{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:K4ZEUMISAHJJH6C77HSKD26IVP","short_pith_number":"pith:K4ZEUMIS","canonical_record":{"source":{"id":"2207.10432","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2022-07-21T12:02:50Z","cross_cats_sorted":[],"title_canon_sha256":"fc86859e12c7345ab061d6ae141f6435bdab516dd7cefbe0b51ec3ff09a20374","abstract_canon_sha256":"84c88b4985c95bf260a7e6545d7632e9ce8bbbac8ff1d7069da0cf6ca089957f"},"schema_version":"1.0"},"canonical_sha256":"57324a311201d293f85ff9e4a1ebc8abf67bd5ad2a2a2417fe44effc0b29c6a1","source":{"kind":"arxiv","id":"2207.10432","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.10432","created_at":"2026-07-05T04:42:24Z"},{"alias_kind":"arxiv_version","alias_value":"2207.10432v1","created_at":"2026-07-05T04:42:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.10432","created_at":"2026-07-05T04:42:24Z"},{"alias_kind":"pith_short_12","alias_value":"K4ZEUMISAHJJ","created_at":"2026-07-05T04:42:24Z"},{"alias_kind":"pith_short_16","alias_value":"K4ZEUMISAHJJH6C7","created_at":"2026-07-05T04:42:24Z"},{"alias_kind":"pith_short_8","alias_value":"K4ZEUMIS","created_at":"2026-07-05T04:42:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:K4ZEUMISAHJJH6C77HSKD26IVP","target":"record","payload":{"canonical_record":{"source":{"id":"2207.10432","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2022-07-21T12:02:50Z","cross_cats_sorted":[],"title_canon_sha256":"fc86859e12c7345ab061d6ae141f6435bdab516dd7cefbe0b51ec3ff09a20374","abstract_canon_sha256":"84c88b4985c95bf260a7e6545d7632e9ce8bbbac8ff1d7069da0cf6ca089957f"},"schema_version":"1.0"},"canonical_sha256":"57324a311201d293f85ff9e4a1ebc8abf67bd5ad2a2a2417fe44effc0b29c6a1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:42:24.983916Z","signature_b64":"bM4HvbkjWBJxerjdqWAlqj1wJgZgzg4z5xZYRsBr8waixEuxuyhNUuy/bNAI3uzw+1IeDgdWpbV9V2aAKNseCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"57324a311201d293f85ff9e4a1ebc8abf67bd5ad2a2a2417fe44effc0b29c6a1","last_reissued_at":"2026-07-05T04:42:24.983410Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:42:24.983410Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.10432","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:42:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rHRCVWBoqJMbiDnZ4+6nVhiXIVS+Ga16shJfLghxSJtvc68mSDZ88rs1Ns7pGsYLPVQnEgBpkm6sa9uGiouBAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:23:42.005932Z"},"content_sha256":"73b51de74aa2c2a33beb6f41e1252b2534950297464e9c61dab53e4308c3eb6b","schema_version":"1.0","event_id":"sha256:73b51de74aa2c2a33beb6f41e1252b2534950297464e9c61dab53e4308c3eb6b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:K4ZEUMISAHJJH6C77HSKD26IVP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Wavelet Transform and self-supervised learning-based framework for bearing fault diagnosis with limited labeled data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CE","authors_text":"Lei Hou, Ming Du, Yuhong Jin, Yushu Chen","submitted_at":"2022-07-21T12:02:50Z","abstract_excerpt":"Traditional supervised bearing fault diagnosis methods rely on massive labelled data, yet annotations may be very time-consuming or infeasible. The fault diagnosis approach that utilizes limited labelled data is becoming increasingly popular. In this paper, a Wavelet Transform (WT) and self-supervised learning-based bearing fault diagnosis framework is proposed to address the lack of supervised samples issue. Adopting the WT and cubic spline interpolation technique, original measured vibration signals are converted to the time-frequency maps (TFMs) with a fixed scale as inputs. The Vision Tran"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.10432","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2207.10432/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:42:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lcA2UPMOxzApTogxqK/x4JHiBrwh4k+VvRfMNFp+bVVVj1ZkuRkcqf3sXviEQhGeD0zGVq3S8le06GZd+J7FBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:23:42.006430Z"},"content_sha256":"c91ec09c0b8998cc075161b73c1623603273bfd81adf51f699f4212a15afe0d3","schema_version":"1.0","event_id":"sha256:c91ec09c0b8998cc075161b73c1623603273bfd81adf51f699f4212a15afe0d3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/K4ZEUMISAHJJH6C77HSKD26IVP/bundle.json","state_url":"https://pith.science/pith/K4ZEUMISAHJJH6C77HSKD26IVP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/K4ZEUMISAHJJH6C77HSKD26IVP/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-05T15:23:42Z","links":{"resolver":"https://pith.science/pith/K4ZEUMISAHJJH6C77HSKD26IVP","bundle":"https://pith.science/pith/K4ZEUMISAHJJH6C77HSKD26IVP/bundle.json","state":"https://pith.science/pith/K4ZEUMISAHJJH6C77HSKD26IVP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/K4ZEUMISAHJJH6C77HSKD26IVP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:K4ZEUMISAHJJH6C77HSKD26IVP","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"84c88b4985c95bf260a7e6545d7632e9ce8bbbac8ff1d7069da0cf6ca089957f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2022-07-21T12:02:50Z","title_canon_sha256":"fc86859e12c7345ab061d6ae141f6435bdab516dd7cefbe0b51ec3ff09a20374"},"schema_version":"1.0","source":{"id":"2207.10432","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.10432","created_at":"2026-07-05T04:42:24Z"},{"alias_kind":"arxiv_version","alias_value":"2207.10432v1","created_at":"2026-07-05T04:42:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.10432","created_at":"2026-07-05T04:42:24Z"},{"alias_kind":"pith_short_12","alias_value":"K4ZEUMISAHJJ","created_at":"2026-07-05T04:42:24Z"},{"alias_kind":"pith_short_16","alias_value":"K4ZEUMISAHJJH6C7","created_at":"2026-07-05T04:42:24Z"},{"alias_kind":"pith_short_8","alias_value":"K4ZEUMIS","created_at":"2026-07-05T04:42:24Z"}],"graph_snapshots":[{"event_id":"sha256:c91ec09c0b8998cc075161b73c1623603273bfd81adf51f699f4212a15afe0d3","target":"graph","created_at":"2026-07-05T04:42:24Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2207.10432/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Traditional supervised bearing fault diagnosis methods rely on massive labelled data, yet annotations may be very time-consuming or infeasible. The fault diagnosis approach that utilizes limited labelled data is becoming increasingly popular. In this paper, a Wavelet Transform (WT) and self-supervised learning-based bearing fault diagnosis framework is proposed to address the lack of supervised samples issue. Adopting the WT and cubic spline interpolation technique, original measured vibration signals are converted to the time-frequency maps (TFMs) with a fixed scale as inputs. The Vision Tran","authors_text":"Lei Hou, Ming Du, Yuhong Jin, Yushu Chen","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2022-07-21T12:02:50Z","title":"A Wavelet Transform and self-supervised learning-based framework for bearing fault diagnosis with limited labeled data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.10432","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:73b51de74aa2c2a33beb6f41e1252b2534950297464e9c61dab53e4308c3eb6b","target":"record","created_at":"2026-07-05T04:42:24Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"84c88b4985c95bf260a7e6545d7632e9ce8bbbac8ff1d7069da0cf6ca089957f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2022-07-21T12:02:50Z","title_canon_sha256":"fc86859e12c7345ab061d6ae141f6435bdab516dd7cefbe0b51ec3ff09a20374"},"schema_version":"1.0","source":{"id":"2207.10432","kind":"arxiv","version":1}},"canonical_sha256":"57324a311201d293f85ff9e4a1ebc8abf67bd5ad2a2a2417fe44effc0b29c6a1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"57324a311201d293f85ff9e4a1ebc8abf67bd5ad2a2a2417fe44effc0b29c6a1","first_computed_at":"2026-07-05T04:42:24.983410Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:42:24.983410Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bM4HvbkjWBJxerjdqWAlqj1wJgZgzg4z5xZYRsBr8waixEuxuyhNUuy/bNAI3uzw+1IeDgdWpbV9V2aAKNseCA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:42:24.983916Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.10432","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:73b51de74aa2c2a33beb6f41e1252b2534950297464e9c61dab53e4308c3eb6b","sha256:c91ec09c0b8998cc075161b73c1623603273bfd81adf51f699f4212a15afe0d3"],"state_sha256":"0adeca2fb79c4b497db73152e724e43565d2b87361e6b967af4c07058767f304"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AjGikmIO34rYzWEOBjLijGTXdGlDl/FXDHeLpqDJShSPICxQvo92OUc48qFIGNjHlNR0tkkO7vCTqOljjeKlAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T15:23:42.009989Z","bundle_sha256":"a90db708bb68bc9f14cdcfb2d6d2ce55ba0d5a6d2eb6bd51a1a474ffe24c6dfc"}}