Intelligent blockage positioning method for screw air compressor

Abstract

The invention discloses an intelligent blockage positioning method for a screw air compressor, and relates to the technical field of intelligent operation and maintaining.According to the method, oil return behaviors of an oil return hole and an adjacent channel of the oil return hole serve as research objects, and the internal rhythm change of the oil return hole and the cooperative change of the channel are objectively split; and an oil return rhythm behavior object and a channel cooperation behavior object are constructed under a unified time reference. A mismatch type is constructed based on a time sequence relation of an intra-hole rhythm change event and a channel collaborative change event by identifying the intra-hole rhythm change event and the channel collaborative change event. Furthermore, statistical analysis is carried out on the occurrence frequency, continuity and regression characteristics of the mismatch type in the operation cycle, a structure flow mismatch situation index is formed, and the abnormal source of the oil return hole is judged according to the structure flow mismatch situation index. And finally, through the cross evaluation of the mismatch type and the mismatch characteristic, the area direction judgment of the blockage position of the oil return hole is realized, and the in-hole structure abnormity, the channel bearing abnormity and the non-dominant abnormity state are distinguished.

Description

Technical Field

[0001] This invention relates to the field of intelligent operation and maintenance technology, specifically to an intelligent blockage location method for screw air compressors. Background Technology

[0002] As one of the most widely used power devices in the industrial field, the stable operation of screw air compressors highly depends on the reliability of the oil return structure in the lubrication system. The oil return port, as a key component connecting the oil-gas separation structure and the oil return channel, plays a crucial role in lubricating oil return, pressure balance, and system stability. During long-term operation, factors such as oil aging, impurity deposition, structural wear, and fluctuations in operating conditions can easily lead to problems such as localized blockage, abnormal throttling, or delayed oil return in the oil return port area. These problems do not manifest as complete blockage but rather evolve gradually in a hidden state, such as rhythmic disorder and mismatch. Traditional monitoring methods relying on single parameters such as pressure and flow rate are insufficient to characterize the dynamic correlation between the internal structure of the oil return port and the channel, resulting in delayed fault identification. Therefore, developing an intelligent blockage location method for screw air compressors that reflects the structural operating mechanism, based on the inherent coupling relationship between oil return behavior, channel coordination, and structural response, has become an important technological direction for improving equipment operational reliability.

[0003] Existing methods for diagnosing screw air compressor blockages primarily rely on static threshold judgments or single-point signal anomaly identification. They typically focus only on whether return oil pressure and flow exceed limits, lacking the ability to analyze the evolution of return oil behavior. In particular, they struggle to distinguish between "abnormalities in the return oil orifice structure" and "disturbance transmission from the channel side." When the return oil orifice is in an early blockage or semi-blockage state, the manifestation is not a sudden drop in flow, but rather a time misalignment, phase drift, or disruption of coordination between the return oil rhythm and the channel response. These phenomena are easily misinterpreted as fluctuations in operating conditions or load changes in traditional monitoring systems, thus delaying maintenance. Furthermore, most existing methods lack the ability to characterize the persistence, repeatability, and evolutionary trends of anomalies, failing to differentiate between short-term disturbances, staged mismatches, and structural problems, leading to generalized diagnostic conclusions and insufficient localization accuracy. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an intelligent blockage location method for screw air compressors, solving the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an intelligent blockage positioning method for a screw air compressor, comprising the following steps:

[0006] S1. Obtain the oil return behavior of the oil return hole, and sort the oil return behavior by time based on the obtained timestamp and calculate the change in oil return rhythm and channel coordination by difference. Based on the change in oil return rhythm and channel coordination, perform threshold comparison to identify the rhythm change event and channel coordination change event in the hole.

[0007] S2. Time-stamp aligns the events of rhythmic change within the orifice with the events of coordinated change in the channel. Based on the alignment results, the structural game mismatch type is identified and the mismatch type is mapped to a structural flow mismatch status index.

[0008] S3. The number of occurrences of each type of mismatch in the statistical structural flow mismatch trend index within the operating cycle and the number of consecutive time windows in which they occur, and the mismatch characteristics are determined based on the statistical results;

[0009] S4. Perform cross-evaluation on the mismatch type and mismatch characteristics, and determine the oil return behavior status of the screw air compressor oil return hole based on the cross-evaluation results;

[0010] S5. Based on the oil return behavior status determination result, perform area orientation determination on the oil return hole of the screw air compressor, and output positioning orientation according to the area orientation determination result.

[0011] Preferably, S1 includes S11;

[0012] S11. During the operation of the screw air compressor, the oil return behavior of the oil return hole, the oil return hole inlet channel, and the oil return channel is acquired in real time based on the installed status monitoring equipment. The oil return behavior of the oil return hole is sorted by time based on the acquisition timestamp to form an oil return rhythm behavior object A that represents the oil return behavior inside the oil return hole. At the same time, based on the acquisition timestamp of the oil return behavior between the oil return hole and the oil inlet channel and the oil return channel, the oil return behavior between the oil return hole and the oil inlet channel and the oil return channel is sorted by time to form a channel coordination behavior object B that represents the coordination relationship between the oil return hole and the oil inlet channel and the oil return channel.

[0013] The condition monitoring equipment includes a flow meter, a pressure sensor, and a velocity meter;

[0014] The oil return behavior includes oil return flow rate, oil return pressure, and oil flow volume.

[0015] Preferably, S1 further includes S12;

[0016] S12. Based on the synchronous sampling sequence of the return oil rhythm behavior object A and the channel coordinated behavior object B, the continuously acquired return oil rhythm behavior object A and the channel coordinated behavior object B are divided into several time windows according to a fixed sampling time. The combination of the several time windows constitutes an operating cycle.

[0017] The first-order difference method is used to perform difference calculations on the oil return rhythm behavior object A and the channel coordination behavior object B in adjacent time windows to obtain the oil return rhythm change and the channel coordination change.

[0018] Extract the changes in return oil rhythm and channel coordination during historical return oil channel operation. Calculate the mean values ​​of return oil rhythm changes and channel coordination changes based on statistical methods, and preset them as rhythm change thresholds and coordination change thresholds, respectively. Compare these values ​​with the return oil rhythm changes and channel coordination changes. When the return oil rhythm change is greater than the rhythm change threshold, it is determined that the return oil rhythm behavior object A has changed and is marked as a rhythm change event within the channel. When the channel coordination change is greater than the coordination change threshold, it is determined that the channel coordination behavior object B has changed and is marked as a channel coordination change event.

[0019] Preferably, S2 includes S21;

[0020] S21. The time stamps of the rhythmic change events in the orifice and the coordinated change events in the channel are aligned, and the mismatch type is determined based on the temporal relationship. The specific mismatch type is determined as follows;

[0021] When the occurrence time of the intra-orifice rhythm change event is earlier than the channel coordination change event, it is determined that there is an intra-orifice preceding mismatch relationship within the current time window and it is marked as Mlag type;

[0022] When the channel coordination change event occurs earlier than the orifice rhythm change event, it is determined that there is a channel-leading mismatch relationship within the current time window and it is marked as Mlead type;

[0023] When the intra-orifice rhythm change event and the channel coordinated change event occur simultaneously within the same time window, and both of them exhibit the following behavior within the current time window: the return oil rhythm behavior object A exceeds the rhythm change threshold and the channel coordinated behavior object B exceeds the coordinated change threshold, it is determined that there is a synchronous blocking mismatch relationship within the current time window, and it is marked as Mdrop type.

[0024] Preferably, S2 further includes S22;

[0025] S22. Perform situational merging processing on the mismatch type markings of each time window to generate a structural flow mismatch situational index representing the structural state of the return oil hole, specifically including S221 and S222.

[0026] S221. Summarize the mismatch types identified in each time window, and construct a mismatch type sequence according to the time order of the mismatch types. Based on the mismatch type sequence, use statistical methods to count the number of occurrences of each mismatch type in the running cycle and the maximum number of windows in continuous time windows.

[0027] When the number of occurrences of a mismatch type within a time window is higher than that of other mismatch types, and the number of time windows corresponding to it is not less than the preset continuous window threshold, the current mismatch type is determined as the primary mismatch type in the current running cycle.

[0028] Preferably, in step S222, after determining the main mismatch type, its situation indicators in adjacent time windows are judged, as follows;

[0029] When the primary mismatch type exists in both adjacent time windows and no other mismatch type appears between adjacent windows, the current primary mismatch type is determined to be a continuous situation.

[0030] When the main mismatch type is missing in adjacent time windows, the current main mismatch type is determined to be a discontinuous situation.

[0031] The continuous window threshold is used to statistically obtain the maximum number of continuous windows for various mismatch type situation indicators of the return oil hole under normal operating conditions based on statistical methods.

[0032] Preferably, S3 includes S31;

[0033] S31. Based on statistical methods, the number of occurrences of each mismatch type in the structural flow mismatch situation index during the operating cycle and the number of consecutive time windows in which they occur are statistically analyzed, and the start and end time nodes of each mismatch type are marked.

[0034] Based on the number of occurrences of each type of mismatch within the operating cycle and the number of consecutive time windows in which they occur, the residence characteristics of the mismatch type are determined as follows;

[0035] When the number of consecutive windows of the mismatch type within the runtime is less than the consecutive window threshold, the current dwell characteristic is determined to be a discrete dwell state.

[0036] When the mismatch type exists in both adjacent time windows and the number of consecutive windows is greater than or equal to the consecutive window threshold, the current dwelling characteristic is determined to be a continuous dwelling state.

[0037] When the mismatch type exists throughout the entire runtime, the current residency characteristic is determined to be a full-cycle residency state.

[0038] Preferably, S3 further includes S32;

[0039] S32. Determine the regression characteristics of mismatch types based on the start and end times of various mismatch types, as detailed below;

[0040] When the mismatch type no longer appears in subsequent running cycles at the end of the recording time, the current regression characteristic is determined to be a fully regressive state;

[0041] When the mismatch type reappears in a subsequent running cycle at the end of the recording time, and the duration of the mismatch type is greater than the time window of each monitoring segment, the current regression characteristic is determined to be a residual regression state.

[0042] When a mismatch type has been present since the first start time point, and the time interval between adjacent occurrences of the mismatch type is less than or equal to the time window of each monitoring segment, the current regression characteristic is determined to be a non-regression hold-up state.

[0043] Preferably, S4 includes S41;

[0044] S41. Cross-evaluate the mismatch type and mismatch characteristics, and determine the oil return behavior of the screw air compressor based on the cross-evaluation results, as follows;

[0045] When the mismatch type is Mlag type mismatch or Mdrop type mismatch, and the residence characteristic corresponding to the mismatch characteristic is continuous residence state or full-cycle residence state, and the regression characteristic is non-regression hold state, it is determined that the current anomaly is mainly formed by the internal structural factors of the return oil hole, and it is marked as an anomaly dominated by the return oil hole structure.

[0046] When the mismatch type is mainly Mlead type mismatch, and the regression characteristic corresponding to the mismatch characteristic is a complete regression state or a residual regression state, it is determined that the current anomaly is caused by external channels or operating conditions, and the return oil hole is in a load abnormality, and it is marked as a return oil hole load abnormality.

[0047] When the mismatch type and mismatch characteristics do not meet any of the above judgment conditions, it means that the current abnormal state has all of the above mismatch characteristics at the same time, and there is no stable correspondence between the mismatch characteristics. The current abnormal state is judged to be a non-dominant consistent state.

[0048] Preferably, S5 includes S51;

[0049] S51. Based on the oil return behavior status determination result, determine the direction of the oil return hole of the screw air compressor and output the positioning direction result;

[0050] When the oil return behavior status determination result indicates that the oil return hole structure is the dominant abnormality, the specific judgment is as follows:

[0051] If the main mismatch type of the return oil behavior status determination result is Mdrop type mismatch, it means that the return oil behavior inside and outside the return oil hole is interrupted synchronously. The abnormality is concentrated in the throttling position of the return oil hole itself, corresponding to the orifice diameter and the orifice throttling section.

[0052] If the main mismatch type of the return oil behavior status determination result is Mlag type mismatch, it indicates that there is lag in the return oil behavior in the return oil hole. Combined with the structural flow mismatch status index, the positioning direction is determined: when the residence characteristic is continuous residence state, it points to the throttling section of the orifice neck and orifice opening; when the abnormal residence characteristic is discrete residence state or the regression characteristic is residual regression state, it points to the receiving section of the return oil channel outlet.

[0053] When the return oil behavior status determination indicates abnormal or non-dominant consistent state of the return oil hole, the abnormality is limited to the non-return oil hole itself, and is uniformly pointed to the adjacent channel section of the inlet channel and the adjacent bearing section of the return oil channel.

[0054] This invention provides an intelligent blockage location method for screw air compressors. It has the following beneficial effects:

[0055] (1) This method synchronously collects the return oil flow rate, pressure and volume of the return oil hole, inlet channel and return oil channel in S1, and sorts and differentially processes the return oil rhythm behavior objects and channel coordinated behavior objects with timestamp as the core, so that the return oil behavior is transformed from the original unquantifiable empirical phenomenon into calculable and comparable time series data. On this basis, the orifice rhythm change event and channel coordinated change event are time aligned by S2, and the mismatch type is introduced as an intermediate structural quantity. The return oil anomaly is refined from the coarse-grained judgment of "whether it is abnormal" to three structural relationships: orifice first, channel first or synchronous blockage. This realizes the preliminary determination of the cause direction of the return oil anomaly, and provides a clear data basis and logical starting point for subsequent state analysis and localization.

[0056] (2) Method S3 constructs two representational dimensions—resident characteristics and regression characteristics—by statistically analyzing the occurrence frequency, number of consecutive windows, and evolution patterns of various mismatch types within the operating cycle, enabling the system to distinguish between short-term disturbances, periodic anomalies, and persistent structural anomalies. Simultaneously, S4, through cross-evaluation of mismatch types and characteristics, no longer treats all anomalies equally, but clearly distinguishes between dominant anomalies in the return oil hole structure, load-bearing anomalies in the return oil hole, and non-dominant consistent states, solving the problem in existing technologies of being unable to distinguish the source of blockage and mistakenly treating external disturbances as internal blockages. This mechanism elevates anomaly identification from simple threshold judgment to a comprehensive judgment process with temporal continuity, structural logic, and causal orientation.

[0057] (3) Method S5 maps different mismatch types and their residence and regression characteristics to the location of the return oil hole structure, realizing the differentiation and positioning of the orifice neck, orifice throttling section, adjacent section of the oil inlet channel, and receiving section of the return oil channel. This enables the system to not only determine "whether there is a blockage" but also to point out "where the blockage is more likely to occur". Compared with the method of relying on manual disassembly and inspection or experience inference, this method can complete the positioning analysis while the equipment is in operation, reducing the misjudgment rate and the probability of repeated maintenance, and providing a clear and interpretable basis for subsequent maintenance decisions. Overall, through the synergistic effect of rhythm analysis, mismatch modeling, and situation induction, this scheme realizes a complete closed loop from perception, analysis to positioning of abnormal oil return of screw air compressor, significantly improving the precision and engineering usability of oil return operation status identification. Attached Figure Description

[0058] Figure 1 This is a schematic diagram illustrating the steps of an intelligent blockage positioning method for a screw air compressor according to the present invention;

[0059] Figure 2 This is a block diagram illustrating the logic principle of an intelligent blockage location method for screw air compressors according to the present invention. Detailed Implementation

[0060] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0061] Example 1

[0062] Please see Figure 1 This invention provides an intelligent blockage positioning method for screw air compressors. To achieve the above objectives, this invention employs the following technical solution, comprising the following steps:

[0063] S1. Obtain the oil return behavior of the oil return hole, and sort the oil return behavior by time based on the obtained timestamp and calculate the change in oil return rhythm and channel coordination by difference. Based on the change in oil return rhythm and channel coordination, perform threshold comparison to identify the rhythm change event and channel coordination change event in the hole.

[0064] S2. Time-stamp aligns the events of rhythmic change within the orifice with the events of coordinated change in the channel. Based on the alignment results, the structural game mismatch type is identified and the mismatch type is mapped to a structural flow mismatch status index.

[0065] S3. The number of occurrences of each type of mismatch in the statistical structural flow mismatch trend index within the operating cycle and the number of consecutive time windows in which they occur, and the mismatch characteristics are determined based on the statistical results;

[0066] S4. Perform cross-evaluation on the mismatch type and mismatch characteristics, and determine the oil return behavior status of the screw air compressor oil return hole based on the cross-evaluation results;

[0067] S5. Based on the oil return behavior status determination result, perform area orientation determination on the oil return hole of the screw air compressor, and output positioning orientation according to the area orientation determination result.

[0068] In this embodiment, S1 and S2 complete the structured characterization of the actual operating behavior of the return oil orifice, transforming the traditional method of judging solely based on instantaneous flow rate or pressure into a rhythmic analysis process based on time series. By performing differential calculations on the rhythmic changes in return oil and the coordinated changes in the channel, and introducing a timestamp alignment mechanism, the return oil behavior in the orifice and the return oil behavior in the channel can be compared and analyzed on the same time scale, thereby identifying different types of structural game relationships such as orifice-first, channel-first, or synchronous changes. Compared to existing technologies that can only determine "whether it is abnormal," this step completes the transformation from the existence of anomalies to the distinguishable source of abnormal structures, providing a clear structural criterion basis for subsequent analysis, so that return oil anomalies are no longer limited to the phenomenon level, but have the technical premise of being analyzable and categorizable. Through S3, statistical analysis of the structural flow mismatch situation is performed, introducing the frequency of occurrence of mismatch types within the operating cycle and the characteristics of continuous time windows, enabling the system to distinguish between short-term disturbances, staged anomalies, and continuous anomalies. Further in S4, the mismatch type is cross-evaluated with its residence and regression characteristics to construct a judgment logic for the return oil behavior state, enabling the differentiation between dominant anomalies in the return oil orifice structure, abnormal return oil orifice bearing capacity, and non-dominant consistent states. Compared with existing technologies that rely solely on threshold triggering or single anomaly judgment, this scheme achieves the ability to identify the anomaly evolution process, enabling the system to judge the stability, persistence, and evolution direction of anomalies, avoiding misjudgments caused by short-term fluctuations or changes in operating conditions. After completing the return oil behavior state judgment, S5 further maps the abstract anomaly state to specific structural regions, achieving directional positioning of the return oil orifice throttling section, orifice neck position, and channel bearing area. This step elevates the diagnostic result from judging the existence of an anomaly to clearly identifying the location of the anomaly, solving the problem of existing technologies being unable to accurately locate the blockage location and relying on manual disassembly and inspection. Through the synergistic effect of the above five steps, this method forms a complete technical chain from data acquisition, behavior modeling, structural discrimination to spatial positioning, realizing refined identification and positioning of return oil orifice blockage problems, and improving the interpretability, accuracy, and engineering usability of the diagnosis.

[0069] Example 2

[0070] Please refer to Figure 2 Specifically: S1 includes S11;

[0071] S11. During the operation of the screw air compressor, the oil return behavior of the oil return hole, the oil return hole inlet channel, and the oil return channel is acquired in real time based on the installed status monitoring equipment. The oil return behavior of the oil return hole is sorted by time based on the acquisition timestamp to form an oil return rhythm behavior object A that represents the oil return behavior inside the oil return hole. At the same time, based on the acquisition timestamp of the oil return behavior between the oil return hole and the oil inlet channel and the oil return channel, the oil return behavior between the oil return hole and the oil inlet channel and the oil return channel is sorted by time to form a channel coordination behavior object B that represents the coordination relationship between the oil return hole and the oil inlet channel and the oil return channel.

[0072] The condition monitoring equipment includes a flow meter, a pressure sensor, and a velocity meter;

[0073] The oil return behavior includes oil return flow rate, oil return pressure, and oil flow volume.

[0074] S1 further includes S12;

[0075] S12. Based on the synchronous sampling sequence of the return oil rhythm behavior object A and the channel coordinated behavior object B, the continuously acquired return oil rhythm behavior object A and the channel coordinated behavior object B are divided into several time windows according to a fixed sampling time. The combination of the several time windows constitutes an operating cycle.

[0076] The first-order difference method is used to perform difference calculations on the oil return rhythm behavior object A and the channel coordination behavior object B in adjacent time windows to obtain the oil return rhythm change and the channel coordination change.

[0077] Extract the changes in return oil rhythm and channel coordination during historical return oil channel operation. Calculate the mean values ​​of return oil rhythm changes and channel coordination changes based on statistical methods, and preset them as rhythm change thresholds and coordination change thresholds, respectively. Compare these values ​​with the return oil rhythm changes and channel coordination changes. When the return oil rhythm change is greater than the rhythm change threshold, it is determined that the return oil rhythm behavior object A has changed and is marked as a rhythm change event within the channel. When the channel coordination change is greater than the coordination change threshold, it is determined that the channel coordination behavior object B has changed and is marked as a channel coordination change event.

[0078] In this embodiment, during the normal operation of the screw air compressor, flow meters, pressure sensors, and velocity meters arranged at the oil return port, oil inlet channel, and oil return channel are used to synchronously collect the oil return flow rate, oil return pressure, and oil flow volume. The sampled data are then uniformly sorted based on timestamps to form an oil return rhythm behavior object A, representing the internal flow state of the oil return port, and a channel coordination behavior object B, reflecting the cooperative relationship between the oil return port and the upstream and downstream channels. Based on this, continuous data is divided into time windows using a fixed sampling period, and the oil return rhythm change and channel coordination change are extracted using a first-order difference method, allowing minute fluctuations in the oil return process to be effectively amplified and identified as trends. Furthermore, through statistical analysis of historical operating data, rhythm change thresholds and coordination change thresholds are constructed, making the current operating state comparable to stable operating conditions. When the change exceeds the corresponding threshold, it is automatically identified as an internal rhythm change event or a channel coordination change event. Through the aforementioned technical approach, this implementation method transforms the monitoring of oil return behavior from static quantity monitoring to dynamic rhythm identification. It not only detects the occurrence of abnormal oil return but also clarifies whether the abnormality originates from changes in orifice behavior or channel coordination anomalies, fundamentally solving the problem in existing technologies where a single parameter is insufficient to distinguish the cause of blockage. This not only improves the sensitivity and stability of oil return anomaly identification but also provides a reliable data foundation and logical premise for subsequent mismatch analysis, state determination, and precise location, enhancing the accuracy and engineering applicability of the screw air compressor oil return system's operational diagnosis.

[0079] Example 3

[0080] Please refer to Figure 2 Specifically: S2 includes S21;

[0081] S21. The time stamps of the rhythmic change events in the orifice and the coordinated change events in the channel are aligned, and the mismatch type is determined based on the temporal relationship. The specific mismatch type is determined as follows;

[0082] When the occurrence time of the intra-orifice rhythm change event is earlier than the channel coordination change event, it is determined that there is an intra-orifice preceding mismatch relationship within the current time window and it is marked as Mlag type;

[0083] When the channel coordination change event occurs earlier than the orifice rhythm change event, it is determined that there is a channel-leading mismatch relationship within the current time window and it is marked as Mlead type;

[0084] When the intra-orifice rhythm change event and the channel coordinated change event occur simultaneously within the same time window, and both of them exhibit the following behavior within the current time window: the return oil rhythm behavior object A exceeds the rhythm change threshold and the channel coordinated behavior object B exceeds the coordinated change threshold, it is determined that there is a synchronous blocking mismatch relationship within the current time window, and it is marked as Mdrop type.

[0085] S2 further includes S22;

[0086] S22. Perform situational merging processing on the mismatch type markings of each time window to generate a structural flow mismatch situational index representing the structural state of the return oil hole, specifically including S221 and S222.

[0087] S221. Summarize the mismatch types identified in each time window, and construct a mismatch type sequence according to the time order of the mismatch types. Based on the mismatch type sequence, use statistical methods to count the number of occurrences of each mismatch type in the running cycle and the maximum number of windows in continuous time windows.

[0088] When the number of occurrences of a mismatch type within a time window is higher than that of other mismatch types, and the number of time windows corresponding to it is not less than the preset continuous window threshold, the current mismatch type is determined as the primary mismatch type in the current running cycle.

[0089] S222. After determining the main mismatch type, its situation indicators in adjacent time windows are judged as follows;

[0090] When the primary mismatch type exists in both adjacent time windows and no other mismatch type appears between adjacent windows, the current primary mismatch type is determined to be a continuous situation.

[0091] When the main mismatch type is missing in adjacent time windows, the current main mismatch type is determined to be a discontinuous situation.

[0092] The continuous window threshold is used to statistically obtain the maximum number of continuous windows for various mismatch type situation indicators of the return oil hole under normal operating conditions based on statistical methods.

[0093] In this embodiment, by classifying the rhythmic changes within different time windows into three mismatch types—in-hole type, channel type, and synchronous blocking type—and further statistically summarizing their frequency and continuity within the operating cycle, the dominant characteristics of the return oil orifice structure can be identified from a dynamic evolution perspective. Compared to traditional methods that rely solely on instantaneous parameters or single-point thresholds, this scheme constructs an analysis chain of "mismatch type—temporal continuity—situational induction," upgrading anomaly identification from discrete judgment to a situational judgment process with temporal continuity and structural orientation. Based on this, by analyzing the stability of the main mismatch type in adjacent time windows, continuous and discontinuous situations are further distinguished, determining whether the anomaly is a transient disturbance or a persistent structural problem, providing a reliable basis for subsequent return oil orifice anomaly localization. This method avoids misjudgments caused by short-term fluctuations, improves the accuracy of identifying the blockage evolution process, and transforms the ambiguous judgment of "whether it is abnormal" into a quantitative analysis result of "clear anomaly type, clear evolutionary characteristics, and traceable structural orientation."

[0094] Example 4

[0095] Please refer to Figure 2 Specifically: S3 includes S31;

[0096] S31. Based on statistical methods, the number of occurrences of each mismatch type in the structural flow mismatch situation index during the operating cycle and the number of consecutive time windows in which they occur are statistically analyzed, and the start and end time nodes of each mismatch type are marked.

[0097] Based on the number of occurrences of each type of mismatch within the operating cycle and the number of consecutive time windows in which they occur, the residence characteristics of the mismatch type are determined as follows;

[0098] When the number of consecutive windows of the mismatch type within the runtime is less than the consecutive window threshold, the current dwell characteristic is determined to be a discrete dwell state.

[0099] When the mismatch type exists in both adjacent time windows and the number of consecutive windows is greater than or equal to the consecutive window threshold, the current dwelling characteristic is determined to be a continuous dwelling state.

[0100] When the mismatch type exists throughout the entire runtime, the current residency characteristic is determined to be a full-cycle residency state.

[0101] S3 further includes S32;

[0102] S32. Determine the regression characteristics of mismatch types based on the start and end times of various mismatch types, as detailed below;

[0103] When the mismatch type no longer appears in subsequent running cycles at the end of the recording time, the current regression characteristic is determined to be a fully regressive state;

[0104] When the mismatch type reappears in a subsequent running cycle at the end of the recording time, and the duration of the mismatch type is greater than the time window of each monitoring segment, the current regression characteristic is determined to be a residual regression state.

[0105] When a mismatch type has been present since the first start time point, and the time interval between adjacent occurrences of the mismatch type is less than or equal to the time window of each monitoring segment, the current regression characteristic is determined to be a non-regression hold-up state.

[0106] In this embodiment, statistical analysis of structural flow mismatch indicators shifts the focus from single-event mismatches to a systematic characterization of the frequency, duration, and start and end points of various mismatch types over a cycle-based approach. This transforms return oil anomalies from instantaneous events into time-dependent structural behavioral characteristics, resulting in three distinguishable residence characteristics: discrete residence, continuous residence, and full-cycle residence. These characteristics reflect the stability and evolutionary trend of the anomaly over time. Furthermore, a regression characteristic judgment mechanism is introduced to differentiate between the disappearance, recurrence, and persistence of mismatch behavior in subsequent cycles, resulting in three states: complete regression, residual regression, and non-regression persistence. This constructs a complete chain describing the occurrence, persistence, and regression evolution. Through this two-level judgment mechanism, this method achieves in-depth identification of return oil hole anomalies, moving from simply "existing" to "whether they are stable, recoverable, and have structural root causes." It distinguishes between occasional disturbances and structural blockages, avoiding the difficulty in distinguishing between short-term fluctuations and actual blockages in traditional methods. This not only improves the accuracy and stability of oil return anomaly detection, but also provides clear time and behavioral basis for subsequent location analysis, providing reliable support for accurate location and maintenance decision-making for oil return hole blockage.

[0107] Example 5

[0108] Please refer to Figure 2 Specifically: S4 includes S41;

[0109] S41. Cross-evaluate the mismatch type and mismatch characteristics, and determine the oil return behavior of the screw air compressor based on the cross-evaluation results, as follows;

[0110] When the mismatch type is Mlag type mismatch or Mdrop type mismatch, and the residence characteristic corresponding to the mismatch characteristic is continuous residence state or full-cycle residence state, and the regression characteristic is non-regression hold state, it is determined that the current anomaly is mainly formed by the internal structural factors of the return oil hole, and it is marked as an anomaly dominated by the return oil hole structure.

[0111] When the mismatch type is mainly Mlead type mismatch, and the regression characteristic corresponding to the mismatch characteristic is a complete regression state or a residual regression state, it is determined that the current anomaly is caused by external channels or operating conditions, and the return oil hole is in a load abnormality, and it is marked as a return oil hole load abnormality.

[0112] When the mismatch type and mismatch characteristics do not meet any of the above judgment conditions, it means that the current abnormal state has all of the above mismatch characteristics at the same time, and there is no stable correspondence between the mismatch characteristics. The current abnormal state is judged to be a non-dominant consistent state.

[0113] In this embodiment, a return oil state determination mechanism based on structural behavior logic is constructed by cross-evaluating mismatch type and mismatch characteristics. This mechanism ensures that return oil anomalies are no longer judged solely by a single parameter or empirical threshold, but are comprehensively determined through the three-dimensional relationship of mismatch type, residence characteristics, and regression characteristics. When the mismatch manifests as Mlag type mismatch or Mdrop type mismatch, and the residence characteristic corresponding to the mismatch characteristic is a continuous residence state or a full-cycle residence state, accompanied by a non-regression-maintained regression characteristic, the anomaly can be identified as originating from the structural state of the return oil orifice itself, avoiding misjudging structural blockage as operating condition fluctuation. When the mismatch type is mainly Mlead type mismatch, and the regression characteristic corresponding to the mismatch characteristic is a fully regressive state or a residual regressive state, the anomaly is limited to load changes caused by external channels or operating conditions, avoiding mishandling of the return oil orifice itself. When the mismatch type and mismatch characteristics do not meet any of the above determination conditions, they are classified through a non-dominant consistent state, preserving the discrimination space for anomaly evolution. Through this judgment mechanism, this solution has shifted from "whether it is abnormal" to "the cause of the abnormality and the attribution of responsibility", making the identification of oil return anomalies structurally oriented, logically consistent and engineering interpretable, reducing the risk of misjudgment and incorrect maintenance, and providing a basis for subsequent accurate positioning and maintenance decisions.

[0114] Example 6

[0115] Please refer to Figure 2 Specifically: S5 includes S51;

[0116] S51. Based on the oil return behavior status determination result, determine the direction of the oil return hole of the screw air compressor and output the positioning direction result;

[0117] When the oil return behavior status determination result indicates that the oil return hole structure is the dominant abnormality, the specific judgment is as follows:

[0118] If the main mismatch type of the return oil behavior status determination result is Mdrop type mismatch, it means that the return oil behavior inside and outside the return oil hole is interrupted synchronously. The abnormality is concentrated in the throttling position of the return oil hole itself, corresponding to the orifice diameter and the orifice throttling section.

[0119] If the main mismatch type of the return oil behavior status determination result is Mlag type mismatch, it indicates that there is lag in the return oil behavior in the return oil hole. Combined with the structural flow mismatch status index, the positioning direction is determined: when the residence characteristic is continuous residence state, it points to the throttling section of the orifice neck and orifice opening; when the abnormal residence characteristic is discrete residence state or the regression characteristic is residual regression state, it points to the receiving section of the return oil channel outlet.

[0120] When the return oil behavior status determination indicates abnormal or non-dominant consistent state of the return oil hole, the abnormality is limited to the non-return oil hole itself, and is uniformly pointed to the adjacent channel section of the inlet channel and the adjacent bearing section of the return oil channel.

[0121] In this embodiment, the results of the return oil behavior status determination are used as input. The resulting mismatch type, residence characteristics, and regression characteristics are further transformed into positioning conclusions with clear engineering implications. By analyzing the structural meaning of different mismatch modes, the precise mapping of the abnormal location is achieved. When the abnormality is determined to be dominated by the return oil hole structure, the abnormality is further refined to the throttling section between the orifice neck and orifice opening or the receiving section of the return oil channel, depending on the different main mismatch types. This ensures that the return oil abnormality is no longer limited to the level of "problem exists" but has a clear spatial orientation. When the abnormality is determined to be due to the return oil hole bearing or a non-dominant consistent state, the abnormality is attributed to the influence of external channel structure or operating conditions, thereby avoiding misjudging systemic disturbances as blockage within the orifice. Through this implementation method, a closed-loop transformation from behavior recognition, state judgment, and area positioning is achieved, upgrading the diagnosis of abnormal oil return from qualitative judgment to a locatable, interpretable, and traceable engineering conclusion. Compared with the traditional method that relies on experience or disassembly and inspection for confirmation, it effectively improves the accuracy of fault identification, the reliability of positioning, and the pertinence of maintenance decisions. Thus, without increasing hardware complexity, it significantly improves the technical level of operation analysis and fault handling of screw air compressor oil return systems.

[0122] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended technical solutions and their equivalents.

Claims

1. A method for intelligent blockage location in a screw air compressor, characterized in that: Includes the following steps: S1. Obtain the oil return behavior of the oil return hole, and sort the oil return behavior by time based on the obtained timestamp and calculate the change in oil return rhythm and channel coordination by difference. Based on the change in oil return rhythm and channel coordination, perform threshold comparison to identify the rhythm change event and channel coordination change event in the hole. S2. Time-stamp aligns the events of rhythmic change within the orifice with the events of coordinated change in the channel. Based on the alignment results, the structural game mismatch type is identified and the mismatch type is mapped to a structural flow mismatch status index. S3. The number of occurrences of each type of mismatch in the statistical structural flow mismatch trend index within the operating cycle and the number of consecutive time windows in which they occur, and the mismatch characteristics are determined based on the statistical results; S4. Perform cross-evaluation on the mismatch type and mismatch characteristics, and determine the oil return behavior status of the screw air compressor oil return hole based on the cross-evaluation results; S5. Based on the oil return behavior status determination result, perform area orientation determination on the oil return hole of the screw air compressor, and output positioning orientation according to the area orientation determination result.

2. The intelligent blockage positioning method for a screw air compressor according to claim 1, characterized in that: S1 includes S11; S11. During the operation of the screw air compressor, the oil return behavior of the oil return hole, the oil return hole inlet channel, and the oil return channel is acquired in real time based on the installed status monitoring equipment. The oil return behavior of the oil return hole is sorted by time based on the acquisition timestamp to form an oil return rhythm behavior object A that represents the oil return behavior inside the oil return hole. At the same time, based on the acquisition timestamp of the oil return behavior between the oil return hole and the oil inlet channel and the oil return channel, the oil return behavior between the oil return hole and the oil inlet channel and the oil return channel is sorted by time to form a channel coordination behavior object B that represents the coordination relationship between the oil return hole and the oil inlet channel and the oil return channel. The condition monitoring equipment includes a flow meter, a pressure sensor, and a velocity meter; The oil return behavior includes oil return flow rate, oil return pressure, and oil flow volume.

3. The intelligent blockage positioning method for a screw air compressor according to claim 2, characterized in that: S1 further includes S12; S12. Based on the synchronous sampling sequence of the return oil rhythm behavior object A and the channel coordinated behavior object B, the continuously acquired return oil rhythm behavior object A and the channel coordinated behavior object B are divided into several time windows according to a fixed sampling time. The combination of the several time windows constitutes an operating cycle. The first-order difference method is used to perform difference calculations on the oil return rhythm behavior object A and the channel coordination behavior object B in adjacent time windows to obtain the oil return rhythm change and the channel coordination change. Extract the changes in return oil rhythm and channel coordination during historical return oil channel operation. Calculate the mean values ​​of return oil rhythm changes and channel coordination changes based on statistical methods, and preset them as rhythm change thresholds and coordination change thresholds, respectively. Compare these values ​​with the return oil rhythm changes and channel coordination changes. When the return oil rhythm change is greater than the rhythm change threshold, it is determined that the return oil rhythm behavior object A has changed and is marked as a rhythm change event within the channel. When the channel coordination change is greater than the coordination change threshold, it is determined that the channel coordination behavior object B has changed and is marked as a channel coordination change event.

4. The intelligent blockage positioning method for a screw air compressor according to claim 3, characterized in that: S2 includes S21; S21. The time stamps of the rhythmic change events in the orifice and the coordinated change events in the channel are aligned, and the mismatch type is determined based on the temporal relationship. The specific mismatch type is determined as follows; When the occurrence time of the intra-orifice rhythm change event is earlier than the channel coordination change event, it is determined that there is an intra-orifice preceding mismatch relationship within the current time window and it is marked as Mlag type; When the channel coordination change event occurs earlier than the orifice rhythm change event, it is determined that there is a channel-leading mismatch relationship within the current time window and it is marked as Mlead type; When the intra-orifice rhythm change event and the channel coordinated change event occur simultaneously within the same time window, and both of them exhibit the following behavior within the current time window: the return oil rhythm behavior object A exceeds the rhythm change threshold and the channel coordinated behavior object B exceeds the coordinated change threshold, it is determined that there is a synchronous blocking mismatch relationship within the current time window, and it is marked as Mdrop type.

5. The intelligent blockage positioning method for a screw air compressor according to claim 4, characterized in that: S2 further includes S22; S22. Perform situation merging processing on the mismatch type markings of each time window to generate a structural flow mismatch situation index representing the structural state of the return oil hole, specifically including S221 and S222. S221. Summarize the mismatch types identified in each time window, and construct a mismatch type sequence according to the time order of the mismatch types. Based on the mismatch type sequence, use statistical methods to count the number of occurrences of each mismatch type in the running cycle and the maximum number of windows in continuous time windows. When the number of occurrences of a mismatch type within a time window is higher than that of other mismatch types, and the number of time windows corresponding to it is not less than the preset continuous window threshold, the current mismatch type is determined as the primary mismatch type in the current running cycle.

6. The intelligent blockage positioning method for a screw air compressor according to claim 5, characterized in that: S222. After determining the main mismatch type, its situation indicators in adjacent time windows are judged as follows; When the primary mismatch type exists in both adjacent time windows and no other mismatch type appears between adjacent windows, the current primary mismatch type is determined to be a continuous situation. When the main mismatch type is missing in adjacent time windows, the current main mismatch type is determined to be a discontinuous situation. The continuous window threshold is used to statistically obtain the maximum number of continuous windows for various mismatch type situation indicators of the return oil hole under normal operating conditions based on statistical methods.

7. The intelligent blockage positioning method for a screw air compressor according to claim 6, characterized in that: S3 includes S31; S31. Based on statistical methods, the number of occurrences of each mismatch type in the structural flow mismatch situation index during the operating cycle and the number of consecutive time windows in which they occur are statistically analyzed, and the start and end time nodes of each mismatch type are marked. Based on the number of occurrences of each type of mismatch within the operating cycle and the number of consecutive time windows in which they occur, the residence characteristics of the mismatch type are determined as follows; When the number of consecutive windows of the mismatch type within the runtime is less than the consecutive window threshold, the current dwell characteristic is determined to be a discrete dwell state. When the mismatch type exists in both adjacent time windows and the number of consecutive windows is greater than or equal to the consecutive window threshold, the current dwelling characteristic is determined to be a continuous dwelling state. When the mismatch type exists throughout the entire runtime, the current residency characteristic is determined to be a full-cycle residency state.

8. The intelligent blockage positioning method for a screw air compressor according to claim 7, characterized in that: S3 further includes S32; S32. Determine the regression characteristics of mismatch types based on the start and end times of various mismatch types, as detailed below; When the mismatch type no longer appears in subsequent running cycles at the end of the recording time, the current regression characteristic is determined to be a fully regressive state; When the mismatch type reappears in a subsequent running cycle at the end of the recording time, and the duration of the mismatch type is greater than the time window of each monitoring segment, the current regression characteristic is determined to be a residual regression state. When a mismatch type has been present since the first start time point, and the time interval between adjacent occurrences of the mismatch type is less than or equal to the time window of each monitoring segment, the current regression characteristic is determined to be a non-regression hold-up state.

9. The intelligent blockage positioning method for a screw air compressor according to claim 8, characterized in that: S4 includes S41; S41. Cross-evaluate the mismatch type and mismatch characteristics, and determine the oil return behavior of the screw air compressor based on the cross-evaluation results, as follows; When the mismatch type is Mlag type mismatch or Mdrop type mismatch, and the residence characteristic corresponding to the mismatch characteristic is continuous residence state or full-cycle residence state, and the regression characteristic is non-regression hold state, it is determined that the current anomaly is mainly formed by the internal structural factors of the return oil hole, and it is marked as an anomaly dominated by the return oil hole structure. When the mismatch type is mainly Mlead type mismatch, and the regression characteristic corresponding to the mismatch characteristic is a complete regression state or a residual regression state, it is determined that the current anomaly is caused by external channels or operating conditions, and the return oil hole is in a load abnormality, and it is marked as a return oil hole load abnormality. When the mismatch type and mismatch characteristics do not meet any of the above judgment conditions, it means that the current abnormal state has all of the above mismatch characteristics at the same time, and there is no stable correspondence between the mismatch characteristics. The current abnormal state is judged to be a non-dominant consistent state.

10. The intelligent blockage positioning method for a screw air compressor according to claim 9, characterized in that: S5 includes S51; S51. Based on the oil return behavior status determination result, determine the direction of the oil return hole of the screw air compressor and output the positioning direction result; When the oil return behavior status determination result indicates that the oil return hole structure is the dominant abnormality, the specific judgment is as follows: If the main mismatch type of the return oil behavior status determination result is Mdrop type mismatch, it means that the return oil behavior inside and outside the return oil hole is interrupted synchronously. The abnormality is concentrated in the throttling position of the return oil hole itself, corresponding to the orifice diameter and the orifice throttling section. If the main mismatch type of the return oil behavior status determination result is Mlag type mismatch, it indicates that there is lag in the return oil behavior in the return oil hole. Combined with the structural flow mismatch status index, the positioning direction is determined: when the residence characteristic is continuous residence state, it points to the throttling section of the orifice neck and orifice opening; when the abnormal residence characteristic is discrete residence state or the regression characteristic is residual regression state, it points to the receiving section of the return oil channel outlet. When the return oil behavior status determination indicates abnormal or non-dominant consistent state of the return oil hole, the abnormality is limited to the non-return oil hole itself, and is uniformly pointed to the adjacent channel section of the inlet channel and the adjacent bearing section of the return oil channel.

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