Compressor Fault Warning Method, Device, Electronic Device and Computer Readable Medium

Abstract

Embodiments of the present disclosure disclose a compressor fault warning method, device, electronic device, and computer-readable medium. A specific implementation of the method includes: obtaining compressor operation data of any compressor; generating predicted compressor data and a predicted compressor data sequence; extracting respective predicted index values corresponding to a target index from the predicted compressor data sequence; displaying a compressor fault prediction page; in response to determining that the real-time index value of any index does not meet the alarm condition and the predicted index value meets the warning condition, displaying a warning identifier; in response to determining that the real-time index value meets the alarm condition, displaying an alarm identifier at the position corresponding to any index in the status column; determining the fault information matching the real-time compressor operation data as the target fault information; and displaying the fault cause information and maintenance suggestion information included in the target fault information. This implementation can perform automatic warning according to the trend of compressor operation, without the need for manual determination of compressor faults.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technologies, and in particular, to a compressor fault warning method, apparatus, electronic device, and computer-readable medium. Background Art

[0002] As a core component in industrial equipment, the operation status of a compressor needs to be monitored. Currently, when monitoring the operation status of a compressor, the commonly adopted method is to set hierarchical alarm thresholds to achieve hierarchical alarms for various indicators of the compressor, and then arrange maintenance personnel or notify on-site personnel to handle compressor anomalies.

[0003] However, the inventors found that when monitoring the operation status of a compressor in the above manner, the following technical problems often exist:

[0004] First, the hierarchical alarms all judge based on the real-time operation data of the compressor, and cannot give early warnings according to the operation trend of the compressor, resulting in that technicians cannot make corresponding strategies in advance, and technicians need to analyze compressor faults based on alarm events.

[0005] Second, the degree of automation for handling compressor anomaly events is relatively low, and the methods of reaching the event site or notifying the on-site personnel to handle compressor anomaly events result in a long time for handling compressor anomalies.

[0006] The above information disclosed in this background art section is only used to enhance the understanding of the background of the inventive concept, and thus, it may include information that does not form the prior art known to those of ordinary skill in the art in this country. Summary of the Invention

[0007] This summary part of the present disclosure is used to introduce concepts in a brief form, and these concepts will be described in detail in the subsequent detailed implementation part. This summary part of the present disclosure is not intended to identify the key features or essential features of the claimed technical solution, nor is it intended to be used to limit the scope of the claimed technical solution.

[0008] Some embodiments of the present disclosure propose a compressor fault warning method, apparatus, electronic device, and computer-readable medium to solve one or more of the technical problems mentioned in the above background art section.

[0009] In a first aspect, some embodiments of the present disclosure provide a method for early warning of compressor failures. The method includes: in response to detecting a selection operation on any compressor displayed on the compressor failure early warning overview page, obtaining the compressor operation data of the above-mentioned any compressor, wherein various types of compressors are displayed on the compressor failure early warning overview page, and the compressor operation data includes a historical compressor operation data set and real-time compressor operation data; generating predicted compressor data corresponding to the current moment and a predicted compressor data sequence corresponding to a future time period according to the historical compressor operation data set and the real-time compressor operation data; extracting each predicted index value corresponding to a target index from the predicted compressor data sequence as a predicted index value sequence; displaying a compressor failure prediction page corresponding to the above-mentioned compressor, wherein a compressor failure prediction list and a trend curve graph corresponding to the above-mentioned target index are displayed on the compressor failure prediction page, the predicted compressor data and the real-time compressor operation data are displayed in the compressor failure prediction list, the trend curve graph displays an actual value curve, a predicted curve, and a threshold line corresponding to the above-mentioned target index, and the predicted curve is constructed according to the predicted index value sequence; in response to determining that the real-time index value of any index in the compressor failure prediction list does not meet the alarm condition corresponding to the above-mentioned any index, and the predicted index value of the above-mentioned any index meets the early warning condition, displaying an early warning identifier at the position corresponding to the above-mentioned any index in the status column of the compressor failure prediction list; in response to determining that the real-time index value meets the above-mentioned alarm condition, displaying an alarm identifier at the position corresponding to the above-mentioned any index in the status column of the compressor failure prediction list; determining whether there is a failure information that matches the real-time compressor operation data in the failure information set corresponding to the above-mentioned any compressor, wherein the failure information in the failure information set includes a failure name, failure cause information, and maintenance suggestion information; in response to determining that there is a failure information that matches the real-time compressor operation data in the failure information set corresponding to the above-mentioned any compressor, determining the failure information that matches the real-time compressor operation data as the target failure information; displaying the failure name included in the above-mentioned target failure information on the compressor failure prediction page; in response to detecting a selection operation on the above-mentioned failure name, displaying the failure cause information and maintenance suggestion information included in the above-mentioned target failure information.

[0010] Second aspect, some embodiments of the present disclosure provide a compressor fault warning device, the device comprising: an acquisition unit configured to, in response to detecting a selection operation on any compressor displayed in the compressor fault warning overview page, acquire the compressor operation data of the any compressor, wherein various types of compressors are displayed in the compressor fault warning overview page, and the compressor operation data includes a historical compressor operation data set and real-time compressor operation data; a generation unit configured to generate predicted compressor data corresponding to the current moment and a predicted compressor data sequence corresponding to a future time period according to the historical compressor operation data set and the real-time compressor operation data; an extraction unit configured to extract respective predicted index values corresponding to a target index from the predicted compressor data sequence as a predicted index value sequence; a first display unit configured to display a compressor fault prediction page corresponding to the compressor, wherein a compressor fault prediction list and a trend curve graph corresponding to the target index are displayed in the compressor fault prediction page, the predicted compressor data and the real-time compressor operation data are displayed in the compressor fault prediction list, the trend curve graph displays an actual value curve, a predicted curve and a threshold line corresponding to the target index, and the predicted curve is constructed according to the predicted index value sequence; a second display unit configured to, in response to determining that the real-time index value of any index in the compressor fault prediction list does not satisfy the alarm condition corresponding to the any index and the predicted index value of the any index satisfies the warning condition, display a warning identifier at the position corresponding to the any index in the status column of the compressor fault prediction list; a third display unit configured to, in response to determining that the real-time index value satisfies the alarm condition, display an alarm identifier at the position corresponding to the any index in the status column of the compressor fault prediction list; a first determination unit configured to determine whether there is a fault information in the fault information set corresponding to the any compressor that matches the real-time compressor operation data, wherein the fault information in the fault information set includes a fault name, fault cause information and maintenance suggestion information; a second determination unit configured to, in response to determining that there is a fault information in the fault information set corresponding to the any compressor that matches the real-time compressor operation data, determine the fault information that matches the real-time compressor operation data as the target fault information; a fourth display unit configured to display the fault name included in the target fault information in the compressor fault prediction page; a fifth display unit configured to, in response to detecting a selection operation on the fault name, display the fault cause information and maintenance suggestion information included in the target fault information.

[0011] In a third aspect, some embodiments of the present disclosure provide an electronic device, including: one or more processors; a storage device storing one or more programs thereon, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner of the first aspect above.

[0012] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium storing a computer program thereon, wherein when the program is executed by a processor, the method described in any implementation manner of the first aspect above is implemented.

[0013] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: Through the compressor fault warning method of some embodiments of the present disclosure, automatic warning can be carried out according to the operation trend of the compressor, without the need for manual determination of compressor faults. Specifically, the reason for the inability to carry out warning according to the operation trend of the compressor and the need for manual determination of compressor faults is as follows: Hierarchical alarms all judge based on the real-time operation data of the compressor, and cannot carry out warning according to the operation trend of the compressor, resulting in technicians being unable to make coping strategies in advance, and technicians need to analyze compressor faults according to alarm events. Based on this, in the compressor fault warning method of some embodiments of the present disclosure, first, in response to detecting a selection operation on any compressor displayed on the compressor fault warning overview page, obtain the compressor operation data of the above-mentioned any compressor. Among them, various types of compressors are displayed on the compressor fault warning overview page. The above-mentioned compressor operation data includes a historical compressor operation data set and real-time compressor operation data. Thus, the operation data of the compressor selected by the user and whose operation status needs to be monitored can be automatically obtained. Then, according to the above-mentioned historical compressor operation data set and the above-mentioned real-time compressor operation data, generate predicted compressor data corresponding to the current moment and a predicted compressor data sequence corresponding to a future time period. Thus, the operation status of the selected compressor is predicted in real time and predicted in advance. After that, extract each predicted index value corresponding to the target index from the above-mentioned predicted compressor data sequence as a predicted index value sequence. Thus, the predicted index value sequence can be used as each predicted value of the target index. Secondly, display a compressor fault prediction page corresponding to the above-mentioned compressor. Among them, a compressor fault prediction list and a trend curve graph corresponding to the above-mentioned target index are displayed on the compressor fault prediction page. The above-mentioned compressor fault prediction list displays the above-mentioned predicted compressor data and the above-mentioned real-time compressor operation data. The above-mentioned trend curve graph displays the actual value curve, prediction curve, and threshold line corresponding to the above-mentioned target index. The above-mentioned prediction curve is constructed according to the above-mentioned predicted index value sequence. Thus, the overall operation data of the compressor and the operation trend of the target index can be visualized in the form of a list and a trend graph. Then, in response to determining that the real-time index value of any index in the above-mentioned compressor fault prediction list does not meet the alarm condition corresponding to the above-mentioned any index, and the predicted index value of the above-mentioned any index meets the warning condition, display a warning identifier at the position corresponding to the above-mentioned any index in the status column of the above-mentioned compressor fault prediction list. Thus, when the predicted index value of the compressor at the current moment meets the warning condition, the user can be prompted to pay attention to this index of the compressor with a warning identifier. Then, in response to determining that the above-mentioned real-time index value meets the above-mentioned alarm condition, display an alarm identifier at the position corresponding to the above-mentioned any index in the status column of the above-mentioned compressor fault prediction list. Thus, when the actual index value of the compressor at the current moment meets the alarm condition, the user can be warned to handle the abnormality of the compressor in this index with an alarm identifier.After that, it is determined whether there is a fault information that matches the real-time compressor operation data in the set of fault information corresponding to any of the above compressors. Among them, the fault information in the set of fault information includes a fault name, fault cause information, and maintenance suggestion information. Thus, fault detection of the real-time operation data of the compressor can be realized. Then, in response to determining that there is a fault information that matches the real-time compressor operation data in the set of fault information corresponding to any of the above compressors, the fault information that matches the real-time compressor operation data is determined as the target fault information. Thus, fault information can be matched from each pre-configured fault information. Secondly, the fault name included in the above target fault information is displayed on the compressor fault prediction page. Thus, the matched fault information can be prompted. Finally, in response to detecting a selection operation on the above fault name, the fault cause information and maintenance suggestion information included in the above target fault information are displayed. Thus, when the user selects to view the detailed information of the fault name, the corresponding fault cause information and maintenance suggestion information can be displayed. Also, because the early warning of the compressor is based on the predicted index value at the current moment, the predicted index value at the current moment can represent the index change trend at the current moment, and the displayed trend curve graph can represent the index change trend in the future time period, so that the method of hierarchical alarm can be avoided, and early warning can be performed according to the operation trend of the compressor. Furthermore, technicians can pay attention to the indexes of the early-warning compressors in advance. Also, because fault detection of the real-time operation data of the compressor can be realized, the fault cause information and maintenance suggestion information included in the matched fault information can be directly viewed without manually determining the compressor fault. Thus, automatic early warning can be performed according to the operation trend of the compressor without manually determining the compressor fault. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In combination with the accompanying drawings and with reference to the following specific embodiments, the above and other features, advantages, and aspects of the various embodiments of the present disclosure will become more apparent. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic, and the elements and elements are not necessarily drawn to scale.

[0015] Figure 1 is a flowchart of some embodiments of a compressor fault early warning method according to the present disclosure;

[0016] Figure 2 is a structural schematic diagram of some embodiments of a compressor fault early warning device according to the present disclosure;

[0017] Figure 3 is a structural schematic diagram of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to more thoroughly and completely understand the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not used to limit the protection scope of the present disclosure.

[0019] In addition, it should be noted that for ease of description, only parts related to the relevant invention are shown in the drawings. Without conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other.

[0020] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence relationship of the functions performed by these devices, modules or units.

[0021] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive. Those skilled in the art should understand that unless clearly specified otherwise in the context, it should be understood as "one or more".

[0022] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only for illustrative purposes and are not used to limit the scope of these messages or information.

[0023] The present disclosure will be described in detail below with reference to the drawings and in combination with embodiments.

[0024] Figure 1 Flow 100 of some embodiments of a compressor fault warning method according to the present disclosure is shown. The compressor fault warning method includes the following steps:

[0025] Step 101, in response to detecting a selection operation on any compressor displayed in the compressor fault warning overview page, obtain the compressor operation data of any compressor.

[0026] In some embodiments, the execution subject of the compressor fault warning method (such as a computing device) can, in response to detecting a selection operation on any compressor displayed in the compressor fault warning overview page, obtain the compressor operation data of the above-mentioned any compressor from the above-mentioned any compressor through a wired connection or a wireless connection. Among them, the above-mentioned compressor fault warning overview page can be a page that displays the fault-related information of various types of compressors. Each type of compressor is displayed in the above-mentioned compressor fault warning overview page. The above-mentioned fault-related information can include but is not limited to at least one of the following: a three-dimensional model of the compressor, the fault name of the compressor. Here, the compressor can be a hydrogen compressor. The above-mentioned selection operation can include but is not limited to at least one of the following: clicking, hovering, dragging. The above-mentioned compressor operation data can be various index data when the above-mentioned any compressor is operating. The above-mentioned compressor operation data includes a historical compressor operation data set and real-time compressor operation data. Each historical compressor operation data in the above-mentioned historical compressor operation data set corresponds to a historical moment in a historical time period. The respective historical moments corresponding to the above-mentioned historical compressor operation data set are arranged in continuous ascending order. The above-mentioned historical compressor operation data includes respective historical index values corresponding to each index. Here, each index can include but is not limited to: operating current, gas seal differential pressure of the group, inlet pressure of the first stage of the unit, exhaust pressure of the first stage of the unit, exhaust pressure of the group, inlet temperature of the group, exhaust temperature of the first stage of the unit, inlet temperature of the second stage of the unit, exhaust temperature of the second stage of the unit, shaft displacement. The above-mentioned real-time compressor operation data can be the real-time index values of each index of the above-mentioned any compressor at the current moment.

[0027] It should be noted that the above-mentioned wireless connection method can include but is not limited to 3G / 4G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other currently known or future-developed wireless connection methods.

[0028] Step 102, generate predicted compressor data corresponding to the current moment and a sequence of predicted compressor data corresponding to a future time period according to the historical compressor operation data set and the real-time compressor operation data.

[0029] In some embodiments, the above-mentioned execution subject can generate predicted compressor data corresponding to the current moment and a sequence of predicted compressor data corresponding to a future time period according to the above-mentioned historical compressor operation data set and the above-mentioned real-time compressor operation data.

[0030] In some optional implementation manners of some embodiments, the above-mentioned execution subject can generate predicted compressor data corresponding to the current moment and a sequence of predicted compressor data corresponding to a future time period according to the above-mentioned historical compressor operation data set and the above-mentioned real-time compressor operation data through the following steps:

[0031] First step, for each of the above-mentioned indicators corresponding to the real-time compressor operation data, perform the following steps:

[0032] First sub-step, combine each historical indicator value corresponding to the above-mentioned indicator in the above-mentioned historical compressor operation data set into a historical indicator value sequence.

[0033] Second sub-step, according to the above-mentioned historical indicator value sequence, construct each indicator prediction model corresponding to the above-mentioned indicator. In practice, the above-mentioned execution entity can respectively construct at least two of the following models according to the above-mentioned historical indicator value sequence: linear regression model, moving average model, exponential moving average model, Gaussian process model, and hidden Markov model. Then, the constructed models can be determined as each indicator prediction model.

[0034] Third sub-step, according to the above-mentioned current moment and each indicator prediction model, generate each first predicted indicator value of the above-mentioned indicator at the above-mentioned current moment. Among them, the indicator prediction model in each of the above-mentioned indicator prediction models corresponds to the first predicted indicator value in each of the above-mentioned first predicted indicator values. In practice, the above-mentioned execution entity can use the above-mentioned current moment as an independent variable, and determine each dependent variable corresponding to the above-mentioned current moment of each indicator prediction model as each first predicted indicator value.

[0035] Fourth sub-step, determine the real-time indicator value corresponding to the above-mentioned indicator in the above-mentioned real-time compressor operation data as the target indicator value.

[0036] Fifth sub-step, in response to determining that the above-mentioned indicator meets the minimum limit condition, determine each first predicted indicator value less than or equal to the above-mentioned target indicator value among the generated first predicted indicator values as each second predicted indicator value. Among them, the above-mentioned minimum limit condition can be that the above-mentioned indicator is an indicator that needs to limit the minimum value.

[0037] Sixth sub-step, determine the second predicted indicator value that meets the first preset threshold condition among the above-mentioned second predicted indicator values as the third predicted indicator value. Among them, the above-mentioned first preset threshold condition can be that the difference between the above-mentioned target indicator value and the third predicted indicator value is the smallest.

[0038] Seventh sub-step, determine the indicator prediction model corresponding to the above-mentioned third predicted indicator value among the above-mentioned indicator prediction models as the target indicator prediction model.

[0039] Eighth sub-step, according to the determined target indicator prediction model, generate the predicted indicator value of the above-mentioned indicator at the above-mentioned current moment. In practice, the above-mentioned execution entity can use the above-mentioned current moment as an independent variable, and determine the predicted indicator value corresponding to the above-mentioned current moment of the above-mentioned target indicator prediction model.

[0040] The ninth sub-step is to generate a sequence of predicted index values of the above-mentioned index for the above-mentioned future time period according to the above-mentioned target index prediction model. In practice, the above-mentioned execution entity may use each future moment corresponding to the above-mentioned future time period as an independent variable to determine each predicted index value of the above-mentioned target index prediction model corresponding to each future moment. Then, the determined predicted index values corresponding to each future moment can be combined into a sequence of predicted index values.

[0041] The second step is to determine the predicted compressor data by using the generated predicted index values corresponding to the current moment.

[0042] The third step is to generate a sequence of predicted compressor data corresponding to the above-mentioned future time period according to the sequence of predicted index values corresponding to the above-mentioned future time period.

[0043] Optionally, after the above-mentioned fourth sub-step, the above-mentioned execution entity may also perform the following steps:

[0044] The first step is to, in response to determining that the above-mentioned index meets the height limit condition, determine each fourth predicted index value that is greater than or equal to the above-mentioned target index value among the generated first predicted index values. Among them, the above-mentioned height limit condition may be that the above-mentioned index is an index for which the maximum value needs to be restricted.

[0045] The second step is to determine the fifth predicted index value from the fourth predicted index values that meet the second preset threshold condition. Among them, the above-mentioned second preset threshold condition may be that the difference between the fifth predicted index value and the above-mentioned target index value is the smallest.

[0046] The third step is to determine the index prediction model corresponding to the fifth predicted index value among the above-mentioned index prediction models as the target index prediction model. Thus, an index prediction model with a relatively high prediction accuracy can be selected for the index with a height limit.

[0047] Optionally, after the above-mentioned fourth sub-step, the above-mentioned execution entity may also perform the following steps:

[0048] The first step is to, in response to determining that the above-mentioned index meets the double limit condition, determine the sixth predicted index value from the first predicted index values that meet the third preset threshold condition. Among them, the above-mentioned double limit condition may be that the above-mentioned index is an index for which the maximum value and the minimum value need to be restricted. The above-mentioned third preset threshold condition may be that the distance between the sixth predicted index value and the above-mentioned target index value is the smallest.

[0049] The second step is to determine the index prediction model corresponding to the sixth predicted index value among the above-mentioned index prediction models as the target index prediction model. Thus, an index prediction model with a relatively high prediction accuracy can be selected for the index with a height limit and a defined limit.

[0050] In some alternative implementations of some embodiments, the above-mentioned execution entity may generate a predicted compressor data sequence corresponding to the above-mentioned future time period according to each sequence of predicted index values corresponding to the above-mentioned future time period through the following steps:

[0051] First step, for each future moment included in the above-mentioned future time period, perform the following steps:

[0052] First sub-step, for each sequence of predicted index values in the above-mentioned sequences of predicted index values, extract the predicted index value corresponding to the above-mentioned future moment from the sequence of predicted index values.

[0053] Second sub-step, determine the extracted predicted index values as the predicted compressor data corresponding to the above-mentioned future moment.

[0054] Second step, determine the determined predicted compressor data as the predicted compressor data sequence.

[0055] Step 103, extract each predicted index value corresponding to the target index from the predicted compressor data sequence as the sequence of predicted index values.

[0056] In some embodiments, the above-mentioned execution entity may extract each predicted index value corresponding to the target index from the predicted compressor data sequence as the sequence of predicted index values. Among them, the above-mentioned target index may be the default index of any of the above-mentioned compressors set in advance. The above-mentioned target index may also be the index of any of the above-mentioned compressors currently selected by the user.

[0057] Step 104, display the compressor fault prediction page corresponding to the compressor.

[0058] In some embodiments, the above-mentioned execution entity may display a compressor fault prediction page corresponding to the above-mentioned compressor. Among them, the above-mentioned compressor fault prediction page may be a page for displaying information related to fault prediction of any of the above-mentioned compressors. The compressor fault prediction page displays a compressor fault prediction list and a trend curve graph corresponding to the above-mentioned target indicator. The above-mentioned compressor fault prediction list may be a list that displays the predicted index values of any of the above-mentioned compressors. The predicted compressor data and the real-time compressor operation data may be displayed in the above-mentioned compressor fault prediction list. Each row in the above-mentioned compressor fault prediction list corresponds to an indicator. The respective columns corresponding to the above-mentioned compressor fault prediction list may include, but are not limited to, the following fields: indicator name, indicator unit, real-time indicator value, predicted indicator value, deviation, warning threshold, alarm lower limit value, alarm upper limit value, status. The above-mentioned trend curve graph may be a trend graph of the above-mentioned target indicator. The actual value curve, predicted curve, and threshold line corresponding to the above-mentioned target indicator may be displayed in the above-mentioned trend curve graph. The above-mentioned actual value curve may be a curve formed by connecting the respective actual indicator values of the above-mentioned target indicator at each historical moment and the current moment. The above-mentioned predicted curve is constructed based on the above-mentioned sequence of predicted indicator values. The above-mentioned predicted curve may be a curve formed by connecting the respective predicted indicator values of the above-mentioned target indicator at each historical moment and the current moment. The above-mentioned threshold line may be a straight line where the alarm threshold of the above-mentioned target indicator is located. The above-mentioned alarm threshold may include an alarm upper limit value and / or an alarm lower limit value.

[0059] Step 105, in response to determining that the real-time indicator value of any indicator in the compressor fault prediction list does not meet the alarm condition corresponding to any indicator, and the predicted indicator value of any indicator meets the warning condition, display a warning indicator at the position corresponding to any indicator in the status column of the compressor fault prediction list.

[0060] In some embodiments, the above-mentioned execution entity may, in response to determining that the real-time indicator value of any indicator in the above-mentioned compressor fault prediction list does not meet the alarm condition corresponding to any indicator, and the predicted indicator value of any indicator meets the warning condition, display a warning indicator at the position corresponding to any indicator in the status column of the above-mentioned compressor fault prediction list. Among them, the above-mentioned alarm condition may be that the real-time indicator value is within the alarm value range of any indicator. Here, the alarm value range for any indicator is not limited. The above-mentioned warning condition may be that the predicted indicator value is within the warning value range of any indicator. Here, the warning value range for any indicator is not limited. The above-mentioned warning indicator may be an icon representing a warning. Here, the specific setting of the warning indicator is not limited.

[0061] Step 106, in response to determining that the real-time indicator value meets the alarm condition, display an alarm indicator at the position corresponding to any indicator in the status column of the compressor fault prediction list.

[0062] In some embodiments, the above-mentioned execution entity may, in response to determining that the above-mentioned real-time metric value meets the above-mentioned alarm condition, display an alarm identifier at the position corresponding to any of the above-mentioned metrics in the status column of the above-mentioned compressor fault prediction list. Wherein, the above-mentioned early warning identifier may be an icon representing an alarm. Here, no limitation is imposed on the specific setting of the alarm identifier.

[0063] Step 107, determine whether there is a fault information in the fault information set corresponding to any compressor that matches the real-time compressor operation data.

[0064] In some embodiments, the above-mentioned execution entity may determine whether there is a fault information in the fault information set corresponding to any compressor that matches the above-mentioned real-time compressor operation data. Wherein, the fault information in the above-mentioned fault information set may include a fault name, fault cause information, and maintenance suggestion information.

[0065] Optionally, the above-mentioned real-time compressor operation data may include real-time lubricating oil pressure. Here, the lubricating oil pressure may be the pressure measured by a lubricating oil pressure gauge. The historical compressor operation data in the above-mentioned historical compressor operation data set may include historical lubricating oil pressure.

[0066] In some optional implementation manners of some embodiments, the above-mentioned execution entity may determine whether there is a fault information in the fault information set corresponding to any compressor that matches the above-mentioned real-time compressor operation data through the following steps:

[0067] First step, determine each historical lubricating oil pressure included in the above-mentioned historical compressor operation data set as a historical lubricating oil pressure sequence.

[0068] Second step, determine the historical lubricating oil pressure that meets the preset time condition in the above-mentioned historical lubricating oil pressure sequence as the target historical lubricating oil pressure. Wherein, the above-mentioned preset time condition may be that the historical moment corresponding to the target historical lubricating oil pressure is the closest to the current moment.

[0069] Third step, in response to determining that the difference between the above-mentioned target historical lubricating oil pressure and the above-mentioned real-time lubricating oil pressure is greater than the preset lubricating oil pressure difference, determine whether the above-mentioned real-time lubricating oil pressure is less than the preset lubricating oil pressure. Here, the preset lubricating oil pressure may be 0.1 Mpa. No limitation is imposed on the specific setting of the preset lubricating oil pressure difference and the preset lubricating oil pressure.

[0070] Step 4, in response to determining that the above-mentioned real-time lubricating oil pressure is less than the above-mentioned preset lubricating oil pressure, determine that there is a fault information in the above-mentioned fault information set that matches the above-mentioned real-time compressor operation data, and determine the fault information with the fault name of sudden drop in lubricating oil pressure included in the above-mentioned fault information set as the fault information that matches the above-mentioned real-time compressor operation data. As an example, the fault cause information included in the fault information with the fault name of sudden drop in lubricating oil pressure may be: (1) insufficient lubricating oil in the fuselage; (2) blockage of the filter and filter element; (3) malfunction of the oil pressure gauge; (4) blockage or rupture of the oil pump pipeline; (5) loss of function of the oil pump. The maintenance suggestion information included in the fault information with the fault name of sudden drop in lubricating oil pressure may be: "Refuel immediately, clean, replace the oil pressure gauge, repair the oil pipeline and oil pump gear." Thus, the fault detection of sudden drop in lubricating oil pressure of the compressor can be carried out.

[0071] Step 5, in response to determining that the difference between the above-mentioned target historical lubricating oil pressure and the above-mentioned real-time lubricating oil pressure is less than the above-mentioned preset lubricating oil pressure difference and greater than 0, determine whether the preset number of historical lubricating oil pressures arranged before the above-mentioned target historical lubricating oil pressure in the above-mentioned historical lubricating oil pressure sequence all meet the decreasing condition. Wherein, the above-mentioned decreasing condition may be that the historical lubricating oil pressure is less than the previous historical lubricating oil pressure. Here, the previous historical lubricating oil pressure may be the historical lubricating oil pressure arranged before the current historical lubricating oil pressure in the above-mentioned historical lubricating oil pressure sequence. The above-mentioned preset number may be 4. For the specific setting of the preset number, no limitation is made.

[0072] Step 6, in response to determining that the preset number of historical lubricating oil pressures arranged before the above-mentioned target historical lubricating oil pressure in the above-mentioned historical lubricating oil pressure sequence all meet the above-mentioned decreasing condition, determine that there is a fault information in the above-mentioned fault information set that matches the above-mentioned real-time compressor operation data, and determine the fault information with the fault name of gradual drop in lubricating oil pressure included in the above-mentioned fault information set as the fault information that matches the above-mentioned real-time compressor operation data. As an example, the fault cause information included in the fault information with the fault name of gradual drop in lubricating oil pressure may be: (1) the connection parts of the oil pipeline are not tight; (2) the shaft bush of the moving mechanism is worn too much; (3) the oil filter screen is gradually blocked; (4) the oil pump gear is worn and the axial clearance is large. The maintenance suggestion information included in the fault information with the fault name of gradual drop in lubricating oil pressure may be: "Check, tighten or replace the gasket, repair the shaft bush, and clean the filter screen." Thus, the fault detection of gradual drop in lubricating oil pressure of the compressor can be carried out.

[0073] Step 108, in response to determining that there is a fault information in the fault information set corresponding to any compressor that matches the real-time compressor operation data, determine the fault information that matches the real-time compressor operation data as the target fault information.

[0074] In some embodiments, the above-mentioned execution entity may, in response to determining that there is a fault information in the set of fault information corresponding to any of the above-mentioned compressors that matches the real-time compressor operation data, determine the fault information that matches the real-time compressor operation data as the target fault information.

[0075] Step 109, display the fault name included in the target fault information on the compressor fault prediction page.

[0076] In some embodiments, the above-mentioned execution entity may display the fault name included in the above-mentioned target fault information on the compressor fault prediction page. In practice, the above-mentioned execution entity may cyclically display the fault name in the fault information scrolling area of the compressor fault prediction page.

[0077] Step 110, in response to detecting a selection operation on the fault name, display the fault cause information and maintenance suggestion information included in the target fault information.

[0078] In some embodiments, the above-mentioned execution entity may, in response to detecting a selection operation on the above-mentioned fault name, display the fault cause information and maintenance suggestion information included in the above-mentioned target fault information. In practice, the above-mentioned execution entity may display the fault cause information and maintenance suggestion information included in the above-mentioned target fault information in a drop-down box corresponding to the fault name.

[0079] Optionally, first, the above-mentioned execution entity may also, in response to determining that any real-time index value corresponding to the temperature in the real-time compressor operation data meets the target temperature shutdown condition, control any of the above-mentioned compressors to stop operating. Wherein, any real-time index value corresponding to the temperature may be a real-time index value of any index related to the temperature. The above-mentioned target temperature shutdown condition may be that any real-time index value corresponding to the temperature is within the shutdown numerical range of the corresponding index. The shutdown numerical range of the temperature index may be preset in advance. Thus, the compressor can be controlled to shut down when any temperature index reaches the shutdown condition.

[0080] Then, in response to determining that any real-time index value corresponding to the pressure in the real-time compressor operation data meets the target pressure shutdown condition, determine whether the any real-time index value that meets the above-mentioned target pressure shutdown condition meets the preset adjustment condition. Wherein, any real-time index value corresponding to the pressure may be a real-time index value of any index related to the pressure. The above-mentioned target pressure shutdown condition may be that any real-time index value corresponding to the pressure is within the shutdown numerical range of the corresponding index. The shutdown numerical range of the pressure index may be preset in advance. The above-mentioned preset adjustment condition may be that the index value of the index that meets the above-mentioned target pressure shutdown condition is adjustable. Here, adjustable may mean adjustable by an automatic control method.

[0081] After that, in response to determining that any of the above real-time index values that satisfy the above target pressure shutdown condition do not satisfy the above preset adjustment condition, control any of the above compressors to stop running. Thus, the compressor can be controlled to stop when any pressure index reaches the shutdown condition.

[0082] Finally, in response to determining that any of the real-time index values corresponding to the current in the above real-time compressor operation data satisfy the target current sudden increase condition, control any of the above compressors to stop running, where the target current sudden increase condition is that the difference between any of the real-time index values corresponding to the current and the target historical current index value is greater than the preset current intensity. The above target historical current index value corresponds to the same index as any of the real-time index values corresponding to the current. The above target historical current index value and the moment corresponding to any of the real-time index values corresponding to the current are adjacent. Thus, the compressor can be controlled to stop when any current index reaches the shutdown condition.

[0083] In some optional implementation manners of some embodiments, the above execution entity can control any of the above compressors to stop running through the following steps:

[0084] First step, control any of the above compressors to run under no load. In practice, the above execution entity can control any of the above compressors to unload the load, so that any of the above compressors enters the no-load operation state.

[0085] Second step, control any of the above compressors to disconnect the power connection with the associated device. Among them, the associated device can be a device that needs the compressor to provide compressed gas. For example, the associated device can be an electric motor. Thus, the associated device can be stopped from running.

[0086] Third step, control any of the above compressors to close the cooling water inlet valve.

[0087] Fourth step, control any of the above compressors to open the drain valve. Thus, the stored water in the cylinder and cooler can be discharged to avoid corrosion and freezing of the machine.

[0088] Fifth step, control any of the above compressors to close the inlet pipeline stop valve and the exhaust pipeline stop valve. Thus, the stop operation of the compressor can be realized.

[0089] Optionally, the above execution entity can also execute the following steps:

[0090] First step, in response to detecting a viewing operation on the index configuration page for any of the above compressors, display the index configuration page. Among them, the index configuration page can be a page for configuring various indexes of any of the above compressors. The index configuration page displays an index addition control and each index information of any of the above compressors configured previously. The index information in each of the above index information includes index name, warning configuration threshold information, alarm configuration threshold information, and shutdown condition information. The warning configuration threshold information can be the warning threshold of the index. The alarm configuration threshold information can include an alarm upper limit and an alarm lower limit. The shutdown condition information can be various conditions that need to be met for the compressor to stop running.

[0091] Second step, in response to detecting a selection operation on the above index addition control, display an index addition window. Among them, the index addition window displays an index name input control, a warning configuration threshold information input control, an alarm configuration threshold information input control, and a shutdown condition information input control. The index name input control, the warning configuration threshold information input control, and the alarm configuration threshold information input control can be text input boxes. The shutdown condition information input control can be each control for configuring each shutdown condition. There is a relationship configuration control corresponding to each control. The relationship configuration control can be used to select the logical relationship between conditions.

[0092] Third step, in response to detecting a viewing operation on the fault information configuration page for any of the above compressors, display the fault information configuration page. Among them, the fault information configuration page can be a page for configuring the fault information of any of the above compressors. The fault information configuration page displays the above fault information set and a fault information addition control.

[0093] Fourth step, in response to detecting a selection operation on the above fault information addition control, display a fault information addition window. Among them, the fault information addition window displays a fault name input control, a fault cause information input control, a maintenance suggestion information input control, and a fault rule information input control. The fault name input control, the fault cause information input control, and the maintenance suggestion information input control can be text input boxes. The above fault rule information input control can be each control for configuring each condition for matching fault information. There is a relationship configuration control corresponding to each control.

[0094] Fifth step, create fault information according to each input operation on the above fault name input control, the above fault cause information input control, the above maintenance suggestion information input control, and the above fault rule information input control. In practice, the above execution entity can combine the input fault name, fault cause information, maintenance suggestion information, and fault rule information into fault information.

[0095] Step 6: Add the created fault information to the above fault information set to update the above fault information set.

[0096] The above content, as an inventive point of an embodiment of the present disclosure, solves Technical Problem 2 mentioned in the background art, "The degree of automation for handling compressor abnormal events is relatively low, and the method of reaching the event site or notifying the event site to handle compressor abnormal events results in a relatively long time for handling compressor abnormalities." The factors that often lead to a relatively long time for handling compressor abnormalities are as follows: The degree of automation for handling compressor abnormal events is relatively low, and the method of reaching the event site or notifying the event site to handle compressor abnormal events results in a relatively long time for handling compressor abnormalities. If the above factors are solved, the effect of reducing the time for handling compressor abnormalities can be achieved. To achieve this effect, the present disclosure can automatically determine whether the compressor meets the shutdown condition through the configuration of the shutdown condition, so that the compressor can be shut down when the shutdown condition is met. Thereby, the degree of automation for handling compressor abnormal events is improved, and the time for handling compressor abnormalities is reduced.

[0097] The above embodiments of the present disclosure have the following beneficial effects: Through the compressor fault warning method of some embodiments of the present disclosure, automatic warning can be performed according to the operation trend of the compressor, and there is no need for manual determination of compressor faults. Specifically, the reason for the inability to perform warning according to the operation trend of the compressor and the need for manual determination of compressor faults is as follows: Hierarchical alarms all judge based on the real-time operation data of the compressor, and cannot perform warning according to the operation trend of the compressor, resulting in technicians being unable to make countermeasures in advance, and technicians need to analyze compressor faults based on alarm events. Based on this, in the compressor fault warning method of some embodiments of the present disclosure, first, in response to detecting a selection operation on any compressor displayed in the compressor fault warning overview page, obtain the compressor operation data of the above-mentioned any compressor. Among them, various types of compressors are displayed in the compressor fault warning overview page. The above-mentioned compressor operation data includes a historical compressor operation data set and real-time compressor operation data. Thus, the operation data of the compressor selected by the user to monitor its operation status can be automatically obtained. Then, according to the above-mentioned historical compressor operation data set and the above-mentioned real-time compressor operation data, generate predicted compressor data corresponding to the current moment and a predicted compressor data sequence corresponding to a future time period. Thus, the operation status of the selected compressor is predicted in real time and predicted in advance. After that, extract each predicted index value corresponding to the target index from the above-mentioned predicted compressor data sequence as a predicted index value sequence. Thus, the predicted index value sequence can be used as each predicted value of the target index. Secondly, display a compressor fault prediction page corresponding to the above-mentioned compressor. Among them, a compressor fault prediction list and a trend curve graph corresponding to the above-mentioned target index are displayed on the compressor fault prediction page. The above-mentioned compressor fault prediction list displays the above-mentioned predicted compressor data and the above-mentioned real-time compressor operation data. The above-mentioned trend curve graph displays the actual value curve, prediction curve, and threshold line corresponding to the above-mentioned target index. The above-mentioned prediction curve is constructed according to the above-mentioned predicted index value sequence. Thus, the overall operation data of the compressor and the operation trend of the target index can be visualized in the form of a list and a trend graph. Then, in response to determining that the real-time index value of any index in the above-mentioned compressor fault prediction list does not meet the alarm condition corresponding to the above-mentioned any index, and the predicted index value of the above-mentioned any index meets the warning condition, display a warning identifier at the position corresponding to the above-mentioned any index in the status column of the above-mentioned compressor fault prediction list. Thus, when the predicted index value of the compressor at the current moment meets the warning condition, the user can be prompted to pay attention to this index of the compressor with a warning identifier. Then, in response to determining that the real-time index value meets the above-mentioned alarm condition, display an alarm identifier at the position corresponding to the above-mentioned any index in the status column of the above-mentioned compressor fault prediction list. Thus, when the actual index value of the compressor at the current moment meets the alarm condition, the user can be warned to handle the abnormality of the compressor in this index with an alarm identifier.After that, it is determined whether there is a fault information that matches the above real-time compressor operation data in the fault information set corresponding to any of the above compressors. Among them, the fault information in the above fault information set includes a fault name, fault cause information, and maintenance suggestion information. Thus, fault detection of the real-time operation data of the compressor can be realized. Then, in response to determining that there is a fault information that matches the above real-time compressor operation data in the fault information set corresponding to any of the above compressors, the fault information that matches the above real-time compressor operation data is determined as the target fault information. Thus, the fault information can be matched from each pre-configured fault information. Secondly, the fault name included in the above target fault information is displayed on the compressor fault prediction page. Thus, the matched fault information can be prompted. Finally, in response to detecting a selection operation on the above fault name, the fault cause information and maintenance suggestion information included in the above target fault information are displayed. Thus, when the user selects to view the detailed information of the fault name, the corresponding fault cause information and maintenance suggestion information can be displayed. Also, because the early warning of the compressor is based on the predicted index value at the current moment, the predicted index value at the current moment can characterize the index change trend at the current moment, and the displayed trend curve graph can characterize the index change trend in the future time period, so the method of hierarchical alarm can be avoided, and early warning can be carried out according to the operation trend of the compressor. Furthermore, technicians can pre-pay attention to the indexes of the compressors with early warnings. Also, because fault detection of the real-time operation data of the compressor can be realized, the fault cause information and maintenance suggestion information included in the matched fault information can be directly viewed without manually determining the compressor fault. Thus, automatic early warning can be carried out according to the operation trend of the compressor without manually determining the compressor fault.

[0098] Further reference is made to Figure 2 , as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a compressor fault warning device. These device embodiments correspond to Figure 1 the method embodiments shown, and the device can be specifically applied to various electronic devices.

[0099] As Figure 2As shown in the figure, the compressor fault warning device 200 of some embodiments includes: an acquisition unit 201, a generation unit 202, an extraction unit 203, a first display unit 204, a second display unit 205, a third display unit 206, a first determination unit 207, a second determination unit 208, a fourth display unit 209, and a fifth display unit 210.Among them, the acquisition unit 201 is configured to obtain the compressor operation data of any of the compressors in response to detecting a selection operation on any of the compressors displayed on the compressor fault warning overview page. Among them, various types of compressors are displayed on the compressor fault warning overview page, and the compressor operation data includes a historical compressor operation data set and real-time compressor operation data; the generation unit 202 is configured to generate predicted compressor data corresponding to the current moment and a sequence of predicted compressor data corresponding to a future time period according to the historical compressor operation data set and the real-time compressor operation data; the extraction unit 203 is configured to extract each predicted index value corresponding to a target index from the sequence of predicted compressor data as a sequence of predicted index values; the first display unit 204 is configured to display a compressor fault prediction page corresponding to the compressor. Among them, a compressor fault prediction list and a trend curve graph corresponding to the target index are displayed on the compressor fault prediction page. The predicted compressor data and the real-time compressor operation data are displayed in the compressor fault prediction list. The trend curve graph displays an actual value curve, a predicted curve, and a threshold line corresponding to the target index. The predicted curve is constructed according to the sequence of predicted index values; the second display unit 205 is configured to, in response to determining that the real-time index value of any index in the compressor fault prediction list does not meet the alarm condition corresponding to the any index, and the predicted index value of the any index meets the warning condition, display a warning identifier at the position corresponding to the any index in the status column of the compressor fault prediction list; the third display unit 206 is configured to, in response to determining that the real-time index value meets the alarm condition, display an alarm identifier at the position corresponding to the any index in the status column of the compressor fault prediction list; the first determination unit 207 is configured to determine whether there is a fault information in the fault information set corresponding to the any compressor that matches the real-time compressor operation data. Among them, the fault information in the fault information set includes a fault name, fault cause information, and maintenance suggestion information; the second determination unit 208 is configured to, in response to determining that there is a fault information in the fault information set corresponding to the any compressor that matches the real-time compressor operation data, determine the fault information that matches the real-time compressor operation data as the target fault information; the fourth display unit 209 is configured to display the fault name included in the target fault information on the compressor fault prediction page; the fifth display unit 210 is configured to, in response to detecting a selection operation on the fault name, display the fault cause information and maintenance suggestion information included in the target fault information.

[0100] It can be understood that the units described in the device 200 and the reference Figure 1corresponds to each step in the described method. Thus, the operations, features, and beneficial effects described above for the method also apply to the apparatus 200 and the units included therein, and will not be elaborated herein.

[0101] Reference is made below to Figure 3 , which shows a schematic structural diagram of an electronic device 300 (such as a computing device) suitable for use in implementing some embodiments of the present disclosure. Figure 3 The illustrated electronic device is merely an example and should not impose any limitation on the functions and usage scope of the embodiments of the present disclosure.

[0102] As Figure 3 shown, the electronic device 300 may include a processing device 301 (such as a central processing unit, a graphics processing unit, etc.), which may perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other through a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0103] Generally, the following devices may be connected to the I / O interface 305: an input device 306 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 308 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 309. The communication device 309 may allow the electronic device 300 to communicate with other devices wirelessly or wiredly to exchange data. Although Figure 3 shows the electronic device 300 having various devices, it should be understood that it is not required to implement or include all the shown devices. More or fewer devices may be alternatively implemented or included. Figure 3 Each block shown in

[0104] In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product that includes a computer program carried on a computer-readable medium, and the computer program contains program code for performing the methods shown in the flowcharts. In such some embodiments, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the methods of some embodiments of the present disclosure are performed.

[0105] It should be noted that the computer-readable medium described in some embodiments of the present disclosure can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, the computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, in which computer-readable program code is carried. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable signal medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0106] In some embodiments, the client and the server can communicate using any currently known or future-developed network protocol such as HTTP (HyperText Transfer Protocol), and can be interconnected with digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet), and end-to-end networks (e.g., ad hoc end-to-end networks), as well as any currently known or future-developed networks.

[0107] The above computer-readable medium may be included in the above electronic device; or it may exist independently and not be assembled into the electronic device. The above computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device is caused to: in response to detecting a selection operation on any compressor displayed in the compressor fault warning overview page, obtain the compressor operation data of the any compressor, wherein various types of compressors are displayed in the compressor fault warning overview page, and the compressor operation data includes a historical compressor operation data set and real-time compressor operation data; generate predicted compressor data corresponding to the current moment and a predicted compressor data sequence corresponding to a future time period according to the historical compressor operation data set and the real-time compressor operation data; extract each predicted index value corresponding to a target index from the predicted compressor data sequence as a predicted index value sequence; display a compressor fault prediction page corresponding to the compressor, wherein a compressor fault prediction list and a trend curve graph corresponding to the target index are displayed in the compressor fault prediction page, the predicted compressor data and the real-time compressor operation data are displayed in the compressor fault prediction list, the trend curve graph displays an actual value curve, a predicted curve, and a threshold line corresponding to the target index, and the predicted curve is constructed according to the predicted index value sequence; in response to determining that the real-time index value of any index in the compressor fault prediction list does not meet the alarm condition corresponding to the any index, and the predicted index value of the any index meets the warning condition, display a warning identifier at the position corresponding to the any index in the status column of the compressor fault prediction list; in response to determining that the real-time index value meets the alarm condition, display an alarm identifier at the position corresponding to the any index in the status column of the compressor fault prediction list; determine whether there is a fault information that matches the real-time compressor operation data in the fault information set corresponding to the any compressor, wherein the fault information in the fault information set includes a fault name, fault cause information, and maintenance suggestion information; in response to determining that there is a fault information that matches the real-time compressor operation data in the fault information set corresponding to the any compressor, determine the fault information that matches the real-time compressor operation data as the target fault information; display the fault name included in the target fault information in the compressor fault prediction page; in response to detecting a selection operation on the fault name, display the fault cause information and maintenance suggestion information included in the target fault information.

[0108] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages or combinations thereof. The above-mentioned programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0109] 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 may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing a 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 may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system that performs the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0110] The units described in some embodiments of the present disclosure may be implemented in software or in hardware. The described units may also be provided in a processor. For example, it may be described as: a processor includes: an acquisition unit, a generation unit, an extraction unit, a first display unit, a second display unit, a third display unit, a first determination unit, a second determination unit, a fourth display unit, and a fifth display unit. Among them, the names of these units do not constitute a limitation on the unit itself in some cases. For example, the acquisition unit may also be described as "the unit that acquires the compressor operation data of any compressor in response to detecting a selection operation on any compressor displayed in the compressor fault warning overview page".

[0111] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that can be used include: Field Programmable Gate Arrays (FPGA), Application Specific Integrated Circuits (ASIC), Application Specific Standard Products (ASSP), System on a Chip (SOC), Complex Programmable Logic Devices (CPLD), and so on.

[0112] The above description is only some preferred embodiments of the present disclosure and an explanation of the technical principles applied. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A compressor fault warning method, comprising: Responding to a selection operation detected on any compressor displayed in the compressor fault warning overview page, obtaining the compressor operation data of the any compressor, wherein various types of compressors are displayed in the compressor fault warning overview page, and the compressor operation data includes a historical compressor operation data set and real-time compressor operation data; Generating predicted compressor data corresponding to the current moment and a predicted compressor data sequence corresponding to a future time period according to the historical compressor operation data set and the real-time compressor operation data; Extracting each predicted index value corresponding to a target index from the predicted compressor data sequence as a predicted index value sequence; Displaying a compressor fault prediction page corresponding to the compressor, wherein a compressor fault prediction list and a trend curve graph corresponding to the target index are displayed in the compressor fault prediction page, the predicted compressor data and the real-time compressor operation data are displayed in the compressor fault prediction list, and an actual value curve, a predicted curve and a threshold line corresponding to the target index are displayed in the trend curve graph, and the predicted curve is constructed according to the predicted index value sequence; Responding to determining that the real-time index value of any index in the compressor fault prediction list does not meet the alarm condition corresponding to the any index, and the predicted index value of the any index meets the warning condition, displaying a warning identifier at the position corresponding to the any index in the status column of the compressor fault prediction list; Responding to determining that the real-time index value meets the alarm condition, displaying an alarm identifier at the position corresponding to the any index in the status column of the compressor fault prediction list; Determining whether there is a fault information in the fault information set corresponding to the any compressor that matches the real-time compressor operation data, wherein the fault information in the fault information set includes a fault name, fault cause information and maintenance suggestion information; Responding to determining that there is a fault information in the fault information set corresponding to the any compressor that matches the real-time compressor operation data, determining the fault information that matches the real-time compressor operation data as the target fault information; Displaying the fault name included in the target fault information on the compressor fault prediction page; Responding to a selection operation detected on the fault name, displaying the fault cause information and maintenance suggestion information included in the target fault information.

2. The method according to claim 1, wherein, The generating predicted compressor data corresponding to the current moment and a predicted compressor data sequence corresponding to a future time period according to the historical compressor operation data set and the real-time compressor operation data includes: For each index corresponding to the real-time compressor operation data, performing the following steps: Combining each historical index value corresponding to the index in the historical compressor operation data set into a historical index value sequence; Constructing each index prediction model corresponding to the index according to the historical index value sequence; Generate respective first predicted index values of the index at the current moment according to the current moment and the respective index prediction models, where the index prediction model in the respective index prediction models corresponds to the first predicted index value in the respective first predicted index values; Determine the real-time index value corresponding to the index in the real-time compressor operation data as the target index value; In response to determining that the index meets the lower limit condition, determine the first predicted index values less than or equal to the target index value among the generated first predicted index values as respective second predicted index values; Determine the second predicted index values that meet the first preset threshold condition among the respective second predicted index values as third predicted index values; Determine the index prediction model corresponding to the third predicted index value among the respective index prediction models as the target index prediction model; Generate the predicted index value of the index at the current moment according to the determined target index prediction model; Generate a sequence of predicted index values of the index for the future time period according to the target index prediction model; Determine the respective predicted index values corresponding to the current moment as predicted compressor data; Generate a sequence of predicted compressor data corresponding to the future time period according to the generated sequences of respective predicted index values corresponding to the future time period.

3. The method according to claim 2, wherein, After determining the real-time index value corresponding to the index in the real-time compressor operation data as the target index value, the method further includes: In response to determining that the index meets the upper limit condition, determine the first predicted index values greater than or equal to the target index value among the generated first predicted index values as respective fourth predicted index values; Determine the fourth predicted index values that meet the second preset threshold condition among the respective fourth predicted index values as fifth predicted index values; Determine the index prediction model corresponding to the fifth predicted index value among the respective index prediction models as the target index prediction model.

4. The method according to claim 3, wherein After determining the real-time index value corresponding to the index in the real-time compressor operation data as the target index value, the method further includes: In response to determining that the index meets the double limit condition, determine the first predicted index values that meet the third preset threshold condition among the generated first predicted index values as sixth predicted index values; Determine the index prediction model corresponding to the sixth predicted index value among the respective index prediction models as the target index prediction model.

5. The method according to claim 3, wherein The generating a sequence of predicted compressor data corresponding to the future time period according to the generated sequences of respective predicted index values corresponding to the future time period includes: For each future moment included in the future time period, perform the following steps: For each sequence of predicted index values among the sequences of respective predicted index values, extract the predicted index value corresponding to the future moment from the sequence of predicted index values; Determine the extracted respective predicted index values as the predicted compressor data corresponding to the future moment; Determine the determined respective predicted compressor data as the sequence of predicted compressor data.

6. The method according to claim 1, wherein, The method further includes: In response to determining that any real-time index value corresponding to the temperature in the real-time compressor operation data meets the target temperature shutdown condition, control the any compressor to stop operating; In response to determining that any real-time index value corresponding to the pressure in the real-time compressor operation data meets the target pressure shutdown condition, determine whether the any real-time index value that meets the target pressure shutdown condition meets the preset adjustment condition; In response to determining that the any real-time index value that meets the target pressure shutdown condition does not meet the preset adjustment condition, control the any compressor to stop operating; In response to determining that any real-time index value corresponding to the current in the real-time compressor operation data meets the target current sudden increase condition, control the any compressor to stop operating, where the target current sudden increase condition is that the difference between the any real-time index value of the corresponding current and the target historical current index value is greater than the preset current intensity, the target historical current index value corresponds to the same index as the any real-time index value of the corresponding current, and the target historical current index value is adjacent to the moment corresponding to the any real-time index value of the corresponding current.

7. A compressor fault warning device, comprising: An acquisition unit configured to, in response to detecting a selection operation on any compressor displayed in the compressor fault warning overview page, acquire the compressor operation data of the any compressor, where various types of compressors are displayed in the compressor fault warning overview page, and the compressor operation data includes a historical compressor operation data set and real-time compressor operation data; A generation unit configured to generate predicted compressor data corresponding to the current moment and a predicted compressor data sequence corresponding to a future time period according to the historical compressor operation data set and the real-time compressor operation data; An extraction unit configured to extract each predicted index value corresponding to a target index from the predicted compressor data sequence as a predicted index value sequence; A first display unit configured to display a compressor fault prediction page corresponding to the compressor, where a compressor fault prediction list and a trend curve graph corresponding to the target index are displayed in the compressor fault prediction page, the predicted compressor data and the real-time compressor operation data are displayed in the compressor fault prediction list, the trend curve graph displays an actual value curve, a predicted curve, and a threshold line corresponding to the target index, and the predicted curve is constructed according to the predicted index value sequence; A second display unit configured to, in response to determining that the real-time index value of any index in the compressor fault prediction list does not meet the alarm condition corresponding to the any index, and the predicted index value of the any index meets the warning condition, display a warning identifier at the position corresponding to the any index in the status column of the compressor fault prediction list; A third display unit configured to, in response to determining that the real-time index value meets the alarm condition, display an alarm identifier at the position corresponding to the any index in the status column of the compressor fault prediction list; A first determination unit, configured to determine whether there is fault information matching the real-time compressor operation data in the set of fault information corresponding to any of the compressors, where the fault information in the set of fault information includes a fault name, fault cause information, and maintenance suggestion information; A second determination unit, configured to, in response to determining that there is fault information matching the real-time compressor operation data in the set of fault information corresponding to any of the compressors, determine the fault information matching the real-time compressor operation data as target fault information; A fourth display unit, configured to display the fault name included in the target fault information on the compressor fault prediction page; A fifth display unit, configured to, in response to detecting a selection operation on the fault name, display the fault cause information and maintenance suggestion information included in the target fault information.

8. An electronic device, comprising: One or more processors; A storage device having stored thereon one or more programs, When the one or more programs are executed by the one or more processors, enabling the one or more processors to implement the method according to any one of claims 1-6.

9. A computer-readable medium having a computer program stored thereon, wherein, The computer program, when executed by a processor, implements the method according to any one of claims 1-6.

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