Monitoring process and corresponding system for a rotary system lubricated with grease

Abstract

Monitoring process of a grease-lubricated rotating system comprising the steps of determining whether a learning period is to be performed during which measurement values are recorded for a predetermined period, if this is the case, determining an upper threshold value and a lower threshold value based on a mean value and a standard deviation of the water content within the grease measurement values recorded during the learning period, then for each measurement value, determining whether the current measurement value is greater than or equal to the upper threshold value, when this is the case, determining whether at least a first number of measurement values of a second number of last measurement values are above the upper threshold value, if this is the case, emitting a first event, determining whether the current measurement is less than or equal to the lower threshold value, when this is the case, determining whether at least a first number of measurement values of a second number of last measurement values are below the lower threshold value, then if this is the case, emitting a second event, determining whether at least a first event has been emitted, if this is the case, emitting a warning function of at least the first event.

Description

TECHNICAL FIELD

[0001] The present invention relates to bearing lubrication, in particular to the measurement of water content in bearing grease. BACKGROUND

[0002] Rotating systems require lubrication in order to maintain reliable operation conditions. Such lubrication is usually achieved using oil or grease. However, grease is generally preferred for the lubrication of closed systems such as bearings.

[0003] The grease is contained by a seat (or housing or bearing seat or housing) and a seal. Seal failure usually leads to the ingress of dust and / or water. Low concentrations of water in the grease are acceptable. However, there is a threshold beyond which the presence of water in the grease degrades the lubrication of the rotating system and can lead to damage or destruction.

[0004] The monitoring system allows to determine the water content in the grease so that corrective measures can be taken before the aforementioned threshold is crossed.

[0005] Document US-2018-238851 discloses such a monitoring system comprising an electrode in contact with the grease to be monitored and connected to a resistor (or electrical resistance) R so as to form an RC circuit.

[0006] A change in the water content in the grease is detected when the impedance of the RC circuit changes due to a change in the dielectric contestant of the mixture of grease and water.

[0007] The existing monitoring system involves random sampling of the grease for offline analysis and manual adjustment of the warning and sensor detection thresholds based on the results of the offline analysis.

[0008] The present monitoring system alleviates the need for any sampling or threshold setting. SUMMARY

[0009] The object of the present invention is a monitoring process for a grease-lubricated rotating system comprising a processing unit linked to (or connected to or associated with) a measuring system for measuring the water content in the lubricating grease, the monitoring process comprising the steps of:

[0010] - determining whether a learning time period is to be performed, wherein during said learning time period measurement values are recorded for a predetermined time period, and if so, determining an upper threshold value and a lower threshold value based on the average and the standard deviation of the water content in fat measurement values recorded during said learning time period, then, for each measurement value,

[0011] - determining whether the current measurement value is greater than or equal to said upper threshold value, and when this is the case, determining whether at least a first number of measurement values of a second number of last measurement values are above the upper threshold value, then if this is the case, issuing a first event,

[0012] - determining whether the current measurement value is less than or equal to said lower threshold value, and when this is the case, determining whether at least said first number of measurement values of said second number of last measurement values are below said lower threshold value, then if this is the case, issuing a second event,

[0013] - determining whether at least a first event has been issued, and if this is the case, issuing a warning function of said at least first event.

[0014] The upper threshold value state vector and the lower threshold value state vector can be 1-dimensional vectors of length equal to said second number, comprising a record of up to second number of comparisons of last measurement values with said upper threshold value and said lower threshold value respectively, each vector being initialized by padding with a first value.

[0015] The state vectors can be updated by shifting the current values within each state vector by one value, thereby deleting the last value in the current values, and by inserting a value at the beginning of each state vector.

[0016] after determining that said current measurement value is greater than or equal to said upper threshold value, inserting a second value in said upper threshold value state vector and said first value in said lower threshold value state vector,

[0017] after determining that said current measurement value is below or equal to said lower threshold value, inserting said first value in said upper threshold value state vector and said second value in said lower threshold value state vector,

[0018] after determining that said current measurement value is greater than said lower threshold value and below said upper threshold value, inserting said first value in said upper threshold value state vector and said lower threshold value state vector, and

[0019] After determining that at least the first number of measurement values of the second number of last measurement values is below the lower threshold, the upper threshold state vector and the lower threshold state vector can be reset by padding with a first value.

[0020] It can be determined whether the current measurement value is greater than or equal to a third number times the upper threshold, and if so, a first event is issued.

[0021] A new upper threshold and a new lower threshold can be determined from a preset number of measurement values immediately after the first event is issued.

[0022] A new learning time period can be triggered each time the first event or the second event occurs.

[0023] The rotating system can be a bearing.

[0024] The step of determining whether at least the first event has been issued can be implemented before the new learning time period, after the new learning time period, in the background or in parallel with other steps, and if so, a warning function of at least the first event is issued.

[0025] Another object of the application is a monitoring system for a grease-lubricated rotating system, comprising: a processing unit linked to a measurement system for measuring the water content in the lubricating grease, the processing unit being configured for performing the steps included in the monitoring process as described above.

[0026] The measurement system can comprise: an electrode in contact with the grease, the electrode being connected in series with a current source and a resistor; and a measurement component connected in parallel with the resistor, the output signal of the electrolytic measurement system being linked to the voltage drop across the resistor.

[0027] The monitoring system and process are advantageous because they are simpler and present a lower cost without calibration, due to the use of a relative method instead of an absolute method.

[0028] They also allow a reduced risk of configuration errors and allow the automatic recalculation of the warning levels when a new baseline is established. BRIEF DESCRIPTION OF DRAWINGS

[0029] The application will be better understood from the detailed description of a plurality of embodiments considered by way of purely non-limiting example and illustrated by the attached drawings, in which:

[0030] -[ Figure 1 ] illustrates the main steps of a monitoring process according to a first embodiment of the application. DETAILED DESCRIPTION

[0031] The monitoring system comprises a processing unit linked to a measurement system for measuring the water content in the grease of a rotating system, in particular a bearing. The processing unit generally comprises a processor and at least one memory for storing data.

[0032] The electrolytic measurement system comprises an electrode in contact with the grease, connected in series with a current source and a resistor, and a measurement component connected in parallel with the resistor. The output signal of the electrolytic measurement system is linked to the voltage drop across the resistor.

[0033] Instead of trying to achieve an absolute measurement of the water content in the grease, the system seeks to determine a relative measurement of the water content over a predetermined period of time, in which the water content is considered low enough to avoid any damage to the machine.

[0034] Figure 1 An embodiment of the application is illustrated. The process starts from a first step 1 during which it is determined whether a learning period is to be performed. If this is the case, measurements are recorded for a predetermined period of time. If this is not the case, measurements are recorded for the current occurrence. In step 2, it is determined whether a learning mode has been performed immediately before the current occurrence. If this is the case, the process proceeds to a third step 3. If this is not the case, the process proceeds to step 4.

[0035] During the third step 3, an upper threshold TH and a lower threshold TL are determined. The thresholds are a function of the average μ and the standard deviation σ of the water content measurements recorded during the predetermined period of time.

[0036] TH = μ + x * σ (Equation 1)

[0037] TL = y * μ (Equation 2)

[0038] where 1 < x < 10 and 0.1 < y < 0.9

[0039] The process then continues at step 4.

[0040] If it is determined at step 1 that the learning period is not to be performed, the process continues directly at step 4.

[0041] At step 4, it is determined whether the current measurement is greater than or equal to the upper threshold. If this is the case, the upper threshold status vector and the lower threshold status vector are updated during step 5. The upper threshold status vector is a 1 -dimensional vector of length equal to N, comprising a record of at most the last N measurements compared to the upper threshold TH. The lower threshold status vector is similar in structure and comprises a record of at most the last N measurements compared to the lower threshold TL. Each vector is initialized by padding with first values (i.e. 0). See the updated flowchart for clarity.

[0042] During step 5, the status vectors are updated by shifting the current values within each status vector by one value, thereby deleting the last value in the current value and inserting a second value (i.e. 1) at the beginning of the upper threshold status vector and a value equal to the first value at the beginning of the lower threshold status vector.

[0043] At step 6, it is determined whether the measurement exceeds the upper threshold TH multiplied by a third quantity (i.e. 100).

[0044] If this is the case, the process proceeds to step 7 during which a warning is issued.

[0045] If this is not the case, the process continues to step 8 during which it is determined whether at least a quantity equal to the first quantity of the last measurements equal to a second quantity exceed the upper threshold TH (above the upper threshold TH).

[0046] If this is the case, the process proceeds to step 7.

[0047] If this is not the case, the process resumes at step 1.

[0048] After the warning is issued at step 7, the process proceeds to step 9 during which the state vectors are reset, then to step 10 during which the upper threshold TH and the lower threshold TL are recalculated as a function of equation (1) and equation 2, based on the measurements recorded during the predetermined duration immediately preceding the current occurrence. This recalculation of the thresholds saves a time equal to the predetermined duration of the learning period. Instead of waiting for the recordings necessary for the learning period to be collected, the process determines the new thresholds from the measurements already recorded. The process then restarts at step 1.

[0049] If at step 4 it is determined that the current measurement is below the upper threshold, the process proceeds to step 11. During step 11, it is determined whether the current measurement is below or equal to the lower threshold TL. If this is not the case, the process proceeds to step 16 during which the state vectors are updated. During step 16, the state vectors are updated by shifting the current values within each state vector by one value, thereby deleting the last value in the current values and inserting at the beginning of each state vector a value equal to the first value.

[0050] The process then restarts at step 1.

[0051] If during step 11 it is determined that the current measurement is below or equal to the lower threshold TL, the process proceeds to step 12 during which the state vectors are updated. During step 12, the state vectors are updated by shifting the current values within each state vector by one value, thereby deleting the last one in the current values and inserting at the beginning of the upper threshold state vector a value equal to the first value and at the beginning of the lower threshold state vector a value equal to the second value.

[0052] The process then proceeds to step 13 during which it is determined whether at least a number of the last measurement values equal to the first number are below the lower threshold TL, the number being equal to the second number. If this is not the case, the process restarts at step 1. If this is the case, the process proceeds to step 14 during which the learning mode is enabled. During step 15, the state vectors are reset so that only the first value is included and the process continues with step 1.

[0053] In an alternative embodiment, the second number of measurement values are saved or recorded in memory. Steps 5, 12, 14 and 16 are deleted and alternative steps 8 and 13 comprise determining whether at least a number of the last measurement values equal to the first number are respectively above the upper threshold TH or below the lower threshold TL, the number being equal to the second number.

Claims

1. A monitoring method for a grease-lubricated rotating system comprising a processing unit linked to a measuring system for measuring the water content in the lubricating grease, the monitoring method comprising the steps of: - determining whether a learning period is to be performed, during which a measurement value is recorded for a predetermined period of time, and if so, determining an upper threshold and a lower threshold based on the average and the standard deviation of the water content in the grease measurement values recorded during the learning period, - determining whether the current measurement value is greater than or equal to the upper threshold and, when this is the case, determining whether at least a first number of measurement values of a second number of last measurement values exceed the upper threshold, then if this is the case, issuing a first event, - determining whether the current measurement value is less than or equal to the lower threshold and, when this is the case, determining whether at least the first number of measurement values of the second number of last measurement values are lower than the lower threshold, then if this is the case, issuing a second event, - determining whether at least a first event has been issued, and if this is the case, issuing a warning function of the at least first event.

2. The monitoring method according to claim 1, characterized in that, The upper threshold state vector and the lower threshold state vector are 1 -dimensional vectors of length equal to the second number, comprising a record of at most the second number of last measurement values of the comparison results with the upper threshold and the lower threshold respectively, each vector being initialized by padding with a first value.

3. The monitoring method according to claim 2, characterized in that, The state vectors are updated by shifting the current values within each of the upper threshold state vector and the lower threshold state vector by one value, thereby deleting the last of the current values, and by inserting a value at the beginning of each state vector, after determining that the current measurement value is greater than or equal to the upper threshold, a second value is inserted in the upper threshold state vector and the first value is inserted in the lower threshold state vector, after determining that the current measurement value is lower than or equal to the lower threshold, the first value is inserted in the upper threshold state vector and the second value is inserted in the lower threshold state vector, after determining that the current measurement value is greater than the lower threshold and lower than the upper threshold, the first value is inserted in the upper threshold state vector and the lower threshold state vector, and after determining that at least the first number of measurement values of the second number of last measurement values are lower than the lower threshold, the upper threshold state vector and the lower threshold state vector are re-set by padding with a first value.

4. The monitoring method according to any one of claims 1 to 3, characterized in that, It is determined whether the current measurement value is greater than or equal to a third number times the upper threshold, and if this is the case, a first event is issued.

5. The monitoring method according to any one of claims 1 to 3, characterized in that, New upper and lower thresholds are determined from a preset number of measurement values immediately after the first event is issued.

6. The monitoring method according to any one of claims 1 to 3, characterized in that, A new learning period is triggered each time a first event or a second event occurs.

7. The monitoring method according to any one of claims 1 to 3, characterized in that, The rotating system is a bearing.

8. The monitoring method according to any one of claims 1 to 3, characterized in that, The step of determining whether at least the first event has been issued, and if this is the case, issuing a warning function of the at least first event, is implemented before a new learning period, after a new learning period or in the background. The rotating system is a bearing.

9. A monitoring system for a grease-lubricated rotating system, comprising: a processing unit linked to a measuring system for measuring the water content in the grease, said processing unit being configured for performing the steps comprised in the monitoring method according to any one of claims 1 to 8.

10. The monitoring system of claim 9, wherein, said measuring system comprising an electrode in contact with said grease, said electrode being connected in series with a current source and a resistor, and a measuring member connected in parallel with said resistor, the output signal of said measuring system being linked to the voltage drop across said resistor.

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