge automatic diagnosis and analysis method for a gas turbine includes the following steps: S10, collecting the operating data of the gas turbine through at least two operating data acquisition sensors, a combustion data sensor and a local operating system of the gas turbine data acquisition system 01, the operating data of the gas turbine at least including the operating data and the combustion data of the gas turbine; S20, storing the operating data of the gas turbine in the form of time series data in a time series database through the data storage system 02, the time series data is a data set arranged in time sequence; S30, receiving and analyzing the time series database stored in the data storage system 02 through the diagnosis and analysis system 03 and outputting the analysis results of the diagnostic analysis of the operating data of the gas turbine; S40, receiving and displaying the analysis results through the display unit 04.

[0049] This method can facilitate the automatic collection, storage, diagnosis and analysis of the gas turbine's operating data and display of the results, so that the staff can quickly obtain relevant professional diagnosis and analysis of the gas turbine, and can facilitate the staff to carry out daily maintenance or repair work, thereby improving the efficiency of diagnosis and analysis.

[0050] Specifically, step S30 includes: S31, obtaining the operating data of the gas turbine for a predetermined time period corresponding to the time series database through the report creation module of the diagnostic analysis system 03, and generating a preset time period operating status statistical report of the gas turbine according to the operating data of the gas turbine; wherein the preset time period operating status statistical report includes at least a time series graph generated by the power change data of the gas turbine, a time series graph generated by the temperature change data of the gas turbine, a time series graph generated by the vibration change data of the gas turbine, a time series graph generated by the operating efficiency change data of the gas turbine, a time series graph generated by the power change data of the gas turbine, a time series graph generated by the start-up state change data of the gas turbine, a time series graph generated by the operating time change data of the gas turbine, and a time series graph generated by the real-time performance change data of the gas turbine.

[0051] Step S30 also includes: S32, using the fault prediction analysis model to perform fault analysis on the time series database through the fault prediction analysis module of the diagnostic analysis system 03 to obtain and output the fault analysis findings and predictions of the gas turbine; wherein the fault analysis and prediction of the gas turbine includes the fault analysis and prediction of the valve of the gas turbine, the fault analysis and prediction of the operation data acquisition sensor, the fault analysis and prediction of the combustion data acquisition sensor, the combustion fault analysis and prediction of the gas turbine, the performance degradation analysis and prediction of the compressor of the gas turbine, and the emission fault analysis and prediction of the gas turbine.

[0052] Step S30 also includes: S33, calculating the time series database through the calculation and analysis module of the diagnosis and analysis system 03 to obtain the working performance parameters of the gas turbine. By adopting such a method, it is convenient for the staff to quickly obtain the preset time period operating status statistical report of the gas turbine and / or the fault discovery and prediction of the gas turbine and / or the working performance parameters of the gas turbine, so as to facilitate the staff to fully understand the operating conditions of the gas turbine from different angles.

[0053] The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. An edge automatic diagnosis and analysis system for a gas turbine, characterized in that: The edge automatic diagnosis and analysis system is isolated from the public network, and the edge automatic diagnosis and analysis system includes a gas turbine data acquisition system, a data storage system, a diagnosis and analysis system, and a display unit. The gas turbine data acquisition system and the diagnosis and analysis system are both connected to the data storage system, and the data acquisition system and the diagnosis and analysis system are connected to the display unit; The gas turbine data acquisition system is used to acquire operating data of the gas turbine, wherein the operating data includes operating data and combustion data of the gas turbine. The gas turbine data acquisition system includes at least two operating data acquisition sensors, a combustion data acquisition sensor, and a local operating system. At least two of the operating data acquisition sensors are arranged on the gas turbine to detect and acquire the operating data in real time. At least one of the operating data acquisition sensors is connected to the local operating system. The local operating system is used to collect and store at least part of the operating data. The combustion data acquisition sensor is arranged on the gas turbine to detect and acquire the combustion data in real time. The data storage system is used to store the operating data of the gas turbine in a time series database in the form of time series data, wherein the time series data is a data set arranged in chronological order; The diagnostic analysis system is used to receive and analyze the time series data stored in the data storage system and output the analysis results of the diagnostic analysis of the operating condition data of the gas turbine; The display unit is used to receive and display the analysis result.

2. The edge automatic diagnosis and analysis system for a gas turbine according to claim 1, characterized in that: The analysis result includes at least a statistical report of the operating status of the gas turbine during a preset period of time, fault discovery and prediction of the gas turbine, and operating performance parameters of the gas turbine.

3. The edge automatic diagnosis and analysis system for a gas turbine according to claim 1, characterized in that: The diagnostic analysis system comprises: A report creation module, the report creation module is used to obtain the operating data of the gas turbine in a predetermined period corresponding to the time series database, and generate a statistical report on the operating status of the gas turbine in the preset period according to the operating data of the gas turbine; Among them, the preset time period operating status statistical report at least includes a time series graph generated by the power change data of the gas turbine, a time series graph generated by the temperature change data of the gas turbine, a time series graph generated by the vibration change data of the gas turbine, a time series graph generated by the operating efficiency change data of the gas turbine, a time series graph generated by the power change data of the gas turbine, a time series graph generated by the start-up status change data of the gas turbine, a time series graph generated by the operating time change data of the gas turbine, and a time series graph generated by the real-time performance change data of the gas turbine.

4. The edge automatic diagnosis and analysis system for a gas turbine according to claim 1, characterized in that: The diagnostic analysis system comprises: A fault prediction analysis module, wherein the fault prediction analysis module uses a fault prediction analysis model to perform fault analysis on the time series data of the time series database to obtain and output fault analysis findings and predictions of the gas turbine; The fault prediction analysis model includes at least one of the following models: A sensor health diagnosis model, which predicts the acquisition trend of sensor signals through a time series prediction algorithm and diagnoses the health of sensor hardware; A combustion state early warning model, wherein the combustion state early warning model determines the combustion state of the gas turbine according to the trend prediction of the combustion data and recommends combustion optimization parameters; a burner state diagnosis model, wherein the burner state diagnosis model determines the blockage and degradation of the burner by analyzing the exhaust gas temperature at the outlet of the gas turbine and the trend of partial combustion data collected by sensors related to the burner of the gas turbine; A gas turbine emission optimization model, wherein the gas turbine emission optimization model recommends combustion optimization data by analyzing the emission data and combustion data of the gas turbine, so as to optimize the emission level of the gas turbine; A gas turbine vibration early warning model, wherein the gas turbine vibration early warning model determines the vibration trend of the gas turbine based on the analysis of the vibration data of the gas turbine, so as to give early warning of vibration hazards and analyze the vibration faults that occur.

5. The edge automatic diagnosis and analysis system for a gas turbine according to claim 1, characterized in that: The diagnostic analysis system comprises: A calculation and analysis module, wherein the calculation and analysis module is used to calculate the time series data in the time series database to obtain the working performance parameters of the gas turbine.

6. The edge automatic diagnosis and analysis system for a gas turbine according to claim 1, characterized in that: There are at least two local operating systems; Among them, the data collection frequencies of at least two of the local operating systems are different.

7. The edge automatic diagnosis and analysis system for a gas turbine according to claim 1, characterized in that: At least two of the operating data acquisition sensors include an acceleration sensor for acquiring acceleration data of the impeller of the gas turbine, a speed sensor for acquiring speed data of the impeller of the gas turbine, an angle sensor for acquiring angle data of the gas turbine, and a vibration sensor for acquiring vibration data of the gas turbine; wherein the acceleration sensor, the speed sensor and the angle sensor are all connected to the local operating system, and the vibration sensor is connected to the data storage system.

8. The edge automatic diagnosis and analysis system for a gas turbine according to claim 1, characterized in that: The combustion data includes temperature data, pressure data and combustion performance data; the combustion data acquisition sensors are at least two, and the at least two combustion data acquisition sensors include a temperature sensor for acquiring temperature data of the gas turbine and a pressure sensor for acquiring pressure data of the gas turbine; the gas turbine data acquisition system also includes a combustion data storage calculation module, the combustion data storage calculation module is connected to the data storage system, and at least two of the combustion data acquisition sensors are connected to the combustion data storage calculation module; The combustion data storage and calculation module is used to store the temperature data and the pressure data, and calculate the combustion performance data according to the temperature data and the pressure data.

9. An automatic edge diagnosis and analysis method for a gas turbine, which utilizes the automatic edge diagnosis and analysis system for a gas turbine according to any one of claims 1 to 8, characterized in that: The edge automatic diagnosis and analysis method for a gas turbine comprises the following steps: S10, collecting the operating data of the gas turbine through at least two operating data acquisition sensors, a combustion data acquisition sensor and a local operating system of a gas turbine data acquisition system, wherein the operating data of the gas turbine includes the operating data and the combustion data of the gas turbine; S20, storing the operating data of the gas turbine in a time series database in the form of time series data through a data storage system, wherein the time series data is a data set arranged in time order; S30, receiving and analyzing the time series database stored in the data storage system through the diagnostic analysis system and outputting the analysis result of the diagnostic analysis of the operating condition data of the gas turbine; S40, receiving and displaying the analysis result via a display unit.

10. The edge automatic diagnosis and analysis method for a gas turbine according to claim 9, characterized in that: The step S30 comprises: S31, obtaining the operating data of the gas turbine for a predetermined period of time corresponding to the time series database through the report creation module of the diagnostic analysis system, and generating a preset period operating status statistical report of the gas turbine according to the operating data of the gas turbine; wherein the preset period operating status statistical report at least includes a time series graph generated by the power change data of the gas turbine, a time series graph generated by the temperature change data of the gas turbine, a time series graph generated by the vibration change data of the gas turbine, a time series graph generated by the operating efficiency change data of the gas turbine, a time series graph generated by the power change data of the gas turbine, a time series graph generated by the startup state change data of the gas turbine, a time series graph generated by the operating time change data of the gas turbine, and a time series graph generated by the real-time performance change data of the gas turbine; and / or, S32, performing fault analysis on the time series database by using a fault prediction analysis model through the fault prediction analysis module of the diagnostic analysis system to obtain and output fault discovery and prediction of the gas turbine; wherein the fault analysis and prediction of the gas turbine includes fault analysis and prediction of valves of the gas turbine, fault analysis and prediction of the operation data acquisition sensor, fault analysis and prediction of the combustion data acquisition sensor, combustion fault analysis and prediction of the gas turbine, performance degradation analysis and prediction of the compressor of the gas turbine, and emission fault analysis and prediction of the gas turbine; and / or, S33, calculating the time series database through the calculation and analysis module of the diagnosis and analysis system to obtain the working performance parameters of the gas turbine.

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